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Sodium butyrate prevents antibiotic-induced increase in ethanol drinking in C57BL/6J mice by modulating neuroinflammatory response

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Sodium butyrate prevents antibiotic-induced increase in ethanol drinking in C57BL/6J mice by modulating neuroinflammatory response

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SODIUM BUTYRATE REVERSE ANTIBIOTIC-INDUCED INCREASE IN ETHANOL
DRINKING IN C57BL/6J MICE BY MODULATING NEUROINFLAMMATORY
RESPONSE

By

Lei Gao

A Thesis Presented to the
FACULTY OF THE USC SCHOOL OF PHARMACY
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
PHARMACEUTICAL SCIENCE

August 2021

Copyright 2021 Lei Gao
ii

Acknowledgements
This work was funded by Rose Hills foundation Innovator Award (USC; to LA),
NIAAA R01AA022449 (NIAAA, to DLD), USC School of Pharmacy and USC Good
Neighbors.

I would like to Show my appreciations to Dr. Liana Asatryan and Dr. Daryl Davies
for their guidance and patience. I have been sincerely and patiently guided by Dr. Liana.
I feel honored to become the student of her. I also want to thank Dr. Rachel Reyes for
their continuous supports for the past two years. Dr. Rachel Reyes is not only my
academic mentor but also my caring friend. Additionally, I appreciate all the help from all
the undergraduate students. They all played important roles in the process of my
project.

I want to thank my lab colleague Chen Xue and Jifeng Zhang for their hanging out
with me. They enriched my life in LA. Also, I have learned some knowledge and lab
skills from other senior students in Dr. Davies lab. Lastly, I really appreciate helps and
loves from my family. I have gained financially support from my parents and I can
always count on my twin brother Zhen Gao.

iii

TABLE OF CONTENTS
Acknowledgements .......................................................................................................... ii
List of Tables ................................................................................................................... v
List of Figures .................................................................................................................. vi
Abbreviations ................................................................................................................. vii
Abstract ......................................................................................................................... viii
Chapter 1: Background ................................................................................................... 1
Introduction .................................................................................................... 1
The problem of AUD and current therapeutic options ................................... 2
Gut microbiome and its metabolites related to AUD ...................................... 2
Gut-brain axis during AUD ............................................................................. 4
Neuroinflammation as a potential mechanism for AUD related behavior....... 5
Role of cytokines ........................................................................................... 6
Involvement of glial cells................................................................................ 7
Anti-inflammatory role of butyrate as HDAC inhibitor .................................... 9
Chapter 2: Hypothesis ................................................................................................... 10
Chapter 3: Materials and methods ................................................................................ 12
Animals........................................................................................................ 12
“Drinking in the Dark” (DID) model .............................................................. 12
Two-bottle choice (TBC) model ................................................................... 13
Sample collection ........................................................................................ 14
Serum blood ethanol concentration (BEC) levels ........................................ 15
PT-qPCR ..................................................................................................... 15
Immunohistochemistry (IHC) ....................................................................... 16
Image analysis ............................................................................................ 17
Statistical analysis ....................................................................................... 18
Chapter 4: Results......................................................................................................... 19
iv

Co-treatment of ABX and SB didn’t change bodily parameters but changed
cecal and adipose tissue .............................................................................. 20
SB supplementation prevented increases in ethanol intake level that induced
by ABX treatment ......................................................................................... 21
HSB treatment decreased ethanol preference in a two-bottle choice model 22
ABX did not affect mRNA level of some key cytokines (TNF-α, IL-1β, MCP-1
and IL-10) but increased the mRNA level of IL-6 ........................................ 23
Sodium butyrate supplementation reduced the mRNA expression level of
both pro- and anti-inflammatory cytokines (IL-1β, MCP-1 and IL-10) with and
without ABX treatment ................................................................................. 26
ABX and SB treatment alone decreased the mRNA level of enzyme histone
deacetylase (HDAC) in brain ........................................................................ 28
SB treatment prevented ABX-potentiation of DID-induced activation of
microglial cells in the hippocampus .............................................................. 29
SB treatment prevented ABX-enhancement of DID-induced reduction in the
activity of astrocytes in the hippocampus ..................................................... 32
Chapter 5: Discussions ................................................................................................. 37
Alcohol-related behaviors ............................................................................ 37
Neuroinflammation ...................................................................................... 39
Bibliography .................................................................................................................. 45

v

List of Tables
Table. 1. DID study assigned treatment groups ............................................................ 13
Table. 2. TBC study assigned treatment groups ........................................................... 14
Table. 3. Primer sequences for cytokines testes in RT-qPCR ..................................... 16

vi

List of Figures
Fig. 1. Treatment with ABX didn’t change the level of food consumption and weight but
changed cecum and adipose tissues ............................................................................ 20
Fig. 2. ABX and/or SB treatments affected ethanol intake level and BEC ..................... 21
Fig. 3. Figure 3. Liquid preference for 20E and HSB in the two-bottle choice model .... 23
Fig. 4. DID exposure induce neuroinflammation by increasing the mRNA levels of both
pro-inflammatory and anti-inflammatory cytokines in brain ........................................... 25
Fig. 5. ABX did not affect mRNA levels of both pro-inflammatory and anti-inflammatory
cytokines in brain except IL-6 within DID model ............................................................ 26
Fig. 6. SB supplementation reduced mRNA levels of pro- and anti-inflammatory
cytokines in brain with DID exposure ............................................................................ 28
Fig. 7. Treatments with ABX, SB and their combination decreased the mRNA levels of
enzyme histone deacetylase (HDAC) subtypes in brain................................................ 29
Fig. 8. Treatment effects on hippocampal microglia ...................................................... 31
Fig. 9. Treatment effects on the morphology of hippocampal microglia ........................ 32
Fig. 10. Treatment effects on astrocytes in the hippocampal region of the brain .......... 35
Fig. 11. Treatment effects on the morphology of astrocytes in the hippocampal region of
the brain. ....................................................................................................................... 36

vii

Abbreviations
CNS Central nervous system
AUD Alcohol use disorder
DID Drinking in the Dark
SCFA Short-chain fatty acid
SB Sodium butyrate
IBD Inflammatory bowel disease
BLA Basolateral amygdala
HDAC Histone deacetylase
Iba-1 Ionized calcium binding adaptor molecule 1
GFAP Glial fibrillary acidic protein
FAS Fetal Alcohol Syndrome
H2O Water group
ABX Group treated with antibiotic cocktail treatment only
HSB Group treated with sodium butyrate in water
ASB Group treated with sodium butyrate with antibiotic cocktail treatment
20E 20% ethanol
NBF Neutral buffered formalin
VNS Vagal nerve stimulation

viii

Abstract
Building evidence supports the crucial role of bidirectional interactions between
changes in the gut microbiota and the central nervous system (CNS) during the
progression of neuropathology. Patients who have alcohol use disorder (AUD) expressed
different intestinal bacterial compositions when comparing to non-drinkers. Whether
alcohol-induced microbiota changes can lead to related behaviors such as alcohol
addiction, needs further exploration. In initial study, we found an increase in the ethanol
consumption behavior when mice were exposed to a “Drinking in the Dark” (DID)
paradigm, caused by treatment with a antibiotic cocktail (ABX) treatment. In parallel, there
was a dramatic reduction in short-chain fatty acid (SCFA) producing microbial phyla. We
further tested the effect of a common SCFA, sodium butyrate (SB), in C57BL/6J mice on
ABX-induced ethanol intake. Supplementation with SB prevented ABX effect on ethanol
intake and resulted in a lower ethanol preference compared to control mice within
respective models, DID and two bottle choice paradigms. Subsequent work focused on
identification of potential mechanisms underlying these effects. As a histone deacetylase
inhibitor, SB is known to impact numerous host activities, such as neuroinflammation,
which has been considered to be an important mechanism underlying AUD. Additionally,
butyrate treatment has been shown to effectively improve memory deficits and inhibit
neuroinflammation in the treatment of neurodegenerative diseases. Based on these, we
set forth a hypothesis that SB protects against increased antibiotic-induced ethanol
consumption in mice by modulating the ethanol-triggered neuroinflammatory responses.
ix

The qPCR data demonstrated that ABX alone did not affect neuroinflammation induced
by ethanol exposure while SB supplementation reduced it with or without ABX treatment.
In addition, treatments with ABX and ethanol alone or with their combination regulated
the cell density of GFAP- and Iba-1-positive cells, suggesting altered activities of astrocyte
and microglia, respectively. Moreover, SB supplementation altered the numbers of both
astrocyte and microglia in the hippocampus. Our results indicate that gut microbiota
influence alcohol drinking behavior in mice through the modulation of neuroinflammation.
The findings of the current study will uncover new insights in the communication between
different microbiome compositions in intestine and ethanol related behaviors, emerging
the microbiome as a promising therapeutic approach to treat AUD and other substance
use disorders.

1

Chapter 1. Background
Introduction
Alcohol use disorder (AUD) is a common disorder that has been detrimental to the
society for a long time. Research focusing on gut - brain axis is growing, but little
knowledge is known about the interactions between ethanol, the gut microbiota bacteria,
the CNS and alcohol-related behaviors [1]. Emerging evidence links symbiotic microbial
ecosystems to the healthy functions in human, including behavioral responses, and the
central nervous system [2, 3]. Multiple studies have shown that changes in metabolites
of the intestinal microbiome are crucial in AUD-related behavior and pathology. For
example, plasma levels of SCFAs, have been shown to have anti-inflammatory effects
and are associated with AUD [4, 5]. Even though previous studies have shown a strong
connection between AUD and the gut microbiome, It is still insufficiently evident to show
the potential mechanism underlying the microbiome influencing alcohol consumption
behavior.

Targeting the neuroimmune system is a new approach to develop effective drug
therapy for AUD. One of the potential mechanisms for AUD is the neuroimmune system,
which may manipulate alcohol-related behaviors. Most relevant studies have explored
changes in intestinal microbial metabolites and their possible role in mediating observed
alcohol-related behaviors [6-8]. However, few studies have investigated the potential
relationship between changes in the host microbiome and alcoholic behavior, pointing out
2

that neuroinflammation is an important player [9, 10].

The problem of AUD and current therapeutic options
AUD has been considered as a serious social problem in different groups of
American citizens [11]. Drug therapy is able to psychosocial therapy through satisfying
one or more than one neurobiology mechanisms that are related to AUD. In three FDA-
approved drug treatments for AUD, disulfiram and naltrexone exerts the positive
reinforcing stimulatory effects of alcohol and increases its aversive effects [12]. Disulfiram
modulates alcohol metabolism by inhibiting acetaldehyde dehydrogenase, and as an
opioid receptor antagonist naltrexone blocks alcohol-induced release of endorphins [13,
14]. Another FDA-approved drug, butyric acid, is probably the most commonly used drug
to treat alcoholism in the United States. Unlike other alcohol-treating drugs, which either
reduce the pleasurable effects of alcohol or have frightening side effects, sodium butyrate
works by affecting the glutamate and gamma-aminobutyric acid (GABA) systems to
reduce the brain's dependence on alcohol [15]. Some drugs partially replace alcohol,
maintaining its neurobehavioral effects without causing harmful effects.

Gut microbiome and its metabolites related to AUD
The gut microbiome is the sum of the bacteria and microorganisms in the
gastrointestinal tract. Its composition and function are dynamic with changes in the dietary
habits [16]. Disruption of intestinal microbiota homeostasis, called dysbiosis, is a key
3

player in the development of a range of diseases, such as inflammatory bowel disease
(IBD) [17], cancer [18], obesity [19] and cardiovascular disease [20]. Dysbiosis can be
caused by environmental factors, including diet [21], disruption of circadian rhythms [22],
and alcoholic beverage consumption [23, 24]. A recent study demonstrated that oral
antibiotic treatment significantly reduced gut bacterial load and further protected from
alcohol-induced neuroinflammation [25].

Alcohol abuse leads to a series of health problems, like alcoholic liver disease,
cardiovascular diseases and depression; and gut microbiota was observed to be a critical
player in the progression of these diseases [26]. Multiple researches illustrated that
alcohol causes bacterial overgrowth and disorders. Adrenoleukodystrophy in alcohol-fed
mice is associated with bacterial overgrowth in the small intestine and cecal dysregulation
[24]. Ethanol intake may affect the bacteria and phyla level in the gut [27], consequently
affecting gut microbiota functions. Studies have shown that alcohol consumption can
disrupt the intestinal barrier by disrupting tight junctions and promoting high intestinal
permeability, thereby allowing translocation of some pro-inflammatory/pathogenic
microbial products (including endotoxin LPS) [28].

Focusing on one of the important microbiome metabolite, SCFAs, provides a method
to assess the gut microbiota function in alcoholic patients. SCFAs are the fermentation
product of the indigestive food in the small intestine. Most of the SCFAs are absorbed by
4

the host as an energy source. Besides, SCFAs are key mediators in the communication
between the gut microbiota [29]. Common short-chain fatty acids, including butyric acid,
propionic acid and acetate, function as metabolizers of substrates and signaling
molecules in the host [30]. Acetate ions are normally occurring metabolites in catabolism
or anabolism, such as glycogen formation, cholesterol synthesis, degradation of fatty
acids, acetylation of amines, etc., that provide energy to muscles and other tissues [31].
Second, propionic acid is the main microbiome metabolite, which has health effects
beyond intestinal epithelial cells and is also believed to reduce lipogenesis, serum
cholesterol levels and carcinogenic effects [32]. Butyric acid is a "HDAC inhibitor,"
meaning it helps prevent colorectal cancer and inflammation by inhibiting the activity of
certain immune cells to achieve anti-cancer and anti-inflammatory functions [33]. In
addition, SCFAs exert anti-inflammatory and anti-proliferative effects [34]. In general, gut
microbes are able to affect the production of several nutrients, and changes within
metabolites and gut microbial composition can affect host health.

Gut-brain axis during AUD
The gut-brain axis is made up of the bidirectional communication between brain and
the enteric nervous system through the combined modulation of vagus nerve, endocrine
system, and immune systems [35]. Dysregulation of the intestinal microbiota is associated
with neurodevelopmental abnormalities, neuroinflammation, and brain dysfunction [36].
Two possible mechanisms may be used to explain this association, one involving the
5

stimulation of intestinal endocrine cells by G-protein coupled receptors (GPCRs). GPCRs
act as chemical sensors that collect all cytokines signals in the intestine, followed by the
interaction with the vagus nerve system. Another pathway is the regulation of central
neurotransmitters produced by gut microbes, which are key players in the reward system
associated with alcohol-related behavior. At present, the mechanism of gut brain
association has not been fully established, especially with regard to alcohol consumption
behavior and AUD. Therefore, the direct association between vagal endings and gut
innate immune cells and their role in gut brain connectivity has not been established.

Neuroinflammation as a potential mechanism for AUD related behaviors
To further explore the mechanism of microbial metabolites, such as SCFAs, on
alcohol consumption behaviors, it is necessary to explore the potential mechanism of
neuroimmune system modulating the ethanol-related behaviors. Previously, innate
immune signaling pathways have been shown become a key player in the pathogenesis
of nerve infections [37] and neurodegenerative diseases [38]. Pascual et al.
demonstrated the key influence of activation of the neuroinflammatory system on ethanol-
related behavior. Studies have shown that ethanol activates the innate immune system
by stimulating glial toll-like receptor 4 (TLR4) signaling, triggering the release of
inflammatory mediators and leading to neuroinflammation [39]. Long-term alcohol
consumption can cause a translocation of bacterial components in the gut from the
intestinal cavity into the circulation [40, 41]. Several researches targeted the direct
6

influence of ethanol on the CNS system [42, 43], little is known about the mediating role
that gut microbiome and their products play in the development of neuroinflammation and
alcohol-related behaviors.

Role of cytokines
Long-term alcohol intake is able to result in the inflammation in brain and
degeneration within the neurons. In the pathogenesis of multiple neurodegenerative
diseases, different types of inflammatory cytokines, such as NO, MCP-1, and IL-1β,
affecting neurons and synapses, involving in several disorders (as reviewed in [44]).
The presence of MCP-1 and TNF-α were found in the post-mortem brains of alcoholic
patients [45, 46]. IL-1β were induced in rodent brains after alcohol intake through a known
mechanism [45]. Similarly, Studies have shown that in DID mode, high ethanol intake is
evident to induce the cytokines level of IL-1β, suggesting that acute excessive ethanol
intake leads to the dysregulation in neuroimmune mechanism [47].

Cytokine dysregulation has also been observed as a basis for addiction-like
behaviors, including alcoholism. While many studies have focused primarily on pro-
inflammatory cytokines such as IL-6 and TNF-α and alcohol dependence, other studies
have been further investigated by identifying the effects of excessive ethanol consumption
on anti-inflammatory cytokines such as interleukin-10 (IL-10) [47, 48]. The study
7

concluded that binge-like alcohol intake model lowered the cytokines level of IL-10, and
the administration of IL-10 in the basolateral amygdala (BLA) decreased binge-like
alcohol intake level [47]. Thus, pro- and anti-inflammatory cytokines are both capable of
modulating the ethanol consumption behavior based on previous studies. In addition,
reduced neurotrophic activity has been shown to be involved in the etiology of ethanol-
induced neurodegeneration and alcohol-related neurodevelopmental disorders in the
adult brain [49].

Involvement of glial cells
Microglia are important regulator in sensing and responding to alcohol-related
behaviors and are associated with multiple immunology signaling pathways [50].
Previous study showed that adolescent binge ethanol exposure alters microglia
morphology and induces microglia proliferation in an adolescent binge alcohol model [51].
Besides, antibiotics were reported to protect mice from ethanol-induced cytokine
expression in different areas of the brain and from induced stimulation of microglia,
triggered by ethanol intake [52]. Antibiotic treatment was able to prevent alcohol-induced
morphological changes through the identification of microglia marker Iba-1 [25].
Collectively, microglia have been thought as an important marker to explore the dominant
effect of neuroinflammation on the antibiotic-induced or SCFA-induced changes in alcohol
related behaviors.
8

Recent studies have also confirmed the function of astrocytes, the most numerous
glial cells that support neurons and are key regulators of alcohol consumption behavior.
The effect of ethanol on astrocyte function appears to have significant followed-by effects
on excitability, neurotransmission, and neuronal health [53]. Several studies have been
conducted on the measurement of the immunoreactivity of GFAP, the major structural
filament of astrocyte, as its expression level correlates with the activation state of these
cells. Furthermore, the density of astrocytes expressing GFAP positive cells was lower in
the prefrontal cortex of ethanol-untreated rats with high ethanol preference [54].
Importantly, changes in GFAP+ astrocyte density in standard inbred rats were dependent
on the time, region, and method of ethanol administration [55]. In addition to the changes
in cell density, changes in the morphology, i.e. cell volume and processes of astrocytes,
were found to be suggestive of their activation state. For example, a significant reduction
in astroglia volume and processes were associated with the delay in the progression of
Alzheimer’s Disease in a murine model [56]. As above mentioned, to deeply study the
potential mechanism of modulating the alcohol related behaviors, it is necessary and
meaningful to assess the altered cell activity in brain for both astrocyte and microglia.
Additionally, the growing studies suggests that the hippocampus in adolescents is highly
susceptible to structural damage and behavioral deficits caused by alcohol.

9

Anti-inflammatory role of butyrate as HDAC inhibitor
As previously mentioned, butyrate has anti-inflammatory activity and beneficial effect
of butyrate may be a direct modulation of immune function [57]. However, as a well-known
HDAC inhibitor, indicating its potential role in the modulation of neuroinflammation.
Recently, epigenetic factors have emerged as important contributors to both depression
and AUD [58]. Specifically, the underlying mechanism is that the acetylation of the N-
terminal tail of the histone that packs DNA into nucleosomes is altered during stress-
induced depression models and alcohol withdrawal. Previous studies have shown that
rats abstained from ethanol exhibit depression-like behavior, with increased levels of
HDAC2 mRNA and protein. HDAC inhibitors were observed to reduce the glial
inflammatory response in vitro and in vivo [59]. However, the role of HDAC inhibitors in
the brain remains controversial. Glial cells show sustained HDAC activities and its
inhibition inhibits the neuroinflammatory response because it directly impairs the
transcriptional mechanism [59]. The study showed a novel role of chromatin
reconstruction in the neuroinflammatory process and further demonstrated HDAC
inhibitors are the potential agents for the treatment of alcohol withdrawal symptoms.

10

Chapter 2. Hypothesis
Building evidence supports the critical role of bidirectional interplay in the gut
microbiome composition and CNS during the progression of some neurodegenerative
diseases [36]. Patients diagnosed with AUD has been reported to have altered gut
microbiome composition compared to healthy people [60]. In previous study, we found a
significant increase in ethanol consumption when C57BL/6J mice were exposed to a
binge-like “Drinking in the Dark” (DID) paradigm, induced by treatment with a non-
absorbable antibiotic cocktail (ABX) treatment. At the same time, mice with an ABX
treatment exhibited the altered gastrointestinal (GI) microbiota [8]. In addition, treatment
with major SCFA butyrate has been shown to have anti-inflammatory effects in the
treatment of neurodegenerative diseases, effectively ameliorating memory deficits and
inhibiting neuroinflammation. We asked a question whether microbiota changes can lead
to alcohol-related behaviors such as drinking behaviors. Therefore, we hypothesized that
the absence of these SCFA-producing microbiota was involved in the upward trend
ethanol consumption behavior observed in ABX-treated mice in our study. Presently, we
examined the influence of sodium butyrate (SB) supplementation on increased ethanol
consumption in the ABX-induced DID paradigm. We expect SB supplementation to
protect against the effects of ABX on ethanol consumption.

In agreement with our hypothesis, our results demonstrated that SB treatment
protects against the effect of ABX treatment on the ethanol intake level without causing
11

alterations in SCFA-producing microbiome bacteria and phyla levels. As a histone
deacetylase inhibitor, SB is known to impact numerous host activities and exert anti-
inflammatory effect in the progress of neurodegenerative diseases. Based on these, we
set forth a new hypothesis that SB protects against the ABX-induced increase in ethanol
consumption level in mice by the modulation of ethanol-triggered neuroinflammatory
response.

12

Chapter 3. Materials and methods
Animals
In this study, we used male C57BL /6J 6-8 weeks old mice that from Jackson
Laboratories. Mice were individually housed in a specialized vivarium and they were put
in the animal vivarium room for at least 2 wks to acclimate to the environment before they
were assigned to different groups for the study purpose. The animals always had ad
libitum access to the facility-provided mouse chow and drinking water unless otherwise
indicated.

An ABX cocktail treatment comprised of 0.5 mg/mL bacitracin (Sigma, USA), 2.0
mg/mL neomycin (GoldBio, USA), and 0.2 mg/mL vancomycin (Thermo Fisher, USA) was
used in mice ad libitum in their daily drinking tap water throughout the whole duration of
the study. Anti-fungal pimaricin (1.2 ug/mL, Molekula, USA) was also used with ABX
cocktail to suppress gut fungal overgrowth due to the prolonged antibiotic tretament.
Sodium butyrate (SB, Sigma, USA) was used to the mice ad libitum for the experiment
purpose.

“Drinking in the Dark” (DID) model
We assigned all mice to 4 different groups as shown in Table 1. In our current study,
we used a modified version of this program that used a bottle of 20% ethanol (20E) per
day for 2 hours with limited intervals from 3 hours to the circadian dark period (3pm to
13

5pm), 5 days a week (Monday to Friday) for 4 weeks. This approach has been shown to
maintain consistent levels of ethanol intake over five consecutive days of 20E exposure
[61]. When the DID time, drinking bottle with different treatment liquid from all the groups
were switched with a specific drinking bottle containing 20E. 20E intake was recorded in
mLs.

Table. 1. DID study assigned treatment groups
Treatment
(24hrs)
DID Study
(DID bottle = M-F, 3-5pm)
Sample
Size
Drinking bottle
DID bottle
20E
20E
20E
20E
n
H 2O 9
ABX 9
HSB 11
ASB 11
2wks 4wks

Two-bottle choice (TBC) model
We assigned all mice to 4 treatment groups as shown in Table 2. During the TBC
procedure, mice had intermittent limited access to two bottles, one with their own
treatment solution (TBC bottle 1 - H2O, ABX, HSB or ASB) and the second one containing
20E solution (TBC bottle 2). The access to 2 bottles started at 3 hrs into the dark cycle
and lasted for 2 hrs (3:00 - 5:00 pm), paralleling the schedule used during DID. Two
additional HSB groups were also set for testing the SB and sucrose preference (Table 2).
14

During the 2 hr access with 2 bottles, mice had access to HSB containing bottle (TBC
bottle 1) and a bottle containing either H2O or 5 % sucrose (TBC bottle 2).

Table. 2. TBC study assigned treatment groups

Sample collection
The mice were euthanized by CO2 suffocation and diaphragmatic puncture. Blood
was extracted from the heart and the portal vein. Serum was separated two hours after
the blood extraction. We cut livers into small pieces and flash frozen them. They were
then fixed in 10% neutral buffer formalin (NBF). After 24 hrs fixation, they were transferred
to 70% ethanol to maintain their structure. Cecum samples were immediately excised
during necropsies, flash frozen, and stored in −80 °C until further processing. We cut brain
samples in half. One hemisphere was put in 10% neutral buffer formalin (NBF) and then
Treatment
(24hrs)
Two-Bottle Choice (TBC) Study
(TBC bottle 1, 2 = M-F, 3-5pm)
Sample
size
Drinking bottle TBC bottle 1 TBC bottle 2
20E
20E
20E
20E
n
H 2O H 2O 5
ABX ABX 5
HSB HSB 6
ASB ASB 6
HSB HSB H 2O
sucrose
6
HSB HSB 6
2 wks 2 wks
15

transferred to 30% sucrose to maintain its mechanical properties. The other half was flash
frozen and put in 70% ethanol 24 hrs later.

Serum blood ethanol concentration (BEC) levels
For the measurement of BEC levels, we used the mice from the TBC study following
a 1 wk of ethanol wash-out period. Mice were administered an intraperitoneal injection of
ethanol at a concentration of 3.5 g/kg based on the weight of each mice individually. 45
mins after each injection, mice were euthanized, extracted blood, prepared serum and
stored in -80°C.

RT-qPCR
We used a 1.5 ml pestle (Kimble, USA) to destroy and homogenize brain tissue.
mRNA was extracted by using the specific RNeasy kit (Qiagen, Germantown, MD, USA).
After acquiring the RNA solution, RNA concentration was measured by using Nanodrop
One (1μL per drop) (Thermo Scientific, Waltham, MA, USA). After that, we transcribed in
total of 300 ng total RNA per reaction by using a reverse transcription system (Promega,
Madison, WI, USA). The SYBR-Green real-time quantitative fluorescence PCR was
performed using QuantStudio K12 Flex real-time quantitative fluorescence PCR (Thermo
Scientific, Waltham, MA, USA). PowerUP ™SYBR™Green Master Mix (Applied
Biosystems, Carlsbad, CA, USA) and primers (Integrated DNA Technologies, Coralville,
Iowa, USA) were added to a 10 μL reaction system on a 384-well plate. The comparison
16

threshold cycle method is used to calculate the expression relative to the control group.
The final result is represented by the multiple change between the GAPDH corrected
sample and the control. Primer sequences that were used for the experiments are listed
in Table 3.

Table. 3. Primer sequences for cytokines testes in RT-qPCR
Target gene Forward primer (5’>3’) Reverse Primer (5’>3’)
GAPDH AGGTCGGTGTGAACGGATTTG TGTAGACCATGTAGTTGAGGTCA
IL-10 CGGGAAGACAATAACTGCACCC CGGTTAGCAGTATGTTGTCCAGC
IL-6 ACAACCACGGCCTTCCCTACT T CACGATTTCCCAGAGAACATGTG
TNF- α GGTGCCTATGTCTCAGCCTCTT GCCATAGAACTGATGAGAGGGAG
IL-1β TGGACCTTCCAGGATGAGGACA GTTCATCTCGGAGCCTGTAGTG
MCP-1 GCAGCAGGTGTCCCAAAGAA ATTTACGGGTCAACTTCACATTCAA
HDAC 1 TGGGGCTGGCAAAGGCAAGT GACCACTGCACTAGGCTGGAACA
HDAC 2 CGTACAGTCAAGGAGGCGGCAA TGAGGCTTCATGGGATGACCCTGG
HDAC 3 ACGTGCATCGTGCTCCAGTGT AGTGTAGCCACCACCTCCCAGT

Immunohistochemistry (IHC)
We extracted brains and the fixed them in 10% Neutral buffered formalin (NBF), and
cryoprotected them in 30% PBS buffer in case they are damaged by the heat. Brain
sections with hippocampus showing were mounted in OCT mounting medium (Sakura
Finetek, USA), and 30 μm-thick sagittal sections were prepared using a Microm HM525
Cryostat (ThermoFisher, Waltham, MA, USA). We then wash them in PBS buffer, sections
were then incubated in blocking buffer (3% normal serum/0.1% Triton-X/TBS) for 30 min
to remove noise activity. We performed the IHC based on a free-floating procedure with
the following primary antibodies: mouse anti-GFAP (GA5; Cell Signaling Technology,
17

catalog #3670, Danvers, MA, USA) or rabbit anti-Iba1 (Wako, catalog # 019-19741,
Richmond, VA, USA). After overnight incubation in primary antibodies, sections were
incubated in species appropriate fluorophore-conjugated secondary antibody: goat anti-
rabbit IgG – DyLight 550 or goat anti-mouse IgG - Alexa Fluor Plus 550 (both from
ThermoFisher, Waltham, MA, USA). Sections were mounted onto slides and imaged in
Cytation 5 Cell Imaging Multi-Mode Reader (BioTek, Winooski, VT, USA). DAB staining
was conducted by using Ultra-Sensitive ABC Rabbit IgG Staining Kit (Thermo Scientific,
Waltham, MA, USA) and Metal Enhanced DAB Substrate Kit (Thermo Scientific, Catalog
#34065, Waltham, MA, USA). Bright field images were taken by Zeiss Axio Scope A1
microscope (ZEISS, Ontario, CA, USA).

Image analysis
Fluorescence and DAB images were analyzed by using Image J software and
Photoshop to standardize density of astrocyte and microglia. Then we quantifies the pixel
area per region of interest (Hippocampus). Importantly, we measured positive cell counts
manually using the Image J cell counter plugin. Analysis was performed in a sample-
blinded manner. The following analysis parameters was used: GFAP positive cell
count/pixels^2 was calculated by the ratio of GFAP positive cell counts to pixel area. Iba-
1 positive cell count/pixels^2 was calculated by the ratio of Iba-1 positive cell counts to
pixel area. We summarized Branches length per astrocyte, Branches per astrocyte,
Junctions per astrocyte and Maximum branch length from the Analyze Skeleton plugin
18

data output and normalized all data.

Statistical analysis
Kruskal-Wallis test were used to assess the significant difference in the mRNA
expression level of cytokines in the parameter fold change. Additionally, Ordinary one-
way ANOVA multiple comparisons were used to illustrate the significant difference in the
cell density of both astrocyte and microglia between different groups.

19

Chapter 4. Results
Co-treatment of ABX and SB didn’t change bodily parameters but changed cecal
and adipose tissue
Supplement ABX and/or SB in drinking water at random 2 weeks prior to onset of
DID exposure (Table.1). In addition, ABX treatment was continued up to 4 weeks of DID
to maintain microbiome dysregulation. All mice steadily gained weight throughout the
study with no differences between groups in average weekly weights (Fig. 1A; two-way
RM ANOVA: F(3,36) = 0.85, p = 0.47) and food consumption (Fig. 1B; two-way RM
ANOVA: F(3,36) = 0.37, p = 0.78). No significant differences were detected in the liquid
intake among H20, ABX and ASB groups. Of note, Mice treated with HSB drank
significantly more from treatment vials (containing HSB) compared with the other three
treatment groups (Fig. 1C; two-way RM ANOVA: F(3,36) = 7.7, p < 0.01).

Compared with H2O group and HSB group, the cecum in ABX and ASB group was
enlarged, but adipose tissue was not obvious (Fig. 1D, Top). Furthermore, these ABX-
treated groups (ABX and ASB group) had significantly greater cecum weights compared
to controls (Fig. 1D, Bottom; Kruskal-Wallis test: **p < 0.01, ABX and ASB mice compared
to H2O and HSB mice).

20

Fig. 1. Treatment with ABX didn’t change the level of food consumption and weight but changed cecum and
adipose tissues. A) Body weight and B) food intake were not changed among all the four groups: H 2O, ABX, HSB,
ASB. C) HSB mice drank more their treatment liquid (SB in water only) when comparing to the other 3 treatment
groups. D) Among the top panels, within post-mortem necropsy images, red arrows showed ABX-induced cecum
enlargement and blues stars indicated the reduced level of adipose. Mice with ABX and ASB treatment showed
significantly more cecum weights compared to control groups respectively shown in the bottom panel.

SB supplementation prevented increases in ethanol intake level that induced by
ABX treatment
In the ABX group, mice consistently and immediately consumed significantly higher
amounts of 20E compared to H2O mice right after 2 wks treatment (two-way RM ANOVA:
F (60, 713) = 1.454, p=0.0167). Importantly, ASB mice consumed a significantly lower
21

20E level than mice in ABX group, with a mean consumption of 5.8 g/kg/2hrs and 7.9
g/kg/2hrs, respectively for ASB and ABX groups. In addition, HSB treatment did not affect
the 20E consumption compared to H
2
O group (p=0.42, HSB vs H2O).

Additionally, we tested whether any of the treatments caused changes in ethanol
metabolism in a separate cohort of mice after 2 wks of H2O, ABX, SB and ASB treatments.
Serum blood ethanol concentrations (BECs) were measured in sera collected. The BECs
were not significantly different among the groups (comparison of mean BEC per group in
mmol/L: H2O = 67.1 ± 9.6, ABX = 70.9 ± 5.4, HSB = 76.0 ± 7.7, ASB = 84.5 ± 5.6; Kruskal-
Wallis test: p = 0.22, n = 6-10/group).

Fig. 2. ABX and/or SB treatments affected ethanol intake level and BEC. A) Mice with ABX treatment drank
higher amounts of 20E compared to control group. ABX and SB co-treatment protected against the increases in
ethanol intake within DID model. B) 2 wks of ABX treatment with and without SB supplementation didn’t significantly
change the BEC level in serum.

22

HSB treatment decreased ethanol preference in a two-bottle choice model
We used a revised schedule based on our previously used DID schedule. All mice
were exposed to the TBC during the dark cycle for 2 hrs Monday-Friday for the duration
of 2 wks (Table 3). Within this paradigm, SB supplementation decreased the 20E
preference (%) in mice with SB treatment (HSB and ABS group) compared to H2O and
ABX mice, respectively. (Fig. 3A, FDR – Benjamini and Hochberg multiple comparisons:
H2O vs HSB group, p=0.003; ABX vs ASB group, p =0.043). Surprisingly, H 2O and ABX
groups of mice showed a similar level of 20E ethanol preference (Fig. 3A, FDR –
Benjamini and Hochberg multiple comparisons: H2O and ABX group, p = 0.56) when
considered the significant differences in ethanol consumption levels within the DID model.

The average 20E intake was not significantly different among all groups. However,
the difference between liquid intake, i.e. between TBC bottles 1 and 2, was the lowest for
the HSB group among all the groups (Fig. 3B-E, 0.021 ml/g/2hr for HSB group vs 0.03
ml/g/2 hrs for all the other groups). This was consistent with the observed higher daily
intake of HSB only during the DID study, suggesting the increased preference for SB.

We then confirmed the higher preference of mice for SB in the TBC study by
comparing HSB vs. H2O or 5% sucrose (Table 3). Mice drank more from the HSB bottle
compared to H2O bottle (Fig. 3F - Left, Mann-Whitney test: p = 0.02) but significantly lower
than the liquid from bottle containing 5% sucrose when tested after 2 wk washout period
23

(Fig. 3F - Right, Mann-Whitney test: p < 0.01).

Fig. 3. Liquid preference for 20E and HSB in the two-bottle choice model. A) HSB and ASB mice drank lower
level of 20E compared to control groups. All of the treatment groups showed a increased trend in their 20E
preference (B-E). F) Mice drank SB only (HSB mice) drank more daily treated liquid than H 2O (F-left) but this was
significantly less than 5% sucrose intake (F-right).

ABX did not affect mRNA level of some key cytokines (TNF-α, IL-1β, MCP-1 and IL-
10) but increased the mRNA level of IL-6

Chronic ethanol is shown to induce a neuroinflammatory response that can lead to
behavioral alterations [62]. To investigate the potential for ABX to aggravate ethanol-
24

induced neuroinflammation, we tested for mRNA levels of both pro-inflammatory and anti-
inflammatory cytokines.

In agreement with previously published findings, DID exposure induced an increase
in the mRNA level of all cytokine markers: IL-1β, MCP-1, IL-6, TNF-α and IL-10 (Fig. 4A-
4E; IL-1β, MCP-1, IL-6, TNF-α and IL-10, H2O vs H2O-DID, p=0.0019, p=0.002, p=0.015,
p=0.037 and p=0.03). It is interesting that the data showed ABX treatment did not affect
the mRNA levels of proinflammatory IL-1β, MCP-1 and TNF-α and anti-inflammatory IL-
10 (Fig. 5A, 8B, 8D and 8E; IL-1β, MCP-1, TNF-α and IL-10, H2O-DID vs ABX-DID,
p=0.99, p=0.99, p=0.09 and p=099). ABX treatment caused a significant increase in
ethanol-induced mRNA levels of IL-6 (Fig. 5C; IL-6, p=0.01). ABX induced
neuroinflammation by increasing the mRNA level of IL-6.

25

Fig. 4. DID exposure induce neuroinflammation by increasing the mRNA levels of both pro-inflammatory and
anti-inflammatory cytokines in brain. Pro-inflammatory cytokines:IL-1β(A), MCP-1 (B), IL-6 (C) and TNF-α (D) and
anti-inflammatory cytokine IL-10(E) were assessed by real-time RT-qPCR in this study.

26

Fig. 5. ABX did not affect mRNA levels of both pro-inflammatory and anti-inflammatory cytokines in brain
except IL-6 within DID model. In terms of IL-6, ABX treatment induced neuroinflammation by increasing its mRNA
level. Pro-inflammatory cytokines:IL-1β(A), MCP-1 (B), IL-6 (C) and TNF-α (D) and anti-inflammatory cytokine IL-
10(E) were assessed by real-time RT-qPCR in this study.

Sodium butyrate supplementation reduced the mRNA expression level of both pro-
and anti-inflammatory cytokines (IL-1β, MCP-1 and IL-10) with and without ABX
treatment

We found that SB reduced the mRNA expression level of both key proinflammatory
and anti-inflammatory cytokines (IL-1β, MCP-1 and IL-10) when comparing H2O-DID
group vs HSB-DID group and ABX-DID group vs ASB-DID group (Fig. 6A, 9B and 9E; IL-
6, MCP-1 and IL-10, H2O-DID vs HSB-DID, Ordinary one-way ANOVA multiple
27

comparisons, p=0.026, p=0.002 and p=0.006; ABX-DID group vs ASB-DID group,
p=0.0002, p=0.0005 and p=0.0071). Similarly, with ABX treatment, the combined SB and
ABX supplementation (ASB) reduced the mRNA level of TNF-α, the key pro-inflammatory
cytokines in the brain (Fig. 6D; TNF-α, ABX-DID vs ASB-DID, p=0.016). However, there
wasn’t any statistically significance shown in the comparison between H2O-DID and HSB-
DID groups despite a decreasing trend after SB supplementation (Fig. 6D; TNF-α, H2O-
DID vs HSB-DID, p=0.14). Though the IL-6 mRNA data with SB supplementation with and
without ABX treatment showed decreases similar to IL-1β, MCP-1 and IL-10, however
those changes did not get to be statistically significant (Fig. 6C; IL-6, H2O-DID vs HSB-
DID, p=0.19; ABX-DID group vs ASB-DID group, p=0.108). Of note, the non-significance
in some of the changes in TNF-α and IL-6 was likely due to the small samples size in all
treatment groups. However, there were clear trends worth presenting and prompting
future more detailed investigation.

28

Fig. 6. SB supplementation reduced mRNA levels of pro- and anti-inflammatory cytokines in brain with DID
exposure. Pro-inflammatory cytokines: IL-6, TNF-α, IL-1β and MCP-1 and anti-inflammatory cytokine IL-10 (E) were
assessed by real-time RT-qPCR in this study.

ABX and SB treatment alone decreased the mRNA level of enzyme histone
deacetylase (HDAC) in brain
SB has been used in the treatment of some neurodegenerative diseases as a HDAC
inhibitor [63]. In this study, we assessed the changes in mRNA level of three different
HDAC class I enzymes: HDAC1, HDAC2 and HDAC3. As expected, SB treatment
decreased mRNA levels of HDAC1, HDAC2 and HDAC3 with DID exposure (Fig. 7.). The
effect on HDAC1 and HDAC 2 were significant (Fig. 7A and 10B; HDAC1 and HDAC2,
H2O-DID vs HSB-DID, Ordinary one-way ANOVA multiple comparisons, p=0.02 and
29

p=0.043), whereas the decrease in HDAC3 did not reach statistical significance (Fig. 7C;
HDAC3, H2O-DID vs HSB-DID, p=0.77).

We found that ABX treatment also decreased the mRNA levels of HDACs in brain
within the DID model, with significance reaching only for HDAC2 (Fig. 7B; HDAC2, H 2O-
DID vs ABX-DID, p=0.032). The effect in HDAC1 showed a trend towards significance,
whereas no statistical significance was found for HDAC3 (Fig. 7A; HDAC1, p=0.054; Fig.
10C; HDAC3, p=0.72, H2O-DID vs ABX-DID,). Combination of ABX and SB did not lead
to more reduction in HDAC mRNA levels. Among all the enzymes, there were no
statistically significant differences between ABX-DID, HSB-DID and ASB-DID groups (Fig.
7A-C).

Fig. 7. Treatments with ABX, SB and their combination decreased the mRNA levels of enzyme histone
deacetylase (HDAC) subtypes in brain. Three different histone deacetylase enzymes: HDAC1 A), HDAC2 B) and
HDAC3 C) were assessed by real-time RT-qPCR in this study.

SB treatment prevented ABX-potentiation of DID-induced activation of microglial
30

cells in the hippocampus
To assess changes in microglia, important regulators of neuroinflammation, we used
IHC staining of hippocampal tissues for Iba1, a microglial marker. As shown in Fig. 11,
DID significantly increased Iba-1 positive cell per pixel compared to control mice (Fig.11,
H2O-DID vs H2O group, Ordinary one-way ANOVA multiple comparisons, p=0.05). There
was also an increase in Iba-1 positive cell count per pixel with ABX treatment which was
significantly higher compared to DID alone (Fig. 8, ABX-DID vs H2O-DID group, p=0.01).
Importantly, SB supplementation was shown to reverse the increased the cell count of
microglia that caused by ABX treatment (Fig. 8, ASB-DID vs ABX-DID, p<0.01).
With regards to morphological changes in microglia, DID exposure induced enlarged
cell bodies and longer more branched extensions compared to no DID (Fig. 9). Similarly,
ABX treatment showed the branched cells (arrows) and microglia in the ASB group
showed morphologies similar to the ABX group (Fig. 9).
31

Fig. 8. Treatment effects on hippocampal microglia. As shown in the upper 20X DAB images in each group, DID
increased Iba1-1 positive cell density in hippocampus and this effect was potentiated by ABX treatment. SB
supplementation administrated with ABX prevented the increase in Iba-1 positive cells induced by ABX treatment.
32

Fig. 9. Treatment effects on the morphology of hippocampal microglia. 40X microglia images from each group
were taken by the microscope in the hippocampus structure and then processed to threshold images by photoshop.
Arrows indicate activated branched microglia.

SB treatment prevented ABX-enhancement of DID-induced reduction in the activity
of astrocytes in the hippocampus
Recent studies suggest a key role for astrocytes in the process of neuroinflammation
[64]. Ethanol-induced effects on astrocyte physiology appear to cause pronounced
downstream effects on excitability, neurotransmission and neuronal health [53]. We
assessed changes in astrocytes using IF staining for GFAP, a selective marker for
33

astrocytes. We used parameter GFAP+ cell count/ pixels^2 to assess the changes in cell
density of GFAP positive cells. As shown from Fig. 10, DID lowered the cell expression of
GFAP positive cells compared to control H2O group (Fig. 10; Ordinary one-way ANOVA
multiple comparisons, H2O group vs H2O-DID group, p<0.01). In addition, mice with ABX
treatment exhibited a significant lower cell density compared to H 2O-DID mice (Fig.13;
Ordinary one-way ANOVA multiple comparisons, H2O-DID group vs ABX-DID group,
p<0.01). Importantly, ABX and SB combined treatment prevented the decrease in GFAP-
positive cell number induced by DID and/or ABX treatment (Fig.10; Ordinary one-way
ANOVA multiple comparisons, ABX-DID group vs ASB-DID group, p<0.01).
We also assessed treatment effects on the morphology of astrocyte in the
hippocampal region of the brain using skeleton analysis. In terms of the parameter:
average branch length in each astrocyte, none of the treatment affected the average
branch length of the astrocyte (Fig.11A; Ordinary one-way ANOVA multiple comparisons,
H2O group vs H2O-DID group, p=0.99; H2O-DID group vs ABX-DID group, p=0.67; ABX-
DID group vs ASB-DID group, p=0.22). Similarly, none of the treatment changed the
average number of junctions per hippocampal astrocytes (Fig.11C; Ordinary one-way
ANOVA multiple comparisons, H2O group vs H2O-DID group, p=0.99; H2O-DID group vs
ABX-DID group, p=0.05; ABX-DID group vs ASB-DID group, p>0.99). In the parameter
branches per astrocyte, ABX treatment increased the average number of branches in
each astrocyte with DID exposure (Fig.11C; Ordinary one-way ANOVA multiple
comparisons, H2O-DID group vs ABX-DID group, p=0.01). Moreover, SB supplementation
34

and ABX co-treatment increased the average maximum length of astrocyte within DID
model (Fig.14D; Ordinary one-way ANOVA multiple comparisons, ABX-DID group vs
ASB-DID group, p=0.013). Overall, treatments (DID, ABX and SB) affected the
morphology of astrocyte with the skeleton assessment of astrocyte.
35

Fig. 10. Treatment effects on astrocytes in the hippocampal region of the brain. ABX treatment and DID
exposure alone or their combination decreased GFAP-positive cell density. SB supplementation reversed the reduced
GFAP cells density when co-administrated with ABX. The data are shown as in one parameter: GFAP+ cell
count/pixels^2.
36

Fig. 11. Treatment effects on the morphology of astrocytes in the hippocampal region of the brain. ABX
treatment and SB supplementation alone or their combination affect the morphology of astrocyte. Four parameters:
Branches length per astrocyte A), Branches per astrocyte B), Junctions per astrocyte C) and Maximum branch length
D) were analyzed based on IHC images by using the plugins in Image J.

37

Chapter 5. Discussion
Alcohol-related behaviors
The project focused on a hypothesis that the use of antibiotics to disrupt the
remodeling of the symbiotic microbiota would significantly affect alcohol-related behavior
by regulating neuroinflammation. Notably, the ABX-treated mice also significantly reduced
butyric acid-producing bacteria in Firmicutes, including the Lachnospiraceae, Clostridium
IV, and Clostridium XIVa at the genera level, among mice that were given high ABX levels
[8]. To test whether ethanol drinking behavioral changes were associated with the
decrease level of butyrate, in our present study, we used C57BL/6J mice treated with SB
to see the underlying behavioral effects. The SB concentration is 8 mg/ml in the drinking
water and it was given ad libitum following a previous procedure, where the same
concentration of SB caused behavioral changes in adult male C57BL/6J mice [65]. SB is
known for its anti-inflammatory effect, which has been considered as the treatment in the
progression of some neurodegenerative diseases. Specifically, butyrate is a major source
of energy for colon cells and is involved in maintaining intestinal health and host
metabolism [66].

As expected, ABX treatment rapidly increased the ethanol intake level while SB co-
treatment significantly prevented the increased change in ethanol consumption level in
mice immediately within the 1st week of DID. Therefore, the alcohol consumption of ABX
mice treated with SB (ASB group) was significantly lower than that of ABX mice, and the
38

intake was close to that of H2O and HSB groups. After 4 weeks of treatment, mice treated
with ASB also showed significant changes.

Interestingly, the ethanol intake in no-ABX treated SB group (HSB) did not differ
compared to control group. This finding agrees with our hypothesis on the potential
alcohol-related effect of SB with the co-treatment of ABX. It’s also consistent with previous
published study, which showed no effect of intraperitoneal injection of SB on operant
intermittent ethanol (20E) self-administration in alcohol non-dependent rats [67]. On the
other hand, SB supplementation reduced ethanol consumption in alcohol dependent rats
during the drinking escalation phase [67]. In parallel, in our experimental paradigm SB
similarly reduced ethanol intake escalated by ABX treatment only. Since mice drank more
of the SB solution compared to other liquids, we conducted a study with the TBC
paradigm to test if ABX or SB treatment influenced the 20E preference. The results
showed that mice had the increased preference for HSB compared to water while
showing a substantial lower level compared to that of sucrose. Additionally, SB treatment
alone or its combination with antibiotic treatment (ABX), decreased 20E preference
compared to H2O and HSB group respectively. These data suggest that the increased SB
taste preference may have some effect during the TBC study where SB containing bottle
is present along with the 20E bottle. However, it is unlikely to have an impact on the
reduction of ethanol intake during the DID study where only a single bottle containing 20E
is available to mice during the test period.
39

Our study also showed that H2O and ABX mice had similar level of ethanol
preferences, although ABX-treated mice consumed more ethanol than the H2O control
group during DID testing [8]. This could be due to an inherent difference between the
preference for ethanol and the motivation to consume ethanol, suggesting that the
addition of a second bottle containing a treating agent during DID exposure may have
added another source of distraction. Overall, our taste preference findings show a casual
link between the gut microbiome and ethanol drinking behavior.

Even though former studies reported that in some diseases within rodent models, SB
administration can modify gut microbiota composition [68], we are not able to find an
effect of SB on microbiome diversity or composition over the ABX-induced changes, while
drinking behavior in SB groups showed significant changes in mice. This is probably due
to the continuous present of ABX cocktail treatment during the study that suppresses the
bacterial growth and overrides any potential influences of SB on different microbiota
populations and their interactions. Collectively, these findings bring about the possibility
that butyrate treatment is able to affect ethanol intake behaviors through direct or indirect
signaling pathways independent of microbiome composition, emphasizing the key role of
metabolites within the gut-brain interaction.

Neuroinflammation
40

The gut-brain axis consists of bidirectional communication between the CNS and the
enteric nervous system through the combined modulation of vagus nerve, endocrine
system, and immune systems [35]. Previous study has illustrated a relationship between
the disruption of the gut microbiome and the abnormal neural development, brain
dysfunction and neuroinflammation [36]. Besides, large body of evidence suggests
neuroinflammation as a mechanism for developing alcohol addiction [69-71]. Based on
this and the anti-inflammatory role of SB, we hypothesized that 1) neuroinflammation may
be the underlying mechanism for ABX treatment-enhancement of ethanol intake in our
experimental model and 2) the beneficial effects of SB may be linked to its ability to reduce
the ABX-induced neuroinflammation. We therefore, studied the levels of inflammatory
cytokines in the brain as well as changes in the glial cells, microglia and astrocytes, that
are key players in the induction of neuroinflammatory responses.

The mRNA levels of inflammatory cytokines indicate that DID induced
neuroinflammatory response and these results agree with previously published findings
[10, 72]. Importantly, DID-induced neuroinflammation was largely same or even increased
during ABX treatment. This was evident with mRNA changes in key cytokines such as IL-
1β and MCP-1 as well as the anti-inflammatory IL-10. ABX treatment further increased
the DID-induced the mRNA levels of IL-6 and TNF-α, suggesting that reduction in gut
microbial diversity and specific bacterial phyla might have negatively impacted DID effects
on neuroinflammatory response. In agreement with this notion, supplementation with SB
41

prevented DID- and ABX+DID-induced neuroinflammatory response as observed with the
mRNA levels of all tested pro- and anti-inflammatory cytokines. Interestingly, beneficial
effects of SB were found in both cases with and without the presence of ABX. When
translated into the ethanol drinking behavior, the reduction in neuroinflammatory response
may have protected against ABX-induced increased ethanol intake but did not prevent
the baseline ethanol intake (no ABX).

A previous study indicated that butyrate treatment can delay brain aging by
preventing or reversing microglial hyperactivation [73]. Furthermore, butyrate was
reported to suppress inflammatory responses from the glial cells due to its action as a
HDAC inhibitor [59]. Similarly, our results showed SB supplementation lowered the
escalated Iba-1 cells expression induced by ABX treatment, suggesting a decreased cell
activity of microglia. Noticeably, DID exposure and ABX treatment both induced
neuroinflammation while combined effect further increased the cell density of Iba-1
positive cells, indicating a much higher level of neuroinflammation. The branched cells
found in groups with DID and ABX treatment alone and in combination also supported the
previous explanation.

Compared to the microglia, astrocyte had an opposite trend when treated with ABX
and/or SB. DID and ABX group showed a significant decrease in the astrocyte cell density
while SB prevented this decreased trend. Astrocyte outnumber neurons and supports
42

neurons in brain, and they play a key role in numerous functions within CNS [74]. DID
exposure and ABX treatment may suppress its activity by lowering the cell density of
astrocyte. Neuron lack of supports from astrocyte may result in the increased level of
neuroinflammation. In contrast, SB supplementation increased the expression of
astrocyte to support neurons and lowered neuroinflammation. It is reasonable as
astrocyte is not the direct indicator for the neuroinflammation though it has been reported
to be involved in the progression of neuroinflammation. Another strong explanation would
be the altering expression of neurotransmitters. Among all glial cells, astrocytes are the
ones with the highest expression of transporters for glutamate [75], activated astrocytes
were reported to release gliotransmitters including glutamate, D-serine, and ATP [76]. It
is possible that the sustained neuroinflammation could regulate the cell density of
astrocytes thus modulating membrane expression of neurotransmitter receptors.
Furthermore, as previously mentioned, GFAP+ astrocyte density changes are dependent
on time, region, and method of ethanol administration. In terms of the skeleton analysis
of astrocyte, treatment had a little effect in all the parameters. This may due to the limited
sample size or imperfect analysis protocol. However, both the mechanism of astrocyte in
neuroinflammation and the trends in the astrocyte skeleton analyses are worth future
more in-depth investigation.

Both molecular and cellular findings of the current study supported that butyrate can
protect against the increased level of voluntary alcohol intake that induced by ABX
43

treatment by modulating the neuroinflammatory responses. Butyrate has been
extensively studied pharmacologically as a HDAC inhibitor and as such serves as an
attractive therapeutic candidate. We, therefore, explored whether the anti-inflammatory
mechanism of SB was due to its action as HDAC inhibitor. We tested the mRNA levels of
three classic HDAC class I enzymes: HDAC1, HDAC2 and HDAC3 and the results
showed that treatments with not only SB but also with ABX and their combination all
decreased the mRNA levels of HDAC-I subtypes in the brain. These findings illustrated
that SB supplementation and ABX treatment can potentially regulate the gene expression
in the brain. However, this action cannot fully explain why SB supplementation reduced
the ABX-increase in ethanol intake and why ABX treatment promoted more
neuroinflammation. These findings suggest that there are other mechanisms that each of
the treatments or their combinations touch upon. This will await future more detailed
investigations.

Limitations of this study include the inherent difficulty of associating butyric acid
treatment with an increase in serum butyric acid levels. Most SCFAs are rapidly absorbed
by the intestinal mucosa and utilized by colon cells for energy metabolism [77]. Even
though our current study has confirmed the important role of neuroinflammation in the
modulation of alcohol-related behavior, our future focus will be assessing the exact
“footprints” of SB treatment through measurements of activation of signaling pathways
and epigenomic changes due to the unclear mechanism (astrocyte and HDACs). Multiple
44

analysis, such as Sholl analysis could be conducted to deeply investigate the morphology
changes and spatiotemporal complexity for astrocyte and microglia. This study further
strengthens the importance of the neuroinflammation with respect to alcohol consumption
behaviors, allowing for the discovery and development of microbiome-targeted strategies
to address alcohol abuse and other substance use disorders.

45

Bibliography
1. Sacks, J.J., et al., 2010 National and State Costs of Excessive Alcohol
Consumption. Am J Prev Med, 2015. 49(5): p. e73-e79.
2. Foster, J.A., L. Rinaman, and J.F. Cryan, Stress & the gut-brain axis: Regulation
by the microbiome. Neurobiol Stress, 2017. 7: p. 124-136.
3. Thion, M.S., et al., Microbiome Influences Prenatal and Adult Microglia in a Sex-
Specific Manner. Cell, 2018. 172(3): p. 500-516.e16.
4. Bjorkhaug, S.T., et al., Characterization of gut microbiota composition and
functions in patients with chronic alcohol overconsumption. Gut Microbes, 2019.
10(6): p. 663-675.
5. Mostafa, H., et al., Plasma metabolic biomarkers for discriminating individuals with
alcohol use disorders from social drinkers and alcohol-naive subjects. Journal of
Substance Abuse Treatment, 2017. 77: p. 1-5.
6. Fairfield, B. and B. Schnabl, Gut dysbiosis as a driver in alcohol-induced liver injury.
JHEP Reports, 2021. 3(2): p. 100220.
7. Swanson, G.R., et al., Disrupted diurnal oscillation of gut-derived Short chain fatty
acids in shift workers drinking alcohol: Possible mechanism for loss of resiliency
of intestinal barrier in disrupted circadian host. Translational Research, 2020. 221:
p. 97-109.
8. Reyes, R.E.N., et al., Antibiotic-induced disruption of commensal microbiome
linked to increases in binge-like ethanol consumption behavior. Brain Res, 2020.
1747: p. 147067.
9. Lowe, P.P., et al., Chronic alcohol-induced neuroinflammation involves CCR2/5-
dependent peripheral macrophage infiltration and microglia alterations. Journal of
Neuroinflammation, 2020. 17(1): p. 296.
10. Erickson, E.K., et al., Neuroimmune signaling in alcohol use disorder. Pharmacol
Biochem Behav, 2019. 177: p. 34-60.
11. Swift, R.M. and E.R. Aston, Pharmacotherapy for alcohol use disorder: current and
emerging therapies. Harvard review of psychiatry, 2015. 23(2): p. 122-133.
12. Chick, J. and D.J. Nutt, Substitution therapy for alcoholism: time for a reappraisal?
J Psychopharmacol, 2012. 26(2): p. 205-12.
46

13. Mutschler, J., et al., Disulfiram, an Option for the Treatment of Pathological
Gambling? Alcohol and Alcoholism, 2010. 45(2): p. 214-216.
14. Soyka, M. and S. Rösner, Opioid antagonists for pharmacological treatment of
alcohol dependence - a critical review. Curr Drug Abuse Rev, 2008. 1(3): p. 280-
91.
15. Mason, B.J. and C.J. Heyser, Acamprosate: a prototypic neuromodulator in the
treatment of alcohol dependence. CNS & neurological disorders drug targets, 2010.
9(1): p. 23-32.
16. Rooks, M.G. and W.S. Garrett, Gut microbiota, metabolites and host immunity. Nat
Rev Immunol, 2016. 16(6): p. 341-52.
17. Hold, G.L., et al., Role of the gut microbiota in inflammatory bowel disease
pathogenesis: what have we learnt in the past 10 years? World J Gastroenterol,
2014. 20(5): p. 1192-210.
18. Schwabe, R.F. and C. Jobin, The microbiome and cancer. Nat Rev Cancer, 2013.
13(11): p. 800-12.
19. Turnbaugh, P.J., et al., An obesity-associated gut microbiome with increased
capacity for energy harvest. Nature, 2006. 444(7122): p. 1027-31.
20. Harris, K., et al., Is the gut microbiota a new factor contributing to obesity and its
metabolic disorders? J Obes, 2012. 2012: p. 879151.
21. David, L.A., et al., Diet rapidly and reproducibly alters the human gut microbiome.
Nature, 2014. 505(7484): p. 559-63.
22. Voigt, R.M., et al., Circadian disorganization alters intestinal microbiota. PLoS One,
2014. 9(5): p. e97500.
23. Mutlu, E., et al., Intestinal dysbiosis: a possible mechanism of alcohol-induced
endotoxemia and alcoholic steatohepatitis in rats. Alcohol Clin Exp Res, 2009.
33(10): p. 1836-46.
24. Yan, A.W., et al., Enteric dysbiosis associated with a mouse model of alcoholic liver
disease. Hepatology, 2011. 53(1): p. 96-105.
25. Lowe, P.P., et al., Reduced gut microbiome protects from alcohol-induced
neuroinflammation and alters intestinal and brain inflammasome expression.
Journal of neuroinflammation, 2018. 15(1): p. 298-298.
47

26. Cederbaum, A.I., Alcohol metabolism. Clinics in liver disease, 2012. 16(4): p. 667-
685.
27. Engen, P.A., et al., The Gastrointestinal Microbiome: Alcohol Effects on the
Composition of Intestinal Microbiota. Alcohol Res, 2015. 37(2): p. 223-36.
28. Purohit, V., et al., Alcohol, intestinal bacterial growth, intestinal permeability to
endotoxin, and medical consequences: summary of a symposium. Alcohol
(Fayetteville, N.Y.), 2008. 42(5): p. 349-361.
29. den Besten, G., et al., The role of short-chain fatty acids in the interplay between
diet, gut microbiota, and host energy metabolism. J Lipid Res, 2013. 54(9): p.
2325-40.
30. Cryan, J.F. and T.G. Dinan, Mind-altering microorganisms: the impact of the gut
microbiota on brain and behaviour. Nature Reviews Neuroscience, 2012. 13(10):
p. 701-712.
31. Watts, J.L. and M. Ristow, Lipid and Carbohydrate Metabolism in Caenorhabditis
elegans. Genetics, 2017. 207(2): p. 413-446.
32. Hosseini, E., et al., Propionate as a health-promoting microbial metabolite in the
human gut. Nutr Rev, 2011. 69(5): p. 245-58.
33. Viaud, S., et al., Gut microbiome and anticancer immune response: really hot Sh*t!
Cell death and differentiation, 2015. 22(2): p. 199-214.
34. Corrêa-Oliveira, R., et al., Regulation of immune cell function by short-chain fatty
acids. Clinical & translational immunology, 2016. 5(4): p. e73-e73.
35. Reyes, R.E.N., et al., Microbiome meets microglia in neuroinflammation and
neurological disorders. Neuroimmunology and Neuroinflammation, 2020. 7(3): p.
215-233.
36. Zhu, S., et al., The progress of gut microbiome research related to brain disorders.
Journal of Neuroinflammation, 2020. 17(1): p. 25.
37. Holley, M.M. and T. Kielian, Th1 and Th17 cells regulate innate immune responses
and bacterial clearance during central nervous system infection. J Immunol, 2012.
188(3): p. 1360-70.
38. Glass, C.K., et al., Mechanisms underlying inflammation in neurodegeneration.
Cell, 2010. 140(6): p. 918-34.
48

39. Pascual, M., et al., Cytokines and chemokines as biomarkers of ethanol-induced
neuroinflammation and anxiety-related behavior: Role of TLR4 and TLR2.
Neuropharmacology, 2015. 89: p. 352-359.
40. Bode, C., V. Kugler, and J.C. Bode, Endotoxemia in patients with alcoholic and
non-alcoholic cirrhosis and in subjects with no evidence of chronic liver disease
following acute alcohol excess. J Hepatol, 1987. 4(1): p. 8-14.
41. Lippai, D., et al., Micro-RNA-155 deficiency prevents alcohol-induced serum
endotoxin increase and small bowel inflammation in mice. Alcoholism, clinical and
experimental research, 2014. 38(8): p. 2217-2224.
42. Zorumski, C.F., S. Mennerick, and Y. Izumi, Acute and chronic effects of ethanol
on learning-related synaptic plasticity. Alcohol (Fayetteville, N.Y.), 2014. 48(1): p.
1-17.
43. Roberto, M. and F.P. Varodayan, Synaptic targets: Chronic alcohol actions.
Neuropharmacology, 2017. 122: p. 85-99.
44. Tracey, K.J., Understanding immunity requires more than immunology. Nature
Immunology, 2010. 11(7): p. 561-564.
45. Qin, L., et al., Increased systemic and brain cytokine production and
neuroinflammation by endotoxin following ethanol treatment. Journal of
Neuroinflammation, 2008. 5(1): p. 10.
46. He, J. and F.T. Crews, Increased MCP-1 and microglia in various regions of the
human alcoholic brain. Exp Neurol, 2008. 210(2): p. 349-58.
47. Marshall, S.A., et al., IL-1 receptor signaling in the basolateral amygdala
modulates binge-like ethanol consumption in male C57BL/6J mice. Brain Behav
Immun, 2016. 51: p. 258-267.
48. Neupane, S.P., et al., Cytokine Changes following Acute Ethanol Intoxication in
Healthy Men: A Crossover Study. Mediators of Inflammation, 2016. 2016: p.
3758590.
49. Davis, M.I., Ethanol-BDNF interactions: still more questions than answers.
Pharmacology & therapeutics, 2008. 118(1): p. 36-57.
50. Crews, F.T., et al., The role of neuroimmune signaling in alcoholism.
Neuropharmacology, 2017. 122: p. 56-73.

49

51. McClain, J.A., et al., Adolescent binge alcohol exposure induces long-lasting
partial activation of microglia. Brain Behav Immun, 2011. 25 Suppl 1(Suppl 1): p.
S120-8.
52. Lowe, P.P., et al., Reduced gut microbiome protects from alcohol-induced
neuroinflammation and alters intestinal and brain inflammasome expression.
Journal of Neuroinflammation, 2018. 15(1): p. 298.
53. Adermark, L. and M.S. Bowers, Disentangling the Role of Astrocytes in Alcohol
Use Disorder. Alcoholism, clinical and experimental research, 2016. 40(9): p.
1802-1816.
54. Miguel-Hidalgo, J.J., Lower packing density of glial fibrillary acidic protein-
immunoreactive astrocytes in the prelimbic cortex of alcohol-naive and alcohol-
drinking alcohol-preferring rats as compared with alcohol-nonpreferring and Wistar
rats. Alcohol Clin Exp Res, 2005. 29(5): p. 766-72.
55. Bull, C., et al., Differential response of glial fibrillary acidic protein-positive
astrocytes in the rat prefrontal cortex following ethanol self-administration. Alcohol
Clin Exp Res, 2015. 39(4): p. 650-8.
56. Polis, B., et al., L-Norvaline Reverses Cognitive Decline and Synaptic Loss in a
Murine Model of Alzheimer's Disease. Neurotherapeutics, 2018. 15(4): p. 1036-
1054.
57. Scheppach, W. and F. Weiler, The butyrate story: old wine in new bottles? Curr
Opin Clin Nutr Metab Care, 2004. 7(5): p. 563-7.
58. Chen, W.-Y., et al., The histone deacetylase inhibitor suberoylanilide hydroxamic
acid (SAHA) alleviates depression-like behavior and normalizes epigenetic
changes in the hippocampus during ethanol withdrawal. Alcohol (Fayetteville, N.Y.),
2019. 78: p. 79-87.
59. Faraco, G., et al., Histone deacetylase (HDAC) inhibitors reduce the glial
inflammatory response in vitro and in vivo. Neurobiol Dis, 2009. 36(2): p. 269-79.
60. Leclercq, S., et al., Gut Microbiota-Induced Changes in β-Hydroxybutyrate
Metabolism Are Linked to Altered Sociability and Depression in Alcohol Use
Disorder. Cell Reports, 2020. 33(2): p. 108238.
61. Huynh, N., et al., Preclinical development of moxidectin as a novel therapeutic for
alcohol use disorder. Neuropharmacology, 2017. 113(Pt A): p. 60-70.

50

62. Oliveira, A.C., et al., Chronic ethanol exposure during adolescence through early
adulthood in female rats induces emotional and memory deficits associated with
morphological and molecular alterations in hippocampus. J Psychopharmacol,
2015. 29(6): p. 712-24.
63. Park, M.J. and F. Sohrabji, The histone deacetylase inhibitor, sodium butyrate,
exhibits neuroprotective effects for ischemic stroke in middle-aged female rats.
Journal of Neuroinflammation, 2016. 13(1): p. 300.
64. Linnerbauer, M., M.A. Wheeler, and F.J. Quintana, Astrocyte Crosstalk in CNS
Inflammation. Neuron, 2020. 108(4): p. 608-622.
65. Mayer, E.A., T. Savidge, and R.J. Shulman, Brain–Gut Microbiome Interactions
and Functional Bowel Disorders. Gastroenterology, 2014. 146(6): p. 1500-1512.
66. Jadhav, K.S., et al., Gut microbiome correlates with altered striatal dopamine
receptor expression in a model of compulsive alcohol seeking.
Neuropharmacology, 2018. 141: p. 249-259.
67. Simon-O'Brien, E., et al., The histone deacetylase inhibitor sodium butyrate
decreases excessive ethanol intake in dependent animals. Addict Biol, 2015. 20(4):
p. 676-89.
68. Ma, Q., et al., Impact of microbiota on central nervous system and neurological
diseases: the gut-brain axis. Journal of neuroinflammation, 2019. 16(1): p. 53-53.
69. Leclercq, S., et al., The link between inflammation, bugs, the intestine and the brain
in alcohol dependence. Transl Psychiatry, 2017. 7(2): p. e1048.
70. Orio, L., et al., Oleoylethanolamide, Neuroinflammation, and Alcohol Abuse.
Frontiers in molecular neuroscience, 2019. 11: p. 490-490.
71. Tappenden, K.A. and A.S. Deutsch, The physiological relevance of the intestinal
microbiota--contributions to human health. J Am Coll Nutr, 2007. 26(6): p. 679s-
83s.
72. Thiele, T.E. and M. Navarro, "Drinking in the dark" (DID) procedures: a model of
binge-like ethanol drinking in non-dependent mice. Alcohol, 2014. 48(3): p. 235-
41.
73. Matt, S.M., et al., Butyrate and Dietary Soluble Fiber Improve Neuroinflammation
Associated With Aging in Mice. Front Immunol, 2018. 9: p. 1832.

51

74. Kim, S., A. Covington, and E.G. Pamer, The intestinal microbiota: Antibiotics,
colonization resistance, and enteric pathogens. Immunological reviews, 2017.
279(1): p. 90-105.
75. Huang, Y.H., et al., Astrocyte Glutamate Transporters Regulate Metabotropic
Glutamate Receptor-Mediated Excitation of Hippocampal Interneurons. The
Journal of Neuroscience, 2004. 24(19): p. 4551.
76. Harada, K., T. Kamiya, and T. Tsuboi, Gliotransmitter release from astrocytes:
functional, developmental and pathological implications in the brain. Frontiers in
Neuroscience, 2016. 9(499).
77. den Besten, G., et al., The role of short-chain fatty acids in the interplay between
diet, gut microbiota, and host energy metabolism. Journal of lipid research, 2013.
54(9): p. 2325-2340.

Abstract (if available)

Abstract Building evidence supports the crucial role of bidirectional interactions between changes in the gut microbiota and the central nervous system (CNS) during the progression of neuropathology. Patients who have alcohol use disorder (AUD) expressed different intestinal bacterial compositions when comparing to non-drinkers. Whether alcohol-induced microbiota changes can lead to related behaviors such as alcohol addiction, needs further exploration. In initial study, we found an increase in the ethanol consumption behavior when mice were exposed to a “Drinking in the Dark” (DID) paradigm, caused by treatment with a antibiotic cocktail (ABX) treatment. In parallel, there was a dramatic reduction in short-chain fatty acid (SCFA) producing microbial phyla. We further tested the effect of a common SCFA, sodium butyrate (SB), in C57BL/6J mice on ABX-induced ethanol intake. Supplementation with SB prevented ABX effect on ethanol intake and resulted in a lower ethanol preference compared to control mice within respective models, DID and two bottle choice paradigms. Subsequent work focused on identification of potential mechanisms underlying these effects. As a histone deacetylase inhibitor, SB is known to impact numerous host activities, such as neuroinflammation, which has been considered to be an important mechanism underlying AUD. Additionally, butyrate treatment has been shown to effectively improve memory deficits and inhibit neuroinflammation in the treatment of neurodegenerative diseases. Based on these, we set forth a hypothesis that SB protects against increased antibiotic-induced ethanol consumption in mice by modulating the ethanol-triggered neuroinflammatory responses. The qPCR data demonstrated that ABX alone did not affect neuroinflammation induced by ethanol exposure while SB supplementation reduced it with or without ABX treatment. In addition, treatments with ABX and ethanol alone or with their combination regulated the cell density of GFAP- and Iba-1-positive cells, suggesting altered activities of astrocyte and microglia, respectively. Moreover, SB supplementation altered the numbers of both astrocyte and microglia in the hippocampus. Our results indicate that gut microbiota influence alcohol drinking behavior in mice through the modulation of neuroinflammation. The findings of the current study will uncover new insights in the communication between different microbiome compositions in intestine and ethanol related behaviors, emerging the microbiome as a promising therapeutic approach to treat AUD and other substance use disorders.

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Asset Metadata

Creator Gao, Lei (author)

Core Title Sodium butyrate prevents antibiotic-induced increase in ethanol drinking in C57BL/6J mice by modulating neuroinflammatory response

School School of Pharmacy

Degree Master of Science

Degree Program Pharmaceutical Sciences

Degree Conferral Date 2021-08

Publication Date 07/16/2021

Defense Date 07/14/2021

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

Tag butyrate,gut-brain axis,microglia,neuroinflammation,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Asatryan, Liana (committee chair), Cadenas, Enrique (committee member), Davies, Daryl (committee member)

Creator Email gaolei@usc.edu,leigao489@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC15582113

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