University of Southern California Dissertations and Theses

Maintenance of genome stability at fragile sites in Schizosaccharomyces pombe

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Maintenance of genome stability at fragile sites in Schizosaccharomyces pombe

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Content 44

Maintenance of Genome Stability at
Fragile Sites in Schizosaccharomyces pombe

By

Chance Evan Jones

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
(MOLECULAR BIOLOGY)

May 2023

Copyright 2023 Chance Evan Jones

ii
Dedication
I dedicate this dissertation to my parents, Paul and Charlotte Jones,
who without their support this would not have been possible.

iii
Acknowledgements
I would like to thank my PI Dr. Susan L. Forsburg for allowing me to complete my research
in her lab and providing me all the necessary resources for my research here and in the future. I
wouldn’t be here today without her. In addition, I would also like to thank my undergraduate
research PI Dr. Andrei Barkovskii who started me on the journey of biological research. Back then
I was a mediocre freshman general biology major with no path or direction and he gave me the
opportunity to build a future in something I love. I would especially like to thank my lab mates
Joshua Park, and Tingting Li for their advice, knowledge, skills and most importantly
companionship in the many hours of working in the lab. One should never doubt the importance
of a comfortable, open, and relaxed lab environment, and I found that with them. I would like to
thank the senior lab members who have taught me so much over the years, Dr. Amanda Jensen,
Dr. Seong Min Kim, Jiping Yuan, Dr. Kuofang Shen, and Dr. Vishnu Tripathi who through them
many of my most valuable skills have been refined and perfected. I would like to thank my mentee
Matthew Braga who I first met teaching honors biology lab. In actuality he taught me just as much
about being a good mentor as I taught him how to be a researcher and one of my proudest moments
was his acceptance into an amazing PhD program of his own. Lastly I would like to thank a few
people who are most special to me who have supported me through thick and thin and made me
strong enough to get to the place I am today, Kodie Redongo, Andrew Yu, Caleb Ghione, Kellie
Pitts, and Kirstie Barkoot. Kodie, for all of the late night facetimes while I sit in lab waiting for an
experiment and giving up your time to sit on the couch patiently while I work on this very thesis.
Caleb, for all the time spend in the lab keeping me company during long experiments, and the best
baked goods ever. Andrew, for always being there for whatever I was going through. Kirstie and
Kellie, for making so many great memories together as we traversed our undergrad careers. I
wouldn’t be the same without all of these important people in my life.
Thank you all.

iv
Table of Contents
Dedication .................................................................................................................................. ii
Acknowledgements ................................................................................................................. iii
List of Tables ............................................................................................................................. v
List of Figures ........................................................................................................................... vi
Abbreviations ........................................................................................................................... vii
Chapter 1: Introduction
Introduction ................................................................................................................... 1
DNA repair pathways affect genome stability .............................................................. 2
Genome stability of replication forks ............................................................................ 4
Genome stability of the ribosomal repeats .................................................................... 6
References ................................................................................................................... 13
Chapter 2: Monitoring Schizosaccharomyces pombe genome stress by visualizing end-
binding protein Ku
Introduction ................................................................................................................. 21
Results ......................................................................................................................... 22
Discussion .................................................................................................................... 29
Materials and Methods ................................................................................................ 32
References ................................................................................................................... 35
Supplemental Information ........................................................................................... 39
Chapter 3: Impact of 1,6-Hexanediol on Schizosaccharomyces pombe Genome Stability
Introduction ................................................................................................................. 44
Results ......................................................................................................................... 45
Discussion .................................................................................................................... 53
Materials and Methods ................................................................................................ 54
References ................................................................................................................... 59
Supplemental Information ........................................................................................... 63
Chapter 4: Pathways of rDNA Copy Number Homeostasis in Schizosaccharomyces
pombe
Introduction ................................................................................................................. 66
Results ......................................................................................................................... 68
Discussion .................................................................................................................... 74
Materials and Methods ................................................................................................ 77
References ................................................................................................................... 79
Supplemental Information ........................................................................................... 84
Appendix A: Nanopore sequencing of Schizosaccharomyces pombe
Background .................................................................................................................. 88
Results ......................................................................................................................... 89
Materials and Methods ................................................................................................ 94
Troubleshooting ........................................................................................................... 94
References ................................................................................................................... 99

v
List of tables
Chapter 2: Monitoring Schizosaccharomyces pombe genome stress by visualizing end-
binding protein Ku
Table 1: Strain list ........................................................................................................ 39
Table 2: Primer list ...................................................................................................... 39
Chapter 3: Impact of 1,6-Hexanediol on Schizosaccharomyces pombe Genome Stability
Table 1: Strain list ........................................................................................................ 54
Appendix A: Nanopore sequencing of Schizosaccharomyces pombe
Table 1: Gene mutation read out of ChIII of strain FY333 ......................................... 93

vi
List of Figures
Chapter 1: Introduction
Figure 1: DNA DSB repair pathway choice .................................................................. 3
Figure 2: Sequential eukaryotic origin recognition and licensing ................................. 5
Figure 3: Structure and location of the FPC in association with the CMG complex .... 6
Figure 4: Structure of the S. pombe rDNA repeat and replication fork barrier
system ............................................................................................................................ 8
Figure 5: Visualization of the phase separated nucleolus of S. pombe ........................ 11
Chapter 2: Monitoring Schizosaccharomyces pombe genome stress by visualizing end-
binding protein Ku
Figure 1: Construction of fluorescently tagged strains ................................................ 24
Figure 2: Pku70-citrine colocalization with DNA repair proteins .............................. 26
Figure 3: Colocalization of Mre11-mcherry, Rad52-YFP, and Pku70-Citrine ........... 27
Figure 4: Pku70 localization in a dynamic time course of MMS treatment ................ 28
Sup. Figure 1: Pku-Citrine is competent for NHEJ repair ........................................... 40
Sup. Figure 2: Deletion of Pku80:kan disrupts Pku70-Citrine localization ................ 40
Sup. Figure 3: Colocalization of Pku70 and Mre11 .................................................... 41
Sup. Figure 4: Timelapse of Pku70 and Rad52 ........................................................... 41
Sup. Figure 5: Timelapse of Pku70 and Rad52 ........................................................... 42
Chapter 3: Impact of 1,6-Hexanediol on Schizosaccharomyces pombe Genome Stability
Figure 1: Characteriztion of 1,6 hexanediol effects on S. pombe ................................ 48
Figure 2: Phase separation stabilizes heterochromatic regions ................................... 49
Figure 3: DNA damage protein foci increases but do not colocalize with Gar2
bubbles in 1,6 hexanediol ............................................................................................ 50
Figure 4: rDNA copy number and stability is not phase separation dependent .......... 52
Figure 5: Centromere stability is independent of phase separation ............................. 53
Sup. Figure 1: Acute recovery from 5% 1,6-hexanediol ............................................. 63
Sup. Figure 2: Acute recovery from 2.5% 1,6-hexanediol .......................................... 64
Chapter 4: Pathways of rDNA Copy Number Homeostasis in Schizosaccharomyces
pombe
Figure 1: Ultra low copy number of rDNA leads to increased genome instability ..... 69
Figure 2: Targeted mutant screen reveals pathways of rDNA copy number
homeostasis .................................................................................................................. 72
Figure 3: Pathways of rDNA homeostasis .................................................................. 73
Figure 4: MMS stress causes rDNA array contraction ................................................ 74
Sup. Figure 1: rDNA ratio to WT of all single mutants .............................................. 84
Sup Figure 2: rDNA ratio to WT of all double mutants .............................................. 85
Sup Figure 3: rDNA ratio to WT of selected mutants ................................................ 86
Appendix A: Nanopore sequencing of Schizosaccharomyces pombe
Figure 1: Estimated read length ................................................................................... 91
Figure 2: Original available pores during the sequencing run at interval pore scans .. 91
Figure 3: Pore use during sequencing .......................................................................... 92
Figure 4: Barcoding read count distribution ................................................................ 92
Figure 5: Example alignment of Ch3 of FY333 .......................................................... 92
vii
Abbreviations

ActD: Actinomycin D
AHT: Anhydrotetracycline
BER: Base excision repair
CFP: Cyan fluorescent protein
CPT: Camptothecin
CPU: Central processing unit
DBA: Diamond-blackfan anemia
DFC: Dense fibrillar complex
D-Loop: Displacement loop
DNA: Deoxyribonucleic acid
DSB: Double strand break
ERC: Extrachromosomal rDNA circles
FC: Fibrillar center
FOA: Fluoroorotic acid
FPC: Fork protection complex
GC: Granular component
GFR: Gross chromosomal rearrangement
GFP: Green fluorescent protein
GPU: Graphical processing unit
HD: 1,6-Hexanediol
Hex: 1,6-Hexanediol
HR: Homologous recombination
HU: Hydroxyurea
H3K9me3: Histone 3 Lysine 9 tri-
methylation
IGS: Intergenic sequence
LLPS: Liquid liquid phase separation
MMEJ: Microhomology mediated end
joining
MMS: Methyl methanesulfonate
NHEJ: Non homologous end joining
OD: Optical density
ORC: Origin recognition complex
PCR: Polymerase chain reaction
Phleo: Phleomycin
qPCR: Quantitative PCR
rDNA: Ribosomal DNA
RFB: Replication fork barrier
R-loop: RNA loop (RNA:DNA Hybrid)
RPA: Replication protein A
RNA: Ribonucleic acid
rRNA: Ribosomal RNA
SNP: Single nucleotide polymorphism
SPB: Spindle pole body
S. pombe: Schizosaccharomyces pombe
SSA: Single strand annealing
ssb1: Single strand binding protein 1
ssDNA: Single stranded DNA
TS: Temperature sensitive
USCE: Unequal sister chromatid exchange
WT: Wild type
YES: Yeast extract supplemented media
YFP: Yellow florescent protein
1
Chapter 1: Introduction
Genome stability is a broad term that defines how prone an organisms genetic material is
to mutational changes as the result of intrinsic or extrinsic stress. Sources of these stressors can be
any number of insults to the DNA such as gamma radiation, UV radiation, enzymatic damage,
aging, oxidative stress, replication stress, replication errors, protein adducts and more. As a result
of these genomic insults this often leads to genetic mutations. These mutations have varying effects
depending on the location throughout the genome. For example if in tumor suppressor gene this
can often lead to one of the most detrimental consequences of genome instability, cancer. Cancer
cells are well known for changes in copy number, structural arrangements, indels, and SNPs
(Sieber, O., et al. 2005; Donley, N., & Thayer, M. J. 2013; Jeggo, P. A., et al. 2016).
Fragile sites within the genome are areas where there is an increased risk of genome
instability compared to the rest of the genome. Some examples of these are highly transcribed
regions which has more likelihood of replication transcription collisions leading to fork collapse,
highly repetitive regions that are at increased likelihood of recombinational stress, and more. Such
areas of the genome that are often uniformly considered fragile sites are the
centromere/pericentromere, rDNA repeats, telomeres, late replicating regions of the genome, and
high copy number repeats. The fragility of these sites leading to genome instability can have drastic
consequences for the organism while complete loss of any genetic diversity also can be detrimental
to the adaptability of a population to stresses (Donley, N., & Thayer, M. J. 2013).
Many classic fragile sites described above are often made up or contain some
heterochromatinized repeats. Some examples of these are the telomere,
centromere/pericentromere, and a portion of the rDNA. True heterochromatin is characterized by
trimethylation on the ninth lysine of histone three (H3K9me3) (Grewal, S. I., & Jia, S. 2007; Greer,
E. L., & Shi, Y. 2012). This marker of heterochromatin is uniform across most eukaryotes but is
missing in some earlier species such as S. cerevisiae. This H3K9me3 allows for binding of proteins
containing a chromodomain, while some chromodomain binding proteins bind at a stronger
affinity than others (Schalch, T., et al. 2009; Zocco, M., et al. 2016). One of the most well known
and uniform chromodomain containing heterochromatin binding protein throughout eukaryotes is
the HP1 group protein (Cowieson, N. P., et al. 2000; Eissenberg, J. C., et al. 2000; Sanulli, S., et
al. 2019). This group of proteins aids in chromatin compaction, condensation, heterochromatin
2
replication timing, and recently has been discovered to allow for phase separation of the
heterochromatin domain (Li, P. C., et al. 2011; Li, P. C., et al. 2013; Larson, A. G., et al. 2017;
Sanulli, S., et al. 2019; Keenen, M. M., et al. 2021).
Schizosaccharomyces pombe (S. pombe) is an amazing model organism to study genome
stability of fragile site. The first reason is due to its ease of culturing, growth rate, and solid back
history of genetic research (Forsburg, S. L. 2003). S. pombe also has many genetically homologous
characteristics, protein orthologs, and pathways that are the same in higher eukaryotes and thus
the results can be more far reaching than just for S. pombe. Another characteristic of S. pombe that
makes it perfect to study is that it contains three large chromosomes which require machinery such
as that associated with centromere/pericentromere regions which must be larger and more robust
like in higher eukaryotes (Clarke, L., et al. 1993; Wood, V., et al. 2002). S. pombe also has true
heterochromatin through H3K9 trimethylation (H3K9me3) (Eissenberg, J. C., et al. 2000). Lastly
S. pombe spends most of its life cycle in G2 meaning that cells DNA repair choice is focused
mostly on homologous recombination (HR) using the already duplicated sister chromatid instead
of other more error prone pathways such as non-homologous end joining (NHEJ) (Forsburg, S. L.,
& Nurse, P. 1991; Raji, H., & Hartsuiker, E. 2006). S. pombe is often considered an intermediate
species between earlier organisms such as S. cerevisiae. In fact there is roughly 400 million years
of evolution separating S. cerevisiae and S. pombe and it has even been coined the unicellular
“micromammal” model organism (Berbee, M. L., & Taylor, J. W. 1993; Forsburg, S. L. 2003;
Vyas, A., et al. 2021). These are just a few reasons why S. pombe is an amazing model organism
which has stimulated a plethora of research applicable to the wider area of eukaryotic genetics
research.
1.1 DNA repair pathways affect genome stability
There are numerous types of damage that can occur to DNA as discussed previously. One
of the most deleterious types of DNA damage that can occur is a double strand break (DSB).
Double strand breaks are especially toxic because both ends are liable to nucleolytic degradation,
aberrant recombination, and if not repaired with full fidelity can often lead to permanent mutations.
There are two main pathways associated with repairing DNA double strand breaks which are
homologous recombination (HR) and non-homologous end joining (NHEJ) (Shrivastav, M., et al.
2008; Symington, L. S., & Gautier, J. 2011; Ceccaldi, R., et al. 2016). Other alternative end joining
3
pathways exist as well such as microhomology mediated end joining (MMEJ) and single strand
annealing (SSA) however these are more mutagenic (Fishman-Lobell, J., et al. 1992; McVey, M.,
et al. 2008; Sfeir, A., et al. 2015; Chang, H. H., et al. 2017).

1.1.1 Homologous recombination
In HR broken ends are first bound by the MRN complex consisting of Mre11-Nbs1-Rad50
complex. Activation of the nuclease activity of Mre11 is then triggered by Ctp1 binding
(Zdravković, A., et al. 2021). The MRN complex completes short range resection of 100-300bp
while long range resection is completed by Exo1 or DNA2 which can continue for multiple kb
(Mimitou, E. P., & Symington, L. S. 2008; Zhu, Z., et al. 2008). Resection leaves single stranded
DNA (ssDNA) exposed which is coated by the single strand binding protein Ssb1 (RPA). The
recombination mediator protein Rad52 along with Rad55-Rad57 aid in displacement of RPA with
the single strand binding protein recombinase Rad51. The Rad51 recombinase protein then
initiates strand invasion, displacement loop (D-loop) formation, and homology search. The D-loop
can be extended by DNA polymerase and thus copy any missing information in the original strand
due to the break. Resolution of the copied regions then leads to either crossover or noncrossover
products (Aylon, Y., & Kupiec, M. 2004; Raji, H., & Hartsuiker, E. 2006). HR can often lead to
high fidelity repair leading to little to no loss of information, however too much can lead to
chromosomal instability and a hyperrecombination phenotype.
1.1.2 Non-homologous end joining
Figure1. DNA DSB repair pathway choice
This Figure shows the four main pathways of
DNA DSB repair discussed NHEJ, HR, MMEJ,
and SSA. Adapted from Symington, L. S. 2016

4
Non homologous end joining (NHEJ) is process of DSB repair in which two uniformly
blunt ends are bound by the heterodimer ku70/ku80 (Baumann, P., & Cech, T. R. 2000). The end
bound Ku complex competes with the MRN complex in order to inhibit its exonuclease action and
thus ssDNA formation (Langerak, P., et al. 2011). Thus there is a temporal variation in which DSB
repair pathway will be chosen and is temporally, cell cycle, and even species dependent. After Ku
complex binding other accessory factors are recruited such as Xrc4 and Xlf1 that aid in the function
of the DNA ligase Lig4. Lig4 then ligates the blunt DNA ends together fixing the break (Prudden,
J., et al. 2003).
1.1.3 Alternative repair pathways
Often cells must undergo alternative pathways to repair DSB’s. This can often be when
DSB ends are not blunt or nearly blunt meaning the Ku heterodimer cannot bind and relegate the
ends and the HR pathway is nonfunctional. These alternative end joining pathway mechanisms
function on the annealing of either short or long stretches of homology within the same strand.
They do not undergo strand invasion and thus are Rad51 dependent. Microhomology mediated
end joining (MMEJ) uses only a few nucleotides of homology in length while single strand
annealing (SSA) uses homologous sequences of 10bp or greater. These pathways lead to the
deletion of at least some section of DNA that is between the short or long homologous sequence
and where the break occurred. In longer arrays this often leads to a loss of large segments of the
genome (Fishman-Lobell, J., et al. 1992; McVey, M., et al. 2008; Sfeir, A., et al. 2015; Chang, H.
H., et al. 2017).
1.2 Genome stability of replication forks
High fidelity replication of an entire genome is important for limiting mutagenesis and
inheritance of stable genomes. However replication is a dubious task, cells must first license forks
so as not to have rereplication, replication forks must have all proteins removed off the DNA in
order to duplicate it, and must proceed through hard to replicate regions that often stall the
replication fork. All of these areas are weak points in the system and any dysregulation can easily
lead to genome damage and possibly cell death.
5

1.2.1 Origin recognition and licensing of replication forks
Origins are first recognized by the origin recognition complex (ORC). In S. pombe these
sites are not sequence defined but often contain AT stretches that allow for easier unwinding
(Bailis, J. M., & Forsburg, S. L. 2007). Cdt1 and Cdc18 (Cdc6 in S. cerevisiae) allow for
bidirectional Mcm2-7 helicase binding forming the Pre-RC (Forsburg, S. L., & Nurse, P. 1994;
Grallert, B., & Nurse, P. 1996). CDK and DDK activation allow for Cdc45 and GINS binding to
the MCM 2-7 hexamer which then causes strand melting forming the Pre-initiation complex
(Hopwood, B., & Dalton, S. 1996; Tanaka, T., et al. 1997). Further components are added such as
the polymerases and mcm10 which then allow for the replication fork to proceed bidirectionally
(Hopwood, B., & Dalton, S. 1996; Aparicio, O. M., et al. 1997). Each of these steps allows for a
proper sequential activation of the fork and must occur in the proper order to facilitate proper
origin firing.
1.2.2 Fork protection complex
Figure 2. Sequential eukaryotic origin recognition
and licensing
This Figure shows the main general steps in recognition,
licensing, and therefore firring of eukaryotic replication
forks. Adapted from Wu, L., et al. 2014

6
Replication forks encounter various chromosomal states, nucleotide depletion, DNA
binding proteins, and transcriptional machinery throughout the process of replication. Often times
these adducts lead to slowing or stalling of replication forks. In fact each rDNA repeat contains a
polar replication fork barrier (RFB) which allows for replication to proceed in the same direction
as transcription. Proper stalling of replication forks leads to a maintenance of the helicase and
accessory factors needed for the replication fork to continue to progress if the issue is mitigated.
The most important factors for this process is the fork protection complex (FPC). The two main
FPC proteins in pombe are Swi1 and Swi3 (Krings, G., & Bastia, D. 2004, Leman, A. R., &
Noguchi, E. 2012). Mrc1 (claspin) and pol alpha accessory factor Mcl1 are also often considered
part of the FPC however their role in stalling forks is not as well characterized (Tanaka, H., et al.
2009; Zech, J., et al. 2015). Importantly proper stalling of replication fork barriers is reliant on
DDK phosphorylation of MCM components. Without this FPC components Swi1/Swi3 do not
localize to the replication fork, do then do not antagonize the protein adduct removing helicase
Rrm3 (Pfh1 in S. pombe), resulting in loss of barrier function. (Matsumoto, S., et al. 2005;
Mohanty, B. K., et al. 2006; Bastia, D., et al. 2016).

1.3 Genome stability of the ribosomal repeats
The Eukaryotic genome is one of the most complex environments in the cell. Coordinated
proper duplication of the entire genome consisting of magabase values of DNA must occur every
cycle or complex mechanisms of repair must be initiated in order to mitigate any failures. Along
with this duplication of the genome the cell itself must produce an adequate number of intracellular
Figure 3. Structure and location of the FPC
in association with the CMG complex
This figure shows the recently discovered cryo-
EM structure of the main eukaryotic FPC
components Csm3/Tof1 (S. pombe Swi1/Swi3),
Mrc1, and Ctf4 (Mcl1). Adapted from Baretić,
D., et al. 2020

7
components to support two living cells from one. This requires an intense amount of protein
synthesis that can often be at odds to genome duplication. Both of these processes of high rates of
transcription and difficult DNA replication culminate in the ribosomal DNA (rDNA) repeats in the
nucleolus.
The rDNA poses a risk to genome stability due to programmed fork stalling at replication
fork barriers within each rDNA repeat. In S. pombe there are ~150 rDNA 10.9kb repeats spread
between the two telomere proximal ends of the smallest chromosome III which represent 5-10%
of the genome (Toda, T., et al. 1984). Each of the 150 rDNA repeats all contain a set of four
unidirectional replication fork barriers at the end of each transcriptional unit within the intergenic
sequence (IGS) (Sanchez, J. A., et al. 1998). This unidirectional fork stalling inhibits
transcription/replication fork collisions. Stalled forks are stabilized specifically in the rDNA by
the Smc5/6 complex until a replication fork in the opposite direction merges with the stalled fork
(Peng, X. P., et al. 2018). DDK has also been shown to be required for proper stalling at replication
fork barriers via proper FPC function and removal of the non-histone protein sweepase activity of
Pif1 family helicase Pfh1 in S. pombe (Rrm3 helicase in S. cerevisiae) that removes the Sap1 and
Reb1 proteins from the RFB (Bastia, D., et al. 2016).
The replication fork barrier (RFB) is made up of four common replication termination sites
Ter 1-3 and RFP4. Ter 1 binds the protein Sap1 and Ter 2 and 3 are bound by the Reb1 protein
(Sánchez-Gorostiaga, A., et al. 2004; Krings, G., & Bastia, D. 2005). Interestingly the Reb1
protein also has a secondary role in linking sister chromatid Ter sites known as chromosome
kissing, and which has also been shown to enhance barrier function (Singh, S. K., et al. 2010).
Inhibition of replication fork progression past Ter1-3 is dependent on the fork protection complex
(FPC) components Swi1 and Swi3 and partially dependent on Mrc1/claspin. (Leman, A. R., &
Noguchi, E. 2013; Zech, J., et al. 2015). RFP 4 is the least characterized replication fork barrier
however due to the fact that it lies within the rDNA mRNA transcriptional unit and the fact that it
has no protein binding activity. It is thought that it may be the site of last resort of replication fork
stalling before transcription replication fork collapse occurs (Krings, G., & Bastia, D., 2004). Two
of the four replication fork barriers designated Ter 2 and 3 also act as transcriptional terminators
in the opposing direction and halt any proceeding RNA pol1 progression into the RFB region
(Jaiswal, R., et al. 2016).
8

1.3.1 rDNA copy number
rDNA copy number varies greatly. Yeast such as S. pombe and S. cerevisiae have rDNA
copy numbers that often hover around 100-200 (Maleszka, R., & Clark‐Walker, G. D. 1993;
Nomura, M. 2001). These numbers vary a bit in laboratory cultured strains (Salim, D., et al. 2017).
Higher eukaryotes also vary greatly in their rDNA copy number with human variations going from
the hundreds to thousands with no seaming phenotype (Porokhovnik, L. N., & Lyapunova, N. A.
2019). This suggests that eukaryotes have adapted mechanisms to deal with a vast amount of
possible copies. However due to the fact that the rDNA is susceptible to genome stress cells may
expand or contract their rDNA array from various insults or mutations. Recent evidence has
suggested that loss of rDNA copies may be a coping mechanism to deal with various genome
stresses. One example clearly discovered is an increased growth rate which puts strain on slow
hard to replicate regions of the genome like the rDNA (Xu, B., et al. 2017). In fact Drosophila
strains that are given high nutrient diets decrease their rDNA copy number over successive
generations (Aldrich, J. C., & Maggert, K. A. 2015). Another example is limitation of replication
factors such as experiments showing depletion of Mcm2 in mice showed a contraction of rDNA
Figure 4. Structure of the S. pombe rDNA
repeat and replication fork barrier system
This figure shows the 10.9kb rDNA repeat
along with the four part RFB system. Adapted
from Steinacher, R., et al. 2012 and Singh, S.
K., et al. 2010

9
repeats over time (Salim, D., et al. 2017). These finding suggest that increased growth rate or a
lack of replication factors are a negative pressure on rDNA copy number and that a smaller rDNA
may make it easier for these fast-growing cells to duplicate this fragile site efficiently and with
enough time.
1.3.2 rDNA copy number in cancers
Genome instability has been considered one of the hallmarks of many types of cancers.
Each type of cancer however is vastly unique based on its tissue specificity, intracellular
environment, and genetic/epigenetic differences. However it has been well established that many
different cancer types exhibit nucleolar abnormalities (Derenzini, M., et al. 2009). This can be
nucleolar fragmentation, expansion of nucleoli, and multiplied nucleoli (Hernández-Hernández,
A., et al. 2012; Lindström, M. S., et al. 2018). In fact studies have shown that nucleolar
hypertrophy was a uniform characteristic of many human cancers studied and that rates of rDNA
transcription correlated with adverse prognosis (Cmarko, D., et al. 2021). Many cancers have also
been shown to vary greatly in their rDNA copy number compared to the surrounding normal host
tissue (Xu, B., et al. 2017). There are two main hypothesis for why cancers may have a selective
pressure to change their rDNA copy number. First, many actively dividing and growing cancers
may have an increased protein requirement and one way that this can be mitigated is upregulation
in rRNA and ribosome biogenesis factors. Secondly due to the fact that the rDNA is hard to
replicate cancers may have a selective pressure to contract or maintain a contracted rDNA array in
order to mitigate difficulty to replicate this domain especially in an already genome unstable cell.
Looking at rDNA copy numbers has been difficult to study as each cancer type and the
individual characteristics of each patient vary greatly. The overarching theme of rDNA copy
number quantifications of human cancer genomes show that the genome instability of the cancer
usually results in destabilization in the rDNA leading to large variations in rDNA array size
compared to other host tissue. Many studies have found both increases and decreases in the array
size thus both hypotheses for expansion/contraction of the rDNA may be plausible depending on
the individual cancer (Wang, M., & Lemos, B. 2017; Hosgood III, H. D., et al. 2019; Valori, V.,
et al. 2020; Feng, L., et al. 2020). A study by Stults D. M., et al. 2009 also showed that over half
of solid tumors studied show detectable rDNA rearmaments even without changes in copy number.
Other recent studies have also revealed that cancers with a contracted rDNA array are often due to
10
hyperactivity of the mTOR pathway from a downregulation in the mTOR inhibitor PTEN (Xu, B.,
et al. 2017). These studies all conclude that cancer genomes that are unstable to begin with often
have large rearrangements in the rDNA that can lead to either expansions or contractions in the
array.
1.3.3 Ribosomopathies
Ribosomes are the center of protein production taking mRNAs and translating them into
protein. In Mammals these ribosomes are made up of 80 proteins and 4 rRNA subunits. Various
tissues contain ribosomal modifications and also varying requirements for ribosomal production.
Tissues that require faster regeneration such as skin, muscle, liver, blood, and the gastrointestinal
tract have the highest requirement for protein synthesis and thus require a plethora of available
ribosomes (Kampen, K. R., et al. 2020).
Ribosomopathies are the result of either single copy mutations in specific ribosomal genes,
or a lack of ribosome biogenesis factors such as rRNA or accessory proteins. The most well defined
and researched ribosomopathy is Diamond-blackfan anemia (DBA) (Draptchinskaia, N., et al.
1999). DBA along with many of the other ribosomopathies usually have a well-defined clinical
presentation of bone marrow and skeletal growth impairment while other tissues, and even those
that have a high protein/ribosome requirement remain seemingly unaffected (Kampen, K. R., et
al. 2020). There is also a high variability in severity of ribosomopathies among patients and even
in familial studies (Mills, E. W., & Green, R. 2017). Researchers have come up with two
hypotheses for the tissue specificity of ribosomopathies. The first is that ribosome dysfunction
affect global mRNA translation and that certain cells or tissues are particularly vulnerable while
the second is that ribosomal modifications or varying accessory proteins could be responsible.
More research is needed to discover the exact cause of the tissue specificity of these
ribosomopathies.
1.3.3 Nucleolar phase separation
Phase separation is the process of nonmembrane bound organelle formation based on weak
and reversible protein binding. This weak and reversible binding is often brought about through
intrinsically disordered domains of the protein that have no specific binding partner but allow for
generalized weak binding or separation based on weak hydrophobicity (Protter, D. S., et al. 2018;
Boeynaems, S., et al. 2018). The nucleolus is the largest of the phase separated non-membrane
11
bound organelles in the eukaryotic cell. Other phase separated domains are stress granules, PML
bodies, cajal bodies and paraspekles (Mao, Y. S., et al. 2011; Shin Y., and Brangwynne C. P.,
2017; Handwerger, K. E., et al. 2003; Banani, S. F., et al. 2017). Phase separation of the nucleolus
is also tripartite in higher eukaryotes and is theorized to be based on increasing levels of
hydrophobicity toward the center regions. The center most regions the fibrillar center (FC) is the
center of PolI occupancy and rDNA transcription occurs on its barrier. Transcribed rRNA exits the
FC border into the dense fibrillar complex (DFC) where it is trimmed and modified. Finally the
rRNA enters the granular component (GC) for final modification before it is exported from the
nucleolus (Cheutin, T., et al. 2002; Farley, K. I., et al. 2015; Tchelidze, P., et al. 2017). Phase
separation of the nucleolus is essential for proper rRNA production and maturation as well as other
cellular processes.

The phase separated nucleolus has in recent years also been discovered to be a sort of
storage and quality control system for the cell (Alberti, S., & Carra, S. 2019). Various proteins the
cell would not like to have actively used in the nucleus are shuttled of the nucleolus until needed
(Boisvert, F. M., et al. 2007). The most often stored types of proteins in the nucleolus are cell cycle
related proteins such as the yeast cdc14 and DNA damage repair proteins (Boisvert, F. M., et al.
2007). One example of this is that Cdc14 in S. cerevisiae required for mitotic exit is sequestered
in the nucleolus until needed and then shuttled back afterward (Shou, W., et al. 1999; Azzam, R.,
et al. 2004). Another great example of this process is HDM2 in mammals. HDM2 is the main
Figure 5. Visualization of the phase
separated nucleolus of S. pombe
This figure shows the phase separated non
membrane bound organelle the nucleolus in S.
pombe cells. The nucleolus is represented by
the Gar2-mCherry nucleolar protein in red
while cell membranes are shown using the
membrane protein marker Ccr1N-GFP in green.

12
ubiquitin ligase of the downstream tumor suppressor protein p53 and is physically sequestered in
the nucleolus by p14ARF upon stress allowing for p53 accumulation thus triggering the stress
response (Wesierska‐Gadek, J., & Horkya, M. 2003). This process shows that not only does the
cell use the nucleolus as a hub for isolating the production and processing mature rRNA’s but it
also uses this phase separated domain to isolate various proteins in order for stochastic activation
and response to external stimuli.
13
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20
Chapter 2
Monitoring Schizosaccharomyces pombe genome stress by visualizing end-
binding protein Ku

Chance E. Jones & Susan L. Forsburg
1

Program in Molecular & Computational Biology
University of Southern California
Los Angeles CA 90089

1
corresponding author Forsburg@usc.edu

Published:
Jones, C. E., & Forsburg, S. L. (2021). Monitoring Schizosaccharomyces pombe genome stress
by visualizing end-binding protein Ku. Biology Open, 10(2), bio054346.

Abstract
Studies of genome stability have exploited visualization of fluorescently tagged proteins in live
cells to characterize DNA damage, checkpoint, and repair responses. In this report, we describe a
new tool for fission yeast, a tagged version of the end-binding protein Pku70 which is part of the
KU protein complex. We compare Pku70 localization to other markers upon treatment to various
genotoxins, and identify a unique pattern of distribution. Pku70 provides a new tool to define and
characterize DNA lesions and the repair response.

21
Introduction
The response to genome stress and DNA repair can be observed in living cells in real time,
by monitoring fluorescently-tagged DNA damage response proteins (Lisby, M. et al. 2004; Lukas,
C., et al. 2005; Nagy, Z., & Soutoglou, E., 2009; Polo, S. E., & Jackson, S. P. 2011). This has
allowed characterization of dynamic processes that respond to damage and preserve genome
integrity, including cell cycle, checkpoint, repair, and recovery pathways. In the fission yeast S.
pombe, accumulation of foci of the single-strand DNA binding protein Ssb1 (a subunit of
Replication Protein A /RPA), and of the recombination protein Rad52, have been used to
characterize intrinsic genome stresses as well as the response to external genotoxins (Meister, P.,
et al. 2003; Kilkenny, M. L., et al. 2008; Carneiro, T., et al. 2010; Bass, K. L., et al 2012; Sabatinos,
S.A., et al. 2012). These proteins recognize and respond to single strand DNA accumulation, which
can result from exonuclease activity, resection, processing of replication forks, and recombination
intermediates, or R-loop or D-loop formation (Zeman, M. K., & Cimprich, K. A., 2014), Sabatinos,
S. A., & Forsburg, S. L., 2015). Importantly, this has led to identification of distinct patterns of
accumulation that can serve as fingerprints for different forms of genome stress (e.g., Sabatinos,
S.A., et al. 2012; Sabatinos, S.A., et al. 2015; Ranatunga, N.S., & Forsburg, S.L., 2016).
The fission yeast Pku70 protein is the orthologue of the Ku70 subunit of the conserved
heterodimeric Ku complex (Baumann, P., & Cech, T. R., 2000). Ku is abundant and binds
efficiently to DNA double strand breaks (DSBs) (Fell, V. L., & Schild-Poulter, C. 2015; Shibata,
A., et al. 2018). Ku is associated with the non-homologous end-joining (NHEJ) mechanism of
DNA double strand break (DSB) repair (Mahaney, B. L., et al. 2009) and protects telomeres
(Baumann, P., & Cech, T. R., 2000; Ferreira, M. G., & Cooper, J. P. 2001). Additionally, it
recognizes “one-sided” double strand breaks and ends associated with regressed replication forks
(Teixeira-Silva, A., et al. 2017; Foster, S. S., et al. 2011; Langerak, P., et al. 2011).
Ku binding at the ends of DNA inhibits resection and accumulation of single strand DNA
that otherwise drives homologous recombination (Shibata, A., et al. 2018). Its activity is
coordinated with the Mre11-Rad50-Nbs1 (MRN) protein complex, another early responder to
DNA double strand breaks (Shibata, A., et al. 2018; Syed, A., & Tainer, J. A. 2018). MRN is also
linked to DNA DSB end binding (Wang, Q., et al. 2014) and resection (Shibata, A., et al. 2014)
and contributes to DNA damage checkpoint activation (Chahwan, C., et al. 2003; Paull, T. T.
2015). The Mre11/Rad32 subunit is able to drive endonucleolytic cleavage of DNA ends that are
22
blocked by covalently bound proteins such as Spo11 or Top2 (Hartsuiker, E., et al. 2009; Milman,
N., et al. 2009; Rothenberg, M., et al. 2009; Hartsuiker, E., et al. 2009; Garcia, V., et al. 2011;
Reginato, G., et al. 2017). To some degree, Ku and MRN act as mutual antagonists; Ku inhibits
short-range resection driven by MRN, and MRN removes Ku to facilitate homologous
recombination (HR) over NHEJ; and to prevent inappropriate repair of single-end breaks
(Langerak, P., et al. 2011; Shao, Z., et al. 2012; Myler, L. R., et al. 2017; Shibata, A., et al. 2018).
Interestingly, loss of Ku partly suppresses the sensitivity to DNA damage and replication blocking
toxins associated with mutation of MRN (Tomita, K., et al. 2003; Williams, R. S., et al. 2008;
Limbo, O., et al. 2007; Langerak, P., et al. 2011; Teixeira-Silva, A., et al. 2017), which can lead
to excessive Exo1-driven resection, but impaired RPA recruitment (Teixeira-Silva, A., et al. 2017).
In this report, we describe the development of a new fluorescent marker for fission yeast,
the Pku70 subunit of the Ku protein complex. We constructed a pku70
+
-citrine fusion and
integrated into the genome in wild type fission yeast under the endogenous promoter. We
examined its behavior and accumulation in treated and untreated wild type cells in response to
different genotoxins. We compared localization of Ku to Rad52, RPA, and Mre11 markers and
observe a pattern of foci that is distinct from other proteins. This provides a new tool to characterize
responses to different forms of genotoxic stress and a useful addition to the fission yeast tool kit
for investigation of the 3-Rs of DNA replication, repair, and recombination.

Results
Construction of strains with fluorescently tagged Pku70 and Mre11
Ku (a heterodimer of Pku70/80) and MRN (Mre11/Rad50/Nbs1) protein complexes are
known for high affinity for binding DNA ends (Fell, V. L., & Schild-Poulter, C. 2015; Shibata,
A., et al. 2018). We tagged Pku70 on its C-terminal end with Citrine fluorescent protein and
integrated into the endogenous locus (see methods). Using a similar strategy, we also tagged
Mre11 on its C terminal end with mCherry fluorescent protein. The resulting strains were
compared to wild type, pku70∆, mre11∆, and rad51∆ for their growth on four typical genotoxic
drugs: methyl methanesulfonate (MMS), which creates alkylation damage that inhibits DNA
replication fork progression; camptothecin (CPT), which blocks Topoisomerase I cleavage;
hydroxyurea (HU), which causes nucleotide starvation and fork pausing; and Phleomycin (phleo),
a radio-mimetic that causes single- and double-strand breaks. Both the Mre11-mCherry and
23
Pku70-Citrine tagged strains behaved the same as WT under normal growth and genotoxic stress.
The Δpku70 strain also shows no sign of genotoxin sensitivity, as reported previously (Manolis,
K. G., et al. 2001; Sánchez, A., & Russell, P. 2015) (Fig. 1A). In order to confirm that Pku70-
Citrine is active, we performed a plasmid religation assay showing the tagged construct retains
NHEJ function. (Supplemental Fig. 1). We also find that deletion of Pku80 abolishes Pku70-citrine
localization, consistent with proper assembly of the Ku heterodimer (Supplemental Fig. 2)

Pku70 and Mre11 have increased nuclear signal following genotoxic stress
In normal growth conditions, the tagged strains show a few scattered foci in Pku70-citrine
cells and diffuse nuclear fluorescence in Mre11-mCherry cells (Fig. 1B). We examined the
distribution of signal in cells treated with MMS, CPT, Phleo, or HU at 32ºC after 4 hours. There
is a significant increase of cells with individual Pku70 nuclear foci in MMS, CPT, and to a lesser
extent Phleo. Cells treated with HU did not show any significant difference from WT (Fig. 1C). In
contrast, the Mre11-mCherry signal showed diffuse pan-nuclear staining in untreated cells (Fig
1B). Following 4 hours of treatment with the four genotoxic drugs, Mre11-mCherry did not show
obvious foci. Rather, we observed generalized areas of increased fluorescence over threshold, but
these typically were not well-defined discrete puncta as seen with other markers.
24

Colocalization of Pku70 and Mre11 with other markers of DNA damage
Previous studies of genome instability in fission yeast have imaged the single stranded
binding protein Ssb1 (Rad11, RPA) and the homologous recombination protein Rad52 in response
to different forms of replication stress (Meister, P., et al. 2003; Kilkenny, M. L., et al 2008;
Carneiro, T., et al. 2010; Bass, K. L., et al., 2012; Sabatinos, S. A., et al. 2012). We examined co-
localization using CPT, MMS, HU and Phleo in a strain with Pku70-citrine, Rad52-mCherry, and
RPA-CFP. Four hours after drug addition at 32ºC, we determined frequency of colocalization
among all three tagged proteins. While there was partial overlap, we observed that Pku70 is not
completely concordant with the other markers (Fig. 2A).
The number of foci per nucleus was calculated and binned as either 1or ≥ 2 foci using an
automatic foci counter in ImageJ as described in the materials and methods (Fig. 2B). We observed
25
that CPT 20µM contained the highest frequency of Pku70 foci, then MMS, Phleo, and HU. The
difference from prior observation likely reflects a somewhat different drug dosage: CPT levels
were raised from 10µM to 20 µM in order to produce an enhanced response and MMS was lowered
from 0.9mM to 0.45mM to better resolve single foci.
Colocalization was determined using the objects-based method in the ImageJ plug-in
JACoP (see materials and methods). Fig. 2C shows the proportion of Pku70-Citrine foci that
overlap with a thresholded region for Rad52-mCherry or RPA-CFP. For CPT, MMS, and Phleo,
these proportions vary from 60-90%. In contrast, the scattered foci in HU showed only about 30%
of Ku co-associating with another marker. Fig 2D shows the proportion of Rad52-mCherry foci
that have a colocalizing Pku70-Citrine focus. CPT contained the highest proportion of Rad52 as
well as RPA with overlapping Pku70 foci, whereas HU contained the lowest.
We performed a similar study with Mre11-mCherry but could not perform the same
quantitation because Mre11-mCherry does not form discrete foci. We observed areas of generally
increased fluorescence but never clear puncta as with Pku70, Rad52, or RPA. Observing these
cells in three-dimensional reconstruction showed no obvious colocalization between Rad52-
YFP/RPA-CFP and Mre11-mCherry in live cell video microscopy, or in static images (Fig. 3A,B;
Supplemental Fig. 3).
26

27
Pku dynamics in S phase specific damage
The genotoxin MMS causes alkylation damage, generating lesions that block DNA
polymerase (Lundin, C., et al. 2005). This typically results in replication template switching
(Barbour and Xiao 2003; Andersen et al. 2008). Previous work has suggested that Ku is recruited
by blocked and regressed replication forks (Teixeira-Silva, A., et al. 2017). Therefore, we
investigated the dynamics of Ku response to MMS treatment as a model for disruptions in
replication fork progression. We used live cell video microscopy to observe cells containing
Rad52-mCherry and Pku70-Citrine over a 5hr period of MMS (.45mM) treatment at 28ºC. We
28
observe distinct dynamics for Rad52 and Pku70 recruitment during treatment. While absolute
timing differs in individual cells, typically a Ku focus appears for a short time and partially co-
localizes with Rad52.
Fig 4A shows a representative newborn cell that is likely in mid S phase, 1h 20m after drug
treatment. The diffuse Rad52-mCherry signal is distributed in smaller foci which then coalesce
into two large foci. Pku70-Citrine colocalizes at the center of these large foci for about 20-40
minutes. The large Rad52-mCherry foci persist for another 60 minutes and then begin to dissipate.
Retention time of Pku-Citrine foci in MMS is ≤ 20 minutes with a fraction of cells maintaining it
longer between 20 and 40 minutes. In contrast, Rad52 foci extend over a much longer period of
time ranging from 20 all the way up to 160 minutes (Fig. 4B). Overall Rad52 tends to appear
slightly earlier than Pku70 in most cells and disappears much later (Fig. 4C). (Additional time-
lapse images found in Supplemental Fig. 4 and 5)

29
Discussion
Localization of repair puncta in fission yeast has been a well-established means of
observing DNA damage, quantified by counting foci, determining pixel intensity or size of foci,
and three-dimensional position in the nucleus (Green, M. D., et al., 2015). The most frequently
used fluorescent tags used in S. pombe for observing DNA lesions are the recombination protein
Rad52 and single strand DNA binding protein Rad11, a subunit of RPA (Meister, P., et al., 2003;
Carneiro, T., et al. 2010; Sabatinos, S. A., et al. 2012). Studies have shown that in cycling wild
type cells, approximately 10-20% of cells show evidence of single RPA or Rad52 foci, likely due
to sporadic S phase damage. The tagged proteins show distinct patterns in response to genotoxic
stresses induced by mutations in the replication or repair pathways (Sabatinos, S. A., et al. 2012;
Sabatinos, S. A., et al. 2015; Ranatunga, N. S., & Forsburg, S. L. 2016), or in response to
exogenous agents such as hydroxyurea (HU), which causes replication fork stalling (Thelander,
L., & Reichard, P. 1979); MMS, an alkylating agent that generates lesions that block the replication
fork (Lundin, C., et al. 2005); camptothecin (CPT), a topoisomerase I inhibitor that leads to S-
phase specific double strand breaks (Li, T. K., & Liu, L. F. 2001); and bleo- or phleomycin,
radiomimetic drugs that causes single- and double-strand breaks (Povirk, L. F. 1996).
The current study seeks to expand the library of tagged proteins, part of our strategy to
develop a fingerprint for the response to different forms of genotoxic stress. We investigated
fluorescently tagged Mre11 and Pku70 as markers for DNA breaks.
The MRN complex is one of the earliest responders to DSBs (Shibata, A., et al. 2018; Syed,
A., & Tainer, J. A. 2018) and is essential to drive resection (Wang, Q., et al. 2014; Shibata, A., et
al. 2018; Langerak, P., et al. 2011; Teixeira-Silva, A., et al. 2017). Our Mre11-mCherry construct
showed a diffuse pan-nuclear signal in untreated cells. We did not see obvious focus formation of
Mre11-mCherry following treatment with genotoxins. Rather, it maintained a diffuse signal with
regions of brightness. In other systems, MRN has been shown to be an immediate responder to
double strand breaks induced by ionizing radiation (Maser, R. S., et al. 1997). Our failure to see
this form of localization may be related to the timing of our analysis, and/or the diffuse distribution
of lesions in drug- treated cells, compared to concentrated sites of damage from of ionizing
radiation.
Previous whole-cell localization of Pku70 in S. pombe was carried out using C terminal
epitope-tagged Pku70 and immunofluorescence on fixed cells (Manolis, K. G., et al. 2001). In
30
unperturbed cells, a diffuse pan-nuclear localization was observed. Association of Ku with DNA
ends has been investigated using chromatin immunoprecipitation; in wild type cells, it is not
enriched unless the MRN complex is missing (Langerak, P., et al. 2011; Teixeira-Silva, A., et al.
2017). Visualization of Pku70 in live fission yeast cells has not previously been performed.
We saw few Ku foci in WT cells, consistent with the previous immunofluorescence studies.
Treatment for 4 hours with our panel of genotoxins showed that HU has little to no accumulation
of Ku foci. Treatment with CPT causes a modest increase in the fraction of cells with foci at 10µM
and a more dramatic increase at 20µM. Similarly, phleomycin, a radiomimetic that causes DNA
breaks throughout the cell cycle, has a modest but limited increase in foci relative to untreated
cells.
We found that the most dramatic increase of cells with Pku70 foci was obtained by treating
with MMS at 0.9mM. MMS is an alkylating agent that results in error-free and error prone base
excision repair during S phase, and thus leading to trans lesion synthesis (Memisoglu, A., &
Samson, L., 2000). This induction in MMS is consistent with prior observations suggesting that
Ku is recruited to regressed or broken replication forks in order to stabilize the free end (Langerak,
P., et al. 2011; Teixeira-Silva, A., et al. 2017). This suggests that even in MRN
+
cells, there are
situations where Ku remains associated with sites of genome stress.
We observed a substantial colocalization between RPA or Rad52 and Ku, in cells treated
with MMS, CPT, or Phleo. This result was a surprise as many models suggest Pku should be
removed by the time resection and recombination proteins are recruited. One possibility for the S
phase specific toxins is that Pku could be binding to reversed forks at repair centers. Previous
studies suggest that Pku plays a role at reversed forks in order to maintain genome stability,
particularly in cells with defective HR repair such as brc1Δ (Sánchez, A., & Russell, P. 2015;
Teixeira-Silva, A., et al. 2017). This may reflect that other mechanisms than exonuclease activity
can generate ssDNA, including helicase unwinding and strand invasion.
To address this finding in dynamic conditions, we examined MMS-treated cells as a model
for stalled replication forks. Previously, we showed that MMS induces a dramatic increase in RPA
and Rad52 foci relative to other genotoxins (Ranatunga, N. S., & Forsburg, S. L. 2016). We
observe substantial recruitment of Rad52-mCherry and brief, partial co-localization of Pku70. The
Pku70 signal, largely in 1-2 foci, appears after Rad52 and disappears before Rad52 is resolved.
Further molecular work will be required to determine what this signal represents.
31
It is likely that Ku foci will define distinct structures associated with particular forms of
replication stress. For example, in a recent study, our lab showed that a mutant mcm4-dg with a
defect in the MCM helicase accumulates Ku foci (Kim, S. M., & Forsburg, S. L. 2020). This
accumulation can be reversed by activation of the Mus81 resolvase. Mus81 is essential for viability
in pku80∆ brc1∆ mutants (Sánchez, A., & Russell, P. 2015), indicating a collaboration between
Ku and Mus81 in response to replication stress. Our Pku70-citrine fusion will be a key reagent in
dissecting this and other activities.
32
Methods
Cell growth and physiology
Fission yeast strains are described in Table 1, and were grown as in (Sabatinos et al., 2012).

Construction of Tagged strains
All fragments were lengthened using the Expand Long Template PCR System (Roche Diagnostics,
Mannheim Germany). Primers were designed using the NCBI Primer design tool and optimized
to an annealing temperature of 52-54ºC (Ye J, et al. 2012). Full length fragments were transformed
using electroporation and selected using the appropriate marker (Sabatinos, S. A., & Forsburg, S.
L. 2010). Upon transformation, instead of plating directly onto selective minimal media, the cells
were first plated on YES for 24 hours then replica plated onto YES-Hph. Candidate colonies
growing on Hph after 4-5 days were then restreaked onto Hph twice and visually screened for
nuclear localizing foci.

Pku-Citrine::Hph
The Pku C-terminal Citrine fragment was formed from 5 fragments, Pku 5’overhang (FY2710 +
FY2711), Citrine (FY2561 + FY2562), Hph (FY2563 + FY2564), Citrine UTR (FY2565 +
FY2566), and Pku 3’ UTR overhang (FY2712 + FY2713). The Citrine and Citrine UTR fragments
were lengthened from addgene plasmid pKT0139 (Sheff, M. A., & Thorn, K. S. 2004). The Hph
fragment was lengthened from pFA6a-hphMX6 (Hentges, P., et al. 2005). The 5’ and 3’ UTR
overhang fragments were lengthened from phenol:chloroform extracted WT (FY527) DNA
(Forsburg, S. L., & Rhind, N. 2006). The Citrine, Hph, and Citrine UTR fragments were first
lengthened to form a full Citrine::HPH fragment. A single PCR reaction was then done with Pku
5’overhang, Citrine HPH, and Pku 3’ UTR overhang fragments forming the full fragment. This
fragment was then used for electroporation transformation.

Mre11-mCherry::Hph
The Mre11 C-terminal mCherry fragment was formed from 4 fragments, Mre11 5’ overhang
(FY2888 + 2998), mCherry (FY2890 + FY2863), Hph (FY2864 + FY2892), Mre11 3’ UTR
overhang (FY2891 + FY2893). The mCherry fragment was lengthened from extracted DNA,
FY8381 (Yu, Y., et al. 2013). The Hph fragment was lengthened from the previously formed
33
Citrine::Hph fragment above. The Mre11 5’ and 3’ UTR overhang fragments were lengthened
from extracted WT DNA (FY527). The mCherry::Hph fragment was first lengthened. The Mre11
5’ overhang, mCherry::Hph, and Mre11 3’ UTR overhang fragments were then combined in one
PCR reaction forming the full fragment. The fragment was then used for electroporation
transformation.

Plasmid Religation Assay
Plasmid pAL19 (Barbet, N., et al. 1992) was previously modified by insertion of a mst1 derivative
in the HindIII sites of the multiple cloning sequence, creating pRCP44. pRCP44 was digested for
one hour at 37ºC with HindIII. The digested fragment containing only the linearized backbone
pAL19 was gel-extracted. This ensured that any nonlinearized plasmid was not contaminating the
sample. All strains contained the leu1-32 mutation and were transformed by lithium acetate
transformation with either the circularized backbone pAL19 or the linearized backbone pAL19
from the digested/extracted fragments of pRCP44 containing the S. cerevisiae LEU2+ gene.
Colonies were grown on -Leu plates for 5 days. Colony counts were normalized to WT plasmid
religation vs circular plasmid transformation rates.

Live Cell Imaging
Cells were prepared as in (Green, M. D., et al. 2015). Medium for all live cell imaging was PMG-
HULALA (PMG + Histidine, Uracil, Leucine, Adenine, Lysine, Arginine) (225mg/L each)
(Sabatinos, S. A., & Forsburg, S. L. 2010). Unless specified all drug concentrations used for
imaging were as follows, MMS .9mM, HU 15mM, CPT 20µM, Phleo 3µM. Strains in liquid
cultures at 32°C were grown to mid-log phase. Cells concentrated by a brief microfuge spin were
applied to 2% agarose pads made from PMG + HULA and prepared on glass slides sealed with
VaLaP (1/1/1 w/w/w vasoline/lanolin/paraffin). Static images were collected at room temperature
22°C and long term timelapse images were taken at a constant temperature of 28°C. Images were
acquired with a DeltaVision Core (Applied Precision, Issaquah, WA) microscope using a 60x N.A.
1.4 PlanApo objective lens and a 12-bit Photometrics CoolSnap HQII CCD. The system x-y pixel
size is 0.109µm. softWoRx v4.1 (Applied Precision, Issaquah, WA) software was used at
acquisition. Excitation illumination was from a Solid-state illuminator, CFP was excited and
detected with a 438/24,470/24 filter set (excitation intensity attenuated to 10%) and a 400ms
34
exposure; YFP was excited and detected with a 513/17,559/38 (excitation intensity attenuated to
32% for Rad52-YFP and 50% for Pku70-Citrine) filter set and a 200ms exposure. A suitable
polychroic mirror was used. Sections of static timepoints were 20 .20µm z-sections. Long-term
time-lapse videos used 8 z-steps of .35µm. 3-D stacks were deconvolved with manufacturer
provided OTFs using a constrained iterative algorithm, images were maximum intensity projected
for presentation. Images were contrast adjusted using a histogram stretch with an equivalent scale
and gamma for comparability. Brightfield images were also acquired.

Image processing and analysis
Images were contrast adjusted using an equivalent histogram stretch on all samples. Significance
was assessed with Mann Whitney tests. Long-term time lapse videos were stabilized in ImageJ
using the package “StackReg” by Philippe Thevanaz from the Biomedical Imaging Group at the
Swiss Federal Institute of Technology Lausanne (Thevenaz, P., et. Al 1998). Foci were
automatically quantified using a computational algorithm based on uniform threshold per
fluorescence channel as described by the light microscopy core facility at Duke University
(https://microscopy.duke.edu/guides/count-nuclear-foci-ImageJ). Object based colocalization
analysis was performed using the ImageJ plug-in JACoP on the same images used for the focus
quantification. However this object based colocalization analysis method still requires observer-
based thresholding before analysis. In order to mitigate observer-based thresholding bias, the
number of observed objects after thresholding per fluorescence channel was calculated to be within
10 foci of the automatically counted foci during the previous computer-based foci quantification
analysis described above.
35

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39
Table 1: Strains
FY527 h- his3-D1 ade6-M216 ura4-D18 leu1-32 Gould, K. L., 1998
FY528 h+ his3-D1 ade6-M210 ura4-D18 leu1-32 Liang, D. T., 1999
FY8488 h+ pku70-Citrine::hph his3-D1 ade6-M210 ura4-D18 leu1-32 This study
FY8558 h- pku70-Citrine::hph his3-D1 ade6? ura4-D18 leu1-32 This study
FY8661 h+ mre11-mCherry::hph his3-D1 ade6-M210 ura4-D18 leu1-32 This study
FY8662 h- mre11-mCherry::hph his3-D1 ade6? ura4-D18 leu1-32 This study
FY8381 h- rad52-mCherry::kan ura4-D18 leu1-32 Yu, Y., 2013
FY8625 h- pku70-Citrine::hph rad52-mCherry::kan his3-D1? ade6? ura4-D18 leu1-32 This study
FY8698 h90 mre11-mCherry::hph, pku70-citrine::hph, his3-D1 ade6? ura4-D18 leu1-32 This study
FY4743 h- rad11-Cerulean::hphMX rad22-YFP-natMX leu1-32 ade6-M210 ura4-D18 Sabatinos, S. A.,
2012
FY8687 h90 mre11-mCherry::hph RPA-Cerulean::hphMX, rad52-YFP-natMX his-D1?
ade6-M210 ura4-D18 leu1-32
This study
FY9381 h- rad11-Cerulean::hphMX pku70-Citrine::hph rad52-mCherry::natMX6 ura4-
D18 leu1-32 his? ade?
This study
FY9620 h- ∆pku80::kan his3-D1 ade6-M216 ura4-D18 leu1-32 This Study
FY9619 h- pku70-Citrine::hph ∆pku80::kan his3-D1 ade6-M216 ura4-D18 leu1-32 This Study
FY9663 h- pku70::kan his3-D1 ade6-M216 ura4-D18 leu1-32 This Study

Table 2: Primer List
FY2561 atgtctaaaggtgaagaattattcac Citrine Fwd This study
FY2562 gtattctgggcctccatgtcttatttgtacaattcatcca Citrine Rev This study
FY2563 gacatggaggcccagattac Hph Fwd This study
FY2564 agtatagcgaccagcattc Hph Rev This study
FY2565 gaatgctggtcgctatactgggcgcgccacttctaaataa 3’ Citrine UTR Fwd This study
FY2566 ccctgttatccctagcggatct 3’ Citrine UTR Rev This study
FY2710 tgttaacattttagcgcgtc 5’ Pku Fwd This study
FY2711 aattcttcacctttagacattaattttttgacatagttcg 5’ Pku Rev This study
FY2712 gaatgctggtcgctatactgacaagaaaatattaaaggat 3’ UTR Pku Fwd This study
FY2713 agcatacgttagtgaaggttga 3’ UTR Pku Rev This study
FY2888 tacgaagctcaaggaaccgt 5’ Mre11 Fwd This study
FY2889 gccctgctcaccatatcatctaaaatttcg 5’ Mre11 Rev This study
FY2890 cgaaattttagatgatatggtgagcaagggc mCherry Fwd This study
FY2863 ctgctcgacatgttcatcctgtacctccgggtctta mCherry Rev w/TEF This study
FY2864 gacgagctgtacaagtaggacatggaggcccagaat Hph Fwd This study
FY2892 atttgataagatcaacagtatagcgaccagcattcacatacg Hph Rev This study
FY2891 ctggtcgctatactgttgatcttatcaaatttttgtttaagtgtacct 3’ UTR Mre11 Fwd This study
FY2893 cgcactatcgctttgtgtgc 3’ UTR Mre11 Rev This study

40
41

42

43
Chapter 3
Impact of 1,6-Hexanediol on Schizosaccharomyces pombe Genome Stability

Chance E. Jones & Susan L. Forsburg
*

Section of Molecular & Computational Biology
University of Southern California
1050 Childs Way, RRI 108
Los Angeles CA 90089

*
corresponding author, forsburg@usc.edu

Submitted: G3 on 2/23/23

Abstract
Phase separation is a major mechanism of macromolecular condensation within cells. A frequently
chosen tool for global disruption of phase separation via weak hydrophobic interactions is
treatment with 1,6-hexanediol. This study evaluates the cytotoxic and genotoxic effects of treating
live fission yeast with 1,6-hexanediol. We find that 1,6-hexanediol causes a drastic decrease in cell
survival and growth rate. We also see a reduction in HP1 protein foci and increase in DNA damage
foci. However, there is no evidence for increased genomic instability in two classically phase
separated domains, the heterochromatic pericentromere, and the nucleolar rDNA repeats. This
study reveals that 1,6-hexanediol is a blunt tool for phase separation inhibition and its secondary
effects must be taken into consideration during its in vivo use.

44
Introduction
Phase separation is the process of protein condensation due to weak and reversible
domain/motif binding of various proteins (Alberti, S., 2017)(Brangwynne, C. P., et al. 2015)(Shin
Y., and Brangwynne C. P., 2017). These weak and reversible bonds are often transient and can be
brought about by long stretches of intrinsically disordered or unstructured regions that can have a
variety of binding partners (Fasting, C., et al. 2012). These condensates can also be brought about
by weak hydrophobic protein domain interactions such as from phenylalanine-glycine repeats
(Ribbeck, K., et al. 2002)(Patel, S. S., et al. 2007). These processes are often aided by another
physical process known as gelation which can further concentrate and compartmentalize proteins
(Harmon, T. S., et al. 2017). Instead of relying upon lipid bilayer membranes that require energy
and transport mechanisms, or upon simple diffusion that requires too many proteins to be produced
to be economical, cells utilize the physical chemistry of the proteins themself to self-concentrate
where needed without any energy expenditure.
There are many examples of phase separated, non-membrane-bound nuclear organelles
including paraspeckles, cajal bodies, PML bodies, stress granules and the nucleolus (Mao, Y. S.,
et al. 2011)(Shin Y., and Brangwynne C. P., 2017)(Handwerger, K. E., et al. 2003)(Banani, S. F.,
et al. 2017). These regions allow concentration of various functions and activities in sub-nuclear
domains. The nucleolus is the largest of the phase separated nuclear organelles and is the center of
rRNA biogenesis (Feric, M., et al. 2016). In higher eukaryotes there are multiple nucleoli per cell
found scattered about the nucleus (Pederson, T. 2011). In eukaryotes with smaller genomes such
as yeast there is only one large nucleolus that is located opposite the centromere/spindle pole body
(SPB) (Matsuda, A., et al. 2017). Unlike other phase separated intracellular organelles, the
nucleolus is further phase separated internal sub-regions. The innermost region, the fibrillar center
(FC) is responsible for initial rRNA transcription and contains the highest concentration of RNA
PolI. The dense fibrillar complex (DFC) is responsible for initial rRNA processing such as
trimming and modifications. The granular component (GC) is generally responsible for final
maturation of rRNAs and is the outermost region in contact with the general nucleus (Feric, M., et
al. 2016). This tripartite phase separation of the nucleolus in these higher eukaryotes also relies
upon the NPM group proteins, which facilitate the multivalency needed for nucleolar phase
separation (Mitrea, D. M., et al. 2018). In simple eukaryotes such as yeast there are only two
45
general regions of the nucleolus the FC and a combined region consisting of the functions of the
DFC and GC (Thiry, M., & Lafontaine, D. L. 2005).
Heterochromatin domains are also phase separated (Strom, A. R., et al. 2017)(Tatarakis,
A., et al. 2017). Heterochromatin is an epigenetically delimited chromatin state that is
transcriptionally repressed. Classically, these regions are marked by tri-methylation of histone H3
lysine 9 (H3K9me3), which creates a binding site for chromodomain-containing proteins including
the HP1 proteins, conserved in many eukaryotes (Bannister, A. J., et al. 2001)( Lachner, M., et al.
2001). In the fission yeast S. pombe, Swi6 is an HP1 family member that has been shown to phase
separate in vitro and in vivo in the presence of H3K9-methylated chromatin (Sanulli, S., et al.
2019). Aggregation of Swi6-bound regions into droplet is presumed to concentrate Swi6 isolate
heterochromatic domains from the rest of the chromatin. This may contribute to three-dimensional
nuclear localization and topologically associated chromatin domains.
Phase separation via weak hydrophobic interactions can be disrupted by treatment with
general compounds such as the aliphatic alcohol 1,6-hexanediol (Ribbeck, K., et al. 2002)(Patel,
S. S., et al. 2007)(Kroschwald, S., et al. 2015)(Peskett, T. R., et al. 2018)( Ulianov, S. V., et al.
2021). While useful in vitro, many studies do not consider potential for broader cytotoxic effects
in vivo. In this study, we examined the in vivo response of fission yeast cells treated with 1,6-
hexanediol, and found it is toxic to cell survival and detrimental to cell growth even at very low
concentrations. We observed partial fragmentation of the nucleolus, with significant disruption of
the localization of Swi6 specifically in heterochromatin domains but not other H3K9me3 binding
proteins. We found that treatment with 1,6 hexanediol increases the number of Rad52 and RPA
foci in the nucleus, leading us to conclude that there is an increase in general genome instability
upon treatment, but this was not localized to nucleolar or heterochromatin domains. We conclude
that 1,6-hexanediol increases general genome instability and cytotoxicity. Thus, it is not indicated
for targeted disruption of locally phase separated regions.

Results
1,6-hexanediol inhibits S.pombe growth
1,6-hexanediol causes an acute loss of liquid-liquid phase separation (LLPS) via weak
hydrophobic interaction (Ribbeck, K., et al. 2002)(Strom et al. 2017). We characterized its effects
on fission yeast cell physiology, survival, and growth rate. Cells were incubated in rich
46
supplemented yeast extract media (YES) with 1,6-hexanediol at 1%, 5%, 10%, 15%, and 20%
(Figure 1A), and plated at different timepoints for viability. After 5 minutes there was a slight
decrease in cell survival at the highest concentrations of 15% and 20% but we observed no effect
at lower concentrations. However, after one hour there was a decrease in viability at concentrations
greater than 10%; at 2 hours, a similar decline was observed for concentrations above 5%. After
24 hours, only the 1% 1,6-hexanediol treated cells survived, with all other concentrations having
a drastic decrease in cell survival. Thus, there is a dose and time dependent decrease in S. pombe
cell survival upon treatment with 1,6-hexanediol.
Complementing our viability analysis, we measured OD 595nm to assess the growth rate
of S. pombe cells in rich media. We took the ratio of OD value of the 1,6-hexanediol treated cells
versus. our untreated WT strain (Figure 1B). At 0.5% 1,6-hexanediol the growth rate is decreased
to around 80% of WT. Increasing concentrations corelate with further reductions in growth rates.
These data confirm that treatment with 1,6-hexanediol causes a dose dependent decrease in S.
pombe growth rate.

Effects on nucleolar domains
It has been established that the nucleolus is phase separated (Weber, S. C., & Brangwynne,
C. P., 2015)(Feric, M., et al. 2016). We examined whether 1,6-hexanediol affects cellular
organization of the nucleolus in S. pombe using live cell microscopy. We looked at the nucleolus
using two different tagged nucleolar protein, nmt(41x):GFP-Nhp2 and Gar2-mCherry and a
spindle pole body (SPB) marker Sad1-mCherry. Nhp2 is part of a small nucleolar binding protein
complex (Maiorano et al. 1999) while Gar2 is the ortholog of the human nucleolin protein (Pinter
et al. 2008). In WT cells, Gar2-mCherry and GFP-Nhp2 overlap almost exactly with each other
and show a diffuse nucleolar localization which is directly opposite the SPB (Figure 1C).
We began by using an intermediate treatment concentration of 2.5% 1,6-hexanediol for 15
minutes. We then processed cells for imaging on pads also containing 2.5% 1,6-hexanediol. We
observed a rapid change in Gar2-mCherry and GFP-Nhp2 localization as soon as imaging was
started at 40 minutes. Gar2 separates from a single element into one large circular focus with a
portion of cells having a few smaller satellite bubbles of variable sizes while GFP-Nhp2 either
forms much smaller puncta within the larger Gar2-mCherry regions or more generally diffuse
localization. Over the time course we could see a gradual decrease in the number of Gar2-mCherry
47
foci into one large circular region usually containing either one bright GFP-Nhp2 focus or scattered
smaller foci. At a higher dose of 5% 1,6-hexanediol, we observed Gar2-mCherry and GFP-Nhp2
disruption occurred as quickly as the lower concentration but Gar2-mCherry showed far more
scattered smaller circular bubbles (5-7) and little to no GFP-Nhp2 was observed. Over the
timelapse the scattered bubble appearance of Gar2-mCherry was maintained however there was a
reduction in overall number of bubbles which coalesced into fewer larger bubbles (1-4) that
maintained the near absence of GFP-Nhp2. (Figure 1C).
Next, we tested to see how the 1,6-hexanediol treated cells were able to recover normal
nucleolar phase separation via WT Gar2-mCherry and GFP-Nhp2 localization. Cells were treated
with either 2.5% or 5% 1,6-hexanediol, grown for 120 minutes, washed twice with 1x PBS and
resuspended in media for 5 minutes then imaged. The 2.5% 1,6-hexanediol treated cells recovered
almost completely by the time imaging was started at 30 minutes post two-time 1x PBS wash. The
5% 1,6-hexanediol treated cells were slower to recover, maintaining the bubble appearance of
Gar2-mCherry and the bright focus of GFP-Nhp2. Over the 100 minute timelapse the cells did
recover to some extent however regions of increased Gar2-mCherry and GFP-Nhp2 localization
were still present.
48

Phase separation Stabilizes Heterochromatic Regions
Another region of the genome linked to phase separations is heterochromatin defined by
the eukaryotic H3K9me3 binding protein HP1 (Strom, A. R., et al. 2017)(Tatarakis, A., et al. 2017)
(Matsuda, A., et al. 2017)(Larson, A. G., et al. 2017). Using live cell imaging we looked at two of
the major H3K9me3 heterochromatin binding proteins in fission yeast: the HP1 homologue Swi6-
GFP and the RITS complex component Chp1-mCherry. Untreated cells have ± 2 foci of Chp1-
mCherry and ±3 Swi6-GFP (Figure 2B), which have been shown previously to correspond to the
centromeres, telomeres, and mating type regions associated with H3K9me heterochromatin
(Ekwall, K., et al. 1995)(Cheutin, T., et al. 2004)( Petrie, V. J., et al. 2005)(Schalch, T., et al.
2009). Upon treatment with 5% 1,6-hexanediol for 2 hours, we observed a decrease in the number
49
of Swi6-GFP foci to around 1 but no change in Chp1-mCherry. Thus, Swi6 foci localization is
partially disrupted upon loss of phase separation.
Within the nucleolus roughly 50% of WT rDNA repeats are heterochromatinized at any
point (French, S. L., et al. 2003)(Lindström, M. S., et al. 2018). Thus, since we had seen such a
drastic decrease in Swi6-GFP foci upon loss of phase separation via 1,6-hexanediol treatment we
hypothesized that loss of this protein could disrupt proper nucleolar structure. Using a Dswi6
background we analyzed the 3D nucleolar volume using the nucleolar GFP-Nhp2 tag previously
used. In WT cells the nucleolus maintained an average nucleolar volume of around .5-1 µm while
cells lacking the Swi6 protein had a slight increase in nucleolar volume size distribution but no
change in the average. These data indicate that while phase separation maintains proper Swi6
heterochromatin foci formation, its absence does not seriously disrupt the 3D structure of the
nucleolus.

1,6-Hexanediol Causes an Increase in General Genome Instability
Since 1,6-hexanediol causes a drastic decrease in cell growth rate and survival and given
its known roles in phase separation of heterochromatin regions and the nucleolus, we next
50
examined whether loss of phase separation via 1,6-hexanediol caused any increase in general
genome instability. In order to do this, we examined localization of the homologous recombination
(HR) protein Rad52-YFP (Rad22) and the ssDNA binding protein Rad11-CFP (RPA). In untreated
cells there was on average ~0.15 foci of both Rad52-YFP and RPA-CFP per nucleus that often
colocalized with the Gar2-mCherry nucleolar marker (Figure 3 A and B). After treatment with 5%
1,6-hexanediol for four hours both Rad52 and RPA foci increased to on average ~0.2 foci per
nucleus (Figure 3A). Even though there was an increase in foci per nuclei these foci did not
colocalize with the disrupted Gar2-mCherry bubbles (Fig. 3B and 3C). These data suggest that
1,6-hexanediol mediated loss of phase separation causes an increase in general genome instability
seen by an increase in nuclear DNA damage protein foci.

Stability of the rDNA repeats and Centromere Upon Treatment with 1,6-hexanediol
Since 1,6-hexanediol causes an increase in general genome instability we sought to identify
what regions of the genome could be most affected. Since we saw a disruption of Gar2 and Nhp2
localization in 1,6-hexanediol, we investigated the copy number of the rDNA repeats. We used
relative qPCR of 18s rDNA copies per act1 gene copy ratio to calculate the average rDNA ratio to
WT per cell (Figure 4A). For our long-term treatment group cells were grown over a 21-day period.
Samples were taken at day 3, 9, and 21 treated with 0.5%, 1%, 1.5%, or a no 1,6-hexanediol
control. There was no change in average ratio rDNA copies to WT in any of the treatment groups.
51
These results show that long term low concentration 1,6-hexanediol treatment does not cause a
substantial change in rDNA copy number repeats.
Even though the relative rDNA copy number via qPCR is maintained we wanted to confirm
if the instability of the repeats were increased yet the number of repeats remained stable. We next
examined whether there was any difference in the loss rate of ura4
+
inserted into the rDNA array
internal noncoding IGS sequence (Thon, G. & Verhein-Hansen, J. 2000). Upon plating on 5’FOA
any cell that has lost or silenced ura4
+
gene from the rDNA will survive on this drug. These cells
were treated with either no 1,6-hexanediol, 0.5% or 1% for 24 hours or 0.5%, 1%, 2.5%, or 5% for
4 hours. A strain with no ura4+ gene inserted in the rDNA was added as a control. Our results
show that across all the treated and untreated groups there is no change in ura4+ loss compared to
WT except for the cells treated for 4 hours at 5% 1,6-hexanediol (Figure 4B). We are unsure of
the cause of this decreased survival on 5’FOA. Three possibilities are that high dose 5% 1,6-
hexanediol was too toxic and thus the cells could not take further insult by the 5’FOA which is
also toxic in itself, the 1,6- hexanediol caused a decrease in heterochromatin at the IGS of the
rDNA allowing much higher rates of ura4
+
transcription, or loss of phase separation via 1,6-
hexanediol caused partial permeabilization of the cell wall allowing a higher dose of 5’FOA to
enter the cells compared to the other treatment groups. Overall, despite complications in the higher
concentration group these results confirm that 1,6-hexanediol does not cause an increase in rDNA
instability compared WT.
52

We next examined the heterochromatic pericentromere, which is a major site for Swi6/HP-
1 binding. We began by using a strain with a minichromosome originally derived from S. pombe
Chromosome 3. This strain contains multiple genetic markers that allow rapid identification of
chromosome loss or gross chromosomal rearrangement (GCR) (Nakamura, K. I., et al., 2008)(Li,
P. C. et al., 2013) (Figure 5A). Cells were treated with either 0.5%, or 1% 1,6-hexanediol for 24
hours or 1%, or 2.5% for 4 hours. We monitored genetic markers to observe if there were any
changes in stability of the minichromosome, including chromosome loss, or gross chromosome
rearrangement. Our results indicate that in all treated groups observed there is no increase in either
GCR or minichromosome loss. These data suggest that the increase in genome instability seen by
an increase in DNA damage protein foci is not due to 1,6-hexanediol mediated loss of phase
separation destabilizing the centromere/pericentromere.
53

Discussion
Phase separation has recently emerged as a major principle in the organization of the
nucleus, allowing separation of chromatin domains and concentration of proteins without
membrane delimited organelles (Weber, S. C., & Brangwynne, C. P., 2015)(Feric, M., et al. 2016).
Some forms of phase separation rely on weak hydrophobic binding and can be disrupted by
treatment with the aliphatic alcohol 1,6-hexanediol (Romero, P., et al. 2001)(Ribbeck, K., et al.
2002)(Kroschwald, S., et al. 2015)(Uversky, V. N. 2017). In this study, we investigated the
consequences to fission yeast cells following treatment with 1,6-hexanediol. We observed a dose-
dependent decrease in cell survival and growth rate even at low concentrations. At these low
concentrations, we saw an increase in general DNA damage as measured by an increase in foci of
DNA damage response proteins RPA and Rad52, consistent with a disruption in genome stability.
We assessed the effects of 1,6-hexanediol on regions of the genome that are known or
presumed to be phase separated: the rDNA array, and the heterochromatin. We observed that the
nucleolar markers Gar2 and Nhp2 were disrupted in treated cells, suggesting that proper nucleolar
structure is disrupted. We also observed partial delocalization of the heterochromatin protein HP1-
54
Swi6 from some of the foci where it is usually found. These observations suggested that normal
function of these repetitive HP1 bound heterochromatin domains might be impaired.
We assessed genome stability in the rDNA by examining the number of copies of rDNA
repeats and observed no difference following 1,6-hexanediol treatment. Similarly, using a
minichromosome with multiple markers, we determined the rates of chromosome loss or
chromosome rearrangement, both of which are associated with loss of swi6 (Li, P. C., et al. 2013),
and observed no changes. Thus, even though there may be disruption of phase separation in the
nucleolus and pericentromere, we do not see consequences on genome stability.
Many studies have focused on using the phase disrupting molecule 1,6-hexanediol to test
the phase separation capability of various proteins (Ribbeck, K., et al. 2002)(Patel, S. S., et al.
2007)(Kroschwald, S., et al. 2015)(Peskett, T. R., et al. 2018)( Itoh, Y., et al. 2021)(Ulianov, S.
V., et al. 2021). Our study suggests that its effects on live cells are broadly cytotoxic, and the
genome instability and DNA damage that result from low levels of 1,6-hexanediol cannot be
obviously linked to known phase separated domains. More precise methods of targeting phase
separation will be required to dissect its role in different domains.

Material and Methods
Cell growth and physiology
Table 1: Strain list
FY261 h+ leu1-32 ade6-M216 ura4-D18 can1-1 Forsburg, S. L., & Nurse, P. 1994
FY528 h+ his3-D1 ade6-M210 ura4-D18 leu1-32 Liang, D. T., et al. 1999
FY1520 h90 ura4-DS/E leu1 YIP2.4 pUCura4-7 Thon, G. & Verhein-Hansen, J. 2000
FY4101 h+ nmt1(41X)-GFP-nhp2::leu1* his7-366 ade6-M210 ura4-D18 leu1-32 Maiorano, D., et al. 1999
FY4267 h- nmt1(41X)-GFP-nhp2::leu1* sad1-mCherry::Ura4+ gar2-mCherry-KanR
leu1-32 ura4-D18 his5- ade6-M210
This study
FY5187 h- ade6-∆ ura4-D18 leu1-32 his1-102 ChL[ubcp4::LEU2::chk1 hph:spccB3.18
spcc1322.09::ura4+ ade6+]
Li, P. C., et al. 2013
FY5546 h+ gar2-mCherry::kanR rad11-Cerulean::hphMX rad22-YFP::natMX leu1-32
ura4-D18
This study
FY8900 h+ Swi6-GFP::kanMX6 Chp1-mCherry::natMX6, leu1-32 ura4-D18 ade6-M210 This study
FY9279 h+ nmt1(41X)-GFP-nhp2::leu1* ∆swi6::kanMX ade6-M210 ura4-D18 leu1-32 This study
55
Fission yeast cell growth and physiology was matched to previous lab protocol described
in Forsburg, S. L., & Rhind, N. (2006) and Sabatinos S. A., et al. (2012).

Cell survival and growth rate
In order to measure cell survival on 1,6-hexanediol S. pombe cells were incubated at 32°C
in 10mL of rich Yeast Extract Supplemented (YES) media for 24 hours to mid log phase. The cells
were then treated with the corresponding concentration of 1,6 Hexanediol. Samples for the 24 hour
timepoint were diluted ½ with more YES media to compensate for increased growth over the
longer time point. Cells were then counted using a hemocytometer and 500 cells were plated onto
YES media using glass beads for spreading. Colonies were then counted and ratioed against
untreated cells.
To calculate growth rate in 1,6-hexanediol S. pombe was incubated in 5mL of rich YES
media overnight. Each replicate was counted using a hemocytometer and 5x10^6 from each were
divided into 100mL of rich YES media in 250 mL flasks with either no 1,6-hexanediol or the
corresponding concentrations described in figure. Cells were then incubated for 12 hours. OD at
595nM was then checked at T=12 to T=24. OD ratios were calculated to the WT OD of that
corresponding replicate.

Live cell imaging
Methods for live cell imaging are adapted from Forsburg, S. L., & Rhind, N. (2006) and
Green, M. D., et al. (2015). S. pombe cells were taken from plates and grown overnight in 5mL of
rich YES media. They were then spun down, washed once with 1xPBS, and a portion of cells were
incubated in PMG-HULALA (PMG +Histidine, Uracil, Leucine, Adenine, Lysine, and Arginine,
225mg/L each) at 32°C overnight (Sabatinos, S. A., & Forsburg, S. L., 2010). Upon reaching mid
log phase cells were treated with either no 1,6-hexanediol or the corresponding percentage outlined
in each figure. Cells were then spun down after the described about of time and placed on 1%
agarose/PMG HULALA pads that were made at least 1 hour prior allowing them to dry slightly.
Pads were then covered with a coverslip and sealed with VaLap (1/1/1 w/w/w
Vaseline/lanolin/paraffin) and imaged directly. During long term timelapse imaging a small gap
of roughly 1-2mm in length was left unsealed using VaLap. Fully sealing the coverslip leads to
condensation and pressure buildup causing bulging that will move cells and inhibit long term
56
automatic imaging. Static images were taken at room temperature 22°C and long term timelapses
were taken at 30°C.
Images were acquired with a DeltaVision Core (Applied Precision,Issaquah, WA, USA)
microscope using a 60× N.A. 1.4 PlanApo objectivelens and a 12-bit Photometrics CoolSnap HQII
CCD. The system x-y pixelsize is 0.109 μm. softWoRx v4.1 (Applied Precision, Issaquah, WA,
USA) software was used at acquisition. Three-dimensional stacks were deconvolved with
manufacturer provided OTFs using a constrained iterative algorithm. Excitation illumination was
from a solid-state illuminator and a proper polychromic mirror and filter set was used according
to the individual or combined fluorophores. Appropriate excitation intensities and exposure times
are available in the following section.

Image processing and analysis
All image processing and analysis was done using the imaging software and plugin package
ImageJ-FIJI (Schindelin, J., et al. 2012). All foci counting was quantified using a computational
algorithm based on uniform threshold per fluorescence channel as described by the light
microscopy core facility at Duke University (https://microscopy.duke.edu/guides/count-nuclear-
foci-ImageJ).
Foci based colocalization analysis was performed using the ImageJ plugin JACoP-
manders coefficient (Bolte,S. & Cordelières, F.P., 2006). Colocalization was quantified using a
observer set standardized threshold per replicate and per treatment vs. non-treatment. 3D nucleolar
volume was calculated using the nucleolar marker GFP-Nhp2 in a WT and Dswi6 background. 40
Z-stack segments with a .1µm distance using a 100x objective were taken. Light source intensity
was set at 32% with an exposure time of .08 sec per image. Image stacks were 3D projected which
was made into a 3D mask for further analysis. The ImageJ plugin 3D Objects Counter was used to
calculate the 3D internal volume of the GFP-Nhp2 marker for the nucleolus (Bolte,S. &
Cordelières, F.P., 2006).
Long-termtime lapse videos of GFP-Nhp2 and Gar2-mCherry were taken every 10 minutes
for a total of 180 minutes. 10 z-stack images were taken at each time point per channel with a z
distance of .35µm. Light source intensity was set at 32%. for .05 sec for mCherry and 10% for .45
sec for GFP. mCherry and GFP images were bleach corrected using the ImageJ plugin Bleach
correction-histogram matching (Miura, K., et al. 2020). GFP images in 1,6-hexanediol treated cells
57
were not bleach corrected due to the lack of bright enough GFP-Nhp2 signal. Images were
stabilized in ImageJ-Fiji (Schindelin, J., et al. 2012) using the package ‘StackReg’ by Philippe
Thevanaz from the Biomedical Imaging Group at the Swiss Federal Institute of Technology
Lausanne (Thevenaz, P., et al. 1998).

qPCR assay
Long term growth in 1,6-hexanediol rDNA copy number ratio change was calculated via
18s rDNA sequence to the act1 gene. Genomic DNA was first extracted after the particular number
of days growth in 1,6-hexanediol and rich media (YES) using phenol chloroform extraction
(Forsburg, S. L., & Rhind, N. 2006). DNA concentration was calculated via a Nanodrop 1000
spectrophotometer (Thermo Scientific). Aliquots of 20ng/µL were made and both samples were
stored at -20°C until used. qPCR was done using iTaq universal SYBR green supermix (Biorad)
and a CFX96 connect real time PCR system (Biorad). 20uL samples were run with a final
concentration of 1ng/µL. Standard curves with a R
2
>.98 were used for relative quantification.
Final values were calculated as 18s/act1 gene ratios. Primer sequences were developed using
Primer-BLAST (National Institute for Biotechnology Information). Primers sequences used were
18sFWD 5’-ATT GGA GGG CAA GTC TGG TG-3’, 18sREV 5’-CAG TCG ACC AGG CTC
AAA-3’, act1FWD 5’-TGC TAC GTC GCT TTG GAC TT-3’, act1REV 5’-GGA AAA GAG
CTT CAG GGG CA-3’.

Recombination assays
rDNA recombination rates were calculated via loss of a singular ura4+ gene located within
the rDNA repeats. This strain and assay was performed via the protocol developed by Thon, G. &
Verhein-Hansen, J. (2000). Centromere stability was observed via the minichromosome loss assay
developed by Nakamura, K. I., et al. (2008) and modified in Li, P. C., et al. (2013).
58
Acknowledgements
We thank members of the lab for helpful comments and Ji-Ping Yuan for technical help.

Competing interests
The authors declare no competing or financial interests.

Funding
This research was supported by the National Institute of General Medical Sciences [R35-
GM118109] (S.L.F). C.E.J was partially supported as well by the National Institute of General
Medical Sciences [T32-GM1182829]
59
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63

64

65

Chapter 4
Pathways of rDNA Copy Number Homeostasis in Schizosaccharomyces pombe

Chance E. Jones, Ji-ping Yuan, Susan L. Forsburg
*

Section of Molecular & Computational Biology
University of Southern California
1050 Childs Way, RRI 108
Los Angeles CA 90089

*
corresponding author, forsburg@usc.edu

In progress for future publication

Abstract
Fragile sites across the genome pose an increased risk of instability. The rDNA repeats have an
increased risk of instability due to being highly repetitive, replication transcription collisions,
polar replication fork barriers, late S replication completion, and more. In this study we look at
the effects of an artificially contracted rDNA array, evaluate responses to alkylation damage in
the rDNA, and genomic pathways that affect rDNA copy number maintenance. We find that a
decreased rDNA array leads to a decreased growth rate, cell size, and increased genotoxic
sensitivity to alkylation damage from MMS. In order to deal with this alkylation damage large
rDNA arrays were also shown to contract over time in a time/concentration dependent manner.
We also showed various pathways that affect rDNA copy number including the fork protection
complex FPC, fork licensing, H3K56ac, and DDK. These results confirm that the rDNA repeats
are a genome fragile site and that various pathways affect its level of instability and ability to
deal with genotoxic stresses.

66
Introduction
Ribosomal DNA (rDNA), encoding the ribosomal RNA genes, is located in the nucleolus
of eukaryotic cells. Due to the high demand for ribosome biogenesis the rDNA is maintained in
one or more high copy number arrays. In the fission yeast S. pombe there are roughly ~150 repeats
distributed between the two telomere proximal ends of Chromosome III (Toda, T., et al. 1984).
However roughly half of these repeats are actively transcribed and half are heterochromatinized in
actively dividing WT cells (French, S. L., et al. 2003; Ide, S., et al. 2010). These rDNA repeats
code for the highly transcribed pre rRNA sequence and are then subsequently processed in the
nucleolus to the 18s, 5.8s, and 28s rRNA before nucleolar export (Good, L., et al. 1997).
Transcription of these rRNAs make up roughly 60% of the eukaryotic transcriptome (Ide, S., et al.
2010). Along with the coding regions, each array contains an intergenic sequence (IGS) which has
a replication fork barrier (RFB) and a single origin of replication known as an autonomously
replicating sequence (ARS) (Kim, S. M., & Huberman, J. A. 2001; Kobayashi, T., & Ganley, A.
R. 2005). Due to the high rate of transcription of the rDNA and in order to avoid replication
transcription collisions, the RFB is targeted by specific proteins to ensure unidirectional DNA
replication transcription blocks (Jaiswal, R., et al. 2016).
The RFB mechanism and function varies among eukaryotes. In S. cerevisiae a singular
Fob1 protein binds to the RFB causing abrupt replication fork block and is essential for rDNA
recombination (Kobayashi, T., 2003). In S. pombe there is a quaternary RFB system where the
first Ter site is bound by the Sap1 protein, Ter2 and 3 are bound by the Reb1 protein and RFB4
which is not protein bound and found in the terminal transcription region of the preceding 35s
rDNA (Sánchez-Gorostiaga, A., et al. 2004; Krings, G., & Bastia, D. 2005). This system is more
similar to higher eukaryotes which also have multiple pausing sites at each RFB (Akamatsu, Y.,
& Kobayashi, T. 2015). Members of the fork protection complex (FPC), Swi1/Swi3 and Mrc1,
Tof1/Csm3 and Mrc1 in S. cerevisiae, are essential for proper fork pausing. However while Swi1/3
are essential for any RFB pausing loss of Mrc1 only causes a 26% decrease in RFB pausing
(Krings, G., & Bastia, D. 2005; Zech, J., et al. 2015). Using these mechanisms of fork pausing the
cell mitigates the toxicity of replication transcription collisions on one hand and replication fork
collapse from stalled forks on the other. Proper function of these processes is required for
maintaining stability of the repeats and thus rDNA copy number homeostasis.
67
Cells have developed multiple mechanisms to maintain a proper rDNA copy number
homeostasis. The most well-known and studied is via cohesin restraining neighboring sister
chromatid rDNA repeats which restricts unequal sister chromatid exchange (USCE) in S.
cerevisiae (Kobayashi, T., & Ganley, A. R. 2005). In the regulation of this system the histone
deacetylase Sir2 represses the expression of the E-pro transcript from the rDNA IGS sequence
which restricts cohesin binding (Kobayashi, T., et al. 2004). A decrease in the number of available
rDNA repeats leads to a feedback loop resulting in repression of Sir2 and thus allowing for E-pro
expression in the rDNA which dislodges IGS cohesin. Dislodging of cohesin can lead to
misaligning of rDNA repeats between sister chromatids resulting in unequal sister chromatid
exchange (USCE) (Kobayashi, T., et al. 2004; Kobayashi, T., & Ganley, A. R. 2005). Another
mechanism maintaining rDNA copy number homeostasis is large intra-chromatid recombination
most often leading to extrachromosomal rDNA circles (ERCs). These can undergo excision and
reinsertion into the genome creating large changes in rDNA chromosomal copy number without
much effect on rRNA output. This process of ERC formation and rDNA excision has also been
correlated with limited replicative aging in yeast (Sinclair, D. A., & Guarente, L. 1997; Kobayashi,
T. 2011). Another mechanism maintaining proper rDNA copy number homeostasis is that of rDNA
heterochromatin formation silencing unused rDNA repeats (Srivastava, R., et al. 2016). It is has
been proposed that heterochromatin formation restricts transcription replication collisions thus
stabilizing unused repeats. In fact Drosophila mutants lacking the main heterochromatin binging
protein HP1 had a gradual decrease in rDNA repeats (Lawrence, R. J., et al. 2004 Pontvianne, F.,et
al. 2012). Overall cells rely on various mechanisms to respond to high or low rDNA copy numbers
to maintain a particular homeostatic copy number, however based on the genomic environment
these mechanisms may not be able to cope with rDNA instability thus leading to an increase or
decrease in rDNA copy number away from homeostasis.
In this study we perform a comprehensive candidate approach in fission yeast to evaluate
how different mutants affect homeostasis of the rDNA. Additionally, we determine the
consequences of having an engineered minimal rDNA array. We find that cells with a contracted
rDNA are more sensitive to genotoxic drugs, and that many pathways that are involved in fork
licensing, fork protection, DNA damage signaling, chromatin modifiers, and DNA repair
mechanisms are essential to maintaining proper stability and homeostasis in the rDNA repeats. We
68
also find that constant DNA alkylation damage resulting in fork slowing and requiring the TLS
and BER pathways result in a selection over time for a smaller rDNA array.

Results
Reduced copy number of rDNA leads to impaired cell growth and sensitivity to genotoxins
In order to evaluate the cellular response to an artificially contracted rDNA array we used
a Tet inducible I-PpoI endonuclease to reduce the rDNA copy number of otherwise WT S. pombe.
All eukaryotes contain a particular I-PpoI endonuclease recognition site in each rDNA repeat
(Ellison, E. L., & Vogt, V. M. 1993). The site in S. pombe is located within the 25s rRNA sequence
and upon I-PpoI induction surviving cells contain a T insert (Sunder, S., et al. 2012). This T insert
into the rDNA has so far been deemed harmless and results in only a small increase in generation
time ref. Upon ahTet induction we noticed a drastic variability in colony size of survivors (Sunder,
S., et al. 2012). We hypothesized that due to induced double strand breaks, the surviving strains
would have a contraction in their arrays and this could be the cause of the variation in colony size.
We used qPCR to measure rDNA copy number by determining the ratio of 18S to the euchromatin
gene act1. The smallest of the colonies contained approximately 20% of wt rDNA content.
We compared the rate of cell growth, cell length, and drug sensitivity of the minimal rDNA
strain to WT. Growth rate of the 20% rDNA strain was drastically reduced when comparing the
OD over a 24hr period at 595nm (Figure 1B). The 20% rDNA strain cells also had a much smaller
cell size compared to WT (Figure 1 C and D). When serially diluted onto the genotoxic drugs
methyl methanesulfonate (MMS), camptothecin (CPT), the transcritpion inhibitor actinomycin D
(ActD), or the phase separation inhibitor 1,6-hexanediol, the 20% strain was more sensitive to all
these drugs, with particular sensitivity to MMS. In contrast, a strain with 40% WT rDNA copy
number ratio only shows increased sensitivity to MMS (Figure 1E).
69

Candidate screen reveals pathways of rDNA copy number homeostasis
To evaluate mechanisms that maintain rDNA homeostasis in S. pombe we determined the
ratio of 18s to act1 copy number. Since this analysis compares relative and not absolute copy
number, we then divided the number compared to a control S. pombe strain FY261 which has the
same rDNA content as the original isolate strain 972 (data not shown). To confirm our results, we
compared these ratio values to a previous PFGE of three representative strains ∆cds1, ∆mrc1 and
wild type FY261 (Figure 2B). We used a candidate screen to compare at rDNA copy number using
the 18s/act1 gene ratio compared to WT rDNA on a larger scale. The entire list of tested mutants
is available in supplemental information figure S1. Selected mutant strains are shown in figure 2C.
A mutation in the recombination mediator ∆rad52 had the lowest rDNA content of any
strain we examined. Surprisingly other HR associated mutants such as ∆rad54, ∆rad55, ∆rad57,
70
and ∆rad51 had maintained an array closer to wild type. We observed that a mutation in the
helicase ∆fbh1 also very low rDNA. Since ∆fbh1 is a common spontaneous suppressor found in
many ∆rad52 lab strains (Osman F., 2005), it is possible that mutation of ∆fbh1 is responsible for
the reduced rDNA levels in our ∆rad52strain.
As observed previously, other mutants with very low rDNA content are those of the
replication fork protection complex (FPC) ∆swi1, ∆swi3, and ∆mrc1 (Noguchi, E., et al. 2004;
Zech, J. et al. 2015). The Swi1 and Swi3 proteins have been previously implicated in replication
fork termination in the rDNA (Krings, G., & Bastia, D. 2004). In contrast, loss of the FPC-
associated mrc1 causes only moderate reduction (26%) in RFB stalling by comparison (Zech, J.,
et al. 2015). Mrc1 also plays a role in activation of the DNA replication checkpoint kinase Cds1
(Tanaka, K., & Russell, P. 2004). We used two separation of function mutants Mrc1
T645A,T653A
and
Mrc1
S/TQ to AQ
(Figure 2C). Both of these alleles have mutations in the sites necessary for proper S
phase damage signaling transduction while leaving the rest of the Mrc1 FPC functions as normal
(Xu, Y., et al. 2006). These mutant alleles show a slightly larger rDNA array compared to full
deletion ∆mrc1. Deletion of the S phase checkpoint kinase Cds1 also showed a similar rDNA ratio
to the Mrc1
T645A,T653A
allele. However, the reb1∆ mutant which also disrupts fork termination in
the rDNA (Sánchez-Gorostiaga, A., et al. 2004) did not have an effect on rDNA copy number,
suggesting it is not polar termination per se that is responsible for the reduced rDNA size.
Using tetrad dissection, we isolated strains in which a normal sized rDNA was crossed into
a ∆swi1 or ∆mrc1 background. We found that over the space of approximately 60-70 generations,
the rDNA shrank closely to the size observed in our original strain (Figure 3A). This shows there
is a stark variability in response to rDNA stress. It is possible that mutants that cause a more
unstable rDNA will contract at a higher rate than those that do not. Further research must be
conducted to fully validate this hypothesis.
The FPC acts with the DNA replication kinase DDK in the response to replication stress
(Matsumoto, S., et al. 2005; Sommariva, E., et al. 2005; Shimmoto, M., et al. 2009). DDK
comprises a kinase Hsk1
Cdc7
and a regulatory subunit Dfp1
Dbf4
(Masai, H., et al. 1995; Pasero, P.,
et al. 1999). We observed reduced rDNA array in C-terminal truncation mutant dfp1-r35, missing
the last 25 amino acids of the Dfp1 protein (Dolan, W. P., et al. 2010). Similar results were
observed in two other C-terminal truncation mutants dfp1(1-376) and dfp1(1-459) (Fung, A. D., et
al. 2002). The C-terminal mutants of Dfp1 have been proven to be poor activators of Hsk1, have
71
a role in MMS response, implicated to function post initiation, and is essential for proper meiosis
(Fung, A.D., et al. 2002; Le, A. H., et al. 2013; Dolan W.P., et al. 2010). DDK plays many
important roles in eukaryotic DNA replication and genome stability (Figure 3C). We evaluated
rDNA levels in multiple mutants in the pathways affected by DDK including centromere stability
(dfp1-3A,Dswi6,rad21-K1), fork licensing (psf2-209, cdc45ts), translesion synthesis (pol κ, ζ,
η+rev1, pcn1 K164R, rad8), and replication fork stalling via the FPC (Δswi1, Δswi3, Δmrc1, Δhst4,
Δrtt109) (Figure 3D). Only the FPC and fork licensing pathways shared a similarly low level of
rDNA.
Fission yeast rDNA is partially heterochromatinized via H3K9 trimethylation and binding
of HP1 orthologue Swi6 (Allshire, R. C., et al. 1995; Cam, H. P., et al. 2005). This mechanism is
absent from S. cereivisae (Rusche, L. N., et al. 2003). We tested mutants with disruptions in
essential heterochromatin proteins. Chp1 and Dcr1 are parts of the RITS complex associated with
reestablishment of heterochromatin after replication by targeting the Clr4 histone
methyltransferase (Petrie, V. J., et al. 2005; Schalch, T., et al. 2009). Swi6 is the HP1 orthologue
protein that is responsible for H3K9me binding and condensation of heterochromatin domains
(Allshire, R. C., et al. 1995; Cam, H. P., et al. 2005). Unexpectedly unlike other studies such as in
Drosopila (Lawrence, R. J., et al. 2004; Pontvianne, F.,et al. 2012) even without the essential
functions of heterochromatin formation we found that ∆swi6, ∆dcr1, ∆clr4 and ∆chp1 all have a
normal rDNA copy number.
Unlike H3K9me, another histone modification H3K56ac is conserved between S. pombe
and S. cerevisiae and is associated with DNA replication and DNA damage response (Hardy, J.,
et al. 2019). The H3K56 histone acetyltransferase Rtt109 has been implicated in budding yeast
rDNA homeostasis (Ide, S., et al. 2013). Deletion of S. cerevisiae rtt109 causes striking expansion
of rDNA to 3 times that of the wild type (Ide, S., et al. 2013). A similar expansion is observed in
S. cerevisaie ∆mms22. (Ide, S., et al. 2013). In contrast to the magnitude of the effect in budding
yeast, we observed only a modest increase in size of the rDNA arrays in ∆rtt109 or ∆mus7
mms22

strains. Deletion of the histone deacetylase ∆hst4, which antagonizes Rtt109, had no effect.
72

Epistasis analysis of pathways of rDNA homeostasis
We investigated the phenotype of double mutants to assess interaction between pathways
that increase or decrease rDNA arrays. First, we examined double mutants with ∆rtt109.
Interestingly, the ∆rtt109 ∆reb1 double mutant had a notably smaller rDNA array than either single
mutant. This implies that Reb1 dependent termination at the RFB is required to stabilize the
expanded array size seen with loss of H3K56ac. Loss of ∆rtt109 also did not notably change the
already shrunken array associated with ∆swi1, but ∆rtt109 ∆mrc1 had an increased array size. One
explanation is that loss of FPC components Swi1/Swi3 lead to complete loss of fork stalling at
rDNA RFB however loss of Mrc1 only leads to a 26% reduction in fork stalling at RFB (Zech, J.,
et al. 2015). Thus these results along with the ∆rtt109∆ reb1 further suggest that RFB stalling is
essential for stability of the expanded rDNA array size seen in ∆rtt109 and thus loss of H3K56ac.
Strikingly, a combination of psf2-209 ∆rtt109 or cdc45ts ∆rtt109 also rescued the small array
73
associated with psf2-209 or cdc45ts alone. This suggests that improper fork licensing leading to a
contracted rDNA can be rescued by loss of H3K56ac.
Combination of psf2-209 and ∆reb1 lead to an even further contraction of the rDNA array
size as well as cdc45ts and ∆reb1. The observed decreases are from 46% in the psf2-209 single
mutant to 31% in the psf2-209 ∆reb1 and 49% in the cdc45ts single mutant to 38% in the cdc45ts
∆reb1 double mutant. This is a substantial decrease suggesting that loss of RFB function and
proper replication fork licensing may play separate role in rDNA homeostasis and thus
combination of loss of proper function leads to a combinatorial decrease in rDNA copy number.

Alkylation damage causes a decrease in rDNA repeats
Methyl methanesulfonate (MMS) perturbs replication fork progression by causing the
addition of a methyl group to mostly adenines and guanines (Beranek, D.T., 1990; Lundin, C., et
al. 2005). Yeast cells deal with these adducts either via base excision repair pathways (BER) or
via replication fork progression using error prone translesion polymerases (Memisoglu, A. &
Samson, L. 2000; Plosky, B.S., et al. 2008). These processes interfere with transcription and
74
replication machinery progression and must proceed despite the other competing processes. Since
the rDNA completes replication late in S phase further delay of the rDNA repeats due to ongoing
repair may further sensitize larger arrays to greater instability. We hypothesized that long term
growth of cells in low concentrations of MMS would lead to a gradual contraction in rDNA copy
number to cope with the added stress of completing rDNA replication in a timely manner. Our
results show that even at .001% MMS over a 20-day period there is a gradual decrease in rDNA
copy number even in WT cells (Figure 4). The speed of rDNA copy number contraction was
further exacerbated upon increasing the treatment to .004%. After 20 days even at the highest
percentage there was a gradual homeostasis met at around 65% of WT rDNA.

Discussion
In this study, we examined rDNA homeostasis in the fission yeast. rDNA is found in two
arrays on the ends of chromosome III (Toda, T., et al. 1984). Previous work from our lab using
PFGE shows that many various mutants contain a condensed ChIII on the size scale of 100-
1000kbs (Data not shown). We proposed that this could be due to instability in the rDNA leading
to copy number loss as large losses of the 10.9kb array could result in these changes. In fact work
in budding yeast suggests that the size of rDNA arrays acts as a buffer for genome instability, and
is also correlated to replicative lifespan (Kobayashi, T. 2011; Fine, R. D., et al. 2019). First, we
established an assay to determine the ratio of rDNA observed by qPCR to act1 and normalized
this to a control wild type strain, FY261. In the course of this work, we determined that there is a
narrow range of wild type array size in wild type cells, and FY261 falls on the upper end of this
distribution similar to the canonical wild type 972h
-
. This assay correlates with the size of
75
chromosome III. Importantly, however, we did not independently assess the presence of
extrachromosomal repeats (ERCs) which would be included in the qPCR.
Next we examined the consequences of an artificially contracted rDNA array to about 20%
of wild type levels. We find that this strain has a reduced growth rate, delayed cell cycle length,
and increased sensitivity to a range of drugs. Compared to a strain with a 40% array size, we find
that both of these are notably sensitive to the alkylating agent MMS. This is also seen in many of
the mutants in our screen that we observed having an expanded or contracted rDNA array such as
∆rtt109, ∆mus7, ∆swi1/3, ∆mrc1, dfp1-r35, ∆fml1/2, ∆rqh1, ∆cds1 (Xu, Y., 2006; Han, J., 2007;
Yokoyama, M., 2007; Noguchi, C., 2012; Harris MA, et al. 2021). However conversely there are
also many mutants in our screen that had a normal rDNA copy number ratio but are reported to be
MMS sensitive such as ∆rad3 ∆rad55 ∆chk1 ∆rad54 cdc21-c106 (Harris MA, et al. 2021). These
results show that MMS sensitivity is not a determinant factor of rDNA array abnormality however
a contracted or expanded rDNA array may sensitize fission yeast to MMS.
As discussed previously MMS creates DNA alkylation damage which is typically repaired
by base excision repair (BER) or translesion synthesis pathways (Memisoglu, A. & Samson, L.
2000; Plosky, B.S., et al. 2008). This damage can result in transcriptional and replication inhibition
and thus must be repaired for proper cellular processes to proceed. In cells with a contracted rDNA
array there is a much higher rDNA POLI occupancy on fewer rDNA repeats (Ide, S., et al. 2010).
Competition between transcriptional machinery and repair machinery may sensitize the rDNA
further in a strain with an already contracted rDNA array. Conversely strains with a large rDNA
array such as ∆rtt109 or ∆mus7 may be sensitive to MMS due to the inability to complete rDNA
replication efficiently due to ongoing repair in the rDNA array competing with replication fork
progression, or by inhibition of late firing origins which may further delay rDNA replication
completion (Shirahige, K., et al. 1998). Since replication of the rDNA repeats completes late in S
phase, completion of replication of a much larger array along with replication delay due to repair
functions may further sensitize these strains (Kim, S. M., & Huberman, J. A. 2001). In fact even
in WT S. pombe we saw a selective contraction in the rDNA repeats in order to cope with rDNA
stress from MMS treatment (Figure 4). These results altogether confirm that MMS alkylation
damage sensitizes S. pombe with expanded or contracted rDNA arrays and that contraction of an
expanded rDNA array may allow for more efficient completion of rDNA replication in coping
with MMS stress.
76
Our screen revealed many previously uncharacterized mutants containing a reduced rDNA
copy number and included many that were previously well known for this phenotype. One such
well known group of proteins that causes rDNA instability is the FPC proteins especially
Swi1/Swi3 (Noguchi, E., et al. 2004). A less well characterized group for their rDNA instability
is replication fork licensing mutants such as psf2-209 and cdc45ts (Dolan, W. P., et al. 2005;
Gómez, E. B., et al. 2005). Thirdly we revealed the particular sensitivity of our c-terminal
truncation mutant dfp1-r35 (Dolan, W. P., et al. 2010). Interestingly DDK plays a distinct role in
both of these processes. Dfp1 is responsible for targeting the Hsk1 kinase to phosphorylate MCM
proteins during replication fork licensing. This allows for Cdc45 and GINS binding and thus
facilitates fork licensing and replication firing (Dolan, W. P., et al. 2005, Ilves, I.,et al. 2010;
Aricthota, S., & Haldar, D. 2021). During fork progression DDK also travels with the fork and is
responsible for phosphorylating MCM proteins in response to genome damage resulting in
replication fork stalling via the FPC (Dolan, W. P., et al. 2010). In fact FPC proteins Tof1-Csm3
(Swi1 and Swi3) association with MCM proteins is dependent on DDK and thus abrogation of
DDK leads to fork collapse instead of stabilized stalled forks in S. cerevisiae (Matsumoto, S., et
al. 2005; Mohanty, B. K., et al. 2006; Bastia, D., et al. 2016). It seems that DDK plays a duel role
in rDNA stability and rDNA copy number homeostasis through proper replication fork licensing
as well as proper FPC function and thus stabilized stalled replication forks. Our c-terminal dfp1-
r35 substantiate these claims and reveal that sensitization of these two pathways with this mutant
leads to an extreme drop in rDNA copy number.
We also discovered that Drtt109 and Dmus7 do not have as much of a drastic effect as in
S. cerevisiae (Ide, S., et al. 2013). The drastic increase in rDNA repeats seen in the Drtt109 in S.
cerevisiae were revealed to be due to ERC formation and not USCE (Ide, S., et al. 2013). It is
possible that ERC formation does not play the same role in Drtt109 in S. pombe. More research
must be conducted on the exact mechanisms that underlie S. pombe rDNA expansion and
contraction as clear differences in these systems are apparent.
One final result that we found interesting is the lack of any change in rDNA copy number
ration in any of our heterochromatin mutants Dclr4, Dchp1, Ddcr1, and Dswi6. Previous research
has shown that proper heterochromatinization of silent rDNA repeats is essential for maintaining
rDNA copy number homeostasis (Lawrence, R. J., et al. 2004; Pontvianne, F.,et al. 2012). In fact
research has shown that HP1 mutant Drosophila have a successive contraction in their rDNA array
77
over many generations (Aldrich, J. C., & Maggert, K. A. 2015). However we do not see any such
contraction in any S. pombe heterochromatin protein mutants including the HP1 orthologue Swi6.
These results conclude that either other mechanisms maintain rDNA copy number homeostasis in
S. pombe or our experiments did not result in enough generations of growth to see subsequent
contraction of the array.

Materials and Methods
Cell growth and physiology
Fission yeast cell growth and physiology was matched to previous lab protocol described
in Forsbur, S.L., & Rhind (2006) and Sabatinos, S. A., et al. (2012). Cell growth rate was
calculated using OD 595nm over a 13 hr period from hr 12-24. Cell length was calculated using a
observer drawn map of cell lengths in imageJ-FIJI (Schindelin, J., et al. 2012). Longterm growth
in MMS was performed by serial dilution once each day for the number of days tested. DNA
extraction and rDNA quantification protocol is described below.

Artificially contracted rDNA array
A strain with a TET inducible I-PpoI endonuclease originally developed by Sunder, S., et
al. (2012) was grown on 3µM anhydrotetracycline rich YES media plates for 5 days. Colonies of
various sizes were taken and grown overnight in rich liquid YES media and DNA was extracted
via phenol chloroform extraction. rDNA quantification was calculated as below.

rDNA mutant screen
Biological triplicate or more mutant strains were either grown at 32°C for 6 days or 25°C
for 8 days (for ts mutants) in 5mL of liquid rich YES media. Strains were serially diluted once
each day to maintain growth in log phase as much as possible. On the last day of growth the 5mL
culture was spun down and DNA was extracted via phenol chloroform extraction as in Forsburg,
S. L., & Rhind, N., (2006). DNA concentration was calculated via a Nanodrop 1000
spectrophotometer (Thermo Scientific). Aliquots of 20ng/µL were made and both samples were
stored at -20°C until used. qPCR was done using iTaq universal SYBR green supermix (Biorad)
and a CFX96 connect real time PCR system (Biorad). 20uL samples were run with a final
concentration of 1ng/µL. Standard curves with a R2 >.98 were used for relative quantification.
78
Final values were calculated as 18s/act1 gene ratios. Primer sequences were developed using
Primer-BLAST (National Institute for Biotechnology Information). Primers sequences used were
18sFWD 5’-ATT GGA GGG CAA GTC TGG TG-3’, 18sREV 5’-CAG TCG ACC AGG CTC
AAA-3’, act1FWD 5’-TGC TAC GTC GCT TTG GAC TT-3’, act1REV 5’-GGA AAA GAG
CTT CAG GGG CA-3’.
79
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84

Supplemental figure 1. rDNA ratio to WT of all
single mutants observed in this screen.
85

Supplemental figure 2. rDNA ratio to WT of all
double mutants observed in this screen.
86

Supplemental figure 3. rDNA ratio to WT of selected
mutants psf2-209, swi1/3, hsk1-1312, dfp1-r35
87
Appendix
Nanopore sequencing of Schizosaccharomyces pombe

Chance E. Jones & Susan L. Forsburg
*

Section of Molecular & Computational Biology
University of Southern California
1050 Childs Way, RRI 108
Los Angeles CA 90089

*
corresponding author, forsburg@usc.edu

88
Background
One of my side projects during my time in the Forsburg lab was to facilitate the purchase,
setup, and troubleshooting associated with Oxford Nanopore Sequencing. Nanopore sequencing
has developed commercially since roughly 2016. Original sequencing platforms using nanopores
had extremely high error rates with some runs not even reaching 90% accuracy (Lu, H., et al.
2016). However one of the benefits many saw in pushing forward with this revolutionary
technology is the ability to sequence long reads. Long read sequencing is much more able to easily
resolve structural variants at lower coverage compared to the extreme high coverage needed with
illumina sequencing (Tusso, S., et al. 2019; Dixon, K., et al. 2023). Illumina sequencing while it
allows for rapid sequencing of large genomes at high coverage, the sequence read length is at most
limited to about 300bp with current technology, and usually requires PCR based amplification.
Nanopore sequencing however is virtually unlimited in its read length and can be directly
sequenced if enough sample DNA is available eliminating the need for preamplification bias. Read
length is only determined by the length of the DNA sample you put into it. According to labs
utilizing the oxford nanopore sequencing platform there have been records of up to 5Mb DNA
strands sequenced so far (Lin, B., et al. 2021).
Nanopore sequencing uses micron size small protein pores, nanopores, positioned across
an electrically insulative thin barrier within a charged buffer. During preparation specialized
adapter proteins are ligated to the DNA. Tether proteins on the barrier bring the adapter protein in
contact with a available nanopore which then unwinds the DNA. One strand is ejected into the
surrounding buffer while the other strand is fed through the nanopore. Sensors in the well recognize
changes in the flow of ions through the nanopore based on the occlusion by the nucleotides. As
the ssDNA is fed through the nanopore the overall charge of the nanopore changes and is recorded
for basecalling.
A couple of the most revolutionary breakthroughs for nanopore sequencing has been the
structure of the nanopore/chemistry used and the computation of basecalling. Firstly Oxford
nanopore has multiple available flow cells with varying accuracy nanopores. We began by utilizing
their Q20+ capable pre-release flow cell 10.4 with Kit 12 chemistry which has a read rate of ~200-
250bp per second. Raw read simplex sequencing with this chemistry and pore can reach accuracies
up to 99.6%. Increasing coverage will further increase accuracy as will computationally selecting
for duplex reading. Structural variant calling depending on the computational method of variant
89
calling and coverage can reach accuracies up to 96%. Secondly the other revolutionary
breakthrough oxford nanopore has achieved is computational accuracy of basecalling. As the
single strand DNA passes through the nanopore there is a change in ion flow. Sensors record this
change in charge and average that against the speed that the DNA is traveling through the pore.
Afterward or in tandem Oxford nanopore uses in house designed algorithms to interpret the change
in charge and relate that to evaluating which base appears where in a particular strand. CPU based
mechanisms are not optimized for this process as running it in sequence for every strand would
take exceptionally long. Therefore oxford nanopore utilizes the Nvidia CUDA toolkit for running
all of these calculations in packets in parallel on a graphical processing unit (GPU) instead of the
CPU. This drastically cut down on the computation time needed for these processes allowing for
calculation of basecalling in as little as a few hours. (Technical specifications retrieved from
https://nanoporetech.com/)

Results
In order to evaluate the accuracy and real world application of Oxford nanopore sequencing
in our lab I selected eight stored mutants with the strain numbers FY333-340 that were rescue
mutants for over production of the G1 cyclin Puc1 originally isolated by Susan Forsburg PhD. The
overall sequencing run results are as follows, run time 37hr 21min, read count 921.37k, estimated
bases sequences 11.4Gb, 8 barcoded genomes sequences. Original pore scans reveal this new flow
cell began with 1311 available pores at the start of sequencing out of the original 2048. This flow
cell was used roughly 3 weeks after receipt of the flow cell thus showing the drastic decrease in
pores during the process of shipping and storage. Figure 1 shows that the N50 is 33.15 kb meaning
roughly 50% of the data is from sequences greater than 33.15kb in length. Figure 2 shows the
number of usable pores out of the original 2048 while figure 3 shows the number of pores being
occupied out of the number available. Usable pores are dependent on the stability of the nanopores
and if they are available to sequence while pore occupancy is dependent on quality and quantity
of the input library. These results show that as time progresses more pores degrade as to be
expected and as sequencing progresses the amount of available DNA/sequencing resources in the
buffer decreases as well. Figure 4 reveals that barcode ligation efficiency as well as library
preparation efficiency is not 100% and variabilities in barcoding results vary. Optimization of
input DNA amount and quality will aid in maximizing equal barcode sequencing.
90
After sequencing the results were basecalled using the Oxford nanopore super resolution
basecalling model and then barcoded and trimmed. Resulting barcodes were separated and aligned
to the S. pombe 972 NCBI annotated genome database sequence using Minimap2 in the genome
analyzing software Geneious. Figure 5 shows an example of the aligned chromosome 3 of strain
FY333. Aligned chromosomes are then processed using the in house Geneious SNP identifier. As
nanopore sequencing is notorious for inaccurately sequencing long homopolymers the
homopolymer reduction coefficient during the SNP analysis was turned to 90%. A list of properly
identified SNPs were then selected for SNPs within coding sequences resulting in the results in
table 1.
91

Figure 1. Estimated read length
N50 shows that 50% of the data comes from sequences greater than 33.15kb.

Figure 2. Original available pores during the sequencing run at interval pore scans.
The number of available single pores at the beginning of sequencing is 1311. The other pores are
unable to be used for sequencing.

92

Figure 3. Pore use during sequencing
Pore occupancy at the beginning of sequencing is extremely high, above 90%. As sequencing over
10-20 hours proceeds there is a decrease in pore occupancy due to a decrease in available DNA as
well as consumables required for nanopore function in the buffer.

Figure 4. Barcoding read count distribution
Barcoding efficiency was high and relatively even however there are differences that can be
mitigated via DNA amount and purity.

Figure 5. Example alignment of Ch3 of FY333
93
This is an example of a typical sequence map of an aligned chromosome. Small horizonal white
lines below represent sequenced reads aligned to the reference genome. After zooming in these
become nucleotides and differences compared to the reference are color coded.

Table 1. Gene mutation read out of ChIII of strain FY333
Table 1shows a typical read out of any point mutations in strain FY333 compared to the reference
genome. The last two mutations, ght8 and ags1 have also been identified in subsequent WT strains
contained in the Forsburg collection and are thus most likely not novel mutations.

Nucleotide
change
Nucleotide
Result
Codon
change
Amino
acid
change
Gene Protein description Protein
mutation
type
Confidence
G -> A SNP (transition) GAT -> AAT D -> N rhp42 DNA repair protein Rhp42 Substitution 93.80%
C -> T SNP (transition) AGG ->
AGA
rhp16 ATP-dependent helicase None 100.00%
C -> G SNP
(transversion)
TCC -> TGC S -> C hmg1 3-hydroxy-3-methylglutaryl-
CoA reductase Hmg1
Substitution 100.00%
A -> T SNP
(transversion)
GTT -> GAT V -> D ght8 putative hexose transporter ght8 Substitution 100.00%
A -> T SNP
(transversion)
TAT -> TTT Y -> F ags1 alpha-1,4-glucan synthase ags1 Substitution 94.30%
94

Materials and Methods
Sequencing was performed on the Oxford nanopore Mk1C sequencer using a 10.4 version
flow cell utilizing kit chemistry 12. DNA was isolated using the Qiagen 100/g genomic tip
protocol. The barcoding sequencing kit used was the Native Barcoding Kit 24 (SQK-NBD112.24).
DNA end prep and repair was done using the NEB companion kit containing NEBNext FFPE
DNA Repair Mix and NEBNext Ultra II End Repair /dA-tailing module. For barcoding ligation
the NEB Blunt/TA Ligase Master Mix was used. Sequencing protocol was adapted from the
Barcoding sequencing kit protocol from the Oxford Nanopore website. Sequence basecalling and
barcoding was done using the Guppy basecaller SUP model provided by Oxford nanopore and
used a Windows operating system on a Alienware Aurora R13 with an Intel I9 12900KF and a
Nvidia 3090 GPU. Sequencing analysis was done using the genome analysis software Geneious,
and the genome alignment program Minimap2 to the NCBI genome database annotated S. pombe
972 genome. SNP analysis was done using the in program Geneious SNP analyzer with a 90%
homopolymer reduction.

Troubleshooting
Extraction method: High molecular weight genome extraction kit- Qiagen 100/G
Relatively clear cut protocols for yeast extraction can be found at
https://www.qiagen.com/us/resources/resourcedetail?id=d2b85b26-16dd-4259-a3a7-
a08cbd2a08a3&lang=en. You should purchase the Genomic DNA buffer set unless you prefer to
make the buffers yourself on page 62. https://www.qiagen.com/sg/spotlight-pages/ias/automated-
qpcr-workflow/purification/genomic-dna-buffer-set/ There are a few modifications needed for use
with S. pombe in the Forsburg lab. First of all the number of yeast cells for extraction is far too
high as stated in their protocol. Instead of 7x10
9
, this number should be changed to 1-2x10
9
and
slight adjustments can be made from there. Using too many cells will easily clog the genomic tip.
Special care should be taken as to the concentration of RNase stock solution. The protocol calls
for 10ul of 200ug/ml however most labs contain other concentrations. Quiagen Proteinase K
solution is also the best option during the protein degradation step and is located in the refrigerator.
Lastly do not try precipitating DNA using a glass rod, this will not work. Use protocol 5B instead
by centrifuging at 8000xg at 4°C. Note any more than 8000xg will crack the 15ml conical tubes.
95
Finally the DNA should be stored in TE pH 8.0 buffer obtained from thermo sci. Do not use lab
diluted stock. Redissolving DNA in TE may be difficult if you over dried the pellet so please
beware not to air dry for long, 5 min at most. The last note for DNA extraction is to never leave
your DNA samples in the fridge more than 24 hours. I had substantial DNA losses and shortening
of fragments after more than 24 hours. It is advisable to have all of your DNA extracted the day
before and the next day perform the sequencing kit and sequencing right away. If you need to wait
it is also possible to freeze these samples at -80C however I never tried this.

Ligation sequencing kit:
The proper sequencing kit protocol can be found on the Oxford nanopore website. Please
be sure to choose the correct kit for your application. If you need an amplification step vs. native
DNA this will make a big difference in the kit you use. Also make sure you purchase the correct
NEB companion kit separately. Ligation sequencing kits with and without barcoding require
different NEB companion kit enzymes and you need to make sure you have the correct one. For
example if barcoding you will need the Blunt/TA ligase mastermix. This does not come with the
DNA repair mix or Ultra II end repair mix. Also always use Eppendorf low bind DNA tubes of
which we have boxes available under the sequencer. Always use these as you will see a drastic
decrease in your DNA read length as longer DNA fragments get stuck to normal tubes. Going
through and making sure you have all the appropriate supplies very far in advance is essential.
When performing sequencing prep using one of the kits it is often advisable to extend some
of the waiting times for the enzyme steps as well. For example if doing the blunt ligation of
barcodes, the protocol says incubate for 20 minutes at room temperature. However I have often
found that these protocols were made for ease and speed of use. Increasing incubation time of
enzyme trimming or ligations will likely increase your yield if you are having problems with low
sequencing DNA amounts. This is also true for other steps like the rotation step after AXP bead
binding. The protocol often says let the bead mixture sit in the nuclease free water at 37°C for 10
minutes with agitation by flicking 10 seconds every 2 minutes. This was never enough for me. I
needed to do this for at least 20 minutes to get enough DNA to unbind from the beads. Waiting
longer also increases the length of the DNA since longer DNA fragments stay stuck to the beads
longer.
96
Also you need to adjust the volume of Input DNA. Even though oxford nanopore says that
you need usually 1000ng gDNA per sample etc this will not be enough. When I perform my
sequencing runs I always start with 5000ng at least. Throughout the process of using the ligation
sequencing kit or native barcoding kit there is a lot of DNA that is lost in the process even with
longer incubation times as discussed previously. Oxford nanopore is a bit optimistic in order to get
their customers to think they can work with small amounts of DNA but this will usually result in
low pore occupancy during a run and wasted flow cells. If barcoding of course working with a
smaller amount of DNA per barcode is acceptable but always take the cautious approach and at
least double if not triple or more the amount of starting DNA they suggest.
According to Oxford nanopore sequencing kits are insured for 6 months at the time of
writing but most people say they are still functional out to a year. Please check to make sure you
have some available and not expired. This is also essential for NEB enzymes, although I have not
tested how good they are beyond the expiration date however I would assume they remain much
longer as with other NEB enzymes.
Prepped DNA should be placed in the sequencer right away. Prepped libraries/samples
easily degrade even just overnight in the 4°C.

Flow cell and sequencing run:
One of the best things I discovered when using the flow cell is that it is best to take the
flow cell out of the 4C at least an hour before you plan to run anything on it and put it into the 25C
incubator for 45 min and then the 30C incubator for at least 15-45 min. During the flow cell check
when you first put the flow cell into the minion it heats up the pores rapidly to 37C or 30C during
an actual run. Too rapid heating of the flow cells from refrigerator temperatures causes bubbles to
form inside of the flow cell completely damaging huge numbers of flow cells. Slowly heating up
the flow cell is the best method to combat this and will make your flow cell last much longer.
Make sure that you heed the instructions and use a pipet to suck any bubble out of the
priming port. Injecting liquid without doing this step will inject a large amount of air into the
nanopore area and completely inactivate them. After a run and using the flow cell wash kit I have
noticed that the nanopores often do not recover very much.
Lastly use the flow cells immediately as fast as you can. The longer they spend in 4C
temperatures it drastically reduces the number of available pores. According to Oxford nanopore
97
the 10.4 flow cells we are using degrade very quickly and are suggested to never be used for any
type of field application. In fact the 9.4.1 flow cells are under warranty for 12 weeks while the
10.4 flow cells are only warranted for 4 weeks. My suggestion is to use them within the first two
weeks at most. For me when I waited 4 weeks the number of available pores had gone from 2048
to around 1000. Oxford nanopore will only replace the flow cell within the 4 weeks waranty if the
number of available pores goes below 800. Making sure you have your DNA already extracted,
everything ready to go and your ligation/barcoding kit ready to go as well are essential. Make sure
that if you are ordering a ligation/barcoding kit that you verify that Oxford nanopore will send
them together. If they send you a flow cell while a barcoding kit is on backorder and will need a
lead time of 4 weeks well then you’ve completely wasted your flow cell since it will be almost
useless after 4 weeks when your sequencing kit arrives. Oxford nanopore does not keep track of
this so its up to you to verify with them.

Basecalling:
Basecalling is done on the Alienware desktop using the dedicated Nvidia 3090 GPU. This
computer was specifically purchased for sequencing basecalling and analysis. The genome
analysis software Geneious is also installed and contains both the NCBI S. pombe preloaded
annotated genome for alignment, as well as our common lab strain FY528 sequenced on the
nanopore at >100x coverage for reference.
Using filezilla transfer all Fast5 files from the Mk1C sequencer. Use the minknow software
in order to do basecalling with the SUP basecalling algorithm. Using the SUP basecalling
algorithm increases the basecalling accuracy substantially far far above that of the fast basecalling
algorithm. When I first tried using the fast basecalling algorithm used by the Mk1C integrated
GPU the raw accuracy was roughly 88-89% which was atrocious and extremely hard to call SNPs
with reasonable confidence without extreme coverage. After super resolution basecalling the raw
single accuracy was around 96% and with 15x coverage the overall accuracy was increased to
99.6%. The dedicated GPU in this system was built and programmed by me specifically for rapid
super resolution basecalling. Updating any of the guppy basecalling algorithms may increase
accuracy in the future but you really need to make sure what you are doing before you endeavor
on this. The software is not optimized for windows and required a fair amount of coding within
windows for me to get it working.
98
Make sure that you turn on all functions for trimming automatically. After basecalling load
the Fastq files into Geneious and use Minimap2 in order to map the genome to the NCBI reference
genome. Then perform SNP analysis. I was never able to fully troubleshoot structural variant
calling and the best I could do was De novo genome alignment and look for structural variants.
Another good tool that many have used, but require substantial coding skills, is CuteSV
https://github.com/tjiangHIT/cuteSV

99

References

Dixon, K., Shen, Y., O’Neill, K., Mungall, K. L., Chan, S., Bilobram, S., ... & Jones, S. J. (2023).
Defining the heterogeneity of unbalanced structural variation underlying breast cancer
susceptibility by nanopore genome sequencing. European Journal of Human Genetics, 1-
5.
Lin, B., Hui, J., & Mao, H. (2021). Nanopore technology and its applications in gene sequencing.
Biosensors, 11(7), 214.
Lu, H., Giordano, F., & Ning, Z. (2016). Oxford Nanopore MinION sequencing and genome
assembly. Genomics, proteomics & bioinformatics, 14(5), 265-279.
Oxford Nanopore Technologies. (n.d.). Retrieved March 11, 2023, from https://nanoporetech.com/
Tusso, S., Nieuwenhuis, B. P., Sedlazeck, F. J., Davey, J. W., Jeffares, D. C., & Wolf, J. B. (2019).
Ancestral admixture is the main determinant of global biodiversity in fission yeast.
Molecular biology and evolution, 36(9), 1975-1989.

Abstract (if available)

Abstract Fragile sites across the genome pose an increased risk of instability. The rDNA repeats have an increased risk of instability due to being highly repetitive, replication transcription collisions, polar replication fork barriers, late S replication completion, and more. There are multiple ways to evaluate this instability. This research firstly summarizes a new way to evaluate genome instability through end binding protein Ku localization by live cell fluorescent imaging. Phase separation is one way cells maintain proper rDNA localization in the nucleolus and thus we evaluated the effects of the phase separation inhibitor 1,6-hexanediol on various aspects of cellular health and general genome stability including the rDNA. We found that 1,6-hexanediol decreases cell survival and increases genome instability generally but not specifically localized to either heterochromatin or rDNA domains. Lastly In this study we looked more specifically at the rDNA through the effects of an artificially contracted rDNA array, evaluating responses to alkylation damage in the rDNA, and genomic pathways that affect rDNA copy number maintenance. We find that a decreased rDNA array leads to a decreased growth rate, cell size, and increased genotoxic sensitivity to alkylation damage from MMS. In order to deal with this alkylation damage large rDNA arrays were also shown to contract over time in a time/concentration dependent manner. We also showed various pathways that affect rDNA copy number including the fork protection complex FPC, fork licensing, H3K56ac, and DDK. These results confirm that the rDNA repeats are a genome fragile site and that various pathways affect its level of instability and ability to deal with genotoxic stresses.

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Asset Metadata

Creator Jones, Chance Evan (author)

Core Title Maintenance of genome stability at fragile sites in Schizosaccharomyces pombe

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Molecular Biology

Degree Conferral Date 2023-05

Publication Date 04/14/2024

Defense Date 03/28/2023

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

Tag 1,6-hexanediol,fragile sites,genome stability,Ku,OAI-PMH Harvest,rDNA,schizosaccharomyces pombe

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Forsburg, Susan L. (committee chair), Boedicker, James (committee member), Chiolo, Irene (committee member), Michael, Matthew (committee member)

Creator Email chance.jones31@gmail.com,chancejo@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113015579

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