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Engineering genetic tools to illustrate new insights into the homeostatic control of synaptic strength

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Engineering genetic tools to illustrate new insights into the homeostatic control of synaptic strength

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Content - 1 -

Engineering genetic tools to illustrate new insights into the homeostatic control of
synaptic strength

by
Yifu Han

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
Neuroscience

December 2021

Copyright 2021 Yifu Han
i

Acknowledgements
I would like to share my gratitude for all the support and advice I received during my past
6 years for my PhD training. I feel extremely fortunate to be able to attend USC for my graduate
study and join Dr. Dickman’s lab. I would like to express my greatest appreciation to my adviser,
Dr. Dion Dickman, who has given me insightful guidance and excellent mentorship and training
throughout my PhD career. Also, I would like to thank my committee members, and all the great
guidance and suggestions from Dr. Karen Chang, Dr. Bruce Herring, Dr. Scott Fraser, and Dr.
Andrew Hires.
I feel extremely lucky to meet all the current and former lab members in Dickman’s lab,
that fulfill my six years with a lot of fun and memorable experiences. First, I would like to thank
Sarah Perry for all the collaborations during my research, including our ALS paper and our work
in chapter 2, which is in review now. Sarah has been an insightful and supportive adviser in my
PhD research in Dickman lab. Second, special thanks to Pragya Goel for initiating the project
and quantifying the initial phenotypes in chapter 3 and 4, and for all the help and advice for my
research. Also, I would like to thank Keke Ding in David Anderson’s lab in Caltech who
collaborated in our paper published in Elife. Many thanks to another major collaborator in the
lab, Nancy Tran, who has made great help with the genetic in my research; Kaikai He, who has
pioneered in the STED imaging in lab that has pushed our research to a new level in lab; and
Jerry Chien, who has a lot of communication in my research and has been pushing me for
physical training that energized my life. And many thanks to everyone who has worked with me
in Dickman lab. I could not achieve what I have now without you.
Many thanks to my family and my wife. They have been supportive in my life over the
ups and downs in my long PhD career.

ii

Abstract
Homeostatic plasticity maintains stable function of the nervous system in response to
multiple internal and external challenges during development, learning and disease processes.
Several mechanisms are adopted by the nervous system to achieve homeostatic modulation of
neuronal activity, including the homeostatic control of intrinsic excitability (Marder, 2011;
Nerbonne et al., 2008; Parrish et al., 2014; Temporal et al., 2012; Turrigiano, 2011; Wenner,
2011), neurotransmitter receptor expression (Turrigiano, 2011; Wenner, 2011), and presynaptic
neurotransmitter release (Davis, 2006; O’Brien et al., 1998; Turrigiano and Nelson, 2004;
Turrigiano et al., 1998). In the central nervous system, homeostatic control of synaptic efficacy
is one of the mechanisms to balance the run-away effect from Hebbian plasticity. At
neuromuscular junctions, presynaptic release is homeostatically modulated in a bi-directional
way when the synapses are challenged by inhibition of postsynaptic receptor or excess
glutamate release. Over the past 20 years, despite extensive efforts have been made to identify
presynaptic genes (Delvendahl and Müller, 2019; Frank, 2014; Frank et al., 2020; Goel and
Dickman, 2021) and machineries required for the expression of presynaptic homeostatic
potentiation (PHP), however the postsynaptic muscle initiate and integrate retrograde signaling
still lack thorough investigation. Moreover, the Drosophila body wall muscles are innervated by
two individual motor neurons, the “tonic” Ib and the “phasic” Is, which differ in many properties,
including firing pattern, release probability and synaptic strength (Choi et al., 2004; Karunanithi
et al., 2002; Lu et al., 2016). However, synaptic transmission and plasticity have been studied
as an ambiguous average between two distinct synapses due to lack of tools to separate them.
In this thesis work, I established new reagents to interrogate a non-ionotropic model underlying
the induction of PHP signaling in the postsynaptic muscle and engineered a genetic tool to
separate the converging Ib and Is inputs at Drosophila NMJ.
iii

In chapter 2 we developed a host of specific antibodies and new mutant alleles using
CRISPR/Cas9 approaches to interrogate the role of GluRIIA, postsynaptic Ca
2+
, and CaMKII
activity in retrograde PHP induction. This work has revealed that CaMKII activity and PHP
induction is not influenced by diminished Ca
2+
at postsynaptic compartments. Rather, active
CaMKII requires an intimate interaction with the GluRIIA C-tail. Loss of this interaction is
necessary to allow retrograde signaling and PHP expression, highlighting a unique and
unanticipated inductive mechanism.
In chapter 3, we developed a botulinum toxin (BoNT-C) to completely block both evoked
and spontaneous glutamate transmission at Drosophila NMJ without inducing any impact on
synaptic growth, structure, or innervation. With the amenability to selectively silence Ib or Is
motor neurons, we were able to functionally dissect the transmission and the release patterns
from the tonic Ib vs phasic Is synapses.
In chapter 4, we generated the first null mutations that specifically ablate GluRIIA and
GluRIIB receptors using CRISPR/Cas9 gene editing. These mutants have enabled us to probe
how GluR fields are established during development and in response to synaptically released
glutamate, and how competition between GluRA and GluRB determine the impact of glutamate
on adaptive GluR plasticity. These studies revealed that GluRA and GluRB compete to establish
postsynaptic receptor fields and exhibit distinct responses to synaptic glutamate. However, in
the absence of competition, synaptically released glutamate homeostatically scale GluRA
receptor abundance while GluRB receptors are insensitive to glutamate. Moreover, postsynaptic
Ca
2+
transient through GluRA receptors is required for this homeostatic receptor rescaling.
In chapter 5, we engineered Neuropeptide Release Reporters (NPRRs): novel
genetically encoded sensors with high temporal resolution and genetic specificity. Using the
Drosophila larval neuromuscular junction (NMJ) as a model, we provide evidence that NPRRs
recapitulate the trafficking and packaging of native neuropeptides, and report stimulation-
iv

evoked neuropeptide release events as real-time changes in fluorescence intensity, with sub-
second temporal resolution.

v

Table of Contents
Acknowledgements ................................................................................................................... i
Abstract ..................................................................................................................................... ii
List of Figures and Tables ...................................................................................................... vii
Chapter 1: Homeostatic plasticity at the Drosophila neuromuscular junction .................... 1
1.1 Homeostatic plasticity maintains the stability of the nervous system. ................................ 2
1.2 The induction mechanisms of retrograde homeostatic potentiation ................................... 3
1.3 Input-specific mechanisms of presynaptic expression of PHP .......................................... 5
1.4 Homeostatic modulation of glutamate receptors at Drosophila NMJ. ................................ 7
Chapter 2: A Glutamate Receptor C-tail Recruits CaMKII to Suppress Retrograde
Homeostatic Signaling ............................................................................................................ 9
2.1 Abstract ...........................................................................................................................10
2.2 Introduction ......................................................................................................................11
2.3 Results ............................................................................................................................14
2.4 Discussion .......................................................................................................................23
2.5 Materials and Methods ....................................................................................................28
Chapter 3: Synaptic silencing by botulinum toxin reveals no heterosynaptic plasticity
between tonic and phasic inputs in Drosophila ...................................................................49
3.1 Abstract ...........................................................................................................................50
3.2 Introduction ......................................................................................................................51
3.3 Results ............................................................................................................................53
3.4 Discussion .......................................................................................................................60
3.5 Materials and Methods ....................................................................................................62
Chapter 4: Synaptic glutamate homeostatically modulates postsynaptic receptor
abundance ...............................................................................................................................76
4.1 Abstract ...........................................................................................................................77
4.2 Introduction ......................................................................................................................78
4.3 Results ............................................................................................................................80
4.4 Discussion .......................................................................................................................86
4.5 Materials and Methods ....................................................................................................89
Chapter 5: Imaging neuropeptide release at synapses with a genetically engineered
reporter ....................................................................................................................................98
5.1 Abstract ...........................................................................................................................99
5.2 Introduction .................................................................................................................... 100
5.3 Results .......................................................................................................................... 101
vi

5.4 Discussion ..................................................................................................................... 107
5.5 Materials and Methods .................................................................................................. 109
Chapter 6: Conclusion .......................................................................................................... 127
References ............................................................................................................................ 132

vii

List of Figures and Tables
Chapter 2
Figure 1 ................................................................................................................................. 33
Figure 2 ................................................................................................................................. 34
Figure 3 ................................................................................................................................. 36
Figure 4 ................................................................................................................................. 37
Figure 5 ................................................................................................................................. 39
Figure 6 ................................................................................................................................. 40
Figure 7 ................................................................................................................................. 42
Supplemental Figure 1........................................................................................................... 43
Supplemental Figure 2........................................................................................................... 44
Supplemental Figure 3........................................................................................................... 46
Supplemental Figure 4........................................................................................................... 47
Supplemental Table 1 ............................................................................................................ 48
Chapter 3
Figure 1 ................................................................................................................................. 65
Figure 2 ................................................................................................................................. 66
Figure 3 ................................................................................................................................. 68
Figure 4 ................................................................................................................................. 69
Figure 5 ................................................................................................................................. 70
Figure 6 ................................................................................................................................. 71
Supplemental Figure 1........................................................................................................... 73
Supplemental Figure 2........................................................................................................... 74
Supplemental Figure 3........................................................................................................... 75
Chapter 4
Figure 1 ................................................................................................................................. 93
Figure 2 ................................................................................................................................. 94
Figure 3 ................................................................................................................................. 95
Figure 4 ................................................................................................................................. 96
Supplemental Figure 1........................................................................................................... 97
Chapter 5
Figure 1 ............................................................................................................................... 115
Figure 2 ............................................................................................................................... 116
Figure 3 ............................................................................................................................... 117
viii

Figure 4 ............................................................................................................................... 118
Supplemental Figure 1......................................................................................................... 119
Supplemental Figure 2......................................................................................................... 120
Supplemental Figure 3......................................................................................................... 121
Supplemental Figure 4......................................................................................................... 122
Supplemental Figure 5......................................................................................................... 123
Supplemental Figure 6......................................................................................................... 124
Supplemental Figure 7......................................................................................................... 125
Supplemental Figure 8......................................................................................................... 126

1

Chapter 1: Homeostatic plasticity at the Drosophila neuromuscular
junction

2

1.1 Homeostatic plasticity maintains the stability of the nervous system.
Homeostatic mechanisms have been commonly applied by biological organisms to
maintain the stability and normal functions in response to external and internal perturbations. In
the nervous system, homeostatic plasticity is essential for stabilizing neuronal excitability,
presynaptic neurotransmission and maintaining neural circuits (Delvendahl and Müller, 2019;
Marder and Goaillard, 2006; Pozo and Goda, 2010; Turrigiano, 2008). It has been proven that
homeostatic mechanisms orchestrate neural activity on different levels of the nervous system,
including individual synapse (O’Brien et al., 1998), dendrite development (Branco et al., 2008)
and on the neural circuitries (Marder and Goaillard, 2006). Besides, the time scale of the
homeostatic mechanisms ranges from minutes in the peripheral nervous system (Pozo and
Goda, 2010) to hours (Frank et al., 2006; Wang et al., 2016b).
At synapses, the core module of the nervous system, homeostatic control of neural
activity can be achieved through different mechanisms, including modulation of neurotransmitter
release (Cull ‐Candy et al., 1980; Davis and Goodman, 1998; Petersen et al., 1997) and
presynaptic neurotransmitter receptor function and ion channel abundance (Turrigiano et al.,
1998; Wierenga et al., 2005), when synaptic activity is disrupted. Homeostatic regulation of
synaptic strength has been found conservative at the NMJ of s of flies (Davis and Müller, 2015;
Frank et al., 2020; Goel and Dickman, 2021), rodents (Orr et al., 2020; Plomp et al., 1992;
Wang and Rich, 2018; Wang et al., 2016b) and human (Cull ‐Candy et al., 1980), and was
recently reported in the mammalian central nervous system (Delvendahl et al., 2019). Synaptic
homeostatic plasticity when disrupted, has been reported to be related to multiple neurological
and degenerative diseases (Frere and Slutsky, 2018; Jang and Chung, 2016; Ramocki and
Zoghbi, 2008; Wondolowski and Dickman, 2013).

3

1.2 The induction mechanisms of retrograde homeostatic potentiation
Extensive progresses have been achieved to understand the expression mechanisms of
the presynaptic PHP in Drosophila NMJ (Delvendahl and Müller, 2019; Frank, 2014; Frank et
al., 2020). When the postsynaptic GluR faces challenges, the presynaptic terminal adopts two
mechanisms to homeostatically potentiate the neurotransmitter release. Two major machineries
have been reported to achieve the presynaptic potentiation, including increases in presynaptic
Ca
2+
influx and the size of readily releasable pool (Müller and Davis, 2012; Weyhersmüller et al.,
2011). More than 25 genes have been reported required in the presynaptic terminals to achieve
PHP expression by forward genetic screening (Dickman and Davis, 2009; Müller et al., 2011).
As there has been comprehensive understanding of the expression mechanisms of PHP
in the presynaptic compartments, the induction mechanisms of how the PHP is induced in the
postsynaptic compartments following the genetic loss or pharmacological blockade of GluR
receptors still lack investigation. It was first reported 20 year ago that a chronic form of PHP is
induced by genetic loss of GluRIIA-containing receptors is necessary for inducing the retrograde
PHP signaling (Petersen et al., 1997). Then a rapid form of PHP could be induced in 10 minutes
when postsynaptic GluRIIA is inhibited by philanthotoxin-433 (PhTx) (Frank et al., 2006). There
has been an attractive hypothesis that the reduced Ca
2+
following the loss of GluRIIA-type
receptors is the key factor to initiate the PHP signaling in the postsynaptic compartment
(Petersen et al., 1997). Several sets of evidence support this model. First, PHP in GluRIIA
mutants was blocked by overexpression of a constitutively active Ca
2+
/calmodulin kinase II
(CaMKII) in the postsynaptic muscle (Haghighi et al., 2003; Li et al., 2018a). In addition,
phosphorylated CaMKII was reduced postsynaptic density in GluRIIA mutants compared to wild
type by immunostaining of phosphorylated CaMKII (Li et al., 2018a; Newman et al., 2017). With
these results, it was speculated that a reduction in Ca
2+
influx due to loss of GluRIIA-type
receptors is necessary to initiate PHP induction. GluRIIA-type GluRs drive the majority of
synaptic currents and desensitize more slowly compared with B-type GluRs (GluRB) (Diantonio
4

et al., 1999; Han et al., 2015). Consistent with the reduced Ca
2+
model, the only known way to
induce PHP at the fly NMJ requires loss or pharmacological blockade of GluRA receptors, which
necessarily also diminishes postsynaptic Ca
2+
levels. However, this model has not been directly
tested because the coupling between diminished GluRA abundance and reduced postsynaptic
Ca
2+
has never been separated. Moreover, recent evidence showed that acute PHP could be
induced when in saline without Ca
2+
added (Goel et al., 2017a). Thus, acute PHP induction
might not require changes in Ca
2+
influx at the postsynaptic compartment.
Several genetic pathways have been illustrated involved in the postsynaptic induction
mechanisms of PHP signaling by foreward genetics in recent years. Translatinal regulatory
pathways including the target of rapamycin signaling is required for the induction of chronic PHP
in the postsynaptic muscles (Kauwe et al., 2016; Penney et al., 2012, 2016). Furthermore, PHP
can be artificially activated without genetically ablation of GluRIIA as the retrograde PHP can be
induced by Tor overexpression in the muscles (Goel et al., 2017a; Penney et al., 2012). It is
speculated that chronic PHP induction involves translational mechanisms while rapid PHP might
involve posttranslational mechanisms. In detail, translational pathways might not be involved in
the pharmacologically-triggered rapid PHP as rapid PHP can still be triggered when protein
translation is inhibited (Chen and Dickman, 2017; Frank et al., 2006; Goel et al., 2017a, 2019a).
The Drosophila postsynaptic phosphoinostide-3-kinase pathway was illustrated to be required
for the induction of both rapid and chronic PHP in muscles in a systematic forward screening of
postsynaptic kinase and phosphateses (Hauswirth et al., 2018). However, it is still unclear how
PI3K is involved in the induction signaling of chronic PHP which is triggered by loss of GluRIIA.
Meanwhile the evidence shows that membrane trafficking is regulated by PI3K signaling as
Rab-11 is also required in the PHP induction in the postsynaptic muscles (Hauswirth et al.,
2018).

5

1.3 Input-specific mechanisms of presynaptic expression of PHP
The presynaptic active zone is speculated as the target of the homeostatic potentiation
in PHP signaling for several sets of evidence. First, PHP is blocked by genetic mutants of
several genes of active zone components (including the Cav2 Ca
2+
channel Cacophony (Cac;
(Frank et al., 2006) and its auxiliary subunit α2δ (Wang et al., 2016a), the piccolo homolog fife
(Bruckner et al., 2017), the scaffolds RIM (Rab3-interacting molecule; (Müller et al., 2011), Rbp
(Rim binding protein; (Müller et al., 2015), Unc13A (Böhme et al., 2019), and the kainate
receptor DKaiR1D (Kiragasi et al., 2017, 2020). Second, both presynaptic Ca
2+
influx and Cav2
Ca
2+
channels increased at active zone (Goel et al., 2019a; Gratz et al., 2019; Müller and Davis,
2012). Finally, during PHP expression, active zone scaffolds and the sub-cluster organization
undergo remodeling (Böhme et al., 2019; Goel et al., 2017a, 2019a; Gratz et al., 2019; Li et al.,
2018b; Mrestani et al., 2020; Weyhersmüller et al., 2011).
However, the mechanisms allowing homeostatic modulation of active zone and synaptic
release underlying PHP is still unclear. As rapid PHP (Frank et al., 2006; Goel et al., 2017a) and
the underlying active zone remodeling (Böhme et al., 2019) can still be activated with
translational pathways inhibited, a posytranslational pathway is required for the induction of
active zone remodeling. Other aspects of PHP required increase in presynaptic release efficacy
(Müller and Davis, 2012; Weyhersmüller et al., 2011). One mechanism targets enhanced
presynaptic Ca
2+
influx which requires increased Ca
2+
channels at the active zone centers
(Gratz et al., 2019; Müller and Davis, 2012). Another mechanism targets facilitated synaptic
vesicle pool ready for release which include increase in active zone components Brp and
Unc13A (Böhme et al., 2016; Matkovic et al., 2013). The axonal transportation of active zone
components are also required for PHP expression, which provide further evidence. The axonal
motors aplip-1 (App-like interacting protein), srpk79D (serine-arginine protein at 79D), and the
lysosome adaptor arl-8 (arf-like GTPase-8) were involved in rapid expression of PHP process
(Böhme et al., 2019; Goel et al., 2019a). Further, Arl-8-dependent axonal transportation
6

includes active zone and synaptic vesicle proteins (Vukoja et al., 2018). Further study is still
required to understand the remodeling process of active zone required in PHP expression and
how PHP is differentially induced during the distinct time scale in acute and chronic PHP.
Recent progress on the expression mechanisms of PHP has depicted distinct input-
specific machineries at the converging motor neuron synapses at Drosophila NMJ. Unlike the
mammalian NMJ, where one muscle fiber is innervated by single motor neuron input, the fly
larval muscles are innervated by two motor neurons inputs, the tonic (type Ib) and the phasic
(type Is) motor neurons (Atwood et al., 1993; Hoang and Chiba, 2001). For over 40 years, the Ib
and Is transmissions have been studied in a confounded manner as there was no genetic tools
optimal for separating these two transmissions on a single muscle cell. However, recent studies
using optogenetics have suggested that Ib and Is motor neurons are differentially involved in the
chronic or rapid forms of PHP (Genç and Davis, 2019; Newman et al., 2017). First, Ib synapses
express chronic PHP while Is synapses express rapid PHP at low extracellular Ca
2+
. Second,
the Ib and Is synapses are both recruited in both chronic and rapid PHP at high extracellular
Ca
2+
. Finally, Ib and Is synapses are different at baseline transmission, where Ib active zones
have higher release Pr and Ib AZs have lower Pr (Lu et al., 2016; Newman et al., 2017).
Combining these evidences, it is speculated that the rapid and chronic PHP are differentially
expressed in Ib and Is synapses and that the active zones at Ib and Is synapses are distinctly
remodeled in chronic and rapid PHP.

7

1.4 Homeostatic modulation of glutamate receptors at Drosophila NMJ.
Postsynaptic glutamate receptors are dynamically trafficked and modulated at
postsynaptic density in the process of development, plasticity and neuronal diseases. In the
mammalian synapses, activity-dependent homeostatic modulation of glutamate receptors has
been extensively studied (Chowdhury and Hell, 2018; Diering and Huganir, 2018; Turrigiano,
2008) in Hebbian type plasticity. Both ionotropic and non-ionotropic signals through glutamate
receptors are involved in distinct types of homeostatic plasticity targeting the AMPA and NMDA
type receptors at the postsynaptic compartment. The plasticity of GluRs composition,
abundance and properties are modulated by multiple signaling pathways in the postsynaptic
field (Huganir and Nicoll, 2013; Malinow and Malenka, 2002). These include auxiliary GluR
subunits, postsynaptic scaffolding proteins, and signaling transduction molecules such as
CaMKII (Herring and Nicoll, 2016). Extracellular glutamate alone appears to be capable of
inducing synaptogenesis, as photo-uncaging of glutamate in extracellular regions near dendritic
shafts is capable of generating dendritic spines de novo (Kwon and Sabatini, 2011). However,
whether and to what extent synaptically released glutamate itself influences GluR composition
and abundance has not been clearly defined.
At Drosophila NMJ, several examples of homeostatic modulation of postsynaptic GluR
have been reported. First, reduced neuronal input and hypo-innervation enhance GluRs globally
and in a target-specific manner (Goel et al., 2019a, 2020). Second, activation of injury related
neuronal DLK/Wnd signaling induces a downregulation in the abundance of all GluRs (Goel and
Dickman, 2018). This reduction was also non-specific suggesting the signaling pathways and
mechanisms that are activated in response to injury may be distinct from those induced when
vesicular glutamate release is directly modulated. Third, non-vesicular cleft glutamate alters
GluR abundance via glial glutamatergic signaling, and glia shown to regulate GluR abundance
and control glutamate levels, perhaps excess vesicular glutamate in our vGlut-OE also
modulates GluRs via glia (Augustin et al., 2007; Featherstone et al., 2002). Since our results
8

show GluRAs selectively modulated and are major current carrying subunit, perhaps changes in
miniature postsynaptic currents through GluRAs carry information to trigger a downstream
pathway catered for IIA specific modulation. Indeed, minis regulate synaptic growth during
development and dendritic protein synthesis during plasticity (Choi et al., 2014; Sutton and
Schuman, 2006). Physiological signals such as modulations in calcium influx through GluRAs in
response to miniature release could active Ca
2+
dependent intracellular signaling and calcium-
dependent kinases and proteinases (Goel et al., 2017a; Metwally et al., 2019). Finally, kinases
and adhesion molecules known to specifically control GluRIIA but not GluRIIB are possible
factors for this regulation. Finally, neto, an auxiliary factor for GluRs at the fly NMJ (Ramos et
al., 2015), is an attractive candidate induce receptor changes.

9

Chapter 2: A Glutamate Receptor C-tail Recruits CaMKII to Suppress
Retrograde Homeostatic Signaling

10

2.1 Abstract
Presynaptic homeostatic plasticity (PHP) adaptively enhances neurotransmitter release
following diminished postsynaptic glutamate receptor (GluR) function to maintain synaptic
strength. While a lot is now known about the expression mechanisms of this fundamental form
of plasticity, the postsynaptic induction process remains enigmatic. For over 20 years, it was
hypothesized that diminished Ca
2+
influx through postsynaptic GluRs reduces CaMKII activity to
enable retrograde PHP signaling. Here, we have interrogated postsynaptic inductive signaling
and the role of CaMKII at the Drosophila neuromuscular junction. First, we demonstrate that
active CaMKII colocalizes with and requires the GluRIIA receptor subunit. Next, we used
CRISPR mutagenesis to generate calcium-impermeable GluRIIA-containing receptors,
revealing that both CaMKII activity and PHP induction are insensitive to reductions in
postsynaptic Ca
2+
. Rather, a short C-terminal domain encoded in the GluRIIA tail is necessary
and sufficient to recruit active CaMKII to postsynaptic compartments. Finally, we use chimeric
receptors to demonstrate that the GluRIIA tail constitutively occludes retrograde homeostatic
signaling by stabilizing active CaMKII. Thus, the physical loss of the GluRIIA tail is sensed,
rather than reduced Ca
2+
signaling, to enable retrograde PHP signaling, highlighting a unique,
Ca
2+
-independent control mechanism for CaMKII in homeostatic plasticity.

11

2.2 Introduction
Nervous systems are endowed with the ability to express homeostatic synaptic plasticity,
a fundamental process that maintains stable functionality when confronted with internal and
external perturbations. Such homeostatic control of synaptic strength occurs in central and
peripheral nervous systems of invertebrates and mammals, where adaptations in both pre- and
postsynaptic compartments are observed (Li et al., 2019; Pozo and Goda, 2010; Turrigiano,
2012). One major form of homeostatic synaptic plasticity, referred to as presynaptic homeostatic
potentiation (PHP), has been well studied at the Drosophila neuromuscular junction (NMJ). In
this system, genetic loss of the postsynaptic glutamate receptor (GluR) subunit GluRIIA induces
a retrograde signaling system that instructs a compensatory increase in presynaptic
neurotransmitter release to maintain stable levels of synaptic strength (Davis and Müller, 2015;
Frank et al., 2020; Goel and Dickman, 2021). PHP is conserved at NMJs of rodents (Orr et al.,
2020; Plomp et al., 1992; Wang and Rich, 2018; Wang et al., 2016b) and humans (Cull ‐Candy
et al., 1980), and was recently demonstrated in the mouse central nervous system (Delvendahl
et al., 2019). Underscoring the importance of this process, disruption of homeostatic signaling is
associated with a variety of neurological and degenerative diseases (Frere and Slutsky, 2018;
Jang and Chung, 2016; Ramocki and Zoghbi, 2008; Wondolowski and Dickman, 2013)
Important progress has been made in defining presynaptic PHP expression mechanisms
(Delvendahl and Müller, 2019; Frank, 2014; Frank et al., 2020; Goel and Dickman, 2021) and in
identifying possible retrograde signals (Orr et al., 2017; Wang et al., 2014). However, the
postsynaptic induction mechanisms that detect GluR loss and initiate retrograde PHP signaling
are unknown.
When GluRIIA mutants were first characterized and the phenomenon of PHP was
initially described at the Drosophila neuromuscular junction (NMJ) over 20 years ago, it was
hypothesized that a reduction in postsynaptic Ca
2+
influx might be the key postsynaptic signal
12

necessary for PHP induction (Petersen et al., 1997). The possibility that reduced postsynaptic
Ca
2+
is the necessary inductive signal to trigger retrograde PHP expression is an attractive idea
for two reasons. First, several forms of synaptic plasticity are induced through changes in
postsynaptic Ca
2+
, including long-term potentiation and depression (Bayer and Schulman, 2019;
Herring and Nicoll, 2016). Second, the key trigger necessary to initiate PHP, genetic loss of
postsynaptic GluRs at the fly NMJ, results in reduced postsynaptic Ca
2+
levels (Newman et al.,
2017). Postsynaptic GluRs at the fly NMJ exist as heterotetramers comprised of the common
subunits GluRIIC, GluRIID, and GluRIIE plus either the GluRIIA or GluRIIB subunit ((Qin et al.,
2005); Fig. 1A). A-type GluRs (referred to here as GluRA), composed of GluRIIA/C/D/E, drive
the majority of synaptic currents and desensitize more slowly compared with B-type GluRs
(GluRB) (Diantonio et al., 1999; Han et al., 2015). Consistent with the reduced Ca
2+
model, the
only known way to induce PHP at the fly NMJ requires loss or pharmacological blockade of
GluRA receptors, which necessarily also diminishes postsynaptic Ca
2+
levels. However, this
model has not been directly tested because the coupling between diminished GluRA abundance
and reduced postsynaptic Ca
2+
has never been separated.
Evidence has emerged that supports the hypothesis that reduced Ca
2+
triggers a
reduction in postsynaptic Calmodulin-dependent Kinase II (CaMKII) activity to enable retrograde
PHP signaling at the Drosophila NMJ. First, postsynaptic overexpression of a constitutively
active, phosphomimetic CaMKII
T287D
is capable of blocking PHP expression in GluRIIA mutants
28,29. In addition, reduced levels of phosphorylated (active) pCaMKII were observed at
postsynaptic compartments in GluRIIA mutants (Goel et al., 2017a; Li et al., 2018a; Newman et
al., 2017). CaMKII is an appealing potential sensor of reduced Ca
2+
in postsynaptic
compartments at the fly NMJ. This enzyme functions as a central postsynaptic signaling node to
detect and respond to changes in Ca
2+
during the induction of synaptic plasticity (Hell, 2014;
Herring and Nicoll, 2016). CaMKII forms a unique 12-mer holoenzyme that is immensely
abundant in the nervous system (Bayer and Schulman, 2019). The inactive CaMKII holoenzyme
13

exists as a compact structure, inhibiting access to substrates (Fig. 1D). Upon a rise in Ca
2+
, the
regulatory region of CaMKII is displaced which enables autophosphorylation of a key Thr
residue (T287 in Drosophila; T286 in mammals) by neighboring subunits in the holoenzyme.
CaMKII can persist in this activated state long after the transient change in Ca
2+
(Bayer and
Schulman, 2019). Interestingly, however, there is evidence that the C-tail of GluRs and other
scaffolds can also activate CaMKII independently of Ca
2+
(Bayer and Schulman, 2019). The
ability of CaMKII to serve as a secondary Ca
2+
sensor as well as an integral component of the
postsynaptic apparatus further reinforces the potential of this enzyme to transform transient
changes in activity to long term adaptations in synaptic function. However, the role of CaMKII in
PHP signaling, and even whether reduced CaMKII activity is necessary, remains enigmatic.
We have developed a host of specific antibodies and new mutant alleles using
CRISPR/Cas9 approaches to interrogate the role of GluRIIA, postsynaptic Ca
2+
, and CaMKII
activity in retrograde PHP induction. This work has revealed that CaMKII activity and PHP
induction is not influenced by diminished Ca
2+
at postsynaptic compartments. Rather, active
CaMKII requires an intimate interaction with the GluRIIA C-tail. Loss of this interaction is
necessary to allow retrograde signaling and PHP expression, highlighting a unique and
unanticipated inductive mechanism.

14

2.3 Results
Active CaMKII co-localizes and correlates with GluRIIA expression.
To investigate postsynaptic CaMKII function in retrograde PHP signaling, we first
replicated the experiment that most clearly established a relationship between CaMKII and PHP
expression 28. At Drosophila NMJs, genetic deletion of the GluRIIA subunit leads to loss of
GluRA receptors and a reduction in mEPSP amplitude, as expected (Petersen et al., 1997).
However, evoked EPSP amplitudes remain similar to wild-type levels due to a homeostatic
increase in presynaptic neurotransmitter release (quantal content), indicating PHP expression
(Fig. 1B,C). However, when constitutively active CaMKII (CaMKII
T287D
) is postsynaptically
overexpressed in GluRIIA mutants, retrograde homeostatic signaling is blocked, with no
increase in presynaptic release observed (Fig. 1B,C). This provides evidence that a reduction in
CaMKII activity may be necessary to allow retrograde PHP signaling.
In GluRIIA mutants, reductions in pCaMKII immunofluorescence levels have been
observed at the fly NMJ

(Goel et al., 2017a; Li et al., 2018a; Newman et al., 2017). However,
because the commercial antibodies used in these studies were developed against rodent
pCaMKII antigens, it is not clear that these antibodies reflect specific levels and localization of
Drosophila CaMKII. Thus, we generated new Drosophila-specific CaMKII antibodies using
peptides containing the Drosophila CaMKII regulatory domain (Fig. 1E). We successfully
developed two highly specific antibodies: one antibody recognizes total CaMKII levels (anti-
CaMKII), while the other recognizes only the active (T287-phosphorylated) form of the enzyme
(anti-pCaMKII; Fig. 1E). We performed several experiments manipulating CaMKII levels and
activity at the Drosophila NMJ to validate the specificity of these antibodies (Fig. S1).
Remarkably, these new CaMKII antibodies revealed striking differences in CaMKII
localization and activity at the Drosophila NMJ. Total CaMKII localized to postsynaptic
compartments, exhibiting a high degree of overlap with the postsynaptic density marker Discs
Large (DLG; Fig. 1E). In contrast, pCaMKII showed a punctate distribution at postsynaptic areas
15

of the NMJ, co-localizing with the GluRIIA subunit (Fig. 1E). Next, we examined CaMKII and
pCaMKII levels in GluRIIA mutants. In previous studies using commercial (mammalian) CaMKII
antibodies, pCaMKII appeared diffuse at postsynaptic compartments at the fly NMJ and was
reduced by ~50% in GluRIIA mutants

(Goel et al., 2017a; Li et al., 2018a; Newman et al., 2017).
However, using the new antibodies we observed no change in total CaMKII staining, while,
unexpectedly, pCaMKII signals were entirely absent in GluRIIA mutants (Fig. 1F,G).
Conversely, pCaMKII levels were increased when GluRIIA was overexpressed, while no change
was observed in total CaMKII (Fig. 1F,G). Together, these data provide evidence for an
unanticipated tight coupling between GluRIIA levels and CaMKII activity.
Finally, we tested whether manipulation of CaMKII may reciprocally control GluRIIA
receptor levels as well as explored the relationship between CaMKII and pCaMKII. We
observed significant reductions in pCaMKII staining when we knocked down CaMKII expression
or overexpressed inhibitory CaMKII peptides (Fig. S1A,B). However, GluRIIA and GluRIID
levels were only modestly impacted in these conditions (Fig. S1A,B). We also overexpressed
wild type CaMKII and constitutively active CaMKII
T287D
. Both manipulations resulted in marked
increases in pCaMKII staining intensity. Again, GluRIIA and GluRIID levels were only modestly
affected in these genotypes. On the other hand, CaMKII staining is reduced when CaMKII is
knocked down and unaffected by inhibitory peptide expression (Fig. S1C,D). Interestingly,
CaMKII staining is also reduced when CaMKII
T287D
is overexpressed, which may indicate an
equilibrium between active and total CaMKII protein. Thus, while CaMKII activity or levels do not
reciprocally regulate GluRIIA levels, CaMKII activity is sensitively tuned to the abundance of
GluRIIA.
pCaMKII levels are insensitive to reductions in postsynaptic Ca
2+
.
Active pCaMKII is apparently tightly linked to GluRIIA expression. We considered two
possibilities to explain the relationship between pCaMKII and GluRIIA. First, since GluRA
receptors drive the majority of synaptic currents and Ca
2+
influx (Diantonio et al., 1999; Han et
16

al., 2015), gain or loss of these receptors will have a major impact on postsynaptic Ca
2+
levels.
Given that synaptic Ca
2+
levels are well established to be capable of influencing CaMKII activity
(Bayer and Schulman, 2019), postsynaptic Ca
2+
levels at the fly NMJ may therefore tune the
levels of active pCaMKII (schematized in Fig. 2A). In the next series of experiments, we tested
whether CaMKII activity is sensitive to postsynaptic Ca
2+
.
We first attempted to disrupt ionic influx through postsynaptic GluRA receptors using a
previously developed GluRIIA transgene. This transgenic GluRIIA allele, UAS-GluRIIA
M614R
, was
designed to disrupt ionic influx through GluRA receptors by presumably acting as a “dominant
negative”, antagonizing endogenous GluRA receptors (Fig. S2A; (Diantonio et al., 1999).
However, while we did observe a reduction in mEPSP amplitude similar to previous reports
(Table S1), GluR staining revealed poor receptor trafficking, with reductions in GluRIIA, GluRIIB,
and GluRIID levels at the NMJ (Fig. S2B,C). We also observed high levels of GluRIIA that
accumulated in intracellular compartments throughout the muscle, indicating that postsynaptic
overexpression of this transgene generally disrupts GluR trafficking (Fig. S2B). Thus,
postsynaptic overexpression of the GluRIIA
M614R
allele induced a general GluR knock down,
rendering it an ineffective method for determining whether postsynaptic Ca
2+
impacts pCaMKII
levels, independently of GluRIIA abundance.
Therefore, we developed two new approaches to selectively reduce postsynaptic Ca
2+

levels at the larval NMJ without disrupting GluR abundance. First, we used CRISPR/Cas9 gene
editing to generate Ca
2+
impermeable GluRA receptors, while still allowing other ionic
conductances. This was accomplished by mutating a single amino acid in the selectivity pore in
the endogenous GluRIIA locus (Fig. 2B). AMPA and kainate-type GluRs that are Ca
2+

permeable contain a glutamine (Q) residue in the M2 domain; some GluR subunits, including
mammalian AMPA and Drosophila kainate GluRs are unable to conduct Ca
2+
when this Q is
changed to the positively charged arginine (R) amino acid (Fig. 2B; (Li et al., 2016; Ni, 2021;
Traynelis et al., 2010). We therefore targeted the orthologous amino acid in GluRIIA (Q615) for
17

mutagenesis at the endogenous locus to generate a GluRIIA
Q615R
allele (Fig. 2B,C). We
quantified postsynaptic Ca
2+
levels using GCaMP6f targeted to postsynaptic NMJs
(SynaptoGCaMP; (Newman et al., 2017)) and quantified quantal Ca
2+
events (Fig. 2D). Quantal
signals in GluRIIA mutants were reduced by ~50% compared to wild type as observed
previously (Newman et al., 2017), consistent with a major reduction in postsynaptic Ca
2+
due to
loss of GluRAs (Fig. 2D,F). Importantly, while GluRA and GluRB levels were unchanged in
GluRIIA
Q615R
mutants (Fig. 2E,G), a similar ~50% reduction in postsynaptic Ca
2+
was observed
that was statistically indistinguishable from GluRIIA null mutants (Fig. 2D,F). This demonstrates
that the GluRIIA
Q615R
allele reduces postsynaptic Ca
2+
influx to the same levels found in GluRIIA
mutants without altering postsynaptic GluR abundance. Finally, we assayed pCaMKII levels in
GluRIIA
Q615R
mutants and found no significant difference in either total CaMKII or, importantly,
pCaMKII levels (Fig. 2E,G). Therefore, Ca
2+
influx through GluRA receptors does not modulate
CaMKII activity.
We also used a second approach to reduce postsynaptic Ca
2+
levels without
manipulating ionic conductance through postsynaptic GluRs. We cloned the mammalian Ca
2+

buffer parvalbumin (PV) into the strong expression vector pACU2 (Han et al., 2011). PV
localized to postsynaptic compartments when postsynaptically expressed (Fig. S3), and we
observed no significant change in GluR levels (Fig. 2E,G). However, quantal Ca
2+
imaging
revealed an ~40% reduction, reducing Ca
2+
to levels close to that observed in GluRIIA mutants.
Consistent with the results for GluRIIAQ165R, we found no significant difference in total CaMKII
or pCaMKII levels in this condition (Fig. 2E,G). Finally, to reduce postsynaptic Ca
2+
levels below
that observed in GluRIIA mutants alone, we combined the GluRIIAQ165R allele with
postsynaptic PV overexpression. Postsynaptic Ca
2+
was reduced over 60% compared to wild
type (Fig. 2D,F), while GluRIIA, GluRIID, CaMKII, and pCaMKII levels were not significantly
different from wild type (Fig. 2E,G). Thus, CaMKII activity is insensitive to reductions in Ca
2+
at
postsynaptic compartments at the Drosophila NMJ.
18

Reduced postsynaptic Ca
2+
levels are not sufficient to induce PHP expression.
When GluRIIA mutants were first characterized over 20 years ago, it was immediately
speculated that reduced Ca
2+
influx due to loss of high conductance GluRA receptors may be
the primary signal necessary to induce retrograde PHP signaling (Han et al., 2011). Since this
seminal study, this idea has been consistently invoked in subsequent studies (Frank et al.,
2006; Haghighi et al., 2003; Newman et al., 2017). However, this hypothesis has not been
directly tested. We therefore assessed synaptic function in conditions in which postsynaptic
Ca
2+
levels are diminished to the same extent as found in GluRIIA null mutants (GluRIIA
Q615R

mutants and PV overexpression), and even further reduced below this state
(GluRIIA
Q615R
+G14>PV). If reduced postsynaptic Ca
2+
, as observed in GluRIIA mutants, is the
key inductive signal for retrograde signaling and PHP expression, then one should expect
synaptic strength (EPSP amplitude) and quantal content to be enhanced in the manipulations
that reduce postsynaptic Ca
2+
, while miniature activity remains unchanged from baseline.
Electrophysiological recordings from GluRIIA mutants show mEPSP amplitudes reduced over
50% compared with wild type, as expected, but similar EPSP amplitude due to a homeostatic
increase in presynaptic release (quantal content; Fig. 3A-E). It is this increase in quantal content
that defines PHP expression. Recordings from GluRIIA
Q615R
, PV overexpression, and
GluRIIA
Q615R
+PV overexpression NMJs revealed mEPSP amplitudes unchanged from wild type,
as expected. However, no significant difference in EPSP amplitude or quantal content was
found (Fig. 3A-E). This indicates that despite reduced postsynaptic Ca
2+
levels comparable to or
even below that observed in GluRIIA mutants, no change in presynaptic neurotransmitter
release is observed. Therefore, reduced postsynaptic Ca
2+
influx alone is insufficient to induce
retrograde PHP signaling.
Truncation of the GluRIIA C-tail prevents activation of postsynaptic CaMKII.
Having ruled out the conventional Ca
2+
influx model for controlling pCaMKII activity and
PHP induction, we next tested an alternative model in which pCaMKII is stabilized directly or
19

indirectly through a biochemical interaction with a GluR C-tail (schematized in Fig. 4A).
Mammalian NMDARs recruit and activate CaMKII directly through binding sites encoded in their
C-terminal cytosolic tails (Bayer et al., 2001). The GluN2B C-tail contains a “GluN2B-tide” region
that is capable of recruiting CaMKII and promoting T287 phosphorylation (Bayer and Schulman,
2019; Bayer et al., 2001). Other protein domains can also serve as scaffolds to bind and
activate CaMKII, including the Drosophila potassium channel EAG (Castro-Rodrigues et al.,
2018; Sun et al., 2004). Inspired by these studies, we hypothesized that part of the GluRIIA C-
tail may function similarly to promote CaMKII recruitment, stabilization, and/or activation. We
observed a region in the GluRIIA C-tail with homology to both the GluN2B C-tail domain, the
CaMKII autoinhibitory domain, and a region in the Drosophila potassium channel Eag; this
suggested potential interaction sequences with CaMKII (Fig. 4B). In particular, a kinase
consensus sequence (R-Q/R-X-T/S-X-D/E) located at the distal end of the GluRIIA C-tail could,
in principle, interact with CaMKII in a similar manner. This terminal region of the GluRIIA C-tail
was therefore an attractive target to potentially interact with CaMKII.
We used CRISPR/Cas9 mutagenesis to truncate the C-terminal tail of the GluRIIA
subunit at the endogenous locus (Fig. 4C). Specifically, we designed two guide RNAs (sgRNAs)
for Cas9 mutagenesis targeting the final 19 amino acids in the terminal GluRIIA exon (Fig. 4C).
This approach generated two independent truncation alleles (GluRIIA
ΔC20
and GluRIIA
ΔC6
) that
disrupted the last 20 and 6 amino acids of the GluRIIA C-tail, respectively. We also generated a
C-tail deletion in the GluRIIA
Q615R
allele, which ablated the final 19 amino acids (GluRIIA
QRΔC19
).
GluR staining in these alleles confirmed that GluRA receptors trafficked normally, with no
significant differences observed in GluRIIA or GluRIID levels compared to wild type (Fig. 4D,E).
The antigen of the monoclonal GluRIIA antibody 8B4D2 is unknown, but we confirmed that it is
located in the extracellular region of GluRIIA (Fig. S4). To confirm that the C-tail was indeed
disrupted in these new GluRIIA alleles, we generated an antibody against the terminal 18 amino
acids of the GluRIIA C-tail (anti-GluRIIAtail; Fig. 4C) and validated the antigen was intracellular
20

at the fly NMJ (Fig. S4). Using the GluRIIA
tail
antibody, we confirmed that the GluRIIA C-tail was
disrupted in each of the new GluRIIA truncation alleles, as expected (Fig. 4D,E). Remarkably,
pCaMKII was not detectable in either GluRIIA
ΔC20
, GluRIIA
ΔC6
, or GluRIIA
QRΔC19
, while total
CaMKII levels were unchanged (Fig. 4D,E). Thus, a short sequence at the C-terminal cytosolic
tail of the GluRIIA subunit is necessary for activated pCaMKII to be present at postsynaptic NMJ
compartments, consistent with this region serving as a CaMKII docking and activation site,
analogous to NMDARs at mammalian central synapses.
Loss of pCaMKII does not induce retrograde homeostatic signaling.
Active pCaMKII is lost in GluRIIA mutants, and postsynaptic overexpression of
constitutively active CaMKII blocks the expression of PHP (Fig. 1). We therefore considered the
possibility that the absence of active pCaMKII at the NMJ may be sufficient to enable retrograde
PHP signaling alone, or perhaps in combination with reduced Ca
2+
influx. Thus, we performed
electrophysiology in the GluRIIA C-tail truncation alleles and assessed whether any change in
presynaptic neurotransmitter release was observed. mEPSP amplitude was reduced in GluRIIA
null mutants, while mEPSP amplitude was unchanged compared to wild type in each of the new
GluRIIA C-tail truncation mutants, as expected (Fig. 5A,B). However, while presynaptic
neurotransmitter release was nearly doubled in GluRIIA null mutants, no change in EPSP
amplitude or quantal content was found in any of the GluRIIA C-tail truncation alleles (Fig. 5A-
E). Importantly, no change in quantal content indicative of PHP expression was found even
when loss of pCaMKII was combined with diminished Ca
2+
influx in the GluRIIA
QRΔC19
allele (Fig.
5A-E). Thus, loss of pCaMKII, even in combination with reduced Ca
2+
influx, is insufficient to
induce retrograde PHP expression.
Chimeric GluRIIB subunits swapped with the GluRIIA C-tail recruit pCaMKII and suppress
retrograde PHP signaling.
Although loss of pCaMKII at postsynaptic compartments is insufficient to induce PHP
expression, postsynaptic overexpression of constitutively active CaMKII in GluRIIA mutants
21

appears to suppress the retrograde signaling required for PHP expression (Fig. 1; (Haghighi et
al., 2003; Li et al., 2018a)). Therefore, we sought to determine if recruitment of active pCaMKII
at GluRIIA mutant NMJs was sufficient to occlude the signaling necessary for PHP expression.
To address this question, we generated chimeric GluRIIB receptor subunits in which the
entire GluRIIB C-tail was replaced with the GluRIIA C-tail. This chimeric GluRIIB receptor
subunit will be referred to as GluRIIBIIAtail (Fig. 6A). In GluRIIA null mutants, the entire
postsynaptic receptive field is composed of GluRB receptors, mEPSPs are reduced, and PHP is
expressed (Marrus et al., 2004; Petersen et al., 1997). To mimic this condition, we expressed
either wild type GluRIIB or chimeric GluRIIB
IIAtail
receptor subunits in a genetic background in
which both endogenous GluRIIA- and GluRIIB-receptor subunits are absent (IIA/IIB-/-), leaving
only GluRB receptors (Fig. 6B). GluRIIA mutants were indeed phenocopied in this condition,
with absence of GluRIIA expression and similar levels of GluRIIB expression (Fig. 6B,C). To
confirm these receptors encoded either the GluRIIB or GluRIIA tail, we also stained with anti-
GluR
IIAtail
or anti-GluRIIB, where the antigen targets the terminal 15 amino acids of the GluRIIB
C-tail (Marrus et al., 2004). As expected, with wild type GluRIIB expression, we observed loss of
both the anti-GluRIIA and anti-GluR
IIAtail
signals (Fig. 6B,C), as expected. However, this
relationship was reversed when chimeric GluRIIBIIAtail receptor subunits were expressed, with
increased anti-GluRIIA
tail
signal and loss of both anti-GluRIIA and -GluRIIB signals (Fig. 6B,C).
Interestingly, while the pCaMKII signal was absent in both GluRIIA null mutants and with
GluRIIB expression, as expected, the pCaMKII signal was present at wild-type levels when
chimeric GluRIIB
IIAtail
receptor subunits were expressed (Fig. 6B,C). These results demonstrate
that the GluRIIA C-tail is sufficient to recruit active pCaMKII at postsynaptic compartments even
when the native GluRIIA receptor subunit is absent.
Finally, we considered two possibilities for whether PHP could be induced at NMJs
expressing wild type or chimeric GluRB receptors. First, we speculated that pCaMKII may
simply be a marker of the GluRIIA C-tail and its activity may not be involved in endogenous PHP
22

signaling. In this scenario, constitutively active CaMKII expression may block retrograde PHP
signaling through a gain-of-function artifact, perhaps by non-specific phosphorylation of
postsynaptic machinery that ends up perturbing homeostatic signaling. In contrast, we
considered that perhaps a key event for PHP induction was physical loss of the GluRIIA C-tail.
This would lead to loss of pCaMKII and perhaps release a constitutive suppression of
retrograde PHP signaling normally imposed by active pCaMKII.
To distinguish between these possibilities, we recorded from control GluRIIA mutants
(GluRIIA null mutants and GluRIIB expression) or GluRIIA mutants composed of chimeric
GluRB receptors. As expected, mEPSP amplitudes were reduced by over 50% in all three
genotypes compared to wild type (Fig. 7A-C). Also as expected, EPSP amplitudes remained
similar to wild type in GluRIIA mutants and GluRIIB expression due to enhanced presynaptic
neurotransmitter release (quantal content), demonstrating robust PHP expression (Fig. 7A-E).
However, no change in presynaptic neurotransmitter release was observed in with chimeric
GluRIIB
IIAtail
expression, leading to diminished EPSP amplitude and indicating a failure to
express retrograde PHP signaling (Fig. 7A-E). Thus, the GluRIIA C-tail is sufficient to both
activate pCaMKII and suppress retrograde PHP signaling at GluRIIA mutant NMJs. Importantly,
the chimeric GluRIIB
IIAtail
condition is electrophysiologically identical to GluRIIA mutants,
including reduced mEPSP amplitudes and Ca
2+
influx. This suggests that pCaMKII is intimately
associated with the GluRIIA C-tail at postsynaptic compartments where it exerts a constitutive
suppression of retrograde PHP signaling. Loss of pCaMKII is therefore a key event necessary to
disinhibit PHP signaling (schematized in Fig. 7F).

23

2.4 Discussion
Presynaptic homeostatic potentiation was first described in 1997, where genetic loss of
the GluRIIA subunit reduced mEPSP amplitude but, surprisingly, synaptic strength was
unchanged from wild type (Petersen et al., 1997). It was immediately hypothesized that
reductions in postsynaptic Ca
2+
levels, due to loss of GluRIIA, was the key inductive signal to
initiate retrograde PHP signaling. Further studies of CaMKII at the Drosophila NMJ appeared to
support this model

(Goel et al., 2017a; Haghighi et al., 2003; Li et al., 2018a; Newman et al.,
2017), and speculation in favor of this prominent hypothesis has continued (Frank, 2014; Frank
et al., 2006, 2020) despite a lack of direct evidence to support it. Here, we have interrogated this
model and conclude that reduced Ca
2+
in postsynaptic compartments are not sufficient to induce
PHP signaling, nor is CaMKII activation sensitive to changes in Ca
2+
. Rather, our data support
an alternative model in which CaMKII activation is entirely dependent on a small domain
encoded in the C-tail of the GluRIIA receptor subunit, which in turn exerts a constitutive
suppression of retrograde homeostatic signaling. Thus, a key event in enabling PHP is
recognition of the physical loss of the GluRIIA C-tail at postsynaptic compartments.
CaMKII is a central regulator of Hebbian plasticity at postsynaptic compartments in the
mammalian brain. Three major roles for CaMKII have been described: Ca
2+
sensing during
plasticity and learning, structural plasticity, and scaffolding. Dynamic changes in postsynaptic
Ca
2+
are transformed into graded, longer term responses through activation of CaMKII (Hell,
2014). Importantly, CaMKII activity is sensitive to the pattern of Ca
2+
changes in addition to the
absolute amount, where such differences are thought to account for differential induction of
long-term potentiation or depression (Coultrap and Bayer, 2012). Another layer of regulation is
through an association with the NMDA receptor C-tail, which is critical to recruit CaMKII to the
postsynaptic compartment (Sanhueza and Lisman, 2013). This preserves an active CaMKII
state even after Calmodulin dissociation, facilitating autophosphorylation (Bayer and Schulman,
2019). In addition to these roles for CaMKII in Hebbian plasticity and learning, CaMKII is
24

important for structural plasticity at dendritic spines. Here, CaMKII interacts with the dendritic
cytoskeleton to drive spine enlargement (Nourbakhsh and Yadav, 2021; Stein et al., 2021).
Finally, CaMKII serves as a scaffold to promote assembly of signaling machinery in dendrites
(Colgan and Yasuda, 2014). In contrast to the overwhelming evidence for CaMKII having crucial
functions in Hebbian functional and structural plasticity at synapses, however, it is less clear to
what extent CaMKII operates in either homeostatic plasticity or retrograde signaling at
mammalian synapses.
Several lines of evidence suggest CaMKII is uniquely regulated at the Drosophila NMJ in
the context of retrograde homeostatic signaling. First, while Ca
2+
levels are a major control
mechanism to mobilize CaMKII to postsynaptic densities (Bayer and Schulman, 2019), levels of
pCaMKII at the fly NMJ appear to be completely insensitive to Ca
2+
. This is illustrated most
directly by the finding that pCaMKII levels are unchanged in GluRIIA
Q615R
(Fig. 2) despite a
major reduction in postsynaptic Ca
2+
. Second, while interactions with the NMDAR C-tail promote
CaMKII activity along with Ca
2+
in dendrites (Sanhueza and Lisman, 2013), pCaMKII appears to
absolutely require the GluRIIA C-tail. This implies an “all or nothing” binary switch between
CaMKII activation states which is entirely dependent on the presence of the GluRIIA C-tail. In
contrast, total CaMKII levels do not significantly change at postsynaptic NMJ compartments
regardless of the state of GluRIIA or Ca
2+
. These properties parallel associations between
CaMKII and other synaptic components in regulating the transition of sustained CaMKII activity
independently of Ca
2+
/Calmodulin binding in Drosophila (Hodge et al., 2006; Sun et al., 2004). It
is interesting to note that recent studies have demonstrated non-ionotropic signaling through
glutamate receptors 47, and CaMKII regulation by GluRIIA may be a new example of this mode
of signaling. One intriguing possibility is that the interaction between CaMKII and the GluRIIA C-
tail regulates a liquid-liquid phase separation with other postsynaptic components, as was
recently shown in mammals (Hosokawa et al., 2021). Therefore, Hebbian plasticity in the
25

mammalian brain and homeostatic plasticity at the NMJ may utilize distinct modes of CaMKII
regulation and mechanistic action.
Rather than functioning as a classical Ca
2+
sensor, we propose that CaMKII instead
works as a “GluRIIA sensor” to constitutively inhibit retrograde PHP signaling at the fly NMJ. In
this view, CaMKII does operate as a conventional Ca
2+
sensor to monitor ionic activity at
postsynaptic compartments but instead utilizes a docking or scaffolding function to recognize
the physical presence of GluRA receptors. When the GluRIIA subunit is present, PHP is
inhibited and, in this overly simplified model, genetic loss of GluRIIA releases this inhibition.
Clearly, there is more signal transduction necessary to activate the retrograde signaling system
necessary to express chronic PHP, with translational regulation appearing to play a key role
(Goel et al., 2017a; Haghighi et al., 2003). However, one necessary step is disinhibition of
retrograde signaling through loss of pCaMKII. The terminal portion of the GluRIIA C-tail may
serve as a CaMKII docking site to not only stabilize active pCaMKII but also organize its
signaling functions, paralleling CaMKII functions in dendritic spines (Colgan and Yasuda, 2014).
Short peptide domains that interact with CaMKII typically behave as pseudosubstrates by
interacting with the catalytic site to dislodge the Thr regulatory site and promote
autophosphorylation (Hell, 2014). The quintessential example of this type of peptide, the
GluN2B C-terminal domain, contains an optimal CaMKII consensus sequence (Coultrap and
Bayer, 2012). A similar CaMKII docking function has also been observed in the Drosophila Eag
potassium channel (Castro-Rodrigues et al., 2018). A short stretch of the GluRIIA C-tail also
encodes a conserved sequence with homology to these peptides, and CRISPR-mediated
deletion of this sequence abolishes pCaMKII. Thus, this C-tail domain in the GluRIIA subunit is
an attractive direct target for CaMKII interaction and regulation. However, it is possible that
CaMKII may interact with the GluRIIA C-tail indirectly, perhaps through other postsynaptic
components tightly associated with GluRs, such as the auxiliary GluR subunit Neto or
26

postsynaptic scaffold DLG. Indeed, in rodents, CaMKII phase separates with PSD95 and the
auxiliary receptor subunit Stargazin (Hosokawa et al., 2021).
The role we have described here for CaMKII is likely to be specific to chronic PHP
inductive signaling. For the rapid, pharmacological induction of PHP, a distinct process is likely
involved. There is substantial evidence to indicate that disparate postsynaptic signaling systems
operate to enable chronic PHP expression (due to genetic loss of GluRIIA) vs rapid PHP
(following pharmacological blockade of GluRs; (Goel and Dickman, 2021; Goel et al., 2017b; Li
et al., 2018a). For example, some genes are necessary only for chronic PHP, while they are
dispensable for rapid PHP (Goel and Dickman, 2021). Furthermore, while translational
regulation is necessary for chronic PHP

(Kauwe et al., 2016; Penney et al., 2012, 2016), rapid
PHP does not require new protein synthesis

(Böhme et al., 2019; Frank et al., 2006; Goel et al.,
2017b, 2019a). An important component of the postsynaptic signaling system that regulates
both chronic and rapid PHP is mono-ubiquitination by the ubiquitin ligase adapter Insomniac
(Kikuma et al., 2019). While we hypothesize that chronic PHP induction requires loss of the
GluRIIA C-tail and pCaMKII, clearly rapid PHP would necessitate a distinct mechanism, since
the GluRIIA tail still remains present. However, one important commonality between rapid and
chronic PHP is that reduced postsynaptic Ca
2+
does not seem to be involved in either process
(Goel et al., 2017a). Elucidating the induction mechanism of rapid PHP, and determining to what
extent CaMKII is involved, will be an exciting area of future research.
Our study not only reveals a novel interaction between postsynaptic GluRs and CaMKII
regulation at the NMJ, but highlights that PHP, and perhaps other types of homeostatic
plasticity, functions independently of Ca
2+
signaling. At dendrites of glutamatergic synapses in
the brain, Hebbian and homeostatic plasticity mechanisms work in conjunction to calibrate
synaptic strength and efficacy to enable the flexibility necessary for learning and memory while
preventing runaway excitation (Turrigiano, 2011). In this context, it would seem advantageous to
use Ca
2+
as a common signal to integrate the signal transduction and cross talk between
27

various forms of plasticity. However, the NMJ may not require such integration, since potent
homeostatic plasticity stabilizes this synapse to maintain muscle contraction, being essential for
behavior and life, while Hebbian plasticity is more limited. An additional contrast is that while
Hebbian plasticity and homeostatic receptor scaling are bi-directional processes at dendritic
spines (Keck et al., 2017), PHP appears to be uni-directional (Goel and Dickman, 2021).
Although loss of NMJ receptor functionality can clearly lead to motor dysfunction, increased
depolarization of the muscle is tolerated given the safety factor characteristic of all NMJs
(Marrus and DiAntonio, 2005). Thus, the unique characteristics of the NMJ may enable the
discovery of synaptic plasticity mechanisms that may not be as readily apparent at central
synapses.

28

2.5 Materials and Methods
Fly strains: Experimental flies were raised at 25°C on standard molasses food. The
w
1118
strain was used as the wild-type control unless otherwise noted, as this is the genetic
background for which all genotypes are bred. The following fly stocks were used: MHC-CD8-
GCaMP6f-Sh (Newman et al., 2017), G14-GAL4 (Aberle et al., 2002), MHC-GAL4 (Schuster et
al., 1996), GluRIIA
SP22
(Diantonio et al., 1999), MHC-GluRIIA (Petersen et al., 1997),
GluRIIΑ
SP16
(Petersen et al., 1997) and UAS-CaMKII
Ntide
(Chang et al., 1998). The following fly
stains was generated in this study: UAS-PV, UAS-GluRIIA, UAS-GluRIIB, UAS-GluRIIB
IIAtail
,
GluRIIA
Q615R
, GluRIIA
ΔC20
, GluRIIA
ΔC6
, GluRIIA
QRΔC19
. All other stocks were obtained from
Bloomington Drosophila Stock Center (BDSC): w
1118
(#5905), UAS-GluRIIA
M614R
(#64256),
Df(2L)clh4 (#6304), UAS-CaMKII (#29662), UAS-CaMKII-RNAi (#35330), UAS-CaMKIIAla
(#29666), UAS-CaMKII
T287D
(#29665), UAS-GluRIIA-RNAi (#27497), nos-Cas9 (#78782), Tub-
PBac (#8283) and attP2 (#8622).
Molecular Biology: To generate the UAS-PV and UAS-GluRIIB transgenes, we
obtained the cDNAs of PV from Addgene (Addgene #17301) and of GluRIIB from the
Drosophila Genomics Resource Center (DGRC #1374682). We inserted the PV and GluRIIB
cDNA sequences into the pACU2 vector (35; #31223, Addgene). Transgenic stocks were
generated by Bestgene, Inc (Chino Hills, CA 91709, U.S.A.) and inserted into w
1118
(#5905,
BDSC) fly strains by P-element-mediated random insertion. To generate the UAS-GluRIIBIIAtail
transgenes, the 5’ fragment of GluRIIB (1-2511 bp) and the 3’ fragment of GluRIIA (2510-2724
bp) were cloned from the cDNAs of GluRIIB and GluRIIA (Schmid et al., 2008). The GluRIIB
IIAtail

fragment was then generated by overlap extension PCR from the GluRIIB 5’ fragment and the
GluRIIA 3’ fragment. The GluRIIB
IIAtail
fragment was then inserted into pUAST vector (Brand and
Perrimon, 1993). The transgenic stock of UAS-GluRIIB
IIAtail
was generated by Eppendorf
InjectMan (Hamburg, Germany) and inserted into the w
1118
strain.
29

CRISPR/Cas9 mutagenesis: To generate the Ca
2+
impermeable GluRIIA
Q615R
allele, a
sequence containing 1 kb homology arms of the GluRIIA genomic region with the
Q615R
point
mutation was inserted into pHD-DsRed vector (#51434; Αddgene) as the CRISPR donor. Two
single guide RNAs (gRNA1: gaacaactcgacttggctga, gRNA2: ggtgggctccatcatgcaac) were
inserted together into the pAC-U63-tgRNA (#112811; Addgene) vector with intervening
tRNA(F+E) sequences for expressing multiple gRNAs (Poe et al., 2019). The donor construct
and the gRNA construct were then co-injected into a nos-Cas9 (#78782; BDSC) fly strain by
Well Genetics (Taipei City, Taiwan (R.O.C.)) to generate the GluRIIA
Q615R
mutant by homology-
directed repair. Successful CRISPR fly lines were selected by P3>DsRed expression in eyes
and confirmed by PCR. DsRed with flanking PBac sequence was then removed by PBac-
mediated excision suing the Tub>PBac fly strain (#8283, BDSC).
To generate endogenous GluRIIA tail truncations, two independent single guide RNAs
(sgRNAs; gRNA1: tctggaaccggatgatcgcc, gRNA2: ggaaaagtcccgcagcaaga) were inserted
together into the pAC-U63-tgRNA vector. The construct was then injected and inserted into the
attP2 (#8622, BDSC) fly strain by phiC31 integration. Fly strains carrying this transgene were
crossed to nos-Cas9 (#78782; BDSC) to generate putative truncation alleles, and GluRIIΑ
ΔC20

and GluRIIΑ
ΔC6
alleles were confirmed by PCR. GluRIIΑ
QRΔC19
was generated using a similar
approach but crossed to the GluRIIΑ
Q615R
strain.
Electrophysiology: Third-instar larvae were dissected in ice-cold modified HL3 saline
as described (Goel et al., 2019b; Kiragasi et al., 2020). Briefly, modified HL3 saline contained
(in mM): 70 NaCl, 5 KCl, 10 MgCl2, 10 NaHCO3, 115 sucrose, 5 trehalose, and 5 HEPES at pH
7.2. Guts, trachea, and the central nervous system were removed from larval body wall. The
preparation was perfused three times with fresh HL3 saline. For mEPSP and EPSP recordings,
sharp electrode (electrode resistance between 10-35 MΩ) recordings were performed on body
wall muscle 6 of segment Α2 and Α3 in HL3 saline with 0.4 mM CaCl2 added. Recordings were
conducted using an Olympus BX61 WI microscope with a 40x/0.80 water-dipping objective, and
30

acquired using an Axoclamp 900A amplifier, Digidata 1440A acquisition system and pClamp
10.5 software (Molecular Devices). To stimulate evoked EPSPs in muscles, 20 electrical
stimulations at 0.5 Hz with 0.5 msec duration were delivered to motor neurons using an ISO-
Flex stimulus isolator (A.M.P.I.) with stimulus intensities set to avoid multiple EPSPs.
Electrophysiological signals were digitized at 10 kHz and filtered at 1 kHz. Recordings were
rejected with input resistances lower than 5 Ωohm or resting potentials more depolarized than -
60 mV. Data were analyzed using Clampfit (Molecular Devices), MiniΑnalysis (Synaptosoft), or
Excel (Microsoft). Αverage mEPSP, EPSP, and quantal content values were calculated for each
genotype.
Immunocytochemistry: Third-instar larvae were dissected in modified HL3 saline and
stained either with or without 0.03% Triton in PBS as described (Kiragasi et al., 2020). The
following primary antibodies were used: mouse anti-GluRIIΑ (8B4D2; 1:50; Developmental
Studies Hybridoma Bank (DSHB)); rabbit anti-GluRIIIB (1:1000; (Perry et al., 2017)); rabbit anti-
GluRIIC (1:2000; (Goel and Dickman, 2018)); guinea pig anti-GluRIID (1:1000; (Perry et al.,
2017)); rabbit anti-parvalbumin (Pa1-933; 1:1000; Thermo Fisher); mouse anti-DLG (4F3; 1:100;
DSHB). The following primary antibodies were generated in this study, where the following
peptides were injected into animals by Cocalico Biologicals (Stevens, PA, U.S.A): affinity
purified rabbit anti-pCaMKII using the peptide C-VHRQET(p)VDCLKK (1:2000); guinea pig anti-
CaMKII using the peptide C-VHRQET(p)VDCLKK (1:1000); guinea pig anti-GluRIIΑtail using the
peptide C-SGSRRSSKEKSRSKTVS (1:2000). Alexa Fluor-647 conjugated goat anti-HRP
(1:200; Jackson ImmunoResearch) and Donkey anti-mouse, -guinea pig, and -rabbit conjugated
Alexa Fluor 488, Cy3, and DyLight 405 secondary antibodies (Jackson ImmunoResearch) were
used at 1:400.
Confocal imaging and analysis: Samples were imaged using a Nikon A1R Resonant
Scanning Confocal microscope equipped with NIS Elements software and a 100× APO 1.4 NA
or 60x 1.4 oil immersion objective using separate channels with four laser lines (405, 488, 561
31

and 637 nm) as described (Kiragasi et al., 2020). All genotypes compared were immunostained
in the same tube, mounted and imaged using the same procedure with identical reagents. Z-
stacks were acquired with step-size of 200 nm and pixel size of 0.06 nm using the same setting
across all genotypes compared. Maximum intensity projections were applied for quantitative
image analysis of Type Ib motor neuron boutons using Nikon Element software. Puncta of anti-
GluRIIΑ, -GluRIIB, -GluRIIC, -GluRIID, -DLG, -pCaMKII, -CaMKII, and GluRIIΑtail were
detected using thresholding of fluorescence intensity and object size to generate binary objects
in the general analysis tool kit in Nikon Elements software as described 69. Identical parameters
for image analysis were applied across all samples compared.
Ca
2+
imaging and analysis: Third-instar larvae were dissected in ice-cold modified HL3
saline. Larval preparations were imaged using a A1R Resonant Scanning Confocal microscope
equipped with NIS Elements software and a 60x APO 1.0NA water immersion objective as
detailed (Li et al., 2018a). Imaging was performed in modified HL3 saline with 1.5 mM Ca
2+

added. NMJs on muscle 6/7 were imaged with band scanning at a resonant frequency of 100
fps (512 x 86 pixels). Spontaneous Ca
2+
events were recorded at 4-8 individual NMJs during
120 sec imaging sessions from at least two different larvae. Horizontal drifting was corrected
using ImageJ plugins (Kang Li, 2008) and imaging data with severe muscle movements were
rejected as described (Ding et al., 2019). Three ROIs were manually selected using the outer
edge of terminal Ib boutons observed by baseline GCaMP signals with ImageJ (Rueden et al.,
2017; Schindelin et al., 2012). Ib and Is boutons were defined by baseline GCaMP6f
fluorescence levels, which are 2-3 fold higher at Ib NMJs compared to their Is counterparts at a
particular muscle. Fluorescence intensities were measured as the mean intensity of all pixels in
each individual ROI. ΔF for a spontaneous event was calculated by subtracting the baseline
GCaMP fluorescence level F from the peak intensity of the GCaMP signal during each
spontaneous event at a particular bouton. Baseline GCaMP fluorescence was defined as
average fluorescence in 2 secs of each ROI without spontaneous events. ΔF/F was calculated
32

by normalizing ΔF to baseline signal F. For each ROI under consideration, the spontaneous
event ΔF/F value was averaged for all events in the 60 sec time range to obtain the mean
quantal size for each bouton. Data analysis was performed with custom Jupyter Note codes.
Statistical Analysis: Data were compared using either a one-way ANOVA followed by
Tukey’s multiple comparison test or a Student’s t-test (where specified) and were analyzed
using Graphpad Prism or Microsoft Excel software and custom Jupyter Notebook codes.

33

Figure 1: Active CaMKII localizes to postsynaptic glutamate receptor fields and
correlates with GluRIIA expression. (A) Schematic depicting the subunit composition of
GluRA and GluRB glutamate receptor subtypes at the Drosophila NMJ. (B) Schematic and
representative traces illustrating that postsynaptic expression of constitutively active CaMKII
blocks the chronic expression of presynaptic homeostatic potentiation (PHP) that is normally
induced by loss of the GluRIIA subunit. Genotypes: wild type (w
1118
); GluRIIA-/- (w;GluRIIA
SP16
);
G14>CaMKII
T287D
(w;G14-GAL4/+;UAS-CaMKII
T287D
/+); G14>CaMKII
T287D
+GluRIIA-/- (w;G14-
GAL4,GluRIIA
SP16
/GluRIIA
SP16
;UAS-CaMKII
T287D
/+). (C) Quantification of mEPSP amplitude and
quantal content values in the indicated genotypes normalized to baseline values. (D) Schematic
of inactive and active versions of the CaMKII holoenzyme by phosphorylation at Thr-287. (E)
CaMKII protein structure and the antigenic sites used to generate anti-CaMKII- and -pCaMKII-
antibodies. Representative confocal images of the muscle 4 NMJ immunostained with anti-
CaMKII or anti-pCaMKII antibodies and co-stained with either the postsynaptic scaffold Discs
Large (DLG) or GluRIIA. (F) Representative images of NMJ boutons immunostained with anti-
pCaMKII, -GluRIIA, -GluRIID and -CaMKII in the indicated genotypes: GluRIIA RNAi (w;G14-
Gal4/+;UAS-GluRIIARNAi/+); GluRIIA OE (w;+;MHC-GluRIIA). (G) Quantification of mean
fluorescence intensity values of pCaMKII, GluRIIA, GluRIID and CaMKII normalized to wild-type
values in the indicated genotypes. Error bars indicate ±SEM. ***P<0.001, ****P<0.0001; ns, not
significant. Absolute values for normalized data are summarized in Table S1.

CaMKII
antibody
pCaMKII
antibody
GluRIIA RNAi GluRIIA OE GluRIIA
-/-
wild type
GluRIID GluRIIA pCaMKII CaMKII
Kinase
domain
Hub
domain
Regulatory
domain
A
E C
D
Phosphorylation
Activated
pCaMKII
Autoinhibited
CaMKII
B
E C
D
GluRA
receptor
GluRB
receptor
Thr 287- P
CaMKII pCaMKII
5 μm
A C
D E
F G
CaMKII
DLG
pCaMKII
GluRIIA
5 μm
10 mV
50 ms
0.5 s
1 mV
wild type G14>CaMKII
T287D
B GluRIIA
-/-
+GluRIIA
-/-
0
100
200
300
% control
****
***
****
ns
mEPSP
quantal
content
0
100
200
300
GluRIIA
-/-
Mean Intensity (% WT)
***
****
ns
ns
pCaMKII
GluRIIA
GluRIID
CaMKII
0
100
200
300
GluRIIA RNAi
**
****
ns
ns
pCaMKII
GluRIIA
GluRIID
CaMKII
0
100
200
300
GluRIIA OE
****
****
ns
pCaMKII
GluRIIA
GluRIID
CaMKII
ns
Thr 287
34

GluRIIA
Q615R
wild type G14>PV
Ca
2+
model
GluRIIA
Q615R
+G14>PV
GluRIIA
+
M1
M3
M4
M2
Q/R
C
N
wild type GluRIIA
-/-
GluRIIA
Q615R
G14>PV
Q
100% Ca
2+
~50% Ca
2+
~50% Ca
2+
R Q
~60% Ca
2+
R
~40% Ca
2+
GluRIIA
Q615R
+G14>PV
Ca
2+
IIA
Ca
2+
Q
Ca
2+
IIA
Ca
2+
IIA
R
IIA
Ca
2+
Q
PV Ca
2+
PV
IIA
Ca
2+
IIA
R
Ca
2+
PV PV
0
50
100
150 Ca
2+
transient
F/F (%wild type)
****
****
****
****
Ca
2+
Ca
2+
pCaMKII
GluRIID GluRIIB GluRIIA DLG CaMKII pCaMKII
5 μm
0
50
100
150
200
GluRIIA
-/-
Mean Intensity (% WT)
pCaMKII
GluRIIA
GluRIID
CaMKII
****
****
ns
ns
****
DLG
GluRIIB
**
0
50
100
150
200
GluRIIA
Q615R
pCaMKII
GluRIIA
GluRIID
CaMKII
ns ns ns ns ns
DLG
GluRIIB
ns
ns
0
50
100
150
200
G14>PV
pCaMKII
GluRIIA
GluRIID
CaMKII
ns ns ns ns ns
DLG
GluRIIB
ns
ns
0
50
100
150
200
GluRIIA
Q615R
+
G14>PV
pCaMKII
GluRIIA
GluRIID
CaMKII
ns ns ns ns ns
DLG
GluRIIB
ns
ns
ΔF/F=0.5
5 sec
A B C
D
F G
E
800
400
A.U.
400 ms
35

Figure 2: pCaMKII levels are insensitive to reductions in postsynaptic Ca
2+
. (A) Schematic
illustrating that loss of GluRA receptors decreases postsynaptic Ca
2+
influx and may reduce
pCaMKII levels at postsynaptic compartments. (B) Membrane topology of the GluRIIA subunit
with the
Q615R
mutation shown in the pore forming M2 domain. (C) Schematics illustrating Ca
2+

permeability through GluRA receptors and the Ca
2+
buffer parvalbumin (PV), with the associated
reductions in Ca
2+
observed in postsynaptic compartments. Genotypes: GluRIIA
Q615R

(w;GluRIIA
Q615R
); G14>PV (w;G14-GAL4/+;UAS-PV/+); GluRIIA
Q615R
+G14>PV
(w;GluRIIA
Q615R
,G14-GAL4/GluRIIA
Q615R
;UAS-PV/+). (D) Schematized GluRs and postsynaptic
Ca
2+
levels with representative Ca
2+
imaging traces. Line scans below are derived from
postsynaptic GCaMP6f images of individual spontaneous Ca
2+
transients in the indicated
genotypes: wild type (w;MHC-SynaptoGCaMP6f/+), GluRIIA-/- (w;GluRIIA
SP16
;MHC-
SynaptoGCaMP6f/+), GluRIIA
Q615R
(w;GluRIIA
Q615R
;MHC-SynaptoGCaMP6f/+), G14>PV
(w;G14-GAL4/+;UAS-PV/MHC-SynaptoGCaMP6f), GluRIIA
Q615R
+G14>PV (w;GluRIIA
Q615R
,G14-
GAL4/GluRIIA
Q615R
;UAS-PV/MHC-SynaptoGCaMP6f). (E) Representative images of NMJ
boutons immunostained with anti-GluRIIA, -GluRIIB, -GluRIID, -pCaMKII, -CaMKII and -DLG
antibodies in the indicated genotypes shown in (D) without MHC-GCaMP6f expression. (F)
Quantification of the normalized changes in fluorescence intensity (ΔF/F) of spontaneous Ca
2+

transient events at individual boutons in the indicated genotypes in (D). (G) Quantification of the
mean fluorescence intensity of anti-GluRIIA, -GluRIIB, -GluRIID, -pCaMKII, -CaMKII and -DLG
in the indicated genotypes normalized to wild-type values. Error bars indicate ±SEM. **P<0.01,
****P<0.0001; ns, not significant.

36

Figure 3: Reductions in postsynaptic Ca
2+
levels do not induce PHP expression. (A)
Schematic depicting genetic manipulations that reduce postsynaptic Ca
2+
levels at the
Drosophila NMJ. Representative electrophysiological traces are shown below each indicated
genotype. (B-D) Quantification of average mEPSP amplitude (B), EPSP amplitude (C), and
quantal content (D) values in the indicated genotypes in (A). (E) Quantification of mEPSP and
quantal content values of the indicated genotypes normalized to wild-type values. Error bars
indicate ±SEM. ****P<0.0001; ns, not significant. Absolute values for normalized data are
summarized in Table S1.

wild type GluRIIA
-/-
GluRIIA
Q615R
G14>PV
Q Q R
200 ms
20 ms
10 mV
1 mV
GluRIIA
Q615R
+G14>PV
R
A
B C D E
0.0
0.5
1.0
1.5
2.0
mEPSP (mV)
****
ns
ns
ns
0
10
20
30
40
50
EPSP (mV)
ns
ns
ns
*
0
20
40
60
80
quantal content
****
ns
ns
ns
0
50
100
150
200
250
% wild type
mEPSP
quantal
content
ns ns ns
****
****
ns ns ns
37

wild type GluRIIA
-/-
A
B
GluRIIA
M1
M3
M4
M2
C
N
GluRIIB
M1
M3
M4
M2
C
N
GluRIIB
IIAtail
M1
M3
M4
M2
C
N
pCaMKII
pCaMKII
C
G14>GluRIIB
IIAtail
(IIA/IIB null) G14>GluRIIB (IIA/IIB null)
pCaMKII CaMKII DLG
5 μm
GluRIIB IIA
tail
GluRIIA
0
50
100
150
200 G14>GluRIIB
****
****
ns
ns
****
**
pCaMKII
GluRIIA
GluRIIB
CaMKII
GluRIIA
tail
DLG
0
50
100
150
200 G14>GluRIIB
IIAtail
ns
****
ns
ns
ns
*
pCaMKII
GluRIIA
GluRIIB
CaMKII
GluRIIA
tail
DLG
0
50
100
150
200 GluRIIA
-/-
Mean Intensity (% WT)
****
****
****
ns
****
pCaMKII
GluRIIA
GluRIIB
CaMKII
GluRIIA
tail
**
DLG
38

Figure 4: Truncation of the GluRIIA C-tail abolishes active pCaMKII. (A) Schematic
illustrating the possibility that the GluRIIA C-tail stabilizes active pCaMKII at postsynaptic
compartments. (B) Amino acid alignment of the mouse CaMKII autoinhibitory domain and
homologous region in Drosophila, with the interaction sequences encoded in the C-tails of
mouse GluN2B, Drosophila EAG, and the putative CaMKII interaction domain in the Drosophila
GluRIIA C-tail. The black arrow indicates the Thr residue that is phosphorylated in active
pCaMKII. The red Arg residue indicates the necessary R-X-X-S motif; dark gray indicates
strongly conserved while light gray indicates weakly conserved residues. (C) Diagram of the
GluRIIA C-tail amino acid sequence and three mutant truncation alleles of the C-tail induced by
CRISPR mutagenesis. The regions of the two guide RNAs used to generate these alleles are
shown, as well as the antigenic domains of two GluRIIA-specific antibodies. (D) Representative
images of NMJ boutons immunostained with anti-GluRIIA, -GluRIIAtail, -GluRIIC, -pCaMKII, -
CaMKII and -DLG antibodies in the indicated genotypes: GluRIIA
ΔC20
(w;GluRIIA
ΔC20
),
GluRIIAΔC9 (w;GluRIIAΔC9), GluRIIA
QRΔC19
(w;GluRIIA
QRΔC19
). Note that the loss of the terminal
six amino acids of the GluRIIA C-tail is sufficient to completely lose pCaMKII signals. (E)
Quantification of mean fluorescence intensities of the indicated antibody signal normalized to
wild-type values. Error bars indicate ±SEM. *P<0.05, ****P<0.0001; ns, not significant.

39

Figure 5: Loss of active pCaMKII does not trigger retrograde homeostatic signaling. (A)
Schematics and representative traces showing that loss of the GluRIIA C-tail does not alter
spontaneous neurotransmission or presynaptic function. (B-D) Quantification of average
mEPSP amplitude (B), EPSP amplitude (C), and quantal content (D) values in the indicated
genotypes shown in (A). (E) Quantification of mEPSP and quantal content values of the
indicated genotypes normalized to wild-type values. Error bars indicate ±SEM. ****P<0.0001;
ns, not significant. Absolute values for normalized data are summarized in Table S1.

pCaMKII
Q Q Q
wild type GluRIIA
-/-
GluRIIA
ΔC20
GluRIIA
ΔC9
10 mV
200 ms
1 mV
R
GluRIIA
QR ΔC19
A
B C D E
0.0
0.5
1.0
1.5
2.0
mEPSP (mV)
****
ns ns ns
0
10
20
30
40
EPSP (mV)
****
ns ns ns
0
20
40
60
80
quantal content
****
ns ns ns
0
50
100
150
200
250
% wild type
****
ns
mEPSP
quantal
content
ns ns
****
ns ns ns
40

wild type GluRIIA
-/-
A
B
GluRIIA
M1
M3
M4
M2
C
N
GluRIIB
M1
M3
M4
M2
C
N
GluRIIB
IIAtail
M1
M3
M4
M2
C
N
pCaMKII
pCaMKII
C
G14>GluRIIB
IIAtail
(IIA/IIB null) G14>GluRIIB (IIA/IIB null)
pCaMKII CaMKII DLG
5 μm
GluRIIB IIA
tail
GluRIIA
0
50
100
150
200 G14>GluRIIB
****
****
ns
ns
****
**
pCaMKII
GluRIIA
GluRIIB
CaMKII
GluRIIA
tail
DLG
0
50
100
150
200 G14>GluRIIB
IIAtail
ns
****
ns
ns
ns
*
pCaMKII
GluRIIA
GluRIIB
CaMKII
GluRIIA
tail
DLG
0
50
100
150
200 GluRIIA
-/-
Mean Intensity (% WT)
****
****
****
ns
****
pCaMKII
GluRIIA
GluRIIB
CaMKII
GluRIIA
tail
**
DLG
41

Figure 6: Chimeric GluRIIB subunits, swapped with the GluRIIA C-tail, are now able to
recruit pCaMKII. (A) Schematic illustrating the intracellular C-tail domains of GluRIIA, GluRIIB
and the chimeric GluRIIB subunit substituted with the GluRIIA C-tail (GluRIIBIIAtail). (B)
Schematic and representative images of boutons stained with anti-GluRIIA, -GluRIIAtail, -
GluRIIB, -pCaMKII, -CaMKII and -DLG antibodies at NMJs of wild type and those containing
only GluRB receptors in the indicated genotypes: G14>GluRIIB (IIA/IIB-/-) (w;G14-
GAL4,GluRIIA
SP22
/Df(2L)clh4;UAS-GluRIIB/+), G14>GluRIIBIIAtail (IIA/IIB-/-) (w;G14-
GAL4,GluRIIA
SP22
/Df(2L)clh4;UAS-GluRIIBIIAtail/+). Note that GluRB receptors containing the
GluRIIA C-tail recruit pCaMKII at levels unchanged from wild type. (C) Quantification of mean
fluorescence intensity of the indicated antibodies in the indicated genotypes normalized to wild-
type values. Error bars indicate ±SEM. *P<0.05, **P<0.01, ****P<0.0001; ns, not significant.

42

Figure 7: Retrograde PHP signaling is occluded when pCaMKII is recruited to NMJs
lacking GluRA receptors. (Α) Schematic and representative traces illustrating that retrograde
PHP signaling is occluded at NMJs containing chimeric GluRB receptors, while PHP is robustly
expressed at NMJs containing wild-type GluRB receptors. Note that while mEPSP amplitudes
are similarly reduced at NMJs containing only GluRB receptors, presynaptic release does not
increase when pCaMKII is recruited to NMJs by chimeric GluRB receptors. (B) Quantification of
mEPSP and quantal content values in the indicated genotypes normalized to wild-type values.
(C-E) Quantification of average mEPSP amplitude (C), EPSP amplitude (D), and quantal
content values (E) in the indicated genotypes. (F) Schematic summarizing that active pCaMKII
is lost from postsynaptic compartments due to the physical absence of the GluRIIΑ C-tail. This
in turn releases the inhibition of retrograde PHP signaling. Error bars indicate ±SEM.
****P<0.0001; ns, not significant. Absolute values for normalized data are summarized in Table
S1.

20 ms
10 mV
200 ms
1 mV
pCaMKII
Retrograde
PHP signaling
Loss of the GluRIIA C-tail releases the
suppression of retrograde PHP signaling.
GluRIIA
Chronic Presynaptic
Homeostatic Potentiation
A B
C D E F
G14>GluRIIB
IIAtail
(IIA/IIBnull)
G14>GluRIIB
(IIA/IIBnull)
GluRIIA
-/-
wild type
0.0
0.5
1.0
mEPSP (mV) 1.2
**** **** ****
0
10
20
30
40
50
EPSP (mV)
ns
ns
****
0
20
40
60
80
100
quantal content
****
****
ns
0
50
100
150
200
250
% wild type
mEPSP
quantal
content
**** **** ****
**** ****
ns
43

Supplementary Figure S1: Validation of the anti-pCaMKII and -CaMKII antibodies. (A)
Representative images of NMJ boutons immunostained with anti-pCaMKII, -GluRIIA and -
GluRIID antibodies in the indicated genotypes: G14>CaMKIIRNAi (w;G14-GAL4/+;UAS-
CaMKIIRNAi/+), G14>CaMKII
Ntide
(w;G14-GAL4/USA-CaMKII
Ntide
), G14>CaMKIIAla (w;G14-
GAL4/UAS-CaMKIIAla), G14>CaMKII (w;G14-GAL4/+;UAS-CaMKII/+), G14>CaMKII
T287D

(w;G14-GAL4/UAS-CaMKII
T287D
). (B) Quantification of mean fluorescence intensity of pCaMKII,
GluRIIA and GluRIID puncta normalized to wild-type values. (C) Representative images of NMJ
boutons immunostained with anti-CaMKII, -DLG and -GluRIIC antibodies in the same genotypes
in (A). (D) Quantification of mean fluorescence intensity of pCaMKII, GluRIIA, and GluRIID
puncta normalized to wild-type values. Error bars indicate ±SEM. *P<0.05, **P<0.01,
****P<0.0001; ns, not significant. Absolute values for normalized data are summarized in Table
S1.

0
100
200
300
Mean Intensity (% WT)
pCaMKII
GluRIIA
GluRIID
0
50
100
150
200
Mean Intensity (% WT)
CaMKII
DLG
GluRIIC
G14>CaMKII
T287D
G14>CaMKII
Ntide
G14>CaMKII
Ala
G14>CaMKII
RNAi
wild type
GluRIIC DLG CaMKII
B
GluRIID GluRIIA pCaMKII
G14>CaMKII
T287D
G14>CaMKII
Ntide
G14>CaMKII
Ala
G14>CaMKII G14>CaMKII
RNAi
wild type
A
B
C
D
0
50
100
150
200
****
ns ns
CaMKII
DLG
GluRIIC
0
50
100
150
200
**** **
ns
CaMKII
DLG
GluRIIC
0
50
100
150
200
***
ns ns
CaMKII
DLG
GluRIIC
0
100
200
300
pCaMKII
GluRIIA
GluRIID
**
ns ns
0
100
200
300
pCaMKII
GluRIIA
GluRIID
**
**
ns
0
100
200
300
pCaMKII
GluRIIA
GluRIID
*
ns ns
0
100
200
300
pCaMKII
GluRIIA
GluRIID
****
*
ns
5 μm
5 μm
0
50
100
150
200
ns
ns
ns
CaMKII
DLG
GluRIIC
0
50
100
150
200
ns ns
ns
CaMKII
DLG
GluRIIC
0
100
200
300
pCaMKII
GluRIIA
GluRIID
****
ns
*
G14>CaMKII
44

wild type MHC>GluRIIA
M614R
GluRIID GluRIIB GluRIIA HRP
GluRIIA
GluRIIB
10 μm
A
C
0
50
100
150
Mean Intensity (% wild type)
***
***
**
GluRIIA
GluRIIB
GluRIID
0
50
100
150
Mean Intensity (% wild type)
GluRIIA
GluRIIB
GluRIID
B
5 μm
GluRIIA
GluRIIB
GluRIIA
M614R
overexpression
was thought to outcompete
endogenous GluRIIA
GluRIIA
M614R
overexpression
actually disrupts all GluR
trafficking
MHC>GluRIIA
M614R
GluRIIA
45

Supplementary Figure S2: Postsynaptic GluRIIA
M614R
overexpression disrupts GluR
trafficking. (A) Schematic illustrating the expected and actual GluRA and GluRB receptor
distributions at postsynaptic compartments in wild type and postsynaptic GluRIIA
M614R

overexpression. (B) Representative images of muscle 4 NMJs immunostained with anti-
GluRIIA, -GluRIIB, -GluRIID and -HRP antibodies in wild type or postsynaptic overexpression of
the GluRIIA
M614R
transgene: MHC>GluRIIA
M614R
(w;+;MHC-GAL4/UAS-GluRIIA
M614R
). Note that
all GluRs are reduced at postsynaptic compartments in MHC>GluRIIA
M614R
, with high levels of
GluRIIA apparently accumulating in intracellular muscle compartments. (C) Quantification of
mean fluorescence intensities of GluRIIA, GluRIIB and GluRIID subunits at NMJs normalized to
wild-type values. Error bars indicate ±SEM. **P<0.01, ***P<0.001. Absolute values for
normalized data are summarized in SI Appendix, Table S1.

46

Supplementary Figure S3: Parvalbumin localizes to postsynaptic compartments when
expressed in muscle. (A) Representative images of NMJs immunostained with anti-
parvalbumin (PV) and -DLG in wild type and postsynaptic expression of PV: G14>PV (w;G14-
GAL4/+;UAS-PV/+). (B) Images of individual boutons stained with anti-PV, -DLG and -HRP in
the indicated genotypes showing that PV largely overlaps with the postsynaptic density marker
DLG.

WT G14>PV
DLG PV HRP
A
B
10 μm
5 μm
DLG PV
47

Supplementary Figure S4: Antigenic topology of the monoclonal GluRIIA antibody
8B4D2. (A) Schematic illustrating the membrane topology of the GluRIIA subunit and use of
detergent (Triton) to determine the intracellular vs extracellular antigenic location of the
monoclonal GluRIIA antibody 8B4D2. (B) Representative images of NMJ boutons
immunostained with anti-GluRIIA, -GluRIIAtail, and -GluRIIC antibodies. The antigenic region of
the anti-GluRIIA monoclonal antibody resides in an extracellular region of GluRIIA, while both
anti-GluRIIAtail and anti-GluRIIC antibodies recognize the intracellular C-tail of the relevant
GluR subunit, as expected.

Anti-GluRIIA (+Triton) Anti-GluRIIA (-Triton)
GluRIIA GluRIIA
tail
A
B
GluRIIC
5 μm
M1
M3
M4
M2
C
N
M1
M3
M4
M2
C
N
GluRIIA
tail
GluRIIA GluRIIA
GluRIIA
tail
48

Supplementary Table 1: Absolute values for normalized data and additional statistical details.
The figure and panel, genotype, and conditions are noted. Average values (with standard error
of the mean noted in parentheses), data samples (n), and statistical significance tests and
values are shown for all data.

Figure Label Genotype
mEPSP
amplitude
(mV)
EPSP
amplitude
(mV)
QC
mEPSP
frequency
(Hz)
Rinput
(M Ω )
Resing
potential
(mV)
n
P Value
(significance):
mEPSP, EPSP, QC
1C wild type w
1118
1.035
(±0.045)
33.297
(±1.980)
32.125
(±1.100)
3.540
(±1.100)
9.50
(±0.307)
-69.172
(±1.707)
10 -
1C GluRIIA
-/-
w;GluRIIA
SP16
0.463
(±0.027)
31.493
(±0.920)
69.123
(±2.271)
2.978
(±0.097)
11.50
(±0.268)
-71.986
(±1.611)
10
<0.0001 (****),
0.421 (ns),
<0.0001 (****)
1C G14>CaMKII
T287D
w;G14-GAL4/+;
UAS-CaMKII
T287D
/+
1.000
(±0.053)
34.777
(±1.962)
34.707
(±0.520)
3.883
(±1.962)
10.20
(±10.2)
-66.131
(±2.383)
10 -
1C
G14>CaMKII
T287D
+GluRIIA
-/-
w;G14-
GAL4,GluRIIA
SP16
/GluRIIA
SP16
;
UAS-CaMKII
T287D
/+
0.446
(±0.017)
16.213
(±0.365)
69.123
(±2.271)
3.065
(±0.186)
11.80
(±0.359)
-72.855
(±2.812)
10
<0.0001 (****),
0.0001 (****),
<0.072 (ns)
3B-D wild type w
1118
1.018
(±1.018)
31.038
(±0.907)
31.503
(±2.253)
3.530
(±0.082)
9.41
(±0.608)
-69.179
(±2.174)
12 -
3B-D GluRIIA
-/-
w;GluRIIA
SP16
0.433
(±0.025)
29.203
(±1.117)
69.670
(±4.543)
3.095
(±0.263)
10.91
(±0.56)
-71.927
(±1.532)
12
<0.0001 (****),
0.646 (ns),
<0.0001 (****)
3B-D GluRIIA
Q615R
w;GluRIIA
Q615R
0.983
(±0.027)
32.968
(±1.041)
33.579
(±0.884)
3.439
(±0.095)
13.00
(±0.507)
-67.363
(±1.966)
12
0.946 (ns),
0.607 (ns),
0.942 (ns)
3B-D G14>PV
w;G14-GAL4/+;
UAS-PV/+
1.020
(±0.053)
26.675
(±1.670)
26.442
(±1.533)
3.607
(±0.124)
9.08
(±0.542)
-67.656
(±2.418)
12
0.999 (ns),
0.041 (*),
0.437 (ns)
3B-D
G14>PV
+GluRIIA
Q615R
w;GluRIIA
Q615R
,G14-
GAL4/GluRIIA
Q615R
;
UAS-PV/+
0.968
(±0.047)
31.983
(±1.030)
33.966
(±1.933)
3.517
(±0.119)
11.46
(±0.417)
-69.740
(±1.073)
13
0.812 (ns),
0.942 (ns),
0.893 (ns)
5B-D wild type w
1118
0.967
(±0.070)
29.844
(±1.016)
32.255
(±2.184)
3.049
(±0.108)
8.00
(±0.301)
-65.333
(±3.027)
11 -
5B-D GluRIIA-/- w;GluRIIA
SP16
0.475
(±0.028)
27.041
(±0.786)
58.885
(±3.936)
2.805
(±0.137)
11.00
(±0.333)
-66.874
(±3.300)
10
<0.0001 (****),
0.276 (ns),
<0.0001 (****)
5B-D GluRIIA
ΔC 2 0
w;GluRIIA
ΔC 2 0
1.045
(±0.053)
30.345
(±0.753)
30.108
(±1.956)
3.097
(±0.270)
9.30
(±0.307)
-69.720
(±2.299)
13
0.682 (ns),
0.992 (ns),
0.921 (ns)
5B-D GluRIIA
ΔC 9
w;GluRIIA
ΔC 9
1.099
(±0.036)
32.151
(±0.738)
29.661
(±1.262)
2.884
(±0.422)
12.42
(±0.453)
-69.533
(±2.688)
14
0.230 (ns),
0.371 (ns),
0.852 (ns)
5B-D GluRIIA
Q R ΔC 1 9
w;GluRIIA
Q R ΔC 1 9
1.000
(±0.069)
32.980
(±1.972)
34.678
(±2.997)
2.749
(±0.169)
12.90
(±0.414)
-69.449
(±3.077)
11
0.980 (ns),
0.176 (ns),
0.905 (ns)
7C-E wild type w
1118
1.029
(±0.051)
31.476
(±1.345)
31.421
(±2.213)
2.879
(±0.070)
12.00
(±0.381)
-66.272
(±3.715)
12 -
7C-E GluRIIA
-/-
w;GluRIIA
SP16
0.038
(±0.051)
28.283
(±1.265)
63.079
(±4.979)
2.563
(±0.094)
8.90
(±0.433)
-66.272
(±2.485)
10
<0.0001 (****),
0.331 (ns),
<0.0001 (****)
7C-E
G14>GluRIIB
(IIA/IIB null)
w;G14-
GAL4,GluRIIA
SP22
/Df(2L)cl
h4
;
UAS-GluRIIB/+
0.471
(±0.031)
29.264
(±2.159)
65.435
(±6.023)
2.915
(±0.149)
11.90
(±0.563)
-62.019
(±2.631)
11
<0.0001 (****),
0.596 (ns),
<0.0001 (****)
7C-E
G14>GluRIIB
IIAtail
(IIA/IIB null)
w;G14-GAL4,
GluRIIA
SP22
/Df(2L)cl
h4
;
UAS-GluRIIB
IIAtail
/+
0.466
(±0.033)
17.084
(±0.977)
38.857
(±3.815)
2.697
(±0.151)
10.91
(±0.312)
-72.750
(±3.831)
12
<0.0001 (****),
<0.0001 (****),
0.490 (ns)
S2 wild type w
1118
1.054
(±0.047)
30.539
(±2.015)
30.546
(±1.924)
3.027
(±0.089)
9.56
(±0. 772)
-65.493
(±4.576)
10 -
S2 MHC>GluRIIA
M614R
w;UAS-GluRIIA
M614R
/+;MHC-
GAL4/+
0.506
(±0.021)
33.400
(±0.785)
66.560
(±2.759)
2.697
(±0.151)
10.91
(±0.312)
-66.830
(±7.637)
6
<0.0001 (****),
0.573 (ns),
<0.0001 (*****)
Figure Label Genotypes
Quantal size
(Δ F /F )
n
P Value
(significance):
2F wild type w1118 0.020 (±0.00091) 12 -
2F GluRIIA
-/-
GluRIIA
SP16
0.010 (±0.00026) 12 <0.0001 (****)
2F G14>PV w;G14-GAL4/+;UAS-PV/+ 0.138 (±0.00061) 11 <0.0001 (****)
2F GluRIIA
Q615R
w;GluRIIA
Q615R
0.010 (±0.00033) 12 <0.0001 (****)
2F G14>PV+GluRIIA
Q615R
w;GluRIIA
Q615R
,G14-GAL4/GluRIIA
Q615R
;UAS-PV/+ 0.0077 ((±0.00034) 12 <0.0001 (****)
49

Chapter 3: Synaptic silencing by botulinum toxin reveals no
heterosynaptic plasticity between tonic and phasic inputs in
Drosophila

50

3.1 Abstract
The Drosophila larval NMJ has been studied for over 40 years as a model glutamatergic
synapse. Most muscles in Drosophila are innervated by two distinct motor neurons, the tonic
type "Ib" and the phasic type "Is", which differ in excitability, synaptic strength, and
morphological features. However, decades of electrophysiological recordings have been
studying nebulous averages of two independent neurons with very different properties, due to
lack of genetic drivers for selectively manipulating one motor neuron and genetic tools for
silencing both evoked and spontaneous transmission at Drosophila NMJ. This limitation led to
confounding postsynaptic responses that fail to accurately reflect the neurotransmission from
any actual synapse. Here, we developed a botulinum toxin (BoNT-C) to completely block both
evoked and spontaneous glutamate transmission at Drosophila NMJ without inducing any
impact on synaptic growth, structure, or innervation. With the amenability to selectively silence
Ib or Is motor neurons, we were able to functionally dissect the transmission and the release
patterns from the tonic Ib vs phasic Is synapses.
51

3.2 Introduction
The Drosophila NMJ has been studied as an optimal modeling system of glutamatergic
synapses. The NMJ system conserves, to a large extent, the similar molecular mechanisms
underlying synaptic strength, shot-term plasticity, and homeostatic plasticity in the excitatory
synapses in the mammalian central nervous system (Ruiz-Cañada and Budnik, 2006). Unlike
the mammalian NMJ structure where one muscle fiber is only innervated by one motor neuron,
the Drosophila body wall muscles are innervated by two individual motor neurons, the “tonic” Ib
and the “phasic” Is (Atwood et al., 1993; Hoang and Chiba, 2001). Although these two
converging motor neurons are both excitatory glutamatergic inputs, there is evidence that these
motor neuron synapses differ in transmission properties and firing patterns (Choi et al., 2004;
Kurdyak et al., 1994; Lnenicka and Keshishian, 2000; Lu et al., 2016) and participate in distinct
locomotion patterns of Drosophila (Schaefer et al., 2010).
More heterogeneities have been illustrated between these two motor neurons: the tonic
Ib motor neurons have lower release probability, firing patterns and smaller quantal size, while
the phasic Is motor neurons have more robust firing pattern and synaptic strength (Choi et al.,
2004; Karunanithi et al., 2002; Lu et al., 2016). However, the Ib synapses contribute to the
majority of muscle contraction (Newman et al., 2017). Recent studies using optogenetics have
suggested that Ib and Is motor neurons are differentially involved in the chronic or rapid forms of
PHP (Genç and Davis, 2019; Newman et al., 2017). First, Ib synapses express chronic PHP
while Is synapses express rapid PHP at low extracellular Ca
2+
. Second, the Ib and Is synapses
are both recruited in both chronic and rapid PHP at high extracellular Ca
2+
. Finally, Ib and Is
synapses are different at baseline transmission, where Is active zones have higher release Pr
and Ib AZs have lower Pr (Lu et al., 2016; Newman et al., 2017). Combining these evidence, it
is speculated that the rapid and chronic PHP are differentially expressed in Ib and Is synapses
and that the active zones at Ib and Is synapses are distinctly remodeled in chronic and rapid
PHP.
52

However, synaptic transmission and plasticity have been studied as an ambiguous
average between two distinct synapses due to lack of tools to separate them. In this thesis
work, I established new reagents to interrogate a non-ionotropic model underlying the induction
of PHP signaling in the postsynaptic muscle and engineered a genetic tool to separate the
converging Ib and Is inputs at Drosophila NMJ. We next developed BoNT-C as optimal genetic
tool for selectively manipulating synaptic transmission between the converging tonic and phasic
motor neurons at Drosophila NMJ. By comparing BoNT-C with several established genetic tools
existing many years in this field, we confirmed that BoNT-C provides a complete blockade of
both spontaneous and evoked transmission without inducing heterosynaptic plasticity. Thus, we
at the first time can clearly dissect the input-specific transmission from Ib and Is motor neurons
and to thoroughly study how the tonic and phasic synapses are distinctly involved in
homeostatic plasticity at Drosophila NMJ.

53

3.3 Results
Suboptimal approaches for selectively manipulating strong and weak neurotransmission
at the Drosophila NMJ.
To selectively target Ib or Is motor neurons, we verified the expression pattern of the
input specific GAL4 drivers previously reported (Broihier and Skeath, 2002; Genç and Davis,
2019). We overexpressed a GFP reporter driven by the dHB9-GAL4 (Ib) and R27E09-GAL4 (Is)
and co-stained postsynaptic scaffold protein Disc Large (DLG) to identify Ib and Is synapse (Fig.
S1C,D), which is more robustly accumulated at postsynaptic density at Ib synapse than Is
synapses at muscle 6/7(Menon et al., 2013). We then verified that the Ib driver targets the Ib
motor neurons innervating muscle 7,6 13 and 12, while the Is driver targets the Is motor
neurons innervating muscle 7, 6, 13, 12, 4, 3, 2 and 1 (Fig. S2A,C).
To functionally separate the synaptic transmissions from Ib and Is motor neurons, we
revisited several genetic tools previously used for manipulating neuron activities. First, we
overexpressed a tetanus toxin (TNT) (Sweeney et al., 1995) with Ib- or Is-specific GAL4 driver
to selectively silence the synaptic transmission in either of the two motor neurons (Fig. 1A).
However, the mEPSP from either Is or Ib is not significantly different from wild type level (Fig.
1B), which is in the contrary to the previous report that Is has larger quantal size and Ib smaller
(Newman et al., 2017). In addition, although EPSP in either Is or Ib synapses silenced by TNT is
significantly reduced than wild type level, the mEPSP frequency is not reduced from wild type
level (Fig. 1B). This is consistent with previous report that TNT only block evoked transmission
but does not completely remove spontaneous transmission (Sweeney et al., 1995). Second, we
overexpressed Reaper (Rpr) and Hid to selectively induce apoptosis in Ib or Is motor neurons
(Zhou et al., 1997) to genetically ablate the input. Overexpression of Rpr and Hid in Is cleanly
eliminated Is boutons at muscle 6/7 NMJ (Fig. S2B). However, genetic ablation of Ib motor
neurons at muscle 6/7 NMJ resulted in inconsistent removal of Ib boutons across all sample,
with total loss of Ib boutons in only 37% NMJ, partial bouton loss in 55% NMj and mild bouton
54

loss in 7% NMJ (Fig. S2E). This might be due to a various or late initiation of the Ib-specific
GAL4 driver. Moreover, Ib ablation led to failure of Is innervation across all samples (Fig. S2D).
As expected, Is ablation led to reduced EPSP similar to Is silencing by TNT and reduction in
mEPSP and mEPSP frequency (Fig. 1C,D). This is consistent with previous observation by
quantal imaging that Ib synapses have smaller quntal size and occupy two third of total
spontaneous transmission (Newman et al., 2017). We then quantified electrophysiological result
in all NMJ that had total loss of Ib boutons in Ib ablation and found completely depleted EPSP
and mEPSP (Fig. 1C,D). Third, we applied tissue-specifc knock out of vesicular glutamate
transporter (vGlut) in Is or Ib neurons which was previously reported to deplete entire synaptic
transmission at adult Drosophila NMJ (Banerjee et al., 2021). To our surprise, synaptic
transmission from neither Is or Ib synapses showed substantial defects (Fig. 1E,F), which might
be due to persistent maternally-contributed vGlut in 3
rd
instar larval NMJ. Overall, all these
approaches led to suboptimal result to distinguish synaptic transmissions between the tonic Ib
and the phasic Is motor neurons.
BoNT-C expression cleanly eliminates both spontaneous and evoked transmission.
After trying all the approaches discussed above and deeming them to be insufficient to
electrophysiologically separate the functional properties of the strong Is and weak Ib synapses,
we decided to develop a new approach. As potent clostridial toxins, botulinum toxins (BoNT)
function as protein enzymes to cleave SNARE proteins and disable synaptic transmission
(Backhaus et al., 2016; Sakaba et al., 2005). We cloned a series of botulinum neurotoxins
(BoNTs) for transgenic expression in Drosophila and evaluated the toxicity when each of these
BoNT was expressed with a pan-neuronal (C155) (Lin and Goodman, 1994) and a motor
neuron-specific (OK6) (Sanyal, 2009) GAL4 driver (Fig. S1A). If any of these BoNTs was able to
eliminate synaptic transmission in the entire nervous system or from all motor neurons, it should
cause lethality at larval stage. Driven by pan-neuronal driver, BoNT-B, -C and -E caused
lethality at larval stage while BoNT-A is viable. Only BoNT-B and -C caused lethality driven by
55

motor neuron-specific driver (Fig 2C). To avoid the lethality by BoNTs and to test whether
BoNTs could eliminate synaptic transmission, we overexpressed all the BoNTs with a motor
neuron specific GAL4 driver (OK319) (Sweeney et al., 1995), which only targets a subset of
motor neurons (Fig. S1B). We also overexpressed tetanus toxin (TNT) as a benchmark, which
has been previously reported to block only evoked synaptic transmission but not spontaneous
synaptic transmission at Drosophila NMJ (Sweeney et al., 1995). We found mEPSP and EPSP
were disrupted by BoNT-C (Fig. 2D) while not substantially affected by BoNT-A, -B or -E
compared to wild type level (Fig. S3). Surprisingly, BoNT-C eliminated both mEPSP and EPSP,
while TNT only removed EPSP at Drosophila NMJ (Fig. 2D). We then immunostained the
vesicular marker vGlut and active zone scaffold BRP to understand whether the synaptic
silencing by BoNT-C overexpression was due to disruption of presynaptic development or active
zone structure. Neither bouton number nor BRP density was significantly affected by synaptic
silencing with BoNT-C overexpression (Fig. 2C) while synaptic silencing with TNT caused slight
but significant increase in Is boutons and decrease in Ib boutons as previously reported
(Aponte-Santiago et al., 2020). Thus, with our toxicity and functional screening, we found BoNT-
C could block both mEPSP and EPSP in motor neuron synapses without inducing presynaptic
structural plasticity.
Input-specific silencing by BoNT-C does not induce heterosynaptic structural plasticity
at the m6 NMJ.
Genetic ablation of the phasic Is input induced a compensatory increase in synaptic
growth and in synaptic transmission at the Ib input (Wang et al., 2021). However, it was not
clear whether this heterosynaptic plasticity is caused by the loss of Is input or by the silencing of
Is transmission. This unsolved question raised our concerns that synaptic silencing of one motor
neurons might result in functional plasticity at the converging input, as our goal is to silence
synaptic transmission at converging Ib or Is motor neurons while leave the synaptic
transmission at the other input unaffected. Thus, we over expressed apoptosis effector proteins,
56

Rpr and Hid with Ib or Is driver to selectively ablate Ib or Is synapses. At muscle 6, Is
innervation is eliminated with Is ablation, while Ib slightly increase bouton number as previously
reported (Fig. 3C, (Wang et al., 2021)). Selective ablation of Ib motor neurons, on the other
hand, led to unconsistent ablation of Ib boutons and to failure of Is innervation (Fig 3C) as we
expected. Thus, for further evaluation of input-specific ablation of Ib motor neurons, we
immunostained with synaptic marker vGlut and DLG to rule out the NMJs without a complete
ablation of Ib synapses. On the contrary, synaptic silencing of Ib or Is motor neurons with BoNT-
C did not induce developmental plasticity as bouton number did not change at the silenced
synapses compared to wild type level (Fig. 3C,D). Moreover, neither the Ib or Is synapses
showed changed bouton numbers compared to wild type when the converging input was
silenced (Fig. 3C,D). Thus, BoNT-C is a potential tool to block glutamate transmission without
inducing synaptic growth or structural plasticity at the heterosynaptic input (Fig. 3A,B).
Input-specific silencing by BoNT-C enables accurate dissection of miniature and evoked
transmission from tonic and phasic NMJs.
To separate synaptic transmission between Ib and Is inputs, we overexpressed BoNT-C
with the Ib- or Is-specific driver. The input-specific mEPSP frequency, EPSP and quantal
content with Is or Ib synapses silenced by BoNT-C respectively, are significantly reduced from
wild type level (Fig. 4A,B). This result is consistent with previous studies that the Ib motor
neurons contribute 30% of the EPSP at Drosophila NMJ, while Is 70% (Genç and Davis, 2019;
Newman et al., 2017). Moreover, the Ib-specific mEPSP is 80% of wild type level, while Is-
specific mEPSP is 120% of wild type level (Fig. 4A,B). This difference in quantal size between
Ib and Is synapses have been observed by macropatch and postsynaptic GCaMP quantal
imaging, which might be explained by that the synaptic vesicle size at Is synapses is larger than
in Ib (Karunanithi et al., 2002; Newman et al., 2017).
We then questioned whether selective silencing Ib or Is motor neuron could induce
functional plasticity in the converging synapses. First, the Ib-specific mEPSP frequency occupy
57

70% of the total mEPSP frequency in wild type and the Is-specific mEPSP frequency is about
30 of wild type level (Fig. 4A,B). This is similar to previous observation by quantal imagingr in
wild type background (Newman et al., 2017). Second, the summation of average Ib- and Is-
specific EPSP is comparable to the wild type EPSP level and the proportion of Ib- or Is-specific
EPSP to the total wild type EPSP is consistent to previous report (Fig. 4C,D, (Lu et al., 2016;
Newman et al., 2017)). Finally, the weighted average of Ib- and Is-specific mEPSP on mEPSP
frequency is similar to wild type mEPSP (Fig. 4D), which itself is measured as a weighted
average of the spontaneous neurotransmission from Ib and Is synapse. Thus, input-specific
silencing of synaptic transmission allows accurate dissection of spontaneous and evoke
transmission from Ib and Is motor neurons at Drosophila NMJ.
Tonic and phasic activity does not specialize postsynaptic GluR fields
The postsynaptic glutamate receptors at the NMJ assemble as heteromeric tetramers
containing three essential subunits (GluRIII, IID and IIE) and a variable fourth subunit of GluRIIA
or GluRIIB, with the GluRIIA subtypes having a higher conductance than GluRIIB. Although Ib
and Is motor neurons are both glutamatergic terminals and innervate the same muscle fiber, the
GluRA-type receptors accumulate more abundantly at the Ib postsynaptic receptor field than at
Is receptor field (Marrus et al., 2004). As the glutamate receptor composition is dynamically
modulated by synaptic activity at a single active zone (Schmid et al., 2008), it has been
speculated that the differential accumulation of GluRIIA between Ib and Is receptor fields might
be dependent on the distinct tonic and phasic synaptic transmission from Ib and Is input. We
tested this hypothesis by silencing all synaptic transmission at both Ib and Is synapses at NMJ
and immunostained the GluRIIA, GluRIIB and the common GluRIID subunits. At wild type
NMJs, GluRIIA preferentially accumulated at Ib receptor field than at Is, while GluRIIB and
GluRIID did not differ between Ib and Is synapses (Fig. 5A,B). Surprisingly, when the Ib and Is
synapses are deprived from synaptic transmission, the preferential accumulation of GluRIIA at
Ib receptor field is still present (Fig. 5C,D).
58

The receptor composition at single active zone is another dimension which was also
speculated to be orchestrated by neurotransmission at individual active zones where glutamate
receptor composition is corresponding to heterogeneous release propability of individual active
zones (Akbergenova et al., 2018). At wild type synpases, we observed substantial GluRIIA/B
segregation where GluRIIA concentrated at the center of PSD while GluRIIB at the peripheral of
PSD in both Ib and Is synapses (Fig. 5E). At synapses silenced with BoNT-C, this receptor
composition persisted even with all synaptic transmission eliminated by BoNT-C (Fig. 5F). Thus,
the composition of postsynaptic GluR field is not specialized by the tonic or phasic patterns of
transmission from Ib or Is motor neurons.
Phasic neuronal silencing by BoNT-C does not induce structural or functional
heterosynaptic plasticity at the m12 NMJ.
We observed heterosynaptic plasticity at converging motor neurons with genetic ablation
of Ib or Is inputs induced, while not with synaptic silencing with BoNT-C. However, Ib motor
neurons synapse on one single muscle cell while Is motor neurons innervate multiple muscle
targets at Drosophila segmental NMJs (Fig. S1A). Thus, it is not clear if this heterosynaptic
plasticity between converging motor inputs requires a specific postsynaptic target or is a general
effect at all segmental NMJs. Furthermore, retrograde homeostatic plasticity could occur at one
NMJ but leave the divergent NMJ unaffected from the same motor neuron (Li et al., 2018a).
Therefore, it is important to question whether synaptic silencing Is input would not induce
heterosynaptic plasticity at other NMJs innervated by the same Is input. Because Ib ablation
disrupt convergent Is innervation, we first tested genetic ablation of Is input innervating muscle
12, which receives the same Is innervation as muscle 6. With Is synapses cleanly removed, Ib
synapses showed 30% compensatory increase in bouton number, a robust reduction in EPSP
and a 30% reduction in mEPSP (Fig. 6D), which is consistent with the previously observation
(Wang et al., 2021). On the other hand, no changed bouton number was observed at Ib or Is
synapses with Is silenced with BoNT-C overexpression (Fig. 6E). We observed similar reduction
59

in mEPSP, and mEPSP frequency of Ib transmission with Is silencing compared to Is ablation
but more robust reduction in EPSP (Fig. 6D,E). This was expected as compensatory increase of
EPSP in Ib was observed with genetic ablation of Is input, but not with Is silencing at muscle 6.
Thus, muscle 12 NMJ preserve similar heterosynaptic plasticity in synaptic growth and
transmission at Ib input with genetic ablation of Is input, which is not induced by synaptic
silencing of Is with BoNT-C. As this compensatory change of Ib synapses is conserved on a
different muscle innervated by the same Is motor neuron, it suggested this heterosynaptic
plasticity is not target-specific and BoNT-C could work as an optimal tool for input-specific
silencing at multiple ventral muscles.

60

3.4 Discussion
Several approaches have been attempted to manipulate synaptic transmission in
Drosophila nervous system. First, TNT overexpression in motor neurons does not efficiently
remove spontaneous synaptic transmission while eliminates evoked transmission (Sweeney et
al., 1995). Second, genetic ablation by overexpression of Reaper and Hid in Drosophila Is motor
neurons induces compensatory heterosynaptic plasticity in converging Ib motor neurons (Wang
et al., 2021; Zhou et al., 1997). Finally, tissue-specific knock out of vGlut removes both evoked
and spontaneous synaptic transmission in adult Drosophila NMJ while has no effect in either
transmissions in 3
rd
instar lavae NMJ (Fig. 1E,F). Thus, none of these established genetic tools
provide a clean manipulation of synaptic transmission at Drosophila NMJ. We developed BoNT-
C as optimal genetic tool for selectively manipulating synaptic transmission between the
converging tonic and phasic motor neurons at Drosophila NMJ. By comparing BoNT-C with
several established genetic tools existing many years in this field, we confirmed that BoNT-C
provides a complete blockade of both spontaneous and evoked transmission without inducing
heterosynaptic plasticity. Thus, we at the first time can clearly dissect the input-specific
transmission from Ib and Is motor neurons and to thoroughly study how the tonic and phasic
synapses are distinctly involved in homeostatic plasticity at Drosophila NMJ.
The botulinum toxins, alongside with TNTs disrupts synaptic vesicle fusion by
enzymatically cleaving SNARE components which is essential for Ca
2+
triggered synaptic
vesicle release. Each of the BoNT and TNT has a distinct target in the SNARE complex, which
might result in a specific impact in vesicle release. TNT has been established as a genetic tool
to block synaptic transmissions in Drosophila (Sweeney et al., 1995). However, TNT-dependent
cleavage of Synaptobrevin only eliminates Ca
2+
-depenent evoked synaptic vesicle fusion while
leaves spontaneous synaptic vesicle fusion intact (Sweeney et al., 1995). Moreover, genetically
driven TNT overexpression showed inconsistency in synaptic silencing in distinct cell types in
Drosophila (Rister and Heisenberg, 2006; Thum et al., 2006; Zhu et al., 2009). At mammalian
61

CNS synapses, BoNT-A reduced Ca
2+
sensitivity for vesicle fusion while BoNT-C blocked
vesicle fusion (Sakaba et al., 2005). In Drosophila, previous study showed that BoNT-B
completely cleavage of n-syb, while BonT-A and -C had partial cleavage of SNAP-25 and
Syntaxin (Backhaus et al., 2016). However, it is unclear how BoNTs disrupting different
proteolytic targets in SNARE complex could have unique impact in synaptic transmission at
Drosophila NMJ.
Several lines of evidence suggest synaptic structures are regulated by changing
synaptic activities at Drosophila NMJ. First, genetic ablation of Is motor neurons caused
heterosynaptic plasticity in the converging Ib motor neurons (Wang et al., 2021). However,
synaptic silencing by BoNT-C of either Ib or Is motor neurons did not induce significant
heterosynaptic plasticity in the converging input (Fig. 3C,D). Second, synaptic silencing by
tissue-specific knock out of vGlut after 10 days of enclosion, induced bouton area and active
zone shrinkage, which persisted thoughout larval and early adulthood. Consistenly, synaptic
silencing with boNT-C has no impact on active zoon scaffold BRP area at 3
rd
instar larvae (Fig.
2C). Third, CaMKII is uniquely regulated at the Drosophila NMJ in the context of retrograde
homeostatic signaling.
62

3.5 Materials and Methods
Fly stocks: Drosophila stocks were raised at 25°C on standard molasses food. The
w
1118
strain is used as the wild type control unless otherwise noted as this is the genetic
background in which all genotypes are bred. The following fly stocks were used: UAS-Rpr.Hid
(Zhou et al., 1997), OK319-GAL4 (Sweeney et al., 1995), OK6-GAL4 (Sanyal, 2009). B3RT-
vGlut-B3RT, UAS-B3, vGlut
SS1
(Sherer et al., 2020).The following fly stains was generated in
this study: UAS-BoNT-A, UAS-BoNT-B, UAS-BoNT-C and UAS-BoNT-E. All other stocks were
obtained from Bloomington Drosophila Stock Center (BDSC): UAS-TNT (#28838), R27E09-
GAL4 (#49227), dHB9-GAL4 (#83004), UAS-CD4-tdGFP (#35839).
Molecular Biology: To generate UAS-BoNT-A, -B -C and -E plasmids, light chains of
BoNT-A (KR260972), -B (KR260973), -C (KR260974), and -E (KR260975) were obtained from
Genbank and inserted into the pACU2 vector (35; #31223, Addgene). Transgenic stocks were
generated by Bestgene, Inc (Chino Hills, CA 91709, U.S.A.) and inserted into w
1118
(#5905,
BDSC) fly strains by P-element-mediated random insertion.
Immunocytochemistry: Third-instar larvae were dissected in ice cold 0 Ca
2+
HL-3 and
immunostained using a standard protocol as described (Chen and Dickman, 2017; Goel et al.,
2017a). In brief, larvae were either fixed in Bouin’s fixative for 5 min (Sigma, HT10132-1L),
100% ice-cold ethanol for 5 min, or 4% paraformaldehyde (PFA) for 10 min. Larvae were then
washed with PBS containing 0.1% Triton X-100 (PBST) for 30 min, blocked with 5% Normal
Donkey Serum followed by overnight incubation in primary antibodies at 4°C. Preparations were
then washed 3x in PBST, incubated in secondary antibodies for 2 hours, washed 3x in PBST,
and equilibrated in 70% glycerol. Prior to imaging, samples were mounted in VectaShield
(Vector Laboratories). The following primary antibodies were used: mouse anti-GluRIIΑ (8B4D2;
1:50; Developmental Studies Hybridoma Bank (DSHB)); rabbit anti-GluRIIIB (1:1000; (Perry et
al., 2017)); guinea pig anti-GluRIID (1:1000; (Perry et al., 2017)); mouse anti-GFP (C49; 1:500;
DSHB), guinea pig anti-vGlut (1:1500, (Goel and Dickman, 2018)), rabbit anti-DLG (1:100;
63

(Pielage et al., 2005)). Alexa Fluor-647 conjugated goat anti-HRP (1:200; Jackson
ImmunoResearch) and Donkey anti-mouse, -guinea pig, and -rabbit conjugated Alexa Fluor
488, Cy3, and DyLight 405 secondary antibodies (Jackson ImmunoResearch) were used at
1:400.
Imaging and analysis: Samples were imaged as described (Perry et al., 2017) using a
Nikon A1R Resonant Scanning Confocal microscope equipped with NIS Elements software and
a 100x APO 1.4NA oil immersion objective using separate channels with four laser lines (405
nm, 488 nm, 561 nm, and 647 nm). For fluorescence intensity quantifications of vGlut, DLG,
GluRIIA, GluRIIB and GluRIID, z-stacks were obtained on the same day using identical gain and
laser power settings with z-axis spacing between 0.15-0.20 µm for all genotypes within an
individual experiment. Maximum intensity projections were utilized for quantitative image
analysis using the general analysis toolkit of NIS Elements software. The fluorescence intensity
levels of vGlut, DLG, GluRIIA, GluRIIB and GluRIID immunostaining were quantified by applying
intensity thresholds and filters to binary layers in the 405 nm, 488 nm, and 561 nm channels.
The mean intensity for each channel was quantified by obtaining the average total fluorescence
signal for each individual punctum and dividing this value by the puncta area. The sum intensity
for GluRIIA, GluRIIB, and GluRIID was quantified as the total fluorescence signal of each
individual GluR punctum. A mask was created around the HRP or DLG channel, used to define
the neuronal or postsynaptic membrane, and only puncta within this mask were analyzed to
eliminate background signals. All measurements based on confocal images were taken from
synapses acquired from at least six different animals.
Electrophysiology: All dissections and two-electrode voltage clamp (TEVC) recordings
were performed as described (Kikuma et al., 2019) using modified hemolymph-like saline (HL-3)
containing (in mM): 70 NaCl, 5 KCl, 10 MgCl2, 10 NaHCO3, 115 Sucrose, 5 Trehelose, 5
HEPES, and 0.5 CaCl2, pH 7.2, from cells with an initial Vm between -60 and -75 mV, and input
resistances >6 MΩ. Recordings were performed on an Olympus BX61 WI microscope using a
64

40x/0.80 NA water-dipping objective and acquired using an Axoclamp 900A amplifier, Digidata
1440A acquisition system and pClamp 10.5 software (Molecular Devices). Miniature excitatory
postsynaptic currents (mEPSCs) were recorded in the absence of any stimulation with a voltage
clamp of -80 mV, and low pass filtered at 1 kHz. All recordings were made on abdominal muscle
6, segments A2 and A3 of third instar larvae with the leak current never exceeding 5 nA.
mEPSCs were recorded for 60 seconds and analyzed using MiniAnalysis (Synaptosoft) and
Excel (Microsoft) software. The average mEPSC amplitude and total charge transfer values for
each muscle were obtained from approximately 100 events in each recording.
Statistical analysis: Data were analyzed using GraphPad Prism (version 7.0) or
Microsoft Excel software (version 16.22). Sample values were tested for normality using the
D’Agostino & Pearson omnibus normality test which determined that the assumption of
normality of the sample distribution was not violated. Data were then compared using either a
one-way ANOVA and tested for significance using a Tukey’s multiple comparison test or using
an unpaired 2-tailed Student’s t-test with Welch’s correction. All data are presented as mean +/-
SEM; n indicates sample number and p denotes the level of significance assessed as p<0.05
(*), p<0.01 (**), p<0.001 (***), p<0.0001 (****); ns=not significant.

65

Figure 1: Suboptimal approaches for selectively manipulating strong and weak
neurotransmission at the Drosophila NMJ. (A) Schematic and representative traces of
mEPSP and EPSP illustrating that overexpression of TNT in Ib or Is motor neurons and the
evoked EPSP is reduced by synaptic silencing with TNT. Genotypes: wild type (w
1118
); Is>TNT
(w;+;Is-GAL4/UAS-TNT); Ib>TNT (w;+;Ib-GAL4/UAS-TNT). (B) Quantification of mEPSP (mV),
mEPSP frequency (Hz), EPSP (mV) and quantal content in the indicated genotypes in (A). (C)
Schematic and representative traces of mEPSP and EPSP illustrating that overexpression of
Ripper and Hid in Ib or Is motor neurons and the evoked EPSP is reduced by synaptic ablation
with Rpe and Hid. Note that Is synapses are completely removed with Ib ablation. Genotypes:
wild type (w
1118
); Is>Rpr.Hid (UAS-Rpr.Hid/+;+;Is-GAL4/+); Ib>Rpr.Hid (UAS-Rpr.Hid/+;+;Ib-
GAL4/+). (D) Quantification of mEPSP (mV), mEPSP frequency (Hz), EPSP (mV) and quantal
content in the indicated genotypes in (C). (E) Schematic and representative traces of mEPSP
and EPSP illustrating that overexpression of conditional vGlut knock out in Ib or Is motor
neurons. Genotypes: wild type (w
1118
); Is>vGlut
-/-
(w;vGlut
SS1
/B3RT-vGlut-B3RT;UAS-B3/Is-
GAL4)Is>vGlut
-/-
; Ib>vGlut
-/-
(w;vGlut
SS1
/B3RT-vGlut-B3RT;UAS-B3/Ib-GAL4)Is>vGlut
-/-
. (F)
Quantification of mEPSP (mV), mEPSP frequency (Hz), EPSP (mV) and quantal content in the
indicated genotypes in (E).

50 ms
10 mV
500 ms
2 mV
Is>TNT wild type Ib>TNT
50 ms
10 mV
2 mV
500 ms
Is>Rpr.Hid wild type Ib>Rpr.Hid
A B
C D
E F
Is>vGlut
-/-
wild type Ib>vGlut
-/-
50 ms
10 mV
500 ms
2 mV
0
10
20
30
40
50
EPSP (mV)
****
****
0.0
0.5
1.0
1.5
mEPSP (mV)
ns ns
ns
0
20
40
60
apparant QC
****
**
0
1
2
3
4
mEPSP freq. (Hz)
****
***
0
10
20
30
40
50
EPSP (mV)
****
****
0.0
0.5
1.0
1.5
mEPSP (mV)
**
****
0
20
40
60
apparant QC
****
****
0
1
2
3
4
mEPSP freq. (Hz)
** **
0
1
2
3
4
mEPSP freq. (Hz)
ns *
0
10
20
30
40
50
EPSP (mV)
*
ns
0.0
0.5
1.0
1.5
mEPSP (mV)
ns
*
0
20
40
60
apparent QC
ns
*
66

Figure 2: BoNT-C expression cleanly eliminates both spontaneous and evoked
transmission. (A) Schematic of synaptic vesicular snare proteins and the specificity the
enzymatic target of TNT and BoNTs. (B) Amino acid alignment of the mouse mVamp2,
mSNAP25 and mSyntaxin-1A and the Drosophila n-Syb, dSNAP25 and dSyntaxin. Arrows
illustrate the cleavage sites of TNT, BoNT-A, BoNT-C and BoNT-E. (C) BoNT screening
pipeline. Four BoNT lines were first tested on lethality with expression with a pan-neuronal
GAL4 driver, a motor neuron-specific GAL4 Driver and a subset motor neuron GAL4 driver in
each step. The BoNT lines that did not induce lethality or disrupted synaptic transmission are
removed from the screening at each step. (D) Representative images of NMJ boutons at muscle
6 immunostained with anti-vGlut, -DLG, -BRP and -HRP in the indicated genotypes. Genotypes:
OK319>BoNTC OK319>TNT
vGlut DLG HRP
wild type
Ib BRP Is BRP
Ib BRP Is BRP
5 μm
Ib BRP Is BRP
M6 M6 M6
200 ms
1 mV
20 ms
10 mV
Subset motor
neuron
expression
BoNT-B
Transmission
persists
BoNT-C
BoNT-A
BoNT-B
BoNT-C
BoNT-E
BoNT-B
BoNT-C
BoNT-E
BoNT-B
BoNT-C
Pan-neuronal
expression
BoNT-A
viable
Motor neuron
expression
BoNT-E
viable
Transgenes Lethal
Transmission
eliminated
Lethal
SNAP-25 Syx
nSyb
TNT
BoNT-E
BoNT-C
BoNT-A
BoNT-E
Synaptic vesicle
dn-Syb KLSELDDRADALQQGASQFEQQAGKLKRKFWL
mVamp2 KLSELDDRADALQAGASQFETSAAKLKRKYWW
78 109
TNT & BoNT-B
dSNAP-25 NQNRQIDRINRKGESNEARIAVANQRAHQLLK
mSNAP-25 TQNRQIDRIMEKADSNKTRIDEANQRATKMLG
181 212
BoNT-E BoNT-A
dSyntaxin-1A DYVQTATQDTKKALKYQSKARRKKIMILICLT
mSyntaxin-1A DYVERAVSDTKKAVKYQSKARRKKIMIIICCV
245 276
BoNT-C
A B
C
D
10 μm
E
F G
5 μm 10 μm
0
50
100
150
% wild type M6
ns
Ib Is
ns
Bouton
#
BRP
intensity
*
*
0
50
100
150
% wild type M6
ns
ns
ns
ns
Bouton
#
BRP
intensity
Ib Is
OK319>BoNTC OK319>TNT wild type
0
50
100
% wild type
ns
****
mEPSP
amp
EPSP
amp
120
0
50
100
% wild type
****
****
mEPSP
amp
EPSP
amp
120
67

wild type (w
1118
;+;+); OK319>TNT (w;OK319-GAL4/UAS-TNT;+). Quantification of mean
fluorescence intensity values of BRP and bouton number normalized to wild-type values in the
indicated genotypes in Ib and Is synapses. (E) Representative images of NMJ boutons at
muscle 6 immunostained with anti-vGlut, -DLG, -BRP and -HRP in the indicated OK319>BoNT-
C (w;OK319-GAL4/UAS- BoNT-C;+). Quantification of mean fluorescence intensity values of
BRP and bouton number normalized to wild-type values in (D) in the indicated genotypes in Ib
and Is synapses. (F) Schematic and representative traces illustrating that presynaptic
expression of TNT and blockade of evoked synaptic transmission at Drosophila NMJ.
Quantification of mEPSP and EPSP amplitude in the indicated genotypes normalized to wild
type values. (G) Schematic and representative traces illustrating that presynaptic expression of
BoNT-C and blockade of evoked and spontaneous synaptic transmission at Drosophila NMJ.
Quantification of mEPSP and EPSP amplitude in the indicated genotypes normalized to wild
type values.
68

Figure 3: Input-specific silencing by BoNT-C does not induce heterosynaptic structural
plasticity at the m6 NMJ. (A) Schematic of Ib and Is motor neurons innervating muscle 6 and 7
in the segmental muscle fibers. (B) Table illustrating change in bouton number of Ib or Is
synapses at muscle 6 normalized to wild type value in when Rpr.Hid or BoNT-C overexpressed
with Ib- and Is-specific GAL4 driver. (C) Representative images of NMJ boutons at muscle 6
immunostained with anti-vGlut, -DLG and -HRP in the indicated genotypes: wild type (w
1118
,+,+);
Is>Rpr.Hid (Rpr.Hid/+;Is-GAL4/+); Ib> Rpr.Hid (Rpr.Hid/+;Ib-GAL4/+). Quantification of bouton
number of Ib and Is synapses normalized to wild-type values in the indicated genotype. (D)
Representative images of NMJ boutons at muscle 6 immunostained with anti-vGlut, -DLG and -
HRP in the indicated genotypes: wild type (w
1118
,+,+); Is>BoNT-C (w;+;Is-GAL4/UAS-BoNT-C);
Ib>BoNT-C (w;+;Ib-GAL4/UAS-BoNT-C). Quantification of bouton number of Ib and Is synapses
normalized to wild-type values in the indicated genotype.

Rpr.Hid BoNT-C
Is >
Is Ib Is Ib
Ablated 15% No change No change
Ib >
Is Ib Is Ib
Ablated Ablated No change No change
wild type Ib>BoNTC Is>BoNTC
10 μm
10 μm
wild type Ib>Rpr.Hid Is>Rpr.Hid
A B
C
M7 M6
M7 M6
DLG HRP vGlut DLG HRP vGlut
Ib MN
Is MN
6 7
Muscle 6 Bouton #
0
50
100
150
200
Bouton # (%WT)
Is Ib
****
*
0
50
100
150
200
Bouton # (%WT)
Is Ib
****
****
0
50
100
150
200
Bouton # (%WT)
Is Ib
ns
ns
0
50
100
150
200
Bouton # (%WT)
Is Ib
ns
ns
D
69

Figure 4: Input-specific silencing by BoNT-C enables accurate dissection of miniature
and evoked transmission from tonic and phasic NMJs. (A) Schematic and representative
traces of mEPSP and EPSP illustrating blockade of all synaptic transmission at Is synapses with
presynaptic expression of BoNT-C. Quantification of mEPSP, EPSP, quantal content and
mEPSP frequency in the indicated genotypes normalized to wild type values. (B) Schematic and
representative traces of mEPSP and EPSP illustrating blockade of all synaptic transmission at
Ib synapses with presynaptic expression of BoNT-C. Quantification of mEPSP, EPSP, quantal
content and mEPSP frequency in the indicated genotypes normalized to wild type values. (C)
Schematic and representative traces of mEPSP and EPSP illustrating the intact synaptic
transmission at Ib and Is synapses in wild type. (D) Quantification of mEPSP, EPSP, quantal
content and mEPSP frequency in the indicated genotypes in (A), (B) and (C). The black bars
indicate the summed EPSP, mEPSP and mEPSP frequency and weighted average of mEPSP
in (A) and (B).

200 ms
1 mV
20 ms
10 mV
wild type
Ib>BoNT-C Is>BoNT-C
Is Ib
Is Ib Is Ib
0
50
100
150
200
Is only
% wild type
**
***
*** ****
mEPSP
EPSP
QC
Freq
0
10
20
30
40
EPSP (mV)
WT
Ib
Is
Ib+Is
****
***
0.0
0.5
1.0
1.5
mEPSP (mV)
WT
Ib
Is
Ib+Is
**
**
0
10
20
30
40
Quanal content
WT
Ib
Is
Ib+Is
****
***
0
1
2
3
4
mEPSP freq (Hz)
WT
Ib
Is
Ib+Is
****
****
A B
C D
0
50
100
150
200
Ib only
% wild type
**
****
****
mEPSP
EPSP
QC
****
Freq
70

Figure 5: Tonic and phasic activity does not specialize postsynaptic GluR fields. (A)
Representative images of Ib and Is boutons at muscle 6 immunostained with anti-GluRIIA, -
GluRIIB and -GluRIID in wild type (w
1118
,+,+). (B) Quantification of the mean fluorescence
intensity of anti-GluRIIA, -GluRIIB, -GluRIID in the Is boutons normalized to Ib values in (A). (C)
Representative images of Ib and Is boutons at muscle 6 immunostained with anti-GluRIIA, -
GluRIIB and -GluRIID in OK319>BoNT-C (w,OK319-GAL4/+,UAS-BoNT-C/+). (D) Quantification
of the mean fluorescence intensity of anti-GluRIIA, -GluRIIB, -GluRIID in the Is boutons
normalized to Ib values in (C). (E) Representative images of a single Ib or Is boutons at muscle
6 in wild type (w
1118
,+,+) immunostained with anti-GluRIIA and -GluRIIB and an amplified
imaged zoomed into a single receptor field. Average fluorescence line profiles showing GluRIIA
and GluRIIB normalized to fluorescence range across average PSDs in Ib or Is synapses. (F)
Representative images of a single Ib or Is boutons at muscle 6 in OK319>BoNT-C (w,OK319-
GAL4/+,UAS-BoNT-C/+) immunostained with anti-GluRIIA and -GluRIIB and an amplified
imaged zoomed into a single receptor field. Average fluorescence line profiles showing GluRIIA
and GluRIIB normalized to fluorescence range across average PSDs in Ib or Is synapses.

D
A
IIA IIB IID
wild type
Ib Is
OK319>BoNTC
5 μm
Ib Is
C
wild type OK319>BoNTC
Ib Is
3 μm 100 nm
B
E F
0.0 0.5 1.0
0.0
0.5
1.0
m
0.0 0.5 1.0
0.0
0.5
1.0
0.0 0.5 1.0
0.0
0.5
1.0
m
0.0 0.5 1.0
0.0
0.5
1.0
Ib Is
IIA IIB IID
0
50
100
150
GluR mean intensity (% Ib)
IIA IIB IID
***
ns ns
0
50
100
150
GluR mean intensity (% Ib)
****
ns
ns
IIA IIB IID
71

Rpr.Hid BoNT-C
Is >
Is Ib Is Ib
Ablated 30% No change No change
A B
wild type Is>Rpr.Hid Is>BoNTC
Is Ib
Ib Is
Ib Is
C
D
Muscle 12 Bouton #
12 13
Ib MN
Is MN
Ib + Is
Is > Rpr.Hid
Is > BonT-C
50 μm
50 ms
10 mV
1 mV
500 ms
E
vGlut DLG HRP
0
50
100
150
200
Ib only
% wild type
mEPSP
EPSP
QC
Freq
0
50
100
150
Ib only
% wild type
mEPSP
EPSP
QC
Freq
0
10
20
30
40
EPSP
0.0
0.5
1.0
1.5
2.0
mEPSP
0
10
20
30
40
QC
0
10
20
30
M12 bouton #
Ib Is
0
50
100
150
200
250
M12 bouton # (% WT)
****
**
Ib Is
0
50
100
150
200
M12 bouton # (% WT)
ns ns
Ib Is
72

Figure 6: Phasic neuronal silencing by BoNT-C does not induce structural or functional
heterosynaptic plasticity at the m12 NMJ. (A) Schematic of Ib and Is motor neurons
innervating muscle 12 and 13 in the segmental muscle fibers. (B) Table illustrating change in
bouton number of Ib or Is synapses at muscle 12 normalized to wild type value in when Rpr.Hid
or BoNT-C overexpressed with Ib- and Is-specific GAL4 driver. (C) Representative images of
NMJ boutons at muscle 12 immunostained with anti-vGlut, -DLG and -HRP in wild type
(w
1118
,+,+). Quantification of bouton number of Ib and Is synapses in the indicated genotype.
Schematic and representative traces of mEPSP and EPSP illustrating intact Ib and Is synaptic
transmission in wild type. Quantification of mEPSP, EPSP, quantal content and mEPSP
frequency in the indicated genotypes. (D) Representative images of NMJ boutons at muscle 12
immunostained with anti-vGlut, -DLG and -HRP in Is>Rpr.Hid (Rpr.Hid/+;Is-GAL4/+).
Quantification of bouton number of Ib and Is synapses in the indicated genotype. Schematic and
representative traces of mEPSP and EPSP illustrating overexpression of Ripper and Hid in Is
motor neurons and ablation of Is synapses. Quantification of mEPSP, EPSP, quantal content
and mEPSP frequency normalized to wild type values in (C) in the indicated genotypes. (E)
Representative images of NMJ boutons at muscle 12 immunostained with anti-vGlut, -DLG and
-HRP in Is>BoNT-C (w;+;Is-GAL4/UAS-BoNT-C). Quantification of bouton number of Ib and Is
synapses in the indicated genotype. Schematic and representative traces of mEPSP and EPSP
illustrating overexpression of BoNT-C in Is motor neurons and silencing of Is synapses.
Quantification of mEPSP, EPSP, quantal content and mEPSP frequency normalized to wild type
values in (C) in the indicated genotypes.

73

Supplemental Figure 1: Motor neuron-specific GAL4 expression at the Drosophila NMJ.
(A) Schematic of Ib and Is motor neurons targeted by a motor neuron driver OK6-GAL4, which
innervate muscle 6, 7, 12, 13, 4, 3, 2, and 1. Representative images of body wall muscle
innervated by Ib and Is motor neurons with GFP expression driven by OK6-GAL4. (B)
Schematic of Ib and Is motor neurons targeted by a subset of motor neuron driver OK319-
GAL4, which innervate muscle 6, 7, 12, 13, 4, 3, 2, and 1. Representative images of body wall
muscle innervated by Ib and Is motor neurons with GFP expression driven by OK319-GAL4. (C)
Schematic of Ib motor neurons targeted by a Ib-specific driver dHB9-GAL4, which innervate
muscle 6, 7, 12 and 13. Representative images of body wall muscle innervated by Ib motor
neurons with GFP expression driven by dHB9-GAL4. (D) Schematic of Is motor neurons
targeted by a Ib-specific driver dHB9-GAL4, which innervate muscle 6, 7, 12, 13, 4, 3, 2, and 1.
Representative images of body wall muscle innervated by Ib motor neurons with GFP
expression driven by R27E09-GAL4.
OK6>tdGFP
This M4 does not have Is
synapses. I will update the
example.
OK319>tdGFP
6 7 4 13
12
Is
Ib
Ib>tdGFP
Ib
6 7 4 13
12
Ib
Is>tdGFP
Is
6 7
4
13
12
Is
Is
6 7
4
13
12
Ib
Is
GFP DLG Phalloidin
Ib MN
Is MN
All motor neurons
Ib MN
Is MN
Ib MNs at m6,7,4; All Is MNs
Ib MN
Ib MNs at m6, 7, 12, 13
Is MN
All Is MNs
A
B
C
D
100 μm
OK6-GAL4
OK319-GAL4
dHB9-GAL4 (Ib-GAL4)
R27E09-GAL4 (Is-GAL4)
6 7 4 13 3 2 1 12
5
6 7 4 13 12 3 2 1
5
6 7 4 13 12 3 2 1
5
6 7 4 13 12 3 2 1
5
74

Supplemental Figure 2: Genetic ablation of Ib motor neurons leads to variable ablation of
both motor inputs. (A) Representative images of body wall muscle innervated by Ib motor
neurons with GFP expression driven by R27E09-GAL4, co-stained with anti-DLG and anti-HRP
antibodies. Representative images of body wall muscle innervated by Ib motor neurons with
GFP expression driven by dHB9-GAL4, co-stained with anti-DLG and anti-HRP antibodies. (B)
Representative images of NMJ boutons at muscle 6 immunostained with anti-vGlut, -DLG and -
HRP in the indicated genotypes: wild type (w
1118
;+;+); Is>Rpr.Hid (Rpr.Hid/+;Is-GAL4/+); Ib>
Rpr.Hid (Rpr.Hid/+;Ib-GAL4/+). (C) Quantification of bouton number of Ib and Is synapses
normalized to wild-type values in the indicated genotype. (D) Representative images of NMJ
boutons at muscle 6 with Ib ablation in different conditions of bouton ablations. (E)
Quantification of bouton number of Ib and Is synapses normalized to wild-type values in the
indicated genotype.

Ib>CD4::tdGFP Is>CD4::tdGFP
Ib
Is
Is
Ib
M7 M6 M7 M6
10 μm
GFP DLG
Is>rpr,hid Ib>rpr,hid wild type
Is
Ib
Ib
M7 M6
10 μm
M7 M6
Ib>rpr,hid vGlut DLG HRP
Ib partial loss (55%)
A
B C
D E
0
50
100
150
Is>Riper.Hid
bouton# (% WT)
Is Ib
0
50
100
150
Ib>Riper.Hid
Is Ib
Phalloidin
Ib mild loss (7%) Ib total loss (37%)
0
10
20
30
40
50
bouton# (% WT)
Is Ib
0
10
20
30
40
50
Is Ib
0
10
20
30
40
50
Is Ib
10 μm
75

Supplemental Figure 3: Characterization of BoNT-A, -B and -E expression at the
Drosophila NMJ. (A) Representative images of NMJ boutons at muscle 6/7 immunostained
with anti-vGlut, -DLG and -HRP in wild type (w
1118
;+;+). Quantification of bouton number of Ib
and Is synapses in the indicated genotype. Schematic and representative traces of mEPSP and
EPSP illustrating intact Ib and Is synaptic transmission in wild type. Quantification of mEPSP,
EPSP, quantal content and mEPSP frequency in the indicated genotypes. (B) Representative
images of NMJ boutons at muscle 6/7 immunostained with anti-vGlut, -DLG and -HRP in
OK319>BoNT-A (w;OK319>GAL4/+;+/UAS-BoNT-A). Quantification of bouton number of Ib and
Is synapses in the indicated genotype. Schematic and representative traces of mEPSP and
EPSP illustrating overexpression of BoNT-C in Is motor neurons and silencing of Is synapses.
Quantification of mEPSP, EPSP, quantal content and mEPSP frequency normalized to wild type
values in the indicated genotypes. (C) Same dataset in OK319>BoNT-B
(w;OK319>GAL4/+;+/UAS-BoNT-B).(D) Same dataset in OK319>BoNT-E
(w;OK319>GAL4/+;+/UAS-BoNT-E).

2 mV
200 ms
200 ms
10 mV
A
B
C
M6 wild type
20 μm
D
vGlut
DLG
HRP
0
10
20
30
40
50
Bouton #
Is Ib
0
50
100
150
200
Bouton # (% WT)
ns
ns
Is Ib
0
50
100
150
200
Bouton # (% WT)
*
*
Is Ib
0
50
100
150
200
Bouton # (% WT)
ns
ns
Is Ib
M6 OK319>BoNT-B M6 OK319>BoNT-A M6 OK319>BoNT-E
0.0
0.5
1.0
1.5
mEPSP (mV)
0
10
20
30
40
EPSP (mV)
0
50
100
150
% wild type
ns
ns
mEPSP
EPSP
0
50
100
150
200
250
% wild type
*
**
mEPSP
EPSP
0
50
100
150
% wild type
ns
ns
mEPSP
EPSP
76

Chapter 4: Synaptic glutamate homeostatically modulates
postsynaptic receptor abundance

77

4.1 Abstract
Glutamate receptors (GluRs) are targets for modulation in Hebbian and homeostatic
synaptic plasticity and are remodeled throughout development and disease. Although much is
known about activity-dependent mechanisms that regulate GluRs, the role of synaptically
released glutamate itself in this process is unclear. To probe the role of glutamate in adaptive
GluR plasticity, we have generated the first targeted mutations that ablate either of the two
postsynaptic GluR subtypes at the Drosophila neuromuscular junction, GluRA and GluRB. We
first demonstrate that GluRA and GluRB compete to establish postsynaptic receptor fields and
associated scaffolding. Next, we show that synaptically released glutamate bi-directionally tunes
the abundance of postsynaptic GluRs. Finally, we find that GluRA receptors are homeostatically
regulated by glutamate, while GluRB receptors are insensitive and that Ca
2+
permeability
through GluRAs is required for GluRA remodeling. Thus, glutamate itself selectively targets
GluR subtypes for adaptive modulation at the postsynaptic compartment.

78

4.2 Introduction
Ionotropic glutamate receptors (GluRs) are dynamically trafficked at postsynaptic
densities during development, plasticity, and disease. Although it is clear that postsynaptic GluR
fields can be established in the absence of any glutamate released from presynaptic terminals
(Sando et al., 2017; Sigler et al., 2017), there is large body of work that demonstrates
alterations in activity can drive Hebbian and homeostatic remodeling of GluR fields (Chowdhury
and Hell, 2018; Diering and Huganir, 2018; Turrigiano, 2008). A variety of signaling systems in
the postsynaptic compartment work together to regulate the establishment and plasticity of GluR
composition, abundance, and biophysical properties (Huganir and Nicoll, 2013; Malinow and
Malenka, 2002). These include auxiliary GluR subunits, postsynaptic scaffolding proteins, and
signaling transduction molecules such as CaMKII (Herring and Nicoll, 2016). Extracellular
glutamate alone appears to be capable of inducing synaptogenesis, as photo-uncaging of
glutamate in extracellular regions near dendritic shafts can generate dendritic spines de novo
(Kwon and Sabatini, 2011). However, whether and to what extent synaptically released
glutamate itself influences GluR composition and abundance has not been clearly defined.
The glutamatergic Drosophila neuromuscular junction (NMJ) is an attractive system to
characterize the role of synaptically released glutamate in establishing and modulating
postsynaptic GluR fields. At this synapse, genetic mutations of the vesicular glutamate
transporter vGlut are capable of diminishing glutamate emitted from presynaptic release sites
(Daniels et al., 2006), while overexpression of vGlut enhances glutamate released from
individual synaptic vesicles due to an enlargement in vesicle size (Daniels et al., 2004).
Postsynaptic ionotropic GluRs at the fly NMJ are tetramers composed of three essential
subunits (GluRIIC, GluRIID, and GluRIIE) and contain one of two subunits, GluRIIA or GluRIIB
((Marrus et al., 2004; Qin et al., 2005); Fig. 1A). Here we abbreviate these distinct tetrameric
GluR subtypes as “GluRA” and “GluRB” for receptors containing either the GluRIIA or GluRIIB
subunit respectively. Studies in vivo and in heterologous systems have demonstrated that the
79

majority of synaptic currents are driven by GluRA receptors, while GluRB receptors pass much
less current due to rapid desensitization (Diantonio et al., 1999; Han et al., 2015). However,
insights into the establishment and plasticity of GluR fields at the fly NMJ have been limited by
an absence of clean mutations that specifically target GluRIIA or GluRIIB subunits.
We have generated the first null mutations that specifically ablate GluRIIA and GluRIIB
receptors using CRISPR/Cas9 gene editing. These mutants have enabled us to probe how
GluR fields are established during development and in response to synaptically released
glutamate, and how competition between GluRA and GluRB determine the impact of glutamate
on adaptive GluR plasticity. These studies have revealed that GluRA and GluRB compete to
establish postsynaptic receptor fields and exhibit distinct responses to synaptic glutamate.
However, in the absence of competition, synaptically released glutamate homeostatically scale
GluRA receptor abundance while GluRB receptors are insensitive to glutamate. Moreover, this
remodeling of GluRA by synaptically released glutamtate requires the postsynaptic Ca
2+
influx
throught GluRA.

80

4.3 Results
GluRIIA- and GluRIIB- containing receptor subtypes compete to establish postsynaptic
glutamate receptor fields.
To understand how postsynaptic receptor fields are established at the Drosophila NMJ,
we generated targeted genetic mutations in the two distinctive GluR subunits, GluRIIA and
GluRIIB (Fig. 1A,B). Although a mutation in GluRIIA was generated over 20 years ago using
imprecise transposon excision (Petersen et al., 1997), the lesion did not cleanly disrupt GluRIIA
only, with expression of a neighboring gene, oscillin, also disturbed (Chen and Dickman, 2017).
Specific mutations in GluRIIB have not been reported. We used single guide RNAs targeting
early exons of the GluRIIA or GluRIIB coding regions combined with Cas9-mediated
mutagenesis to generate a series of mutations in either subunit; two independent predicted null
mutations in GluRIIA and GluRIIB were chosen for further analysis (see methods; Fig. 1B). To
validate these mutations, we co-immunostained the larval NMJ with antibodies against GluRIIA,
GluRIIB, and the common essential subunit GluRIID. As expected, GluRIIA was absent in the
GluRIIA mutant, GluRIIB was absent in the GluRIIB mutant, and the common GluRIID signal
was maintained in both (Fig. 1C,D). Thus, this approach has generated the first clean null
mutations in the GluRIIA and GluRIIB receptor subunits.
Next, we used immunostaining and electrophysiology to determine the composition and
functionality of receptor fields that are exclusively composed of GluRA or GluRB. In GluRIIA
mutants, mEPSC amplitude, which reflects the postsynaptic current induced by the
spontaneous release of single synaptic vesicles, was reduced by over 50% (Fig. 1E-G), as
expected by exclusive expression of the low conducting GluRB receptors and observed in
previous GluRIIA mutant studies (Diantonio et al., 1999; Petersen et al., 1997). However, a
compensatory ~170% enhancement in GluRIIB intensity was found, with no significant change
in the common GluRIID subunit (Fig. 1C,D). In GluRIIB mutants, GluRIIA levels were similarly
increased, with no overall change in GluRIID (Fig. 1C,D). This increased expression of GluRA
81

receptors was reflected by a large increase in mEPSC amplitude and charge transfer (Fig. 1E-
G). Finally, we labeled the postsynaptic density in GluRIIA and GluRIIB mutants using
antibodies against Discs large (DLG), a homolog of the mammalian postsynaptic scaffold PSD-
95 (Budnik et al., 1996). Interestingly, we found that DLG levels correlated with GluRA levels,
with an ~30% reduction observed in GluRIIA mutants and an inverse change in GluRIIB
mutants (Fig. 1C,D). Taken together, these experiments suggest that GluRA and GluRB
receptors compete to establish postsynaptic receptive fields, with total GluR abundance
maintained at postsynaptic compartments.
Synaptically glutamate release bi-directionally modulated postsynaptic GluR abundance.
GluRA and GluRB receptors compete to access and establish postsynaptic receptive
fields, but it is not clear what physiological signals regulate this process. We hypothesized that
the levels of synaptically released glutamate may modulate postsynaptic GluR abundance
and/or composition. Genetic manipulations of the vesicular glutamate transporter vGlut can
reduce or enhance vesicular glutamate release at the fly NMJ (Daniels et al., 2004, 2006). To
diminish glutamate release, we used vGlut1, a hypomorphic allele that leaves a substantial
portion of synaptic vesicles devoid of any vGlut and a concomitant failure to release any
glutamate upon fusion of these vesicles (Daniels et al., 2006). vGlut staining is reduced at NMJs
in vGlut1 homozygotes, as expected, with decreased mEPSC frequency but without changing
mEPSC amplitude ((Daniels et al., 2006); Fig. 2A-D). A further reduction in vGlut intensity and
mEPSC frequency is observed in vGlut1 alleles in combination with a vGlut deficiency (Fig. 2A-
C), due to a large proportion of synaptic vesicles devoid of vGlut and a dramatic reduction in
vesicular emission of glutamate (Daniels et al., 2006). We then quantified GluRIIA, GluRIIB,
GluRIID, and DLG immuno-intensity levels in these genotypes. Although no significant changes
in these proteins were observed in vGlut1 homozygotes, we found GluRIIA levels were
enhanced by ~50% in vGlut1/vGlutDf, while no change was observed in GluRIIB levels (Fig.
2E,F). As expected for a selective enhancement of GluRA levels, both GluRIID and DLG levels
82

were similarly increased at NMJs with severely reduced glutamate release (Fig. 2E,F). Thus,
GluRA receptors are uniquely sensitive to diminished glutamate release and appear to be
adaptively increased in abundance.
Next, we tested whether enhanced presynaptic glutamate release impacted postsynaptic
glutamate receptor fields. Neuronal overexpression of vGlut (vGlut-OE) increases the size of
synaptic vesicles and leads to a concomitant increase in the abundance of glutamate emitted
from single synaptic vesicles (Daniels et al., 2004). Transgenic overexpression of vGlut in
glutamatergic neurons using either the Gal4 or LexA binary expression system increased vGlut
intensity at presynaptic NMJ terminals and enhanced mEPSC amplitude, as expected (Fig. 3A-
C). Although vGlut-OE led to a small but significant reduction in GluRIIB levels, a large
reduction in GluRIIA levels was observed at postsynaptic compartments following vGlut-OE
(Fig. 3D,E). This major reduction in GluRA receptors was accompanied by the expected
reduction in GluRIID and DLG levels (Fig. 3D,E). Thus, synaptically released glutamate bi-
directionally modulates postsynaptic GluR abundance through a selective and adaptive
modulation in GluRA receptors.
Excess glutamate homeostatically downregulates GluRA receptors in the absence of
GluRB expression.
Although excess glutamate appears to adaptively reduce GluRA levels, this apparent
change in GluRA abundance is compensatory but is not homeostatic: mEPSC amplitudes are
still increased in vGlut-OE, indicating the reduction in GluRA was not sufficient to maintain
baseline miniature activity. We hypothesized that because GluRA and GluRB exhibit distinct
responses to excess glutamate and also compete to establish receptor fields, this competition
may obscure the specific responses of GluRA vs GluRB to excess glutamate. Thus, we sought
to test this hypothesis by characterizing the response of GluRA receptors to excess glutamate in
the absence of GluRB receptors and vice versa.
83

vGlut-OE at otherwise wild-type NMJs led to the expected ~40% reduction in GluRIIA
levels and small but significant reduction in GluRIIB levels (Fig. 4A,B). However, despite this
reduction in GluRA levels, mEPSC amplitude remained significantly enhanced above baseline
values (Fig. 4A), although below what one might expect given the estimated ~200% increase in
synaptic vesicle volume, and, by extension, glutamate released per vesicle. We next examined
the impact of vGlut-OE on GluRIIA mutant NMJs, which exclusively express GluRB receptors.
mEPSCs were reduced by ~50% in GluRIIA mutants alone compared to wild type, as expected
(Fig. 1F), but were substantially increased by over 70% in GluRIIA+vGlut-OE compared to
baseline values (GluRIIA mutants; Fig. 4C). Interestingly, GluRB levels did not change in
GluRIIA+vGlut-OE compared to GluRIIA mutants alone, indicating the in the absence of GluRA
receptors, GluRB receptors are insensitive to excess glutamate release (Fig. 4D). Finally, we
characterized GluRIIB mutants in which baseline mEPSC amplitudes were elevated by ~50%
compared to wild type due to the exclusive expression of GluRA receptors (Fig. 1F).
Remarkably, however, no significant difference in mEPSC amplitude was observed in
GluRIIB+vGlut-OE compared to GluRIIB mutants alone (Fig. 4E), suggesting that in the
absence of GluRB receptors, GluRA receptors are homeostatically downregulated by excess
glutamate to maintain baseline miniature amplitude. Indeed, vGlut-OE drove a >50% reduction
in already enhanced baseline GluRIIA levels in GluRIIB+vGlut-OE (Fig. 4F), which was
sufficient in amplitude to explain the stable mEPSC values despite excess glutamate driven by
vGlut-OE. Thus, the elimination of competition between GluRA and GluRB receptors reveals
two divergent plasticity responses to excess synaptic glutamate release at fly NMJ receptor
fields: 1) GluRB receptors are immutable, remaining fixed and unresponsive to glutamate, while
2) GluRA receptors become precisely attuned synaptic glutamate, enabling homeostatic
regulation.

84

Ca
2+
permeability through GluRA is necessary for homeostatic receptor scaling.
The postsynaptic GluRA receptor is adaptively modulated by enhanced glutamate
transmission. We considered the postsynaptic Ca
2+
transient as an attractive factor that
homeostatically modulates postsynaptic GluRs in response to changed glutamate transmission.
First, as the GluRA-type receptor is the major conductance to drive synaptic current and Ca
2+

transient, the impact on Ca
2+
transient at postsynaptic compartment by excess glutamate will be
increased when the GluRB-type receptor is removed. Second, given that Ca
2+
is involved in
multiple activity dependent homeostatic plasticity of glutamate receptors in the central nervous
system, the GluRA might be tuned to excess Ca
2+
transient at postsynaptic compartment. In the
next series of experiments, we tested whether homeostatic GluR scaling is sensitive to
postsynaptic Ca
2+
.
Therefore, we developed two a new approach to selectively remove postsynaptic Ca
2+

transient through GluRA receptors at the larval NMJ without disrupting GluR abundance. First,
we used CRISPR/Cas9 gene editing to generate Ca
2+
impermeable GluRA receptors, while still
allowing other ionic conductances. This was accomplished by mutating a single amino acid in
the selectivity pore in the endogenous GluRIIA locus (Fig. 4A). AMPA and kainate-type GluRs
that are Ca
2+
permeable contain a glutamine (Q) residue in the M2 domain; some GluR
subunits, including mammalian AMPA and Drosophila kainate GluRs are unable to conduct Ca
2+

when this Q is changed to the positively charged arginine (R) amino acid (Fig. 4A; (Li et al.,
2016; Ni, 2021; Traynelis et al., 2010)). We therefore targeted the orthologous amino acid in
GluRIIA (Q615) for mutagenesis at the endogenous locus to generate a GluRIIA
Q615R
allele (Fig.
S1A). We quantified postsynaptic Ca
2+
levels using GCaMP6f targeted to postsynaptic NMJs
(SynaptoGCaMP; (Newman et al., 2017)) and quantified quantal Ca
2+
events (Fig. 4B). Quantal
signals in GluRIIA mutants were reduced by ~50% compared to wild type as observed
previously (Newman et al., 2017), consistent with a major reduction in postsynaptic Ca
2+
due to
loss of GluRAs (Fig. 4B). Importantly, while GluRA and GluRB levels were unchanged in
85

GluRIIA
Q615R
mutants (Fig. S1B), a similar ~50% reduction in postsynaptic Ca
2+
was observed
that was statistically indistinguishable from GluRIIA null mutants (Fig. 4B). This demonstrates
that the GluRIIA
Q615R
allele reduces postsynaptic Ca
2+
influx to the same levels found in GluRIIA
mutants without altering postsynaptic GluR abundance. We then tested how Ca
2+
transient is
tuned to postsynaptic ionic signal by measuring GCaMP event in GluRIIB null and vGlut-OE
conditions. There is a 60% increase in GluRIIB null and vGlut-OE (Fig. S1C), which is
consistent with how mEPSC is modulated these backgrounds.
Then we tested whether Ca
2+
transient through is required for homeostatic GluR scaling.
vGlut-OE showed increased mEPSC in GluRIIA
Q615R
(Fig. 4D) while the reduction in GluRs still
persist. This suggested that the homeostatic receptor scaling is still intact when GluRA lost Ca
2+

permeability but GluRB is intact at NMJ. As the mEPSC was homeostatically tuned to wild type
level even after vGlut-OE when GluRB is absent, we then tested mEPSC in a GluRIIA
Q615R
and
GluRIIB double mutant background. Surprisingly, vGlut-OE could not homeostatically tune the
mEPSC to baseline level with GluRIIA
Q615R
and GluRIIB double mutant. As there is no evidence
that blocking postsynaptic Ca
2+
transient could change excess presynaptic glutamate quantal
release, it is possible that this failure in mEPSC homeostasis is due to inhibited GluR scaling.
We found in the GluRIIA
Q615R
and GluRIIB double mutant background, vGlut-OE did not induce
homeostatic down-regulation of GluRA receptor (Fig. 4G), indicating the Ca
2+
permeability
through GluRA receptor is required for the homeostatic recalling of GluR by excess from vGlut-
OE.

86

4.4 Discussion
By generating the first null mutations in GluRIIA and GluRIIB subunits, we have shown a
competition exists that establishes stable postsynaptic fields and that synaptically released
glutamate imposes an additional layer of regulation to this process. In particular, GluRA
receptors constitute the “plastic” receptor subtype, which are bidirectionally tuned in response to
synaptic glutamate release. Finally, when the competition between GluRA and GluRB receptors
is eliminated, GluRB receptors remain insensitive to glutamate-mediated modulation, while the
plastic GluRA receptors are homeostatically adjusted. Hence, this study provides amongst the
first evidence for homeostatic regulation of GluR abundance at this model synapse.
What purpose might two receptor subtypes differing in their strength, plasticity and
biophysics subserve? One idea is that GluRBs provide a baseline ‘noise’ at synapses to
maintain communication while GluRAs are the potent subtype that sets synaptic strength and is
responsive to plasticity. Another idea is that GluRBs are the ‘back-up’ receptors built to overtake
and maintain transmission when GluRAs blocked, a phenomenon that occurs naturally at larval
NMJs (Frank et al., 2006). Since GluRBs are less affected by perturbations, might provide
robustness and stability to the system. Lastly, GluRBs may control other aspects of synaptic
growth and structure since their absence results in enhanced synaptic growth (Schmid et al.,
2006). Thus, the presence of two variants ensures robustness with flexibility, enables a range of
postsynaptic responses, and confers opportunities for synapse specific regulation of synaptic
function and plasticity. What makes GluRAs more plastic than GluRBs? GluRA tails important
substrates for post-translational modifications and targets for structural, scaffolding and
conformational changes that affect GluRA properties, trafficking and stability. More current and
calcium through GluRAs compared to GluRBs might activate downstream signaling pathways
that make them more plastic. Given this potential for change and potency, makes sense for
GluRAs to be under such tight homeostatic control by glutamate.
87

Several layers of regulation operate at postsynaptic compartments to establish GluR
receptor fields. First, transcriptional regulation that controls GluR synthesis is clearly important
for GluR competition that sets receptive fields. This is underscored by experiments
demonstrating overexpression of either subtype leads to near loss of the other (Marrus et al.,
2004). However, the caveat of these overexpression studies is that protein synthesis is
artificially forced which likely warps the PSD, thus results from clean genetic mutants are more
reliable. Second, post-translational processes mediated by proteinases and kinases control
GluR abundance in basal conditions (Metwally et al., 2019; Wang et al., 2016a). Third, there is
evidence that non-vesicular glutamate release and glial transporters negatively regulates GluR
clustering and receptor field size (Augustin et al., 2007; Featherstone et al., 2002). Finally, we
have now shown that synaptically released vesicular glutamate negatively regulates GluR fields,
and competition between GluRAs and GluRBs determines the nature of this regulation.
The mechanism underlying the bidirectional modulation of GluRs by vesicular glutamate
release still remains unclear. Three examples of adaptive GluR modulation at the fly NMJ. First,
reduced neuronal input and hypo-innervation enhance GluRs globally and in a target-specific
manner (Goel et al., 2019a, 2020). Second, activation of injury-related neuronal DLK/Wnd
signaling induces a downregulation in the abundance of all GluRs(Goel and Dickman, 2018).
This reduction was also non-specific suggesting the signaling pathways and mechanisms that
are activated in response to injury may be distinct from those induced when vesicular glutamate
release is directly modulated. Third, non-vesicular cleft glutamate alters GluR abundance via
glial glutamatergic signaling, and glia shown to regulate GluR abundance and control glutamate
levels, perhaps excess vesicular glutamate in our vGlut-OE also modulates GluRs via glia
(Augustin et al., 2007; Featherstone et al., 2002). Since our results show GluRAs selectively
modulated and are major current carrying subunit, perhaps changes in miniature postsynaptic
currents through GluRAs carry information to trigger a downstream pathway catered for IIA
specific modulation. Indeed, minis regulate synaptic growth during development and dendritic
88

protein synthesis during plasticity (Choi et al., 2014; Sutton and Schuman, 2006). Physiological
signals such as modulations in calcium influx through GluRAs in response to miniature release
could active Ca dependent intracellular signaling and calcium-dependent kinases and
proteinases (Goel et al., 2017a; Metwally et al., 2019). Finally, kinases and adhesion molecules
(Albin and Davis, 2004; Xing et al., 2014)known to specifically control GluRIIA but not GluRIIB
are possible factors for this regulation. Finally, neto, an auxiliary factor for GluRs at the fly NMJ,
(Kim et al., 2012; Ramos et al., 2015) is an attractive candidate induce receptor changes.

89

4.5 Materials and Methods
Fly stocks: Drosophila stocks were raised at 25°C on standard molasses food. The
w
1118
strain is used as the wild type control unless otherwise noted as this is the genetic
background in which all genotypes are bred. The following fly stocks were used: vGlut-GAL4
(Mahr and Aberle, 2006), UAS-vGlut (Daniels et al., 2004).
Molecular Biology: GluRIIA
pv3
, GluRIIA
pv7
, GluRIIB
sp5
, and GluRIIB
sp14
mutants were
generated using a CRISPR/Cas9 genome editing strategy as described (Kikuma et al., 2017).
For GluRIIA mutants, a stock was obtained from BDSC (#68059) that ubiquitously expressed a
sgRNA (5’ CAATCGCACCGACGTAATGTTGG 3’) targeting the sixth exon of the GluRIIA locus
(Fig. 1B). To generate GluRIIB mutants, two independent sgRNA lines that targeted the first and
sixth exons (sgRNA1: 5’ GGTGTCTTCATTGGCGCCGCTGG 3’; sgRNA2: 5’
CATTGATGGATTCTACTCCCGGG 3’) were each cloned into the pU6 vector. Constructs were
sent to BestGene Inc. (Chino Hill, CA) for targeted insertion into the VK18 attP site on the
second chromosome. sgRNA flies were crossed to a vas-Cas9 line on the second chromosome
to induce active germline CRISPR mutagenesis, and 20 independent lines generated from each
sgRNA were screened by PCR for mutations. This identified at least 8 independent indel
mutations for each sgRNA that shifted the open reading frame, with GluRIIA
pv3
, GluRIIA
pv7
,
GluRIIB
sp5
, and GluRIIB
sp14
kept for additional analysis (Fig. 1B).
To generate the LexAOp-vGlut transgene, the vGlut cDNA was cloned into the
pJFRC19-13XLexAop2-IVS-myr::GFP vector (Addgene, catalogue # 26224) using standard
cloning approaches. All constructs were sequenced to confirm fidelity and orientation and were
sent to BestGene Inc. for targeted insertion into the VK18 attP site on the second chromosome.
To generate the Ca
2+
impermeable GluRIIA
Q615R
allele, a sequence containing 1 kb
homology arms of the GluRIIA genomic region with the
Q615R
point mutation was inserted into
pHD-DsRed vector (#51434; Αddgene) as the CRISPR donor. Two single guide RNAs (gRNA1:
gaacaactcgacttggctga, gRNA2: ggtgggctccatcatgcaac) were inserted together into the pAC-
90

U63-tgRNA (#112811; Addgene) vector with intervening tRNA(F+E) sequences for expressing
multiple gRNAs (Poe et al., 2019). The donor construct and the gRNA construct were then co-
injected into a nos-Cas9 (#78782; BDSC) fly strain by Well Genetics (Taipei City, Taiwan
(R.O.C.)) to generate the GluRIIA
Q615R
mutant by homology-directed repair. Successful CRISPR
fly lines were selected by P3>DsRed expression in eyes and confirmed by PCR. DsRed with
flanking PBac sequence was then removed by PBac-mediated excision suing the Tub>PBac fly
strain (#8283, BDSC).
Immunocytochemistry: Third-instar larvae were dissected in ice cold 0 Ca
2+
HL-3 and
immunostained using a standard protocol as described (Chen and Dickman, 2017; Goel et al.,
2017a). In brief, larvae were either fixed in Bouin’s fixative for 5 min (Sigma, HT10132-1L),
100% ice-cold ethanol for 5 min, or 4% paraformaldehyde (PFA) for 10 min. Larvae were then
washed with PBS containing 0.1% Triton X-100 (PBST) for 30 min, blocked with 5% Normal
Donkey Serum followed by overnight incubation in primary antibodies at 4°C. Preparations were
then washed 3x in PBST, incubated in secondary antibodies for 2 hours, washed 3x in PBST,
and equilibrated in 70% glycerol. Prior to imaging, samples were mounted in VectaShield
(Vector Laboratories).
Imaging and analysis: Samples were imaged as described (Perry et al., 2017) using a
Nikon A1R Resonant Scanning Confocal microscope equipped with NIS Elements software and
a 100x APO 1.4NA oil immersion objective using separate channels with four laser lines (405
nm, 488 nm, 561 nm, and 647 nm). For fluorescence intensity quantifications of vGlut, DLG,
GluRIIA, GluRIIB and GluRIID, z-stacks were obtained on the same day using identical gain and
laser power settings with z-axis spacing between 0.15-0.20 µm for all genotypes within an
individual experiment. Maximum intensity projections were utilized for quantitative image
analysis using the general analysis toolkit of NIS Elements software. The fluorescence intensity
levels of vGlut, DLG, GluRIIA, GluRIIB and GluRIID immunostaining were quantified by applying
intensity thresholds and filters to binary layers in the 405 nm, 488 nm, and 561 nm channels.
91

The mean intensity for each channel was quantified by obtaining the average total fluorescence
signal for each individual punctum and dividing this value by the puncta area. The sum intensity
for GluRIIA, GluRIIB, and GluRIID was quantified as the total fluorescence signal of each
individual GluR punctum. A mask was created around the HRP or DLG channel, used to define
the neuronal or postsynaptic membrane, and only puncta within this mask were analyzed to
eliminate background signals. All measurements based on confocal images were taken from
synapses acquired from at least six different animals.
Electrophysiology: All dissections and two-electrode voltage clamp (TEVC) recordings
were performed as described (Kikuma et al., 2019) using modified hemolymph-like saline (HL-3)
containing (in mM): 70 NaCl, 5 KCl, 10 MgCl2, 10 NaHCO3, 115 Sucrose, 5 Trehelose, 5
HEPES, and 0.5 CaCl2, pH 7.2, from cells with an initial Vm between -60 and -75 mV, and input
resistances >6 MΩ. Recordings were performed on an Olympus BX61 WI microscope using a
40x/0.80 NA water-dipping objective and acquired using an Axoclamp 900A amplifier, Digidata
1440A acquisition system and pClamp 10.5 software (Molecular Devices). Miniature excitatory
postsynaptic currents (mEPSCs) were recorded in the absence of any stimulation with a voltage
clamp of -80 mV, and low pass filtered at 1 kHz. All recordings were made on abdominal muscle
6, segments A2 and A3 of third instar larvae with the leak current never exceeding 5 nA.
mEPSCs were recorded for 60 seconds and analyzed using MiniAnalysis (Synaptosoft) and
Excel (Microsoft) software. The average mEPSC amplitude and total charge transfer values for
each muscle were obtained from approximately 100 events in each recording.
Ca
2+
imaging and analysis: Third-instar larvae were dissected in ice-cold modified HL3
saline. Larval preparations were imaged using a A1R Resonant Scanning Confocal microscope
equipped with NIS Elements software and a 60x APO 1.0NA water immersion objective as
detailed (Li et al., 2018a). Imaging was performed in modified HL3 saline with 1.5 mM Ca
2+

added. NMJs on muscle 6/7 were imaged with band scanning at a resonant frequency of 100
fps (512 x 86 pixels). Spontaneous Ca
2+
events were recorded at 4-8 individual NMJs during
92

120 sec imaging sessions from at least two different larvae. Horizontal drifting was corrected
using ImageJ plugins (Kang Li, 2008) and imaging data with severe muscle movements were
rejected as described (Ding et al., 2019). Three ROIs were manually selected using the outer
edge of terminal Ib boutons observed by baseline GCaMP signals with ImageJ (Rueden et al.,
2017; Schindelin et al., 2012). Ib and Is boutons were defined by baseline GCaMP6f
fluorescence levels, which are 2-3 fold higher at Ib NMJs compared to their Is counterparts at a
particular muscle. Fluorescence intensities were measured as the mean intensity of all pixels in
each individual ROI. ΔF for a spontaneous event was calculated by subtracting the baseline
GCaMP fluorescence level F from the peak intensity of the GCaMP signal during each
spontaneous event at a particular bouton. Baseline GCaMP fluorescence was defined as
average fluorescence in 2 secs of each ROI without spontaneous events. ΔF/F was calculated
by normalizing ΔF to baseline signal F. For each ROI under consideration, the spontaneous
event ΔF/F value was averaged for all events in the 60 sec time range to obtain the mean
quantal size for each bouton. Data analysis was performed with custom Jupyter Note codes.
Statistical analysis: Data were analyzed using GraphPad Prism (version 7.0) or
Microsoft Excel software (version 16.22). Sample values were tested for normality using the
D’Agostino & Pearson omnibus normality test which determined that the assumption of
normality of the sample distribution was not violated. Data were then compared using either a
one-way ANOVA and tested for significance using a Tukey’s multiple comparison test or using
an unpaired 2-tailed Student’s t-test with Welch’s correction. All data are presented as mean +/-
SEM; n indicates sample number and p denotes the level of significance assessed as p<0.05
(*), p<0.01 (**), p<0.001 (***), p<0.0001 (****); ns=not significant.

93

Figure 1: GluRIIA- and GluRIIB- containing receptor subtypes compete to establish
postsynaptic glutamate receptor fields. (A) Schematic depicting the subunit composition of
GluRA and GluRB glutamate receptor subtypes at the Drosophila NMJ. (B) Diagram of the
GluRIIA and GluRIIB amino acid sequence and four null alleles of GluRIIA and GluRIIB induced
by CRISPR mutagenesis. The regions of the guide RNAs used to generate these alleles are
shown. (C) Representative images of NMJ boutons immunostained with anti-GluRIIA, -GluRIIB,
-GluRIID, and -DLG antibodies in the indicated genotypes: wild type (w
1118
;+;+), GluRIIA
pv3

(w;GluRIIA
pv3
;+), GluRIIB
sp5
(w;GluRIIA
sp5
;+). (D) Quantification of mean fluorescence intensities
of the indicated antibody signal in (C) normalized to wild-type values. (E) Schematic and
representative mEPSC traces illustrating that postsynaptic expression of GluRA and GluRB
receptors in the genotypes indicated in (C). (F-G) Quantification of average total charge (F) and
mEPSC amplitude (G) values in the indicated genotypes in (C). Error bars indicate ±SEM.
**P<0.05, ***P<0.001, ****P<0.0001; ns, not significant.

A
GluRIIB
sp5
GluRIIB
+
GluRIIA-
containing
receptors
A
C
D
E
B
C
D
E
wild type GluRIIA
pv3
GluRIIB
sp5
GluRIIA GluRIIB GluRIID
C D
GluRIIB
sp14
GluRIIB-
containing
receptors
1 913
sgRNA2
T276STOP
M14STOP
E F G
GluRIIA
+
1 907
sgRNA
GluRIIA
pv3
D277STOP
G358STOP GluRIIA
pv7
sgRNA1
TM TM TM TM
TM TM TM TM
B
GluRA GluRB
DLG
1 nA
100 ms
0.0
0.5
1.0
mEPSC amp (nA)
****
****
0
2
4
6
8
10
12
Total charge (pC)
****
****
2 μm 0
50
100
150
200
250
Mean intensity (% wild type)
GluRIIA GluRIIB GluRIID DLG
****
****
****
****
ns
ns
**
**
94

Figure 2: Synaptic glutamate release bi-directionally modulated postsynaptic GluR
abundance. (A) Schematic and representative mEPSC traces illustrating that presynaptic
vesicle and postsynaptic expression of GluRA and GluRB receptors in the genotypes: wild type
(w
1118
;+;+), vGlut
1/1
(w;vGlut
1/1
;+), vGlut
1/DF
(w; vGlut
1/DF
;+). (B) Quantification of mEPSC and
mEPSC frequency in (A) and mean fluorescence intensities of the vGlut antibody signal in (C)
normalized to wild-type values. (C) Representative images of NMJ boutons immunostained with
anti-vGlut, -GluRIIA, -GluRIIB, and -GluRIID antibodies in the indicated genotypes in (A). (D)
Quantification of mean fluorescence intensities of the indicated antibody signal in (C)
normalized to wild-type values. (E) Schematic and representative mEPSC traces illustrating that
presynaptic glutamate release and postsynaptic expression of GluRA and GluRB receptors in
the genotypes: wild type (w
1118
;+;+), vGlut-Gal4>vGlut (w;vGlut-Gal4/UAS-vGlut;+), vGlut-
LexA>vGlut (w;vGlut-LexA/LexAop-vGlut;+). (F) Quantification of mEPSC in (A) and mean
fluorescence intensities of the vGlut antibody signal in (G) normalized to wild-type values. (G)
Representative images of NMJ boutons immunostained with anti-vGlut, -GluRIIA, -GluRIIB, and
-GluRIID antibodies in the indicated genotypes in (E). (H) Quantification of mean fluorescence
intensities of the indicated antibody signal in (G) normalized to wild-type values. Error bars
indicate ±SEM. **P<0.05, ***P<0.001, ****P<0.0001; ns, not significant.

1 nA
A wild type vGlut
1/1
vGlut
1/Df
GluRIIA GluRIIB GluRIID vGlut
2 μm
B
100 ms
0.0
0.2
0.4
0.6
0.8
mEPSC amp (nA)
ns
ns
ns
0
50
100
150
vGlut intensity (% WT)
*
****
0
1
2
3
4
5
mEPSC freq (Hz)
**
****
0
50
100
150
200
250
Mean intensity (% WT)
GluRIIA GluRIIB GluRIID DLG
ns
**
ns
**
ns
**
ns
C D
1 nA
E wild type vGlut
Gal4
>vGlut vGlut
LexA
>vGlut
100 ms
GluRIIA GluRIIB GluRIID vGlut
2 μm
F
G H 0.0
0.2
0.4
0.6
0.8
1.0
mEPSC amp (nA)
**
****
0
50
100
150
200
250
vGlut intensity (% WT)
****
****
0
50
100
150
Mean intensity (% WT)
**
**
****
****
****
****
* *
GluRIIA GluRIIB GluRIID DLG
95

Figure 3: Excess glutamate homeostatically downregulates GluRA receptors in the
absence of GluRB expression. (A) Schematic and representative mEPSC traces illustrating
that presynaptic glutamate release and postsynaptic expression of GluRA and GluRB receptors
in the genotypes: wild type (w
1118
;+;+), vGlut-OE (w;vGlut-Gal4/UAS-vGlut;+). Quantification of
mEPSC normalized to wild-type values. (B) Representative images of NMJ boutons
immunostained with anti-GluRIIA, -GluRIIB, and -GluRIID antibodies in the indicated genotypes
in (A). Quantification of mean fluorescence intensities of the indicated antibody signal
normalized to wild-type values. (C) Schematic and representative mEPSC traces illustrating that
presynaptic glutamate release and postsynaptic expression of GluRA and GluRB receptors in
the genotypes: GluRIIA
pv3
(w;GluRIIA
pv3
;+), +vGlut-OE (w;vGlut-Gal4,GluRIIA
pv3
/UAS-vGlut,
GluRIIA
pv3
;+). Quantification of mEPSC normalized to GluRIIA
pv3
values. (D) Representative
images of NMJ boutons immunostained with anti -GluRIIA, -GluRIIB, and -GluRIID antibodies in
the indicated genotypes in (C). Quantification of mean fluorescence intensities of the indicated
antibody signal normalized to GluRIIA
pv3
values. (E) Schematic and representative mEPSC
traces illustrating that presynaptic glutamate release and postsynaptic expression of GluRA and
GluRB receptors in the genotypes: GluRIIB
sp5
(w;GluRIIB
sp5
;+), +vGlut-OE (w;vGlut-Gal4,
GluRIIB
sp5
/UAS-vGlut, GluRIIB
sp5
;+). Quantification of mEPSC normalized to GluRIIB
sp5
values.
(F) Representative images of NMJ boutons immunostained with anti-GluRIIA, -GluRIIB, and -
GluRIID antibodies in the indicated genotypes in (E). Quantification of mean fluorescence
intensities of the indicated antibody signal normalized to GluRIIB
sp5
values. Error bars indicate
±SEM. **P<0.05, ***P<0.001, ****P<0.0001; ns, not significant.

A
100 ms
1 nA
GluRIIA + vGlut-OE
GluRIIB
wild type vGlut-OE
B
wild type + vGlut-OE
C D
IIA IIB IID DLG
E F
+ vGlut-OE
GluRIIA + vGlut-OE
GluRIIB + vGlut-OE
IIA IIB IID DLG IIA IIB IID DLG
0
50
100
150
200
mEPSC amp (% WT)
**
0
50
100
150
200
mEPSC amp (% GluRIIA)
****
0
50
100
mEPSC amp (% GluRIIB)
120
ns
0
50
100
150
Mean intensity (% WT)
IIA IIB IIDDLG
*
****
**
****
0
50
100
150
Mean intensity (% GluRIIA)
ns
ns
ns
IIA IIB IIDDLG
0
50
100
150
Mean intensity (% GluRIIB)
***
***
ns
IIA IIB IIDDLG
96

Figure 4: Ca
2+
permeability through GluRA is necessary for homeostatic receptor scaling.
(A) Schematic topology of the GluRIIA subunit with the
Q615R
mutation shown in the pore forming
M2 domain. (B) Schematized GluRs levels with representative Ca
2+
imaging traces. Line scans
below are derived from postsynaptic GCaMP6f images of individual spontaneous Ca
2+

transients in the indicated genotypes: wild type (w;MHC-SynaptoGCaMP6f/+), GluRIIA
pv3

(w;GluRIIA
pv3
;MHC-SynaptoGCaMP6f/+), GluRIIA
Q615R
(w; GluRIIA
Q615R
;MHC-
SynaptoGCaMP6f/+). Quantification of the normalized changes in fluorescence intensity (ΔF/F)
of spontaneous Ca
2+
transient events at individual boutons in the indicated genotypes. (C)
Schematic and representative mEPSC traces illustrating that presynaptic glutamate release and
postsynaptic expression of GluRA and GluRB receptors in the genotypes: GluRIIA
Q615R

(w;GluRIIA
Q615R
;+), +vGlut-OE (w;vGlut-Gal4, GluRIIA
Q615R
/UAS-vGlut, GluRIIA
Q615R
;+).
Quantification of mEPSC normalized to GluRIIA
Q615R
values. (D) Representative images of NMJ
boutons immunostained with anti -GluRIIA, -GluRIIB, and -GluRIID antibodies in the indicated
genotypes in (C). Quantification of mean fluorescence intensities of the indicated antibody
signal normalized to wild-type values. (E) Schematic and representative mEPSC traces
illustrating that presynaptic glutamate release and postsynaptic expression of GluRA and GluRB
receptors in the genotypes: GluRIIA
Q615
,GluRIIB
sp5
(w; GluRIIA
Q615
,GluRIIB
sp5
;+), +vGlut-OE
(w;vGlut-Gal4,GluRIIA
Q615
,GluRIIB
sp5
/UAS-vGlut,GluRIIA
Q615
,GluRIIB
sp5
;+). Quantification of
mEPSC normalized to GluRIIA
Q615R
values. (F) Representative images of NMJ boutons
immunostained with anti-GluRIIA, -GluRIIB, and -GluRIID antibodies in the indicated genotypes
in (E). Quantification of mean fluorescence intensities of the indicated antibody signal
normalized to wild-type values. Error bars indicate ±SEM. **P<0.05, ***P<0.001, ****P<0.0001;
ns, not significant.

B
GluRIIA
Q615R
+ vGlut-OE
GluRIIA
Q615R
,GluRIIB
+ vGlut-OE GluRIIA
Q615R
GluRIIA
Q615R
,GluRIIB
IIA IIB IID IIA IIB IID
500 pA
100 ms
500 pA
100 ms
+ vGlut-OE + vGlut-OE
0
50
100
150
200
mEPSC amp (% WT)
****
ns
0
50
100
150
200
mEPSC amp (% GluRIIB)
ns
***
D
E F
2 μm
2 μm
0
50
100
puncta intensity
(% GluRIIA
Q615R
)
****
**
****
IIB IIA IID
120
0
50
100
puncta intensity
(% GluRIIA
Q615R
,GluRIIB)
IIB IIA IID
ns
*
ns
120
GluRIIA A
+
Q/R
C
N
M1
M3
M4
M2
wild type
Q
100% Ca
2+
GluRIIA
~50% Ca
2+
GluRIIA
Q615R
~50% Ca
2+
R
ΔF/F=0.2
2 s
800
400
A.U.
0.0
0.1
0.2
0.3
0.4
0.5
F/F
****
****
C
97

Supplementary Figure S1: Engineering and validation of Ca
2+
impermeable GluRIIA allele.
(A) Schematic topology of the GluRIIA subunit with the
Q615R
mutation shown in the pore forming
M2 domain. Schematics illustrating Ca
2+
permeability through GluRA receptors with the
associated reductions in Ca
2+
observed in postsynaptic compartments. (B) Representative
images of NMJ boutons immunostained with anti -GluRIIA, -GluRIIB, and -GluRIID antibodies in
the genotypes: wild type (w;MHC-SynaptoGCaMP6f/+), GluRIIA
Q615R
(w;GluRIIA
Q615R
;MHC-
SynaptoGCaMP6f/+). Quantification of mean fluorescence intensities of the indicated antibody
signal normalized to wild-type values. (C) Schematized GluRs levels with representative Ca
2+

imaging traces. Line scans below are derived from postsynaptic GCaMP6f images of individual
spontaneous Ca
2+
transients in the indicated genotypes: wild type (w;MHC-
SynaptoGCaMP6f/+), GluRIIA
pv3
(w;GluRIIA
pv3
;MHC-SynaptoGCaMP6f/+), GluRIIA
Q615R
(w;
GluRIIA
Q615R
;MHC-SynaptoGCaMP6f/+), GluRIIB
sp5
(w; GluRIIB
sp5
;MHC-SynaptoGCaMP6f/+)
and +vGlut-OE (w;vGlut-Gal4/UAS-vGlut;MHC-SynaptoGCaMP6f/+). Quantification of the
normalized changes in fluorescence intensity (ΔF/F) of spontaneous Ca
2+
transient events at
individual boutons in the indicated genotypes. Error bars indicate ±SEM. **P<0.05, ***P<0.001,
****P<0.0001; ns, not significant.

GluRIIA
Q615R
GluRIIA
GluRIIA
wild type
Q
100% Ca
2+
GluRIIA
~50% Ca
2+
GluRIIA
Q615R
~50% Ca
2+
R
GluRIIB
Q
~150% Ca
2+
vGlut-OE
R
~150% Ca
2+
GluRIIA
Q615R
wild type
A B
C
+
Q/R
C
N
M1
M3
M4
M2
ΔF/F=0.2
2 s
800
400
A.U.
IIA IIB IID
Ca
2+
IIA
R
IIA
Q
Ca
2+
0
20
40
60
80
100
120
Mean intensity (% WT)
IIB IIA IID
ns ns ns
0.0
0.2
0.4
0.6
0.8
F/F
****
****
****
****
98

Chapter 5: Imaging neuropeptide release at synapses with a
genetically engineered reporter

99

5.1 Abstract
Research on neuropeptide function has advanced rapidly, yet there is still no spatio-temporally
resolved method to measure the release of neuropeptides in vivo. Here we introduce
Neuropeptide Release Reporters (NPRRs): novel genetically encoded sensors with high
temporal resolution and genetic specificity. Using the Drosophila larval neuromuscular junction
(NMJ) as a model, we provide evidence that NPRRs recapitulate the trafficking and packaging
of native neuropeptides, and report stimulation-evoked neuropeptide release events as real-time
changes in fluorescence intensity, with sub-second temporal resolution.

100

5.2 Introduction
Neuropeptides (NPs) exert an important but complex influence on neural function and
behavior (Bargmann and Marder, 2013; Hökfelt et al., 2000; Insel and Young, 2000; Nässel and
Winther, 2010). A major lacuna in the study of NPs is the lack of a method for imaging NP
release in vivo, with subcellular spatial resolution and subsecond temporal resolution. Available
techniques for measuring NP release include microdialysis (Kendrick, 1990), antibody-coated
microprobes (Schaible et al., 1990) and GFP-tagged propeptides visualized either by standard
fluorescence microscopy (van den Pol, 2012), or by TIRF imaging of cultured neurons (Xia et
al., 2009). In Drosophila, a fusion between rat Atrial Natriuretic Peptide/Factor (ANP/F) and GFP
was used to investigate neuropeptide trafficking at the fly neuromuscular junction (NMJ) (Rao et
al., 2001). Release was measured indirectly, as a decrease in ANP-GFP fluorescence intensity
at nerve terminals reporting residual unreleased peptide, on a time-scale of seconds (Wong et
al., 2015). None of these methods combines NP specificity, genetically addressable cell type-
specificity, high temporal resolution and applicability to in vivo preparations. A major challenge
is to develop a tool that encompasses all these features for direct, robust measurement of NP
release in vivo.

101

5.3 Results
Design and Synaptic Localization of an NPRR.
Neuropeptides are synthesized as precursors, sorted into dense core vesicles (DCVs),
post-translationally modified and cleaved into active forms prior to release (Taghert and
Veenstra, 2003). We reasoned that an optimal in vivo real-time NP release reporter should
include (1) a reporter domain that reflects the physico-chemical contrast between the
intravesicular milieu and the extracellular space (Figure 1—figure supplement 1A); and (2) a
sorting domain that ensures its selective trafficking into DCVs (Figure 1—figure supplement 1b).
The NP precursor may function as the sorting domain, suggested by studies of DCV fusion
using pIAPP-EGFP (Barg et al., 2002) and NPY-pHluorin (Zhu et al., 2007) in cultured neurons,
or ANP-GFP in Drosophila (Rao et al., 2001). We therefore developed a pipeline to screen
various transgenes comprising NP precursors fused at different sites to fluorescent reporters, in
adult flies (Figure 1—figure supplement 1B–C). A total of 54 constructs were tested. We found
that optimal trafficking was achieved by substituting the reporter for the NP precursor C-terminal
domain that follows the final peptide (Figure 1—figure supplement 1B). In order to maintain
covalent linkage with the reporter domain, we removed the dibasic cleavage site C-terminal to
the final peptide.
The DCV lumen has lower pH and free calcium (pH = 5.5–6.75, [Ca
2+
]~30 µM)
compared to the extracellular space (pH = 7.3, [Ca
2+
]~2 mM) (Mitchell et al., 2001; Sturman et
al., 2006). These differences prompted us to test validated sorting domains in a functional ex
vivo screen using either pH-sensitive fluorescent proteins (Miesenböck et al., 1998) or
genetically-encoded calcium indicators (GECIs) (Lin and Schnitzer, 2016; Tian et al., 2012)
(Figure 1—figure supplement 1A–D). Reporters based on pHluorins (Miesenböck et al., 1998)
did not perform well in our hands, therefore we focused on GCaMP6s (Chen et al., 2013). The
calcium sensitivity threshold of GCaMP6s is below the calcium concentration in both DCVs and
the extracellular space. However, GCaMP6s fluorescence is quenched in the acidic DCV lumen
102

(Barykina et al., 2016), enabling it to function as a dual calcium/pH indicator (Figure 1A). These
key properties should boost the contrast between GCaMP6s fluorescence in unreleased vs.
released DCVs, potentially allowing us to trace NP release at the cellular level in vivo.
We sought to test several NP precursor-GCaMP6s fusion proteins, called NPRRs
(NeuroPeptide Release Reporters; unless otherwise indicated all NPRRs refer to fusions with
GCaMP6s), in an intact preparation using electrical stimulation to evoke release. Initially for
proof-of-principle experiments, we used the Drosophila larval NMJ to test NPRR
ANP
, a
GCaMP6s fusion with rat ANP (Burke et al., 1997). NMJ terminals are large, individually
identifiable, and easy to image and record. In particular, boutons on muscle 12/13 are diverse --
Type Ib and Type Is boutons contain mostly synaptic vesicles and few DCVs, while Type III
boutons contain an abundance of DCVs but no synaptic vesicles (Menon et al., 2013);
moreover, Type III-specific GAL4 drivers are available (Koon et al., 2010a) (Figure 1B).
Expression of NPRR
ANP
pan-neuronally (under the control of nsyb-GAL4) followed by
double immuno-staining for ANP and GCaMP (anti-GFP) indicated that the sorting domain and
the reporter domains showed a similar localization in Type III neurons (Figure 1—figure
supplement 2). Moreover, the distribution of NPRR
ANP
overlapped that of Bursicon (Figure 1—
figure supplement 3D), an NP that is endogenously expressed in Type III neurons (Loveall and
Deitcher, 2010). Both GCaMP and Bursicon immunoreactivity were strongest within boutons,
consistent with the known subcellular localization of DCVs (Gorczyca and Budnik, 2006).
Glutamate is the only known canonical neurotransmitter used at the larval NMJ (Menon
et al., 2013). This allowed visualization of the subcellular localization of small synaptic vesicles
(SV) by immuno-staining for vGluT, a vesicular glutamate transporter (Fremeau et al., 2001;
Kempf et al., 2013). In Type Ib neurons (which contain relatively few DCVs relative to SVs
(Menon et al., 2013)), vGluT staining was observed as patches with a dim center, which may
reflect clustered SVs, while NPRR
ANP
immunoreactivity was seen in dispersed, non-overlapping
punctae (Figure 1C, α-GFP, inset). In Type III neurons, NPRRs were strongly expressed but no
103

vGluT immunoreactivity was detected (Figure 1C). The subcellular distribution of this NPRR in
larval NMJ neurons, therefore, is similar to that of other DCV-targeted markers previously used
in this system (Rao et al., 2001; Shakiryanova et al., 2006), and appears to reflect exclusion
from SVs.
The diffraction limit of light microscopy precluded definitive co-localization of NPRRs in
DCVs. Therefore, we employed Immuno-Electron microscopy (Immuno-EM) to investigate the
subcellular localization of NPRRs at the nanometer scale. To maximize antigenicity for Immuno-
EM, we generated constructs that replaced GCaMP6s with GFP (NPRR
ANP
-GFP;). NPRR
ANP
-
GFP showed dense labeling in association with DCVs (Figure 1D, arrows), where the average
number of gold particles/µm2 was substantially and significantly higher than in neighboring
bouton cytoplasm (DCV/Bouton ~ 14.26) (Figure 1E, Supplementary file 2). Taken together,
these data indicate that NPRR
ANP
-GFP is localized to DCVs. By extension, they suggest that
NPRR
ANP
-GCaMP6s (which has an identical structure to NPRR
ANP
-GFP except for the
modifications that confer calcium sensitivity) is similarly packaged in DCVs. While these two
reporters show indistinguishable distributions by immunofluorescence (Figure 1—figure
supplement 4), we cannot formally exclude that the substitution of GCaMP for GFP may subtly
alter subcellular localization of the NPRR in a manner undetectable by light microscopy.
NPRR specifically reports neuropeptide release.
To measure the release of NPRRs from DCVs, we next expressed NPRR
ANP
in Type III
neurons using a specific GAL4 driver for these cells (Koon et al., 2010b) (Figure 2E and Figure
1—figure supplement 3D). We delivered 4 trials of 70 Hz electrical stimulation to the nerve
bundle, a frequency reported to trigger NP release as measured by ANF-GFP fluorescence
decrease (Rao et al., 2001; Shakiryanova et al., 2006), and used an extracellular calcium
concentration that promotes full fusion mode (Alés et al., 1999). This stimulation paradigm
produced a relative increase in NPRR
ANP
fluorescence intensity (ΔF/F), whose peak magnitude
increased across successive trials (Figure 2A, red bars and 2D; Video 1; Figure 2—figure
104

supplement 1, A1 vs. A7). Responses in each trial showed a tri-phasic temporal pattern: (1) In
the ‘rising’ phase, NPRR
ANP
∆F/F peaked 0.5–5 secs after stimulation onset, in contrast to the
virtually instantaneous peak seen in positive control specimens expressing conventional
GCaMP6s in Type III neurons (Figure 2A–B). The NPRR
ANP
latency to peak was similar to the
reported DCV fusion latency following depolarization in hippocampal neurons (Xia et al., 2009).
This delay is thought to reflect the kinetic difference between calcium influx and DCV exocytosis
due to the loose association between DCVs and calcium channels (Xia et al., 2009). (2) In the
‘falling’ phase, NPRR
ANP
∆F/F began to decline 1–5 s before the termination of each stimulation
trial, presumably reflecting depletion of the available pool of releasable vesicles. In contrast,
GCaMP6s fluorescence did not return to baseline until after stimulation offset (Figure 2A–B). (3)
Finally, unlike GCaMP6s, NPRR
ANP
exhibited an ‘undershoot’ (∆F/F below baseline) during the
post-stimulation intervals, followed by a ‘recovering’ phase (Figure 2A; Figures 2C,I1–4). This
undershoot may reflect dilution of released fluorescent NPRR molecules by diffusion into the
synaptic cleft (van den Pol, 2012), while recovery may reflect DCV replenishment in the boutons
from vesicles proximal to the imaged release site.
Because NPRR
ANP
fluorescence was preferentially accumulated within boutons, we
asked whether these regions contributed to ∆F/F peaks more significantly than the inter-bouton
intervals (IBIs). To do this, we partitioned the processes into boutons and IBI fields (Figure 2—
figure supplement 2A), and compared the ∆F/F in these regions during stimulation trials. The
time-averaged ratio of bouton/IBI ΔF/F (see Materials and Methods) was significantly higher for
NPRR
ANP
than for GCaMP6s, particularly during later stimulation trials (Figure 2—figure
supplement 2B, green bars, S2-4). This contrast indicates that NPRR
ANP
signals are
preferentially observed in boutons, where DCVs are located, and do not reflect differences in
cytoplasmic free Ca
2+
levels between these regions as detected by GCaMP6s.
To test definitively if NPRR
ANP
∆F/F signals are dependent upon NP release, we blocked
vesicle fusion at terminals of Type III neurons using expression of tetanus toxin light chain
105

(TNT) (Sweeney et al., 1995), a protease that cleaves n-synaptobrevin, a v-snare required for
DCV fusion (Figure 2—figure supplement 3) (Xu et al., 1998). As a control, we used impotent
TNT (TNT
imp
), a reduced activity variant (Sweeney et al., 1995). TNT expression completely
abolished stimulation-induced ∆F/F increases from NPRR
ANP
, while TNT
imp
did not (Figure 2F).
Further analysis revealed that both the ∆F/F peaks and inter-stimulation undershoots were
diminished by TNT (Figure 2G–H). In contrast, neither TNT nor TNT
imp
affected the kinetics of
GCaMP6s signals in Type III neurons (Figure 2—figure supplement 2C), which report cytosolic
Ca
2+
influx. Taken together, these data support the idea that NPRR
ANP
signals specifically reflect
DCV release.
Application of the NPRR approach to a Drosophila neuropeptide.
ANP is a rat NP that lacks a Drosophila homolog (Rao et al., 2001). To determine
whether our method could be applied to detect the release of a specific, endogenous fly NP, we
tested NPRR
dTK
, one of 6 different reporter variants we initially generated from the Drosophila
neuropeptide precursor, DTK (Figure 1—figure supplement 1B). In contrast to ANP which
encodes a single peptide, DTK yields multiple NP derivatives (Winther et al., 2003). Light
microscopy (Figure 3A) and Immuno-EM (Figure 3B, arrows) confirmed that NPRR
dTK
, like
NPRR
ANP
, was localized to DCVs (DCV/bouton ~ 22.19, Figure 3C). Using the Type III-specific
GAL4 driver to express NPRR
dTK
and the same stimulation protocol as used for NPRR
ANP
, the
basic tri-phasic response profile was also observed (Figure 3D). However, peak heights and
baseline fluorescence fell progressively with successive stimulation trials (Figure 3E), in contrast
to NPRR
ANP
where the first peak and undershoot were lower (Figure 2C–D). The reason for this
difference is currently unclear.
NPRR reveals distinct cell-type specific peptide release properties.
We next investigated the relationship between NPRR signal and stimulation intensity, by
delivering to the Type III neurons a series of low to high frequency electrical stimuli (1–70 Hz;
(Levitan et al., 2007)) while imaging the nerve terminals. For direct comparison of NPRR
106

responses across different preparations, we applied a posteriori normalization of fluorescent
peaks in each trial to the highest response obtained among all trials. For both NPRR
ANP
and
NPRR
dTK
(Figure 4A–B), the peak responses showed a positive correlation with stimulation
frequency, analogous to that observed using cytosolic GCaMP6s (Figure 4C). In Type III
neurons, the responses of both NPRRs to stimulation frequencies < 30 Hz (1,5,10,20 Hz) were
not statistically significant from zero. NPRR
ANP
showed a higher sensitivity to high stimulation
frequencies (30 Hz: 18.14%, 50 Hz: 82.40% Normalized peak ∆F/F), while NPRR
dTK
showed a
higher stimulation threshold and lower sensitivity (30 Hz: 3.57%, 50 Hz: 24.67% Normalized
peak ∆F/F).
We next investigated whether the relatively high stimulation frequency required to
observe significant responses with NPRRs was a function of the reporters, or rather of the cell
class in which they were tested. To do this, we expressed both NPRRs in Type Ib neurons, a
class of motor neurons that contains both SVs and DCVs (Figure 1B, Figure 4D–F), and
performed stimulation frequency titration experiments. Strikingly, in Type Ib neurons, significant
increases in ∆F/F could be observed at frequencies as low as 10 Hz (Figure 4D,E; NPRR
ANP
at
20 Hz: 12.50%, NPRR
dTK
at 20 Hz: 17.67% normalized peak ∆F/F). The reason for the
difference in NPRR threshold between Type III and Type Ib neurons is unknown, but parallels
their difference in GCaMP6s response to electrical stimulation (Figure 4C vs. Figure 4F).
Notably, although NPRR
ANP
and NPRR
dTK
presented distinct response profiles in Type III
neurons, their performance in Type Ib neurons was more similar (Figure 4A vs. Figure 4B; cf.
Figure 4D vs. Figure 4E). In summary, the differences in performance we observed between the
two NPRRs appeared to be specific to Type III neurons, and were minor in comparison to the
differences in performance of both reporters between the two cell classes. The reason for the
differences between NPRR
ANP
and NPRR
dTK
sensitivity and kinetics in Type III neurons is
unknown but may reflect differences in how well these reporters compete with the high levels of
endogenous neuropeptide (Bursicon) for packaging, transport or release.
107

5.4 Discussion
Here we present proof-of-principle for a method to detect the release of different
neuropeptides in intact neural tissue, with subcellular spatial and sub-second temporal
resolution. By exploiting the fluorescent change of GCaMP in response to a shift in pH and
[Ca
2+
], we visualized the release of neuropeptides by capturing the difference between the
intravesicular and extracellular microenvironment. NPRR responses exhibited triphasic kinetics,
including rising, falling and recovering phases. In the falling phase, a post-stimulus ‘undershoot’,
was observed in which the fluorescent intensity fell below pre-stimulation baseline. This
undershoot presumably reflect the slow kinetics of DCV replenishment relative to release.
The molecular mechanisms of NP release are incompletely understood (Xu and Xu,
2008). It is possible that individual DCVs only unload part of their cargo during stimulation, in
which case many DCVs that underwent fusion may still contain unreleased NPRR molecules
following a stimulus pulse. Although we are convinced that NPRR signals do indeed reflect NP
release, due to the presence of the recovering phase, we cannot formally exclude that
unreleased NPRRs may contribute to the signal change due to their experience of intravesicular
[Ca
2+
]/pH changes that occur during stimulation. To resolve this issue in the future, an ideal
experiment would be to co-express an NPRR together with a [Ca
2+
]/pH-invariant NP-reporter
fusion. Multiple attempts to generate such fusions with RFP were unsuccessful, due to cryptic
proteolytic cleavage sites in the protein which presumably result in degradation by DCV
proteases during packaging.
To test if NPRR
ANP
∆F/F signals are dependent on NP release, we expressed the light
chain of tetanus toxin (TNT), a reagent shown to effectively block NP release in many (Hentze
et al., 2015; McNabb and Truman, 2008; Zandawala et al., 2018), if not all (Umezaki et al.,
2011), systems. We observed a striking difference in NPRR kinetics in flies co-expressing TNT
vs. its proteolytically inactive ‘impotent’ control form TNT
imp
(Figure 2F). The strong reduction of
108

NPRR signals by TNT-mediated n-syb cleavage is consistent with the idea that these signals
reflect the release of NPRRs from DCVs.
We have tested the generalizability of the principles used to generate NPRRs by (1)
constructing a surrogate NP reporter NPRR
ANP
as well as a multi-peptide-producing
endogenous Drosophila NP reporter NPRR
dTK
(Figures 2–3); (2) characterized NPRR signals in
response to varying intensities of electrical stimulation; and (3) recorded NPRR signals in two
different classes of NMJ motor neurons containing DCVs with or without SVs, respectively
(Figure 4). These experiments revealed, to our surprise, that NPRR responses exhibit cell-type
specific characteristics (Figure 4). As NPRRs are applied to other neuropeptides and cell types,
a systematic characterization of neuropeptide release properties in different peptidergic neurons
should become possible, furthering our understanding of neuropeptide biology.
The method described here can, in principle, be extended to an in vivo setting. This
would open the possibility of addressing several important unresolved issues in the study of NP
function in vivo. These include the ‘which’ problem (which neuron(s) release(s) NPs under
particular behavioral conditions?); the ‘when’ problem (when do these neurons release NPs
relative to a particular behavior or physiological event?); the ‘where’ problem (are NPs released
from axons, dendrites or both?); and the ‘how’ problem (how is NP release regulated?). The
application of NPRRs to measuring NP release dynamics in awake, freely behaving animals
may yield answers to these important long-standing questions.

109

5.5 Materials and Methods
Fly strains: All experimental flies were reared on a 12/12 hr day-night cycle at 25°C.
Standard chromosomal balancers and genetic strategies were used for all crosses and for
maintaining mutant lines. Detailed genotypes used are summarized in Supplementary file 3. The
following strains were obtained from Bloomington Stock Center (Indiana University): R20C11-
Gal4 (#48887), R57C10-Gal4 (#39171), UAS-mCD8::GFP (#32185), UAS-TNT (#28838), UAS-
TNT
imp
(#28840). UAS-opGCaMP6s was made by Barret Pfeiffer (Gerald Rubin’s lab, Janelia
Farm) (Hoopfer et al., 2015).
Construction of transgenic animals: All PCR reactions were performed using
PrimeSTAR HS DNA polymerase (Takara #R045Q). All constructs were verified via DNA
sequencing (Laragen). To construct UAS-NPRR
ANP
, Drosophila codon-optimized ANP and
GCaMP6s were synthesized using gBlocks service (Integrated DNA Technologies), and
subcloned into pJFRC7 vector (from Addgene #26220) (Pfeiffer et al., 2010) using Gibson
cloning. UAS-dTK-NPRR is built in a similar way except the dTK fragment was cloned from the
Drosophila brain cDNA. NPRR
dTK
-GFP and NPRR
ANP
-GFP were built similarly except
Drosophila codon-optimized GFP was used for the subcloning. All the vectors were injected and
integrated into attP2 or attp40 sites (Bestgene Inc; see Supplementary file 3 for attP sites used
for each genotype employed).
Expression screening of NPRR candidates: Adult fly brains were dissected in chilled
PBS and fixed in 4% formaldehyde for 55 min at room temperature. After three 10 min rinses
with PBS, the brains were cleared with Vectashield (#1000, Vectorlabs), mounted, and used for
native fluorescence measurements. We trace the NPF neuron somata and arborization as
ROIs. We selected regions next to NPF neurons and measured its fluorescent intensity as a
reference, which represents background autofluorescence. Candidates whose fluorescence
reached at least 2-fold higher than reference were selected for functional screening.
110

Functional screening of NPRR candidates: For the baseline fluorescence measurement,
we crossed NPF-Gal4 to the candidate lines and generated NPF-Gal4>NPRRx (x = candidate
label) flies for tests. The dissected adult fly brains were mounted on a petri dish and immersed
in Drosophila imaging saline (108 mM NaCl, 5 mM KCl, 2 mM CaCl 2, 8.2 mM MgCl2, 4 mM
NaHCO3, 1 mM NaH2PO4, 5 mM trehalose, 10 mM sucrose, 5 mM HEPES, pH 7.5). To deliver
high potassium challenge, High-K imaging saline was perfused (43 mM NaCl, 70 mM KCl, 2 mM
CaCl2, 8.2 mM MgCl2, 4 mM NaHCO 3, 1 mM NaH2PO4, 5 mM trehalose, 10 mM sucrose, 5 mM
HEPES, pH 7.5). Live imaging series were acquired using a Fluoview FV3000 Confocal laser
scanning biological microscope (Olympus) with a 40×, 0.8 N.A. (Numerical Aperture) water
immersion objective (Olympus). Candidates whose post-stimulation fluorescence reached at
least 2-fold of baseline fluorescence (measured as averaged pre-stimulation fluorescence) were
selected for in vivo tests at NMJ. For each candidate line, at least three brains were tested and
fold-change of each was averaged.
Immunohistochemistry: Larval dissection was performed in chilled HL3 solution (70
mM NaCl, 5 mM KCl, 20 mM MgCl2, 10 mM NaHCO3, 115 mM sucrose, 5 mM trehalose, 5 mM
HEPES and 1.5 mM CaCl2, pH 7.2). Dissected tissues were fixed in 4% formaldehyde or
Bouin’s solution for 30 min at room temperature. After three 15 min rinses with PBS, tissues
were incubated with primary antibodies overnight at 4°C. Following three 15 min rinses with
PBS, tissues were incubated with secondary antibody for 2 hr at room temperature. Following
three 15 min rinses, tissues were cleared with Vectashield (#1000, Vectorlabs) and mounted.
Confocal serial optical sections were acquired using a Fluoview FV3000 Confocal laser
scanning biological microscope (Olympus) with a 60×, 1.30 N.A. silicone oil objective
(Olympus). All image processing and analyses were done using ImageJ (National Institute of
Health).
The following primary antibodies were used: Chicken anti-GFP (1:250-1:1000, Aveslab
#1020), Rabbit anti-ANP (1:500, abcam #14348), Guinea pig anti-vGluT (Goel and Dickman,
111

2018) (1:1500), Rabbit anti-syt1 (Littleton et al., 1993) (1:500) and Rabbit anti-Bursicon (1:2000,
a gift from Dr. Benjamin White).
The following secondary antibodies were used: Alexa Fluor 488 Goat anti-Chicken IgY
(#A11039, Invitrogen), Alexa Fluor 488 Goat anti-Rabbit IgG (#A11008, Invitrogen), Alexa Fluor
568 Goat anti-Rabbit IgG(H + L) (#A11011, Invitrogen), Alexa Fluor 633 Goat anti-Rabbit IgG(H
+ L) (#A21070, Invitrogen), Alexa Fluor 488 Goat anti-Guinea Pig IgG(H + L) (#A11073,
Invitrogen), Alexa Fluor 568 Goat anti-Guinea Pig IgG(H + L) (#A11075, Invitrogen), Alexa Fluor
568 Goat anti-Mouse IgG(H + L) (#A11004, Invitrogen) and Alexa Fluor 633 Goat anti-Mouse
IgG(H + L) (#A21050, Invitrogen).
Electron microscopy: Drosophila tissues were fixed in 4% formaldehyde in PBS and
stored at 4°C until preparation by high-pressure freezing (HPF) and freeze-substitution (FS)
(Buser and Drubin, 2013; Buser and Walther, 2008). Tissues were cryoprotected in 2.3 M
sucrose for 45 min, transferred to 200 µm deep planchettes and high-pressure frozen in an
EMPact2 with RTS (Leica, Vienna, Austria). FS was carried out in an AFS2 (Leica, Vienna,
Austria) in methanol containing 5% water, 0.05% glutaraldehyde and 0.1% uranyl acetate
(−90°C, 3 hr; −90 to −80°C, 10 hr; −80°C, 4 hr; −80°C to 4°C, 24 hr). Samples were washed
once in methanol containing 5% water, infiltrated with hard grade LR White (Electron
Microscopy Sciences, Hatfield, PA, USA) at 4°C ([LR White]: [methanol containing 5% water]
1:1, 24 hr; 100% LR White, 3 × 24 hr) and polymerized in a fresh change of LR White using a
Pelco BioWave (Ted Pella, Inc, Redding, CA, USA) set to 750 W, 95°C for 45 min.
60 nm thin sections (UCT ultramicrotome, Leica, Vienna, Austria) were picked up on
formvar-coated 50 mesh copper grids. The sections were blocked for 3 min in blocking buffer
(PBS with 0.5% bovine serum albumin, which was used for all antibody dilutions), incubated in
anti-GFP antibody (1:500, Aveslab #1020) for 5 min, washed 3 times in blocking buffer,
incubated in rabbit anti chicken antibody (1:50, MP Biomedicals #55302) for 5 min, washed 3
times on blocking buffer, incubated on protein A - 5 nm gold (1:50, Utrecht, Netherlands), and
112

washed 3 times in PBS and 3 times in distilled water. The sections were stained in uranyl
acetate or uranyl acetate and Reynolds lead citrate depending on the desired contrast and
imaged at 80 kV in a Zeiss EM10C (Zeiss, Oberkochen, Germany) using a CCD camera
(Gatan, Pleasanton, CA, USA).
Labeling density was estimated using stereological methods (Griffiths and Hoppeler,
1986). Cross-sections through boutons were recorded and the following parameters were
measured: total image area, total number of gold particles, number of visible dense core
vesicles (DCV), number of gold particles within a 50 nm radius of the DCV center, bouton area
(grid intersection estimate), gold within the bouton cytoplasm, gold within 20 nm of the bouton
plasma membrane, gold outside of the bouton (mainly sER). Background labeling was
estimated using internal controls (labeling on blank resin and on muscle fibers) and a biological
control (non-GFP expressing genotype). Occasional obvious, large gold aggregates were
disregarded. Background was consistently below 0.6 gold/µm2 in independently repeated
labeling experiments.
Electrical stimulation: The dissection of third-instar larvae was performed in zero-
calcium HL3 saline. The CNS was removed to avoid spontaneous motor neuron activity. To
minimize muscle contraction induced by electrical stimulation of motor neurons, the larval body
walls were slightly stretched and incubated in HL3 saline supplemented with 10 mM glutamate
for 5 mins after dissection to desensitize postsynaptic glutamate receptors. Samples were then
shifted to HL3 saline containing 1 mM glutamate and 1.5 mM Ca
2+
. Motor nerves were sucked
into a glass micropipette with a stimulation electrode. In Figure 2 and Figure 3, to induce
maximum dense core vesicle release at type III motor neuron terminals, four repetitive bursts
(70 Hz stimulation for 18–20 s with pulse width of 1 ms) with intervals of 40–42 s were
programmed and triggered with a Master-9 stimulator (A.M.P.I., Israel) connected to an iso-flex
pulse stimulator (A.M.P.I., Israel). The stimulation intensity was tested and set to double the
intensity required to induce muscle contraction by a single pulse stimulation. In Figure 4,
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stimulation trials were delivered with the same duration, but with a series of frequencies
spanning 1 Hz to 70 Hz.
Calcium imaging: A Nikon A1R confocal microscope with resonant scanner and NIS
Element software were used to acquire live Ca
2+
imaging on third instar larvae, bathed with 1
mM glutamate added in 1.5 mM Ca
2+
HL3 saline. Type III motor neuron terminals in abdominal
segments from A2 to A5 were imaged using a 60x APO 1.4 N.A. water immersion objective with
488 nm excitation laser. A 5 min period was used for time-lapse imaging at a resonance
frequency of 1 fps (512 × 512 pixels or 1024 × 1024 pixels), with z-stacks (step length varying
from 1 to 1.5 μm) covering the depth of entire type III motor neuron terminals. The repetitive
electrical stimulation of 70 Hz was delivered during the imaging session. Samples with severe
muscle contractions were abandoned due to imaging difficulties. Maximum intensity projection
(MIP) and image registration were conducted using Image J. Plugins including Image Stabilizer
(K. Li, CMU) and Template Matching (Q. Tseng) were used for compensating drifting and
correcting movement induced by electrical stimulations. ROIs were manually selected by tracing
the outer edge of each neuron based on the baseline fluorescence. If the fluorescence was too
weak to trace, we established a reference stack by empirically adjusting the contrast on a
duplicate of the raw image stack. We used the reference stack for ROI selection and projected
the selected ROIs back onto to the raw image stack for measurement. For frames in which the
sample movement could not be automatically corrected, we manually outlined the ROIs used for
measurements. Preparations with severe movement or deformation artifacts were abandoned to
avoid unreliable measurements. Each ROI represent a traceable neuronal branch except Figure
2—figure supplement 2B, in which the ROIs were further manually partitioned into boutons and
IBIs (Inter-Bouton Intervals) based on morphology. Fluorescence change were normalized to
the pre-stimulation background except for Figure 3E, for which the data in each trial was
normalized to the average ∆F/F during a 5 s period just before stimulation was initiated. No
114

sample size is predetermined based on statistics. Ca
2+
imaging data were acquired from at least
six independent NMJs from at least five animals.
Statistical analysis: Data are presented as mean ± s.e.m. All data analysis was
performed with Graphpad Prism 6, Microsoft Excel and custom Matlab codes (Source code 1).
Mann-Whitney U test was used for comparison except in Figure 4, where One-sample T test
was used for comparison with a specified value (0).

115

Figure 1: Design and Synaptic Localization of an NPRR. (A) Schematic illustrating the
principle of NPRRs (Neuropeptide Release Reporters). NPRR molecules in the DCV lumen (low
pH/low calcium, left) exhibit increased fluorescence when released by fusion into the
extracellular space (neutral pH/high calcium, right). NPRR fluorescent signal is expected to
decay following diffusion into the synaptic cleft. New NPRR-containing DCVs are produced by
synthesis and transport from the soma, not by recycling. NP: Neuropeptide. DCV: Dense Core
Vesicle. SV: Synaptic Vesicle. (B) Distinct motor neuron subtypes at the Drosophila NMJ
(muscle 12/13) have different proportions of DCVs vs. SVs. The GAL4 driver R57C10-Gal4
(nsyb-GAL4) labels all subtypes, while R20C11-GAL4 selectively labels only Type III neurons,
which lack SVs (‘Type III-GAL4’). Light gray circles, black lines and dark gray shading represent
boutons, inter-bouton intervals and subsynaptic reticulum respectively. The studies in this paper
focus on Type Ib neurons and Type III neurons (in red rectangles). (C) Triple immunolabeling for
GFP (green), Bursicon (blue) and vGluT (red), in flies containing nsyb-GAL4 driving UAS-
GCaMP6s (upper), or NPRR
ANP
(lower). Type Ib and Type III boutons are indicated. Scale bar, 5
µm. Inset image (NPRR
ANP
, a-GFP channel) shows details of puncta distribution of NPRR
ANP
in
Type Ib neuron. Scale bar, 2 µm. (D) TEM images of boutons immunolabeled with anti-GFP (5
nm gold particle-conjugated) to detect nsyb>NPRR
ANP
-GFP, which has an identical structure to
NPRR
ANP
, but is a GFP rather than GCaMP6s fusion to improve antigenicity (see Figure 1—
figure supplement 4). Note strong labeling in DCVs (arrows) and the neuronal plasma
membrane (arrowheads). Scale bar, 200 nm. Lower panel shows representative images of
labeled DCVs. Scale bar,100 nm. (E) Quantification for TEM images in (D).

116

Figure 2: NPRR specifically reports neuropeptide release. (A) Trace from a representative
experiment showing changes in NPRR
ANP
fluorescence intensity (∆F/F) in Type III motor
neurons at the larval NMJ evoked by electrical stimulation. BG: background. S1-S4: Stimulation
trials 1–4. I1-I4: Inter-stimulation Intervals (ISIs) 1–4. Green line: ∆F/F averaged across all
boutons in the field of view. Gray shading: s.e.m envelope. Red bar: electrical stimulation trials
(70 Hz). The three typical phases of the response are indicated in S4. The peak height of the
response on the first trial is characteristically lower (see also (D)), and may reflect competition
with unlabeled DCVs in the readily releasable pool. (B) ΔF/F traces in control flies expressing
cytoplasmic GCaMP6s in Type III neurons. (C) Integrated NPRR
ANP
ΔF/F values during trials
S1-4 and intervals I1-4. A.U.: arbitrary units. n = 8. ***, p<0.001. (D) Average NPRR
ANP
ΔF/F
peak heights for trials S1-4. n = 8. *, p<0.05. Plotted values in (C–D) are mean ± s.e.m. (E1–E2)
Representative selection of ROIs (yellow). Details see Materials and methods. Scale bar, 5 µm.
(F) NPRR
ANP
ΔF/F response are abolished in Type III GAL4>UAS NPRR
ANP
flies bearing UAS-
TNT (F1) but not UAS-TNT
imp
(F2). (G) Average peak heights of NPRR
ANP
ΔF/F in combined
stimulation trials (S1-4) from (F). ****, p<0.0001. (H) Average ‘undershoot’, defined as the
integrated ΔF/F during ISIs I1-4 (see (C)). In (C–D) and (G–H).

117

Figure 3: Application of the NPRR approach to a Drosophila neuropeptide. (A) Triple
immunolabeling for GFP (green), Bursicon (blue) and vGluT (red) in Type III-GAL4> UAS
NPRR
dTK
flies. Scale bar, 5 µm. (B) TEM images of boutons immunolabeled against GFP (5 nm
gold) in nsyb-GAL4>UAS NPRR
dTK
-GFP flies. Note strong labeling in DCVs (arrows) and
bouton plasma membrane (arrowheads). Scale bar, 200 nm. Lower panel shows representative
images of labeled DCVs. Scale bar,100 nm. (C) Quantification of TEM images in (B). (D)
NPRR
dTK
ΔF/F curve; stimulation conditions as in Figure 2A. (E) Average NPRR
dTK
ΔF/F peak
height above pre-stimulation baseline (corrected; see Materials and methods) for stimulation
trials S1-4. n = 6. **, p<0.01.
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Figure 4: NPRR reveals distinct cell-type specific peptide release properties. For each
preparation, a series of stimulation trials were delivered at frequencies from 1 Hz to 70 Hz, as
indicated. In-stimulation response peaks were normalized to 70 Hz. The normalized peaks of
NPRRs or calcium responses (measured with cytosolic GCaMP6s) were pooled and plotted for
both Type III (A-C) and Type Ib (D-F) neurons. Responses were compared to zero. n = 6–12.
n.s., not significant. *, p<0.05. **, p<0.01. ***, p<0.001. ****, p<0.0001.

119

Supplemental Figure 1: NPRR screening pipeline. A series of reporter-neuropeptide
precursor fusions were designed, codon-optimized for Drosophila, cloned into expression
vectors under the control of the GAL4 upstream activator sequence (UAS), and used to
generate transgenic flies. (A) Candidate reporters interrogated included (constitutive)
fluorescent reporters, genetically encoded calcium indicators (GECI) and pH indicators
(pHluorins). (B) Sorting domain candidates included different truncated versions of rat Atrial
Natriuretic Peptide (ANP; single-precursor-single-peptide) and Drosophila tachykinin (dTK;
single-precursor-multiple-peptide) precursors. 52 constructs were built and injected. 44 of 54
were successfully integrated as transgenic lines, while eight were excluded due to lethality or
unstable expression. (C–D) Candidate UAS-NPRR lines were crossed with an NPF-Gal4 driver
line and selected based on their expression in NPF terminals in the adult fly brain. The raw
fluorescence intensity of each NPRR candidate was measured using the same microscope
parameters (laser power, HV, offset value). 14 candidates passed this screening. (C) We
screened the performance of difference NPRRs (signal-to-noise contrast) by measuring
fluorescence before and immediately after 70 mM high-potassium challenge in an ex vivo
explant preparation of adult fly brains. The post/pre KCl fluorescence ratio is defined as ΔF/F.
We arbitrarily set the threshold as 100%. 2 NPRRs with highest ΔF/F passed the final round of
screening. Red asterisks indicate the candidates selected for the studies in Figure 2 and Figure
3. Blue asterisk indicates original ANP-GFP fusion) (Burke et al., 1997; Rao et al., 2001).
120

Supplemental Figure 2: Exogeneous neuropeptide ANP dictates the expression pattern
of NPRR
ANP
. Membrane-bound mCD8::GFP fusion (A), cytosolic GCaMP6s (B) and NPRR
ANP

(C) were expressed pan-neuronally in the larval NMJ and stained for both ANP (red) and NPRR
(green, anti-GFP). (C) Note co-localization of ANP and GFP. Scale bar, 5 µm.

121

Supplemental Figure 3: Expression of different reporters in Type III neurons in the larval
NMJ. GAL4 line (R20C11-GAL4, named Type III-GAL4 in this report) allows specific expression
in Type III neurons. Expression patterns of (A) conventional GCaMP, (B) membrane-bound
GFP, (C) NPRR
dTK
and (D) NPRR
ANP
using Type III-GAL4. Arrows indicate boutons in Type III
neurons, which contain the neuropeptide Bursicon. Note that anti-vGluT stains other types of
motor neurons, which are not labeled by the Type III-specific driver used in this experiment.
Scale bar, 5 µm.

122

Supplemental Figure 4: Subcellular distribution of NPRR
ANP
and NPRR
ANP
-GFP. NPRR
ANP

(labeled as NPRR
ANP
-GCaMP6s) (A) and NPRR
ANP
-GFP (B) were expressed pan-neuronally in
the larval NMJ and double immune-labeled with antibodies to vGluT (red) and GFP (green).
Note that the distribution of GFP signal is similar whether the reporter fusion is GCaMP6s (A) or
GFP (B). Scale bar, 5 µm.

123

Supplemental Figure 5: Activation of NPRR
ANP
in situ. Representative still frames (A1–A12)
from video recordings of NPRR
ANP
-expressing Type III neurons at the larval NMJ. ‘On’
(A2,4,7,10) represents the onset of electrical pulses. Color bar: Raw fluorescence intensity.
Scale bar, 50 µm.

124

Supplemental Figure 6: NPRR specifically reports neuropeptide release. (A) Left:
Segmentation of Type III neurons into boutons (orange) and inter-bouton intervals (IBIs, red).
Right: Schematic illustrating DCV distribution in Type III neurons, based on photomicrograph to
the left. Green dots, DCVs. (B) Average time-integrated ratio of ΔF/F in boutons/IBIs (Materials
and Methods), within each stimulation periods. n.s., not significant. *, p<0.05. ***, p<0.001. ****,
p<0.0001. (C) TNT does not affect GCaMP6s ΔF/F kinetics. n = 6–7. GCaMP6s peak
magnitudes were reduced slightly in TNT (C1) in comparison to TNT
imp
(C2) preparations,
perhaps reflecting partial vulnerability of the cytosolic GCaMP6s reporter to TNT-mediated
cleavage and degradation. NPRRs are expected to be protected from TNT by the DCV
membrane.

125

Supplemental Figure 7: NPRR specifically reports neuropeptide release. Blocking DCV
fusion using Tetanus Toxin. (A1, A2) Tetanus toxin (TNT) blocks vesicle fusion by cleavage of
n-synaptobrevin (n-syb).

126

Supplemental Figure 8: Comparison of NPRR response at 30 and 50 Hz. Normalized ΔF/F
peaks in at 30 Hz (A) and 50 Hz (B) electrical stimulation in Figure 4A,B,D,E are replotted and
compared. n = 6–7. *, p<0.05. **, p<0.01. n.s., not significant.
127

Chapter 6: Conclusion

128

By engineering a series of new genetic reagents and tools, our work illustrates new
insight in the induction mechanism of PHP in the muscle and the homeostatic control of
glutamate receptors with excess glutamate release. In addition, with our novel genetic tools, we
provided optimal methods to separate the converging Ib and Is motor neurons at Drosophila
NMJ which is important for studying input-specific mechanisms of the synaptic transmission and
plasticity. Finally, with our new neuropeptide indicator, we established an optimal genetically
encoded indicator for imaging neuropeptide release at the first time with high temporal
resolution.
We first interrogated a long-existing model model and conclude that reduced Ca
2+
in
postsynaptic compartments are not sufficient to induce PHP signaling, nor is CaMKII activation
sensitive to changes in Ca
2+
. Rather, our data support an alternative model in which CaMKII
activation is entirely dependent on a small domain encoded in the C-tail of the GluRIIA receptor
subunit, which in turn exerts a constitutive suppression of retrograde homeostatic signaling.
Thus, a key event in enabling PHP is recognition of the physical loss of the GluRIIA C-tail at
postsynaptic compartments.
The role we have described here for CaMKII is likely to be specific to chronic PHP
inductive signaling. For the rapid, pharmacological induction of PHP, a distinct process is likely
involved. There is substantial evidence to indicate that disparate postsynaptic signaling systems
operate to enable chronic PHP expression (due to genetic loss of GluRIIA) vs rapid PHP
(following pharmacological blockade of GluRs; (Goel and Dickman, 2021; Goel et al., 2017b; Li
et al., 2018a). For example, some genes are necessary only for chronic PHP, while they are
dispensable for rapid PHP (Goel and Dickman, 2021). Furthermore, while translational
regulation is necessary for chronic PHP (Kauwe et al., 2016; Penney et al., 2012, 2016), rapid
PHP does not require new protein synthesis (Böhme et al., 2019; Frank et al., 2006; Goel et al.,
2017b, 2019a). An important component of the postsynaptic signaling system that regulates
both chronic and rapid PHP is mono-ubiquitination by the ubiquitin ligase adapter Insomniac
129

(Kikuma et al., 2019). While we hypothesize that chronic PHP induction requires loss of the
GluRIIA C-tail and pCaMKII, clearly rapid PHP would necessitate a distinct mechanism, since
the GluRIIA tail still remains present. However, one important commonality between rapid and
chronic PHP is that reduced postsynaptic Ca
2+
does not seem to be involved in either process
(Goel et al., 2017a). Elucidating the induction mechanism of rapid PHP, and determining to what
extent CaMKII is involved, will be an exciting area of future research.
Our study not only reveals a novel interaction between postsynaptic GluRs and CaMKII
regulation at the NMJ, but highlights that PHP, and perhaps other types of homeostatic
plasticity, functions independently of Ca
2+
signaling. At dendrites of glutamatergic synapses in
the brain, Hebbian and homeostatic plasticity mechanisms work in conjunction to calibrate
synaptic strength and efficacy to enable the flexibility necessary for learning and memory while
preventing runaway excitation (Turrigiano, 2011). In this context, it would seem advantageous to
use Ca
2+
as a common signal to integrate the signal transduction and cross talk between
various forms of plasticity. However, the NMJ may not require such integration, since potent
homeostatic plasticity stabilizes this synapse to maintain muscle contraction, being essential for
behavior and life, while Hebbian plasticity is more limited. An additional contrast is that while
Hebbian plasticity and homeostatic receptor scaling are bi-directional processes at dendritic
spines (Keck et al., 2017), PHP appears to be uni-directional (Goel and Dickman, 2021).
Although loss of NMJ receptor functionality can clearly lead to motor dysfunction, increased
depolarization of the muscle is tolerated given the safety factor characteristic of all NMJs
(Marrus and DiAntonio, 2005). Thus, the unique characteristics of the NMJ may enable the
discovery of synaptic plasticity mechanisms that may not be as readily apparent at central
synapses.
We next developed BoNT-C as optimal genetic tool for selectively manipulating synaptic
transmission between the converging tonic and phasic motor neurons at Drosophila NMJ. By
comparing BoNT-C with several established genetic tools existing many years in this field, we
130

confirmed that BoNT-C provides a complete blockade of both spontaneous and evoked
transmission without inducing heterosynaptic plasticity. Thus, we at the first time are able to
clearly dissect the input-specific transmission from Ib and Is motor neurons and to thoroughly
study how the tonic and phasic synapses are distinctly involved in homeostatic plasticity at
Drosophila NMJ.
Then, we generated the first null mutations in GluRIIA and GluRIIB subunits. Using
these null mutants, we illustrated a competition exists that establishes stable postsynaptic fields
and that synaptically released glutamate imposes an additional layer of regulation to this
process. In particular, GluRA receptors constitute the “plastic” receptor subtype, which are
bidirectionally tuned in response to synaptic glutamate release. Finally, when the competition
between GluRA and GluRB receptors is eliminated, GluRB receptors remain insensitive to
glutamate-mediated modulation, while the plastic GluRA receptors are homeostatically adjusted.
Hence, this study provides amongst the first evidence for homeostatic regulation of GluR
abundance at this model synapse.
The postsynaptic glutamate receptor field is a specialized structure which is established
and modulated by multiple mechanisms. First, transcriptional regulation that controls GluR
synthesis is clearly important for GluR competition that sets receptive fields. This is underscored
by experiments demonstrating overexpression of either subtype leads to near loss of the other
(Marrus et al., 2004). However, the caveat of these overexpression studies is that protein
synthesis is artificially forced which likely warps the PSD, thus results from clean genetic
mutants are more reliable. Second, post-translational processes mediated by proteinases and
kinases control GluR abundance in basal conditions (Metwally et al., 2019; Wang et al., 2016b).
Third, there is evidence that non-vesicular glutamate release and glial transporters negatively
regulates GluR clustering and receptor field size (Augustin et al., 2007; Featherstone et al.,
2002). Finally, we have now shown that synaptically released vesicular glutamate negatively
131

regulates GluR fields, and competition between GluRAs and GluRBs determines the nature of
this regulation.
As extensive efforts have been made to understand the homeostatic regulation of
presynaptic release from the motor neurons synapses, we illustrated a new insight how the
GluR receptor field is modulated by synaptic activity to maintain stable synaptic strength at
NMJ. Our study provided the first evidence that the GluR receptor is tuned to excess synaptic
glutamate.
Finally, we engineered a novel genetically encoded neuropeptide indicator (NPRR) to
detect the release of different neuropeptides in intact neural tissue, with subcellular spatial and
sub-second temporal resolution. By exploiting the high sensitivity of Ca
2+
and pH difference by
GCaMP indicator, we were able to visualize the release of neuropeptides by capturing the
difference between the intravesicular and extracellular microenvironment. Moreover, using
NPRR, we have illustrated the specific kinetics of three phases during neuropeptide release at
Drosophila NMJ. Moreover, NPRRs can be applied to other neuropeptides and cell types, a
systematic characterization of neuropeptide release properties in different peptidergic neurons
should become possible, furthering our understanding of neuropeptide biology. The advance of
NPRR made it possible to understand the release pattern of multiple neuropeptides with in vivo
setting. This would open the possibility of addressing several important unresolved issues in the
study of NP function in vivo. The application of NPRRs to measuring NP release dynamics in
awake, freely behaving animals may yield answers to these important long-standing questions.
Altogether, these studies established a series of new genetic tools to understand how
the synapse achieve homeostatic control of synaptic strength at presynaptic terminal and
postsynaptic receptor field. Provided new insights into input-specific mechanisms of
homeostatic modulation of converging inputs at Drosophila NMJ. Furthermore, these results
could enable a better understanding of how the synapses achieve stability and adaptation in
normal and challenging environment during develop ment and diseases.
132

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Abstract (if available)

Abstract Homeostatic plasticity maintains stable function of the nervous system in response to multiple internal and external challenges during development, learning and disease processes. Several mechanisms are adopted by the nervous system to achieve homeostatic modulation of neuronal activity, including the homeostatic control of intrinsic excitability, neurotransmitter receptor expression, and presynaptic neurotransmitter release. In the central nervous system, homeostatic control of synaptic efficacy is one of the mechanisms to balance the run-away effect from Hebbian plasticity. At neuromuscular junctions, presynaptic release is homeostatically modulated in a bi-directional way when the synapses are challenged by inhibition of postsynaptic receptor or excess glutamate release. Over the past 20 years, despite extensive efforts have been made to identify presynaptic genes and machineries required for the expression of presynaptic homeostatic potentiation (PHP), however the postsynaptic muscle initiate and integrate retrograde signaling still lack thorough investigation. Moreover, the Drosophila body wall muscles are innervated by two individual motor neurons, the “tonic” Ib and the “phasic” Is, which differ in many properties, including firing pattern, release probability and synaptic strength. However, synaptic transmission and plasticity have been studied as an ambiguous average between two distinct synapses due to lack of tools to separate them. In this thesis work, I established new reagents to interrogate a non-ionotropic model underlying the induction of PHP signaling in the postsynaptic muscle and engineered a genetic tool to separate the converging Ib and Is inputs at Drosophila NMJ. ❧ In chapter 2 we developed a host of specific antibodies and new mutant alleles using CRISPR/Cas9 approaches to interrogate the role of GluRIIA, postsynaptic Ca²⁺, and CaMKII activity in retrograde PHP induction. This work has revealed that CaMKII activity and PHP induction is not influenced by diminished Ca²⁺ at postsynaptic compartments. Rather, active CaMKII requires an intimate interaction with the GluRIIA C-tail. Loss of this interaction is necessary to allow retrograde signaling and PHP expression, highlighting a unique and unanticipated inductive mechanism. ❧ In chapter 3, we developed a botulinum toxin (BoNT-C) to completely block both evoked and spontaneous glutamate transmission at Drosophila NMJ without inducing any impact on synaptic growth, structure, or innervation. With the amenability to selectively silence Ib or Is motor neurons, we were able to functionally dissect the transmission and the release patterns from the tonic Ib vs phasic Is synapses. ❧ In chapter 4, we generated the first null mutations that specifically ablate GluRIIA and GluRIIB receptors using CRISPR/Cas9 gene editing. These mutants have enabled us to probe how GluR fields are established during development and in response to synaptically released glutamate, and how competition between GluRA and GluRB determine the impact of glutamate on adaptive GluR plasticity. These studies revealed that GluRA and GluRB compete to establish postsynaptic receptor fields and exhibit distinct responses to synaptic glutamate. However, in the absence of competition, synaptically released glutamate homeostatically scale GluRA receptor abundance while GluRB receptors are insensitive to glutamate. Moreover, postsynaptic Ca²⁺ transient through GluRA receptors is required for this homeostatic receptor rescaling. ❧ In chapter 5, we engineered Neuropeptide Release Reporters (NPRRs): novel genetically encoded sensors with high temporal resolution and genetic specificity. Using the Drosophila larval neuromuscular junction (NMJ) as a model, we provide evidence that NPRRs recapitulate the trafficking and packaging of native neuropeptides, and report stimulation-evoked neuropeptide release events as real-time changes in fluorescence intensity, with sub-second temporal resolution.

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Asset Metadata

Creator Han, Yifu (author)

Core Title Engineering genetic tools to illustrate new insights into the homeostatic control of synaptic strength

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Neuroscience

Degree Conferral Date 2021-12

Publication Date 11/30/2021

Defense Date 09/21/2021

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag botulinum toxin,CaMKII,Drosophila,glutamate receptor,homeostasis,neuromuscular junction,neuropeptide,OAI-PMH Harvest,synaptic plasticity

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Herring, Bruce (committee chair), Chang, Karen (committee member), Dickman, Dion (committee member)

Creator Email hanyifu2013@outlook.com,yifuhan@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC17789614

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