histone titration by dna sets the threshold for the mid‐blastulact021wp7863/amodeo thesis... ·...

HISTONE TITRATION BY DNA SETS THE THRESHOLD FOR THE MID‐BLASTULA

TRANSITION IN XENOPUS

A DISSERTATION

SUBMITTED TO THE DEPARTMENT OF BIOLOGY

AND THE COMMITTEE ON GRADUATE STUDIES

OF STANFORD UNIVERSITY

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS

FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

Amanda A. Amodeo

February 2013

This dissertation is online at: http://purl.stanford.edu/ct021wp7863

© 2014 by Amanda Anne Amodeo. All Rights Reserved.

Re-distributed by Stanford University under license with the author.

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http://purl.stanford.edu/ct021wp7863

I certify that I have read this dissertation and that, in my opinion, it is fully adequatein scope and quality as a dissertation for the degree of Doctor of Philosophy.

Jan Skotheim, Primary Adviser


Michael Simon


Timothy Stearns

Approved for the Stanford University Committee on Graduate Studies.

Patricia J. Gumport, Vice Provost for Graduate Education

This signature page was generated electronically upon submission of this dissertation in electronic format. An original signed hard copy of the signature page is on file inUniversity Archives.

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Abstract

During early development, animal embryos depend upon maternally deposited

RNA until zygotic genes become transcriptionally active. Prior to this maternal‐

to‐zygotic transition (MZT), many species execute rapid and synchronous cell

divisions without growth phases or cell cycle checkpoints. In Xenopus laevis

embryos, the MZT coincides with cell cycle lengthening, cellular motility onset,

and the addition of cell cycle checkpoints at a stage termed the mid‐blastula

transition (MBT). A long standing model is that the timing of the MBT is

controlled by a maternally loaded inhibitory factor that is titrated against the

exponentially increasing amount of DNA(Newport and Kirschner, 1982b). To

identify the inhibitory factor(s), we developed an assay using Xenopus egg extract

that recapitulates the activation of transcription only above the DNA‐to‐

cytoplasm ratio found in embryos at the MBT. We used this system to

biochemically purify the factor responsible for inhibiting transcription below the

threshold DNA‐to‐cytoplasm ratio. This unbiased approach identified histones H3

and H4 as inhibitory factors. Addition of exogenous H3/H4 tetramers to the

extract increased the threshold concentration of DNA required for transcriptional

activation. Non‐specific removal of endogenous histones reduced the threshold

DNA concentration required for transcription, and the addition of histone H3/H4

tetramers was sufficient to restore the threshold in depleted extracts. Finally,

reduction of H3 protein in embryos induced a premature MBT. Our observations

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support a model for MBT regulation by a maternally loaded titratable factor and

provide an identity for this long‐sought molecule. More broadly, our work

demonstrates how a constant concentration DNA binding molecule can be used

to measure the amount of cytoplasm per genome, a surrogate for cell size.

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Acknowledgments

This work would not have been possible without the intellectual contributions

and support of several communities of people. Foremost, I must thank my

advisors. As a joint student I have benefited from the mentorship of two very

talented and different faculty members at Stanford. Throughout my graduate

career Jan has supported and encouraged me to explore, even when I didn’t think

things would work. His unyielding optimism has spurred me to take risks and try

experiments that I never would have attempted without his encouragement.

Aaron too, has been a remarkable mentor. He welcomed me into his lab as a

visitor and allowed me to stay on as a true member of his lab. I would have never

predicted that my PhD would involve the biochemical purification of an unknown

factor, and I could never have done it with out them.

Along with two advisors came two wonderful sets of labmates and friends. Their

intellectual contributions and help in troubleshooting my experiments cannot be

overstated. Beyond that, their camaraderie made every day and adventure and

their support helped me though those weeks when nothing worked.

In addition to my labmates, I’ve also benefited from the support of my family and

a number of great friends? I’d particularly like to thank my father and brother

who still understand me better than anyone else even after all these years. Words

cannot express how grateful I am for all that you all have done for me.

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Contents

Abstract ................................................................................................................................ iv

Acknowledgments ............................................................................................................ vi

Contents .............................................................................................................................. vii

List of Tables ....................................................................................................................... ix

List of Figures ....................................................................................................................... x

Chapter I: Introduction to cell size control ............................................................... 1

1.1 Introduction: Cells maintain a characteristic cell size ............................................ 1

1.2 The relationship between growth and size control ................................................. 4

1.3 Many potential size‐sensing mechanisms ................................................................... 6

1.4 Cell size correlates with DNA content ........................................................................... 8

1.5 Titration of Cyclins in Budding Yeast .......................................................................... 13

1.6 Titration of DNA‐A in E. coli ............................................................................................ 14

1.7 Geometric size sensing in fission yeast ...................................................................... 17

1.8 The ease of generating titration based size sensors .............................................. 18

Chapter II: Titration and the mid‐blastula transition ......................................... 22

2.1 The maternal to zygotic transition (MZT) ................................................................. 22

2.2 The mid‐blastula transition and titration ................................................................. 24

2.3 Potential titrated factors at the MBT ........................................................................... 26

Chapter III: Histone titration times the MBT .......................................................... 29

3.1 Recreating the MBT in vitro ........................................................................................... 29

viii

3.2 Unbiased biochemical purification .............................................................................. 33

3.3 Effects of histones in extracts ........................................................................................ 36

3.4 Histone reduction and the MBT in vivo ...................................................................... 38

3.5 Supplemental material .................................................................................................... 40

Chapter IV: Methods ........................................................................................................ 51

Chapter V: Conclusions and future directions ........................................................ 58

5.1 Conclusions .......................................................................................................................... 58

6.2 Future directions ............................................................................................................... 62

References .......................................................................................................................... 68

ix

List of Tables

Table of mass spectrometry results ......................................................................... 48

x

List of Figures

Figure 1.1: Cell size verses organ and organism size ............................................. 3

Figure 1.2: Mechanisms for cell size measurement ............................................... 8

Figure 1.3: Endocytosis and cell size ........................................................................ 12

Figure 1.4: Titration mechanisms for cell size measurement in bacteria ... 16

Figure 3.1. in vitro transcription is sensitive to the DNA‐to‐cytoplasmic

ratio via a titratable transcriptional inhibitor ...................................................... 32

Figure 3.2. Isolation of histones H3 and H4 as the inhibitory activity .......... 34

Figure 3.3. H3/H4 tetramers set the threshold for transcriptional activation

in extract ............................................................................................................................ 37

Figure 3.4. Reduction of histone H3 causes premature initiation of the MBT

in vivo .................................................................................................................................. 39

Figure S1. DNA‐to‐cytoplasm ratio controls transcription ............................... 40

Figure S2. The major sperm chromatin transcript is a single stranded Pol III

product ............................................................................................................................... 41

Figure S3. Inhibitory activity can be removed from extract‐treated DNA ... 42

Figure S4. Intermediate gels during biochemical purification ........................ 43

xi

Figure S5. H3/H4 inhibits transcription ................................................................. 45

Figure S6. H3 morpholinos reduce H3 concentrations at the MBT ................ 46

Figure S7. H3 morphant embryos display early MBT in multiple

independent experiments ............................................................................................ 47

Figure 5.1: Mid‐blastula transition controlled by titration of regulators

against DNA ....................................................................................................................... 61

CHAPTER I: INTRODUCTION TO CELL SIZE CONTROL 1

Chapter I: Introduction to cell size control

1.1 Introduction: Cells maintain a characteristic cell size

Cells size varies greatly depending on cell type and species. Among the eukaryotic

cells, 1mm frog oocytes (Wallace et al., 1981), are 1000 times larger than 1

micron diameter phytoplankton, a billion‐fold difference in volume (Palenik et al.,

2007). Bacteria, such as Mycoplasma genitalium, can be as small as 200nm in

diameter (Zhao et al., 2008), while the largest prokaryote, Thiomargarita

namibiensis can be larger than 100 microns (Schulz et al., 1999). Even within an

organism, cells of different type may be of very different sizes. Human blood cells

are tiny (


In contrast to unicellular organisms, cells within multicellular organisms

experience much more constant environments. However, the function of these

cells still strongly depends on their size. For example, blood cells must maintain a

sufficiently small size to allow them to pass through capillaries and neurons must

span great distances in order to transduce singles down the lengths of limbs.

Furthermore, defects in cell size are associated with diseases such as Lhermitte‐

Duclos disease wherein increase in cerebellar granule cell size leads to seizures

and eventual death (Kwon et al., 2001).

In some multicellular organisms, cell size can influence organ and organism size.

This scaling is absolute in C. elegans, where the cell number is fixed and

perturbations to cell size result in proportional changes in organ and organism

size (Cook and Tyers, 2007; Watanabe et al., 2007). However, in a large number

of species, such as the tiger salamander, alterations to cell size can be

compensated for by changes in cell number to preserve organ size (Fankhauser,

1945) (Fig 1.1). In addition, forcing proliferation in the fly wing imaginal discs

alters cell size, but triggers sufficient apoptosis to maintain organ size (Neufeld et

al., 1998).

Due to functional constraints, cells are under pressure to maintain a

characteristic size for their given type. In order to accomplish this size

homeostasis, growth and division must be coupled. For example, yeast grown in

nutrient poor conditions adjust their cell cycle duration to accommodate for

slower growth so that cells divide at roughly similar sizes as in nutrient rich


environments (Di Talia et al., 2007; Di Talia et al., 2009). Yet, how size

homeostasis is maintained has remained elusive. Here, we review recent

advances and discuss a conceptual framework that potentially links a large class

of cell size questions.

Figure 1.1: Cell size verses organ and organism size. In multicellular organisms cell

size can interface with organ and organism size in one of two ways. a. If the

number of cells is fixed, changes in cell size will lead to changes in organ and


subsequently organism size, as in C. elegans. b. If organ size is regulated

independently of cell size, changes in cell size will be compensated by changes in

cell number resulting in a constant organ and organism size, as happens in

salamanders. A mix of both mechanisms is also possible where cell size affects

organ size, but is partially compensated for by changes in cell number.

1.2 The relationship between growth and size control

At its most fundamental, cell size control within a specified interval ensures that

larger cells grow proportionally less than smaller cells. Importantly, size control

does not have to completely compensate for initial cell size differences. Rather,

size control is a quantitative feature whose amount in an interval can be

measured (Di Talia et al., 2009; Sveiczer et al., 1996). For example, weak size

control might require multiple cell division cycles to return an initially aberrantly

large or small cell to the characteristic size, while strong size control could do this

in one cycle.

For some cell growth dynamics, cell size homeostasis can be maintained without

a cell size sensor. All that is required for size homeostasis is that smaller cells

grow proportionally more than larger cells in a cell cycle so that size variation is

reduced in the next generation. For example, in the case of a constant rate of

linear growth, the cells size , will increase at a constant rate so that .

Then, specifying the duration of the cell cycle determines the amount of growth €

V

!

dVdt

= C


so that, in proportion, smaller cells grow more than larger cells and the

population approaches a mean size without any specific size sensing mechanism

(Conlon and Raff, 2003). Thus, some cell growth dynamics do not require a cell

size measurement to maintain size homeostasis.

Other growth dynamics do necessitate a size measurement. One such example is

exponential growth, where the rate of growth is proportional to cell size:

. Here, a timer mechanism will not maintain size homeostasis because

cells born larger would grow proportionally during a specified period.

Fluctuations in division times will then result in a progressively wider size

distribution unless the cell employs a size sensing mechanism to limit cell cycle

duration in larger cells (Tyson and Hannsgen, 1985a; Tyson and Hannsgen,

1985b).

The importance of the dynamics of cell growth for size control has motivated

many studies (Mitchison, 2003). In the case of budding yeast, growth in an

unperturbed cell cycle is likely close to exponential as supported by both some

single cell analysis using fluorescence time‐lapse microscopy and microchannel

resonators, as well as classical bulk experiments using radioactive labeling (Di

Talia et al., 2007; Elliott and McLaughlin, 1978; Godin et al., 2010). However,

other groups have argued that G1 growth is closer to linear based on estimates of

cell volume using time‐lapse phase contrast microscopy (Ferrezuelo et al., 2012)

and that growth rates are altered by cell cycle phase (Goranov et al., 2009). For a

!

dVdt

= "V


more complete discussion of yeast size control and growth see Turner ’12.

Fission yeast growth is certainly less likely to be exponential as reviewed in

(Mitchison, 2003), and metazoan cells are almost certainly not (Kafri et al., 2013;

Son et al., 2012; Sung et al., 2013). The clear deviation from exponential growth

in mammalian and other cells does not imply that these cells do not employ a size

sensor. In cases where size sensors are not strictly necessary, they may still be

desirable to keep the cell within an optimal range of sizes for proliferation and

function. Thus, the only way to determine if cell size sensors are operating in a

given cell type is to determine the molecular mechanism.

1.3 Many potential size‐sensing mechanisms

Active regulation of cell cycle progression in response to cell size requires that

cells have a method to accurately measure their size. Cells might accomplish size

measurement though a geometric mechanism if there is little cell‐to‐cell variation

in their geometry. For example, a geometric mechanism seems unlikely in

amoeboid cells or in the microvilli containing cells of the small intestine, but are

much more plausible in rod like bacteria and fission yeast, which grow in a well‐

specified geometry along a single dimension. One potential method to measure

size using geometry would be to measure the ratio of surface area to volume

since for many geometries surface area will increase much less rapidly than

volume. A related possibility is that cells might sense other aspects of their

geometry such as cell length via intracellular gradients of cell cycle regulators


(Martin and Berthelot‐Grosjean, 2009; Moseley et al., 2009). In this case,

segregation of critical components to designated sub‐cellular locations would

allow the cell to assess the distance between these compartments as a proxy for

cell size.

In multicellular organisms, external landmarks such as tissue edges or junctions

with target cells could be used to constrain cell growth. For example, a neuron

might grow until it makes contact with its target (Guthrie, 2007). However, this

mechanism requires an external pattern to already be in place and cannot

generate size control de novo so we do not focus our attention on this mechanism

in this chapter.

Finally, cells could measure their volume directly by titration of a constant

concentration sensor against a fixed internal “yardstick”. This mechanism

requires that the production of the volume sensor must be proportional to cell

growth and that there be a fixed “yardstick” to measure, i.e., titrate against. Here,

we explore the relevance of titration mechanisms in several biological contexts

(Fig 1.2).


Figure 1.2: Mechanisms for cell size measurement. Cells can potentially sense their

size via a number of different mechanisms including: a. aspects of their cell

geometry such as surface area‐to‐volume or cell length via intracellular

gradients; b. extracellular landmarks; and (C) titration of a constant

concentration regulator, whose amount scales with cell size, against a fixed

“yardstick” to measure cell size.

1.4 Cell size correlates with DNA content

One of the earliest and most consistent observations about cell size is the

relationship between cell size and ploidy. In the early 1900’s, Theordor Boveri


produced sea urchin embryos in a range of ploidies by manipulating the

conditions of fertilization. Haploid embryos divided more than diploid embryos

and thereby maintained a consistent ratio of DNA to cytoplasm. In further

experiments he created triploid and tetraploid embryos through multiple

fertilizations. In these embryos, spindle abnormalities caused an uneven

distribution of chromosomes so that not all cells received integer multiples of the

genome. In all cases, however, Boveri observed that the number of divisions

within a given sector of the embryo compensated for the DNA content that sector

received in the first cleavage. By the pluteus larval stage, cells that had received

more DNA were proportionally larger than those that had received less, which

indicated that the relationship extended beyond a simple size scaling with ploidy.

(Wilson, 1926)

Moreover, the relationship between cell size and ploidy extends well beyond the

embryo. Viable adult salamanders can be created from haploid to pentaploid. In

all cases, the size of the cells within their tissues increased or decreased

correspondingly, though the total organism size remained relatively invariant

due to compensatory alterations to cell number (Fankhauser, 1945). This

relationship is true in unicellular eukaryotes as well. The cell size of budding

yeast correlates with ploidy from haploid to hexaploid (Mayer et al., 1992;

Mortimer, 1958).

Developmentally regulated changes in ploidy correlate with cell size in numerous

large cell types. Often, as in the case of fly salivary gland and the mammalian


trophoblast, cells increase their ploidy by undergoing rounds of

endoreduplication. In many cases, such as the wing scale cells in the moth,

Ephestia, the degree of endoreduplication correlates with cell size within a tissue

(Edgar and Orr‐Weaver, 2001) (Fig 1.3b). Similarly, as the land‐slug Limax grows

over its lifetime it increases the size of the neurons within its brain though

endoreduplication (Yamagishi et al., 2011). A very tight relationship has been

demonstrated between DNA content and cell size in the green algae Eudorina

(Tautvydas, 1976). The filamentous yeast, Ashbya, also contains many copies of

its genome within a single cytoplasm. In this case, individual nuclei appear be

carefully spaced within the growing cells in order to retain a relatively constant

ratio of DNA to cytoplasm (Anderson et al., 2013; Nair et al., 2010).

Endoreduplicative cell cycles increase ploidy by entering a relatively normal S‐

phase but then skipping cytokinesis resulting in a doubling of the DNA content

for each iteration. This process can be repeated a large number of times resulting

in very large ploidies (up to 24,000C in the case of some plant endosperms (Traas

et al., 1998)). Endoreduplicating cell cycles are not simply unregulated or

prolonged S‐phases. Instead, these cells go through a fairly normal G1 and S‐

phase in which the DNA is only replicated once. They then either proceed directly

from G2 into another G1‐like state (called an endocycle), or enter into mitosis but

abort before cytokinesis is completed and return to the G1‐like state (called an

endomitosis) (Zielke et al., 2013) (Fig 1.3a). In both cases, the activity of

conventional M‐phase regulators is absent or prematurely lost. However, G1/S


regulation in endoreduplicating cells appears to be broadly similar to what is

found in conventional mitotic cell cycles (Edgar and Orr‐Weaver, 2001). This

implies that if a mechanism to measure cell size relative to DNA content were

operable at the G1/S transition, it might also explain the ploidy‐size relationship

observed for endoreduplicated cell types.

We note that the relationship between DNA content and cell size is not only true

within single species, but seems to be constant across most eukaryotes with only

small variations between clades across 6 orders of magnitude. A similar

relationship between cell size and DNA content has also been observed in

prokaryotes, although the slope is not the same (Cavalier‐Smith, 2001; Gregory,

2000). However, this does not imply that the mechanism of size measurement is

identical in all clades, but rather that there exist selective pressures that maintain

a roughly linear relationship between DNA content and cell size across

eukaryotes.


Figure 1.3: Endocytosis and cell size. DNA content correlates with cell size in a

variety of organisms and contexts. a. Endoreduplicative cell cycles are similar to

mitotic cycles without cytokinesis. Endocycling cells proceed directly from a S/G2

like state to another G1, while endomitotic cells undergo a partial mitosis but

abort before cytokinesis. b. The wing scale cells of the moth Ephestia vary in


ploidy from 8 to 32N with higher ploidy cells being larger than lower ploidy cells

(modified from (Edgar and Orr‐Weaver, 2001)).

1.5 Titration of Cyclins in Budding Yeast

Cell size control can be most directly studied in unicellular rather than multi‐

cellular organisms because cell size is more easily measured and the number of

cell types limited. For this reason, the yeasts S. cerevisiae and S. Pombe have been

favorite models for the study of cell size regulation.

Budding yeast divide asymmetrically, and size control occurs in the smaller

daughter cells primarily in G1 (Di Talia et al., 2009). Smaller cells spend more

time in G1, but this size control is imperfect since variations in size are not

eliminated in a single cell cycle (Di Talia et al., 2007; Johnston, 1977). Progression

through G1 is initiated by the cyclin Cln3, which binds and activates CDK1 to

partially inactivate the transcriptional inhibitor Whi5 (Bertoli et al., 2013).

Inactivation of Whi5 relieves the inhibition the transcription factor SBF whose

target genes include the additional cyclins, Cln1 and Cln2. These two cyclins

complete inactivation of Whi5 via a positive feedback loop that drives further cell

cycle progression (Eser et al., 2011). Activation of this feedback loop ensures

irreversible commitment to cell cycle progression (Charvin et al., 2010; Doncic

and Skotheim, 2013; Skotheim et al., 2008). Interestingly, the levels of the

upstream rate‐limiting cyclin Cln3 oscillate only weakly within the cell cycle and


may be at constant concentration during early G1 (Tyers et al., 1993). Therefore,

Cln3 might be used to sense cell size via a titration mechanism.

Cln3 may be titrated against the genome itself, or specific binding sites.

Consistent with the later, cell size was shifted by a high‐copy plasmid containing

multiple SBF binding sites in a Cln3‐Whi5‐dependent manner (Wang et al., 2009).

In either case, Cln3‐Cdk complex, whose number is likely proportional to cell size,

would be titrated against a constant DNA yardstick. However, implications of

these Cln3‐titration conjectures remain largely untested.

1.6 Titration of DNA‐A in E. coli

Titration of regulatory molecules against a cellular component whose size is

invariant with growth has been proposed to regulate specific points of the

bacteria cell cycle (Chien et al., 2012). While any point in the cell cycle can

potentially be regulated via a size checkpoint, two specific points of control have

been identified through studies of E. coli and B. subtilis. Bacteria size control has

been reported to impact the onset of DNA replication and cell division. In both

cases, a titration mechanism has been suggested for the origin of size‐dependent

cell cycle progression signals (Chien et al., 2012; Donachie, 1968; Teather et al.,

1974).

To control replication, Donachie (Donachie, 1968) proposed that a constant

concentration activator would accumulate at the origins of replication. In this


model, a regulator whose number increases with cell size would titrate against

the fixed number of origins to yield a size‐dependent activating signal. Consistent

with this model, cell size at the onset of replication in E. coli was similar

regardless of birth size and growth rate. Even in the case of the fastest growing E.

coli, where mass doubling outpaces the duration of replication so that large cells

contain multiple copies of partial genomes, replication is triggered at a constant

size‐to‐origin ratio (Donachie, 1968).

The most likely candidate for Donachie’s titrated replication activator is DnaA,

which binds cooperatively to origins to promote loading of the replication

machinery (Kaguni, 2006). Consistent with the DnaA‐titration model, the size‐to‐

origin ratio at replication initiation is sensitive to DnaA expression levels

(Lobner‐Olesen et al., 1989). Furthermore, mutations affecting cell size at

division, but not cell growth rate, do not change DnaA concentration or the size at

which cells initiate replication. Mutations making cells twice as large lead to cells

containing twice the amount of DNA (Hill et al., 2012). Taken together, this

evidence suggests molecular titration as the most plausible mechanism for

coupling cell size to the onset of DNA replication in E. coli (Fig 1.4a).

In addition to coordinating S‐phase with cell size, E. coli may also coordinate cell

division with cell size (Chien et al., 2012). The accumulation of the constant

concentration regulator FtsZ at the cytokinetic ring could function as a titration

base cell size sensor (Chien et al., 2012; Teather et al., 1974). Since cell growth of

rod shaped bacteria maintains a constant width, the circumference at the midcell


is constant. Thus, titration of FtsZ against the midcell perimeter could yield a

size‐dependent signal to initiate cytokinesis (Fig 1.4b).

Figure 1.4: Titration mechanisms for cell size measurement in bacteria. a. ATPase

DnaA accumulates on origins of replication in a size dependent manner until a

critical threshold triggers replication. b. FtsZ accumulates at the site of

cytokinesis as the cell grows until a threshold triggering cytokinesis


1.7 Geometric size sensing in fission yeast

Similar to E. coli, fission yeast are rod‐shaped and grow by lengthening at a

constant width so that volume is proportional to length (Mitchison, 2003). It has

been proposed that fission yeast employ a spatial gradient of the mitotic inhibitor

Pom1 emanating from its poles to measure cell size geometrically via length

(Martin and Berthelot‐Grosjean, 2009; Moseley et al., 2009). In this model,

division ensues when the concentration of Pom1 dips below a critical

concentration at the midcell, which occurs at a specific cell length.

Pom1 regulates the mitotic trigger network centered on the competing kinase

and phosphatase pair Wee1 and Cdc25 that regulates Cdk activity. Pom1 inhibits

the Wee1‐inhibitory kinases Cdr1 and Cdr2, which localize to specific nodes at

the midcell (Deng and Moseley, 2013). As a cell grows, the gradient in Pom1 from

the poles ensures that its concentration at the midcell decreases, which could

allow Cdr1 and Cdr2 to inactivate Wee1 and thereby promote mitotic entry.

Perturbations of the Pom1 gradient result in both changes to the Cdr2

distribution and cell size (Bhatia et al., 2013; Hachet et al., 2011; Martin and

Berthelot‐Grosjean, 2009; Moseley et al., 2009).

However, several recent results have begun to cast doubt on the gradient model.

First, the length scale of the exponential Pom1 gradient (~1.5µm) appears to be

too short to accurately measure the length of a >10µm cell (Saunders et al.,

2012). Second, the gradient has a difficult time explaining why the DNA‐to‐

cytoplasm ratio is maintained in fission yeast cells of different ploidy and in


temperature sensitive cytokinesis mutants (Neumann and Nurse, 2007). Third, in

fission yeast mutants of different width, volume at mitosis was more variable

than area, suggesting a surface area‐based model (Pan and Chang in publication).

Finally, cell size control occurs, albeit a bit less effectively, in cells lacking

regulation of Cdk1 by Wee1 and Cdc25, indicating that the Pom1 pathway is not

the only size control mechanism (Coudreuse and Nurse, 2010; Wood and Nurse,

2013).

1.8 The ease of generating titration based size sensors

To link growth and proliferation, size sensing mechanisms regulate cell cycle

transitions, which are typically switch‐like and associated with threshold

ultrasensitive responses. Switch‐like transitions are used to ensure coordination

of downstream responses. For example, switch‐like increases in Cdk activity

ensure the coherent transcription of G1/S phase regulators, the all‐or‐none

replication of the genome during S phase, and the robust phosphorylation of

mitotic targets (Ferrell et al., 2009; Georgi et al., 2002; Koivomagi et al., 2011;

Skotheim et al., 2008; Yang et al., 2013b).

Under some conditions titration mechanisms can directly generate ultrasensitive

responses (Buchler and Louis, 2008). For example, titration with a high affinity

stoichiometric inhibitor can generate an ultrasensitive response curve. Consider

two proteins A and B that bind to form an inactive complex AB. The response can

be characterized as the amount of active A as a function of the total amount of A

given a fixed amount of B. For high affinity interactions with B, low amounts of A


will be fully inactivated by B. However, for increasing amounts of A, the inhibitor

B is eventually titrated out so that above a threshold the amount of active A

increases rapidly. In the case of DNA‐binding proteins, such as DnaA high affinity

decoy sites (Kitagawa et al., 1996) could serve the purpose of stoichiometric

inhibitors as these sites will be occupied before the relevant target site and

therefore titrate out the regulator to create an ultrasensitive response.

Although titration mechanisms can produce ultrasensitivity, they need not

generate the switch themselves. Graded upstream signals can be converted

downstream in order to produce a switch‐like response. For example, positive

feedback loops at the G1/S and G2/M transitions convert small changes in the

upstream kinase input signal to dramatic increases in downstream kinase activity

associated with the next cell cycle phase (Pomerening et al., 2003; Skotheim et al.,

2008). In case of budding yeast, a graded Cln3 signal is coupled via Whi5 to a

Cln1/2 positive feedback response in order to generate a sharp transition in Cdk

activity. Thus, downstream switches can generate threshold responses thereby

alleviating any such requirement on the upstream size‐dependent signal.

Whether ultrasensitive or not, titration‐based size sensors are relatively easy to

generate. All they require is one component that is produced proportionally to

cell size and another that is constant. Many proteins fit the profile for the titrated

molecule because the majority of proteins and RNAs are found at roughly

constant concentration during the cell division cycle. This is supported by the fact

that


et al., 1998; Whitfield et al., 2002). Furthermore, a genome wide analysis of GFP

tagged ORFs in budding yeast concluded that most of the variability in protein

abundance arose from variations in cell size (Newman et al., 2006). This is a

natural consequence of larger cells having more protein and that the proportions

of most protein species remain relatively constant during cell growth. Any one of

these “cell cycle independent” proteins could potentially be titrated against a

constant “yardstick” to yield a size sensor.

Constant “yardsticks” are much less common within growing cells because, much

like proteins, the majority of organelles scale with cell size. For example, nuclear

size is always 8‐10% of cell size in yeast mutants (Neumann and Nurse, 2007;

Zhao et al., 2008). In contrast, DNA is a promising candidate because its amount

is fixed for all segments of the cell cycle except S‐phase. Moreover, size scales

with DNA content in many experimental and endogenous contexts as discussed

above. Thus, most DNA binding proteins could potentially be employed as a size

sensor.

Cell size is one of the most basic and defining features of a given cell type, yet the

molecular mechanisms underlying its control have remained elusive. We are

excited by recent work revisiting this long‐standing problem. Here, this chapter

reviewed current understandings of size sensing mechanisms and highlighted the

potential of titration‐based mechanisms. However, because of the ease with

which size‐dependent signals might be generated by any constant concentration

DNA binding protein, we do not expect conservation of the specific regulatory


molecules. One important context in which titration‐based cell size sensors are

likely employed is a developmental transition known as the mid‐blastula

transition (MBT).

CHAPTER II: TITRATION AND THE MID‐BLASTULA TRANSITION 22

Chapter II: Titration and the mid‐blastula

transition

2.1 The maternal to zygotic transition (MZT) To successfully develop from a single fertilized cell into a functioning adult, cells

within a dividing embryo must shift from utilizing maternally contributed mRNAs

and proteins to expressing zygotically encoded genes, which is known as the

Maternal to Zygotic Transition (MZT). In most species, the MZT switch is abrupt

and involves large‐scale degradation of maternal RNAs in addition to activation

of zygotic transcription (Tadros and Lipshitz, 2009). The MZT occurs at different

stages of development in different species. In mammals, the transition occurs as

early as the two‐cell stage (Piko and Clegg, 1982). Drosophila undergo 14

syncytial nuclear divisions before the zygotic genome becomes active. Zebrafish

divide 10 times, while Xenopus divide 12 times prior to the MZT (Kane and

Kimmel, 1993; Newport and Kirschner, 1982a).

The MZT is the period when the embryo becomes dependent on zygotic genes.

Although several genes critical for later development have been shown to escape

global transcriptional repression prior to the MZT (Merrill et al., 1988; Skirkanich

et al., 2011; Yang et al., 2002), most are not (Heyn et al., 2014; Lecuyer et al.,


2007; Tan et al., 2013; Yang et al., 2013a). Moreover, many maternal transcripts

are degraded at the MZT and must be replaced by their zygotic counterparts. For

example, around 35% of all maternal transcripts are destabilized at the MZT in

Drosophila (De Renzis et al., 2007). Although maternal RNAs are deadenylated

throughout early development their destruction does not occur until the onset of

zygotic transcription in many organisms including Xenopus (Audic et al., 1997;

Bashirullah et al., 1999; Duval et al., 1990). In fish, the MZT‐controlled microRNA

mir‐430 marks its targets via their three prime UTRs for destruction (Giraldez et

al., 2006), while in flies, the MZT‐controlled protein Smaug destabilizes RNAs by

binding their three prime UTRs (Tadros et al.).

Several transcription factors are critical for zygotic genome activation. In

Drosophila, a class of pre‐ and early post‐MZT genes has been identified whose

promoters contain heptad repeats which bind the transcriptional regulators

Zelda, and Grainyhead (De Renzis et al., 2007; Harrison et al., 2010; Liang et al.,

2008). Zelda competes with Grainyhead to bind a conserved CAGGTAG cis‐

regulatory element in the promoters of numerous developmental genes.

Depletion of Zelda and overexpression of Grainyhead results in major

developmental defects due to a failure to express Zelda targets at the MZT

(Harrison et al., 2010; Liang et al., 2008). Zelda appears to work as a general

transcriptional regulator in combination with other transcription factors that

determine spatial and temporal expression (Kanodia et al., 2012; Pearson et al.,

2012 2012). Interestingly, Zelda binds its target enhancers several cycles before


transcription is initiated and its abundance is predictive of expression levels

during ZGA. This led to the suggestion that Zelda is a “pioneer transcription

factor” that marks early genes for activation (Harrison et al., 2011; Satija and

Bradley, 2012). The transcription factors Nanog, Pou5f1 (Oct4), and SoxB1 are

present on early genes in zebrafish and have been suggested to play a similar role

in vertebrates (Lee et al.; Leichsenring et al.).

However, while necessary, pioneer transcription factors cannot explain

important aspects of transcriptional activation such as the dependence of many

transcripts on the ratio of DNA to cytoplasm. Interestingly, in Drosophila two

classes of genes are activated at the MBT. One class is likely controlled by the

time after fertilization, while others are controlled by the DNA‐to‐cytoplasmic

ratio (Lu et al., 2009). These results indicate that multiple mechanisms and

pathways could contribute to the MZT in Drosophila.

2.2 The mid‐blastula transition and titration

In a large number of organisms, including flies, fish, and frogs, the MZT coincides

with a more general developmental transition known as the Mid‐Blastula

Transition (MBT) (Tadros and Lipshitz, 2009). The MBT is found in a number of

organisms with large, externally developing eggs. The MBT is characterized by a

transition from rapid synchronous cell divisions without transcription to

asynchronous cell cycles containing growth phases and zygotic transcription.


It is not currently known whether these processes are interdependent or

whether they are separately controlled. It has been suggested that the rapid cell

cycles of the early embryo prevent transcription because there is insufficient

time to initiate and elongate transcripts between each cell cycle without growth

phases (Howe et al., 1995; Kimelman et al., 1987; Newport et al., 1985).

Consistent with this hypothesis, substantial inhibition of transcription in Xenopus

embryos had no effect on cell cycle elongation at the MBT (Newport and

Kirschner, 1982a). However, early transcription at the MBT has been shown to be

important for G1 acquisition in Zebrafish embryos (Zamir et al., 1997). In

Drosophila, the number of syncytial divisions appears to be controlled by zygotic

transcripts including the Cdc25 regulator tribbles (Di Talia et al., 2013; Farrell

and O'Farrell, 2013; Farrell et al.; Sung et al., 2013). Thus, understanding how

changes in cell cycle timing, transcriptional activation and the acquisition of

motility are coordinately controlled at the MBT is an important unresolved

problem.

Several compelling experiments suggest that the ratio of DNA to cytoplasm

controls the MBT. Each round of DNA replication prior to the MBT doubles the

DNA concentration while the cytoplasmic volume remains constant due to the

lack of cell growth in the early embryo. Artificially altering the DNA content by

creating polyspermic embryos, injecting exogenous DNA, or initiating

development in haploid cells shifts the timing of the MBT as predicted by the


DNA‐to‐cytoplasm ratio (Newport and Kirschner, 1982a; Newport and Kirschner,

1982b). Perhaps the most convincing demonstration of the importance of the

DNA‐to‐cytoplasm ratio was performed by Newport and Kirschner (Newport and

Kirschner, 1982a). In this experiment, they constricted a newly fertilized embryo

to restrict the nucleus to one half of the embryo for 2 cell divisions and then

allowed a single nucleus from the nuclear side of the embryo to reenter the

anucleate side. The nucleated side of the embryo had undergone both nuclear

and cell divisions and thus contained cells with a much higher nuclear to

cytoplasmic ratio than the originally anucleate side. Significantly, the cells with

higher nuclear to cytoplasmic ratio underwent the MBT approximately 2 cycles

earlier than cells in the other half of the embryo, providing strong evidence that

the DNA‐to‐cytoplasm ratio is crucial to MBT timing. These experiments also

show that pre‐MBT embryos are capable of transcription but that transcription is

repressed. These observations have lead to the hypothesis that a repressive

factor present in the early embryo is titrated out by the DNA. However, a

definitive test of this model through the identification of the factors controlling

transcription has remained an outstanding question in developmental biology.

2.3 Potential titrated factors at the MBT

A molecular understanding of how transcriptional activation is governed by the

DNA‐to‐cytoplasmic ratio is essential for understanding the coordination

between cell cycle changes and transcription at the MBT. Several candidate


factors have been implicated as part of the transcriptional repressor activity in

the embryo. Chromatin components were first proposed as the potential

titratable factor(s) due to the observation that exogenous DNA is rapidly

incorporated into chromatin (Almouzni et al., 1990; Almouzni et al., 1991;

Newport and Kirschner, 1982b; Prioleau et al., 1994). Coinjection of histones

with exogenous DNA reduces the ability of that DNA to be transiently transcribed

in Xenopus embryos, but these experiments cannot differentiate whether histones

themselves are inhibiting transcription rather than simply facilitating the binding

of another factor (Almouzni and Wolffe, 1995). Another chromatin factor, the

DNA methyl transferase, xDnmt1 has also been proposed to regulate the MBT.

Knockdown of xDmnt1 has a modest effect on transcription onset and is only

expressed in one half of the embryo, indicating that it cannot be the sole factor

responsible for pre‐MZT transcriptional repression (Dunican et al., 2008;

Stancheva and Meehan, 2000).

More recently, two sets of factors have been implicated in S‐phase lengthening at

the Xenopus MBT. The first is the protein phosphatase 2 (PP2A) regulatory

subunit, B55α. PP2A is an important suppressor of ATR, which signals to inhibit

origin firing in response to replication stress. ATR slows S‐phase at high DNA

concentrations in vitro. This appears to be due to limiting quantities of PP2A at

high DNA concentrations as exogenous PP2A restores rapid S‐phases in vitro

(Murphy and Michael, 2013). However, it is unclear if PP2A is, in fact limiting in

vivo. Furthermore, the function of S‐phase checkpoints does not appear to


depend on transcription (Dasso and Newport, 1990) and there the regulation of

their acquisition and the other aspects of the MZT such as transcription may be

independent.

The other set of proposed S‐phase regulators are the replication factors Cut5,

RecQ4, Treslin, and Drf1. These factors become unstable at the MBT, and appear

to be limiting well below the DNA concentrations present at the MBT in vitro.

Greater than five fold overexpression of these four factors in combination is able

to induce one additional fast S‐phase in vivo (Collart et al., 2013). The fact that

these factors become unstable at the MBT suggests that they are likely

downstream of the titrated factor, though this remains to be tested.

Nearly three decades after Newport and Kirshner first proposed the titratable

factor hypothesis, its molecular underpinnings are still unclear. Although the

factors discussed above all have their merits, each was identified through a

specific candidate approach, and none has been conclusively shown to be titrated

at the MBT.

CHAPTER III: HISTONE TITRATION TIMES THE MBT 29

Chapter III: Histone titration times the

MBT

3.1 Recreating the MBT in vitro

To identify the mechanism by which embryos sense the DNA‐to‐cytoplasm ratio,

we developed a cell free system for Xenopus ZGA where we could directly

manipulate the ratio of DNA to cytoplasm. We added varying concentrations of

purified sperm chromatin into a constant volume of cytosolic extracts from

unfertilized Xenopus eggs and used 32P‐α‐UTP to measure RNA synthesis (Fig.

3.1b). The addition of sperm chromatin to the extract induced transcription

dependent on DNA concentration, as predicted by the titration model. Moreover,

the threshold DNA concentration required for transcriptional activation in

extract (~50 ng/µl) (Fig. 3.1c,d) was strikingly similar to the DNA concentration

present in embryos at ZGA (~48 ng/µl). We controlled for the effects of

increasing the number of sperm transcriptional template in the extract by

keeping the sperm number constant and varying the extract volume (Fig. S1). We

measured a similar threshold DNA‐to‐cytoplasmic ratio indicating that the

observed transcripts are responsive to this ratio and not among the small

number of genes known to escape repression prior to ZGA(Skirkanich et al.,

2011; Tan et al., 2013; Yang et al., 2002) The most abundant transcript we


observed off of the sperm chromatin (Fig. 3.1c) is approximately 180‐220

nucleotides, predominantly single stranded based on its ribonuclease sensitivity,

and likely a Pol III transcript based on its sensitivity to transcriptional inhibitors

(Fig. S2). This transcript is likely Sat I/OAX, a 181 nucleotide Pol III‐mediated

transcript activated at the MBT, and previously observed to be highly expressed

from sperm chromatin in Xenopus egg extract (Kimelman et al.; Wolffe, 1989).

Preliminary qPCR results suggest that this transcript increases more than a

thousand fold in transcribing compared to transcriptionally inhibited extracts

(data not shown).*

In order to determine if nonspecific DNA could induce transcription, as has been

observed in Xenopus embryos(Newport et al.), we added λ‐phage DNA to our cell

free system in the presence of low numbers of reporter sperm nuclei. We found

that λ‐DNA was sufficient to induce transcription from the sperm nuclei in a

dose‐dependent manner with a threshold similar to the sperm chromatin alone

(Fig. 3.1e). λ‐DNA alone was not transcribed likely due to a lack of suitable

Xenopus promoters (data not shown). These experiments indicate that titration of

the transcriptional inhibitory activity is not DNA sequence specific and does not

require the titrating DNA to be a template for transcription.

Because DNA binding proteins are likely candidates for a DNA titratable inhibitor

of transcription, we tested whether we could deplete the inhibitory activity from

extracts using DNA as an affinity reagent. To do this, we coupled non‐specific

* Sat I qPCR experiments preformed by David Jukam


plasmid DNA to magnetic beads and added these DNA‐beads to an extract so that

there was a 5‐fold excess of DNA above the threshold required for transcriptional

activation. We then removed the DNA‐beads and any associated factors and

measured the transcriptional response of sperm chromatin titrated into the

extract. We found that extracts depleted with DNA‐beads activated transcription

at lower concentrations of sperm DNA than mock depleted controls (Fig. 3.1f,g).

This is consistent with the removal of an inhibitory factor by the DNA‐beads.

To determine if factor removed from extract retained its activity, we moved DNA‐

beads from one extract to another and assayed for transcription (Fig. 3.1h). If

transfer occurred, DNA‐beads saturated with inhibitory activity from a first

extract would be unable to titrate out additional inhibitor in a second extract.

Since the bead‐associated DNA is not transcribed in extracts, we added small

quantities of sperm chromatin as a reporter for transcription. DNA‐beads

pretreated with extract were unable to induce transcription, consistent with a

transcriptional inhibitor binding to the DNA‐beads (Fig. 3.1i). Loss of titration

ability was not due to DNA degradation because DNA‐beads boiled after

incubation in the first extract regained their ability to titrate out the inhibitory

activity from the second extract (Fig. S3).


Figure 3.1. in vitro transcription is sensitive to the DNA‐to‐cytoplasmic ratio via a

titratable transcriptional inhibitor. a. A schematic of the titratable factor

hypothesis(Newport and Kirschner, 1982b). A maternally loaded inhibitor is

titrated against an exponentially increasing amount of DNA until a threshold is


reached to initiate zygotic transcription. b. Experimental design for (c), (d), and

(f): a constant volume of extract is titrated against variable quantities of sperm

chromatin. c. A representative autoradiograph of new transcription above a

threshold DNA concentration. Transcription in d, e, f and h was quantified using

the indicated boxed band. d. The mean transcriptional response to increasing

amounts of sperm chromatin. Transcription initiates above 50ng sperm DNA/µl

of extract. e. Titration of lambda‐DNA into egg extract activates transcription

from reporter sperm chromatin at a similar DNA concentration as in (d). f. and h.

Schematics of experiments corresponding to panels (g) and (i) respectively. DNA‐

beads are used to bind, deplete and transfer the inhibitory activity in egg extracts.

g. Extracts depleted of a transcriptional inhibitor with DNA coated beads (purple

curve) activate transcription at a lower sperm concentration than extracts

exposed to beads not coupled to DNA (green curve). i. DNA coated beads pre‐

incubated in an extract are unable to induce transcription in a naïve extract

(orange curve) compared to DNA‐beads pre‐incubated with buffer (green curve).

Transcription is measured from reporter sperm chromatin. All error bars

represent SEM.

3.2 Unbiased biochemical purification

To identify the transcriptional inhibitor, we biochemically fractionated the egg

extract and tested the activity of each fraction by adding DNA‐beads to each

fraction and assaying the DNA’s ability to induce transcription in naïve extract


(Fig. 3.2a, Methods, Fig. S4). Two fractions from the purification’s final

chromatographic step exhibited the bulk of the inhibitory activity and contained

4 protein bands as observed by silver staining. These bands were identified by

mass spectrometry as histones H3 and H4 (Fig. 3.2b; Supplemental table) with

the slower mobility bands containing ubiquitinated forms of H4.

The titration hypothesis predicts that the titratable factor should be present in

the embryo at a relatively constant concentration, but should be depleted from

the cytoplasm over the course of the cleavage divisions. To test this, we examined

the concentrations of H3 and H4 in whole embryos by western blot at time points

starting immediately after fertilization until approximately 4 hours post‐MBT.

The total embryo concentrations for both H3 and H4 do not increase over this

time period while the DNA concentration increases exponentially, suggesting that

cytoplasmic histone stores are likely being depleted during the MBT in vivo (Fig.

3.2c,d).


Figure 3.2. Isolation of histones H3 and H4 as the inhibitory activity. a. Top:

autoradiograph of the transcriptional inhibition activity of fractions from the

final size exclusion step of the purification. Fractions 8 and 9 show inhibitory

activity. Bottom: Silver‐stain gel of the proteins bound to the beads in each

fraction. b. and c. Histone H3 (c) and H4 (d) protein levels normalized to tubulin

levels throughout early embryonic development. For each time point, n=3; error

bars represent SEM.


3.3 Effects of histones in extracts

If histones H3/H4 are the inhibitory factors titrated during division, then

increasing histone concentration in the extract should increase the threshold

amount of DNA required for transcription. Adding bacterially produced H3/H4

increased the amount of DNA required to activate transcription in a dosage‐

dependent manner (Fig. 3.3a). We observed a linear trend over a 4‐fold

concentration range in the relationship between the amount of histone H3 in the

extract and the amount of DNA required to activate transcription (Fig. 3.3b).

H3/H4 addition also inhibited transcription from plasmid DNA (Fig. S5a) and

although H2A/H2B dimers could inhibit transcription they did so less efficiently

than H3/H4 (Fig. S5b). The bacterially purified histones we use are not post‐

translationally modified indicating that any histone modifying enzymes that

contribute to transcriptional inhibition in this assay must be present in

concentrations that are not rate limiting.

We tested whether depleting histones from the extract would reduce the amount

of DNA required for transcriptional activation. We removed histones using DNA‐

beads (histone immunodepletion is inefficient from egg extracts) and found that

transcription initiated at lower DNA concentrations (Fig. 3.1f; 3.3c). The specific

addition of purified H3/H4 tetramers to these depleted extracts restored the DNA

threshold to mock‐depleted levels (Fig. 3.3c, d), strongly supporting histones as

the titrated inhibitory molecule.


Figure 3.3. H3/H4 tetramers set the threshold for transcriptional activation in

extract. a. Increasing the levels of histone H3 and H4 in egg extracts increases the

concentration of sperm chromatin required to induce transcription. b. The

concentration of DNA required for transcription activation scales roughly linearly

with histone concentration for both sperm chromatin (blue circles) and λ‐phage

DNA (red diamonds). Each point represents a titration as depicted in (a). Points

above dashed line had thresholds beyond the detection limit. c. Depletion of

histone H3/H4 with DNA‐beads reduces the amount of DNA required to activate


transcription (purple curve) compared to the control (green curve), and adding

back H3 and H4 restores the transcriptional response (blue curve). d.

Relationship between histone concentration and amount of DNA required for

transcriptional activation as described in (b) for add‐back experiments depicted

in (c). Histone H3 concentrations were quantified by Western blot.

3.4 Histone reduction and the MBT in vivo

We tested whether reducing histone H3 levels in embryos altered the timing of

the MBT in vivo using morpholinos(Szenker et al.). Histone H3 reduction by 40‐

56% at 7.5 hours post fertilization (Fig. S6) caused premature initiation of the

MBT. Both cell cycle period lengthening and cell cycle asynchrony begin earlier,

resulting in larger cells (Fig. 3.4a,c; Fig. S7)†. Despite initiating one cell cycle

earlier, H3 morphant embryos displayed otherwise normal cell cycle lengthening

across the MBT (Fig 3.4d and S7). Ultimately, most H3 morphants died during

gastrulation as previously reported(Szenker et al.) (89/92 morphant vs 3/31

control embryos; Fig. 3.4b).

† Data quantified by David Jukam


Figure 3.4. Reduction of histone H3 causes premature initiation of the MBT in vivo.

a. H3 morphant embryos appear normal until the MBT when they display

increased cell cycle lengthening and larger cells compared to controls. The

location of the zoomed panels is marked by the black box. b. H3 morphant

embryos die at gastrulation. c. The cumulative effect of longer cell cycles results

in larger cells and therefore lower cell density in the H3 morphant embryos (H3

MO) compared to control injected embryos (Control). Data shown for 215

minutes after the 9th division (n=3 embryos) d. H3 morphant embryos display


early cell cycle lengthening compared to control embryos. The mean and cell

cycle duration increases one cell cycle early in H3 morphant embryos compared

to control morpholino. Circles represent embryos that did not reach a 15th

division before the movie limit. All data shown for >15 cells per embryo, with 3

control embryos and 4 H3 morphant embryos from the same clutch. The box

height represents 25th to 75th percentile, and the centerline represents the

median. The whiskers extend to the furthest data point that is not an outlier.

Asterisks (*) represent p‐values less than 10‐4 Outliers are plotted as diamonds.

Results from two similar experiments are shown in Figure S7.

3.5 Supplemental material

Figure S1. DNA‐to‐cytoplasm ratio controls transcription. Extract volume was

varied (as labeled on top x‐axis) while the quantity of sperm chromatin was kept


constant (1µg per sample), resulting in indicated ratios of DNA to cytoplasm

without varying the quantity of template. Reactions containing less extract

resulted in greater total transcription.

Figure S2. The major sperm chromatin transcript is a single stranded Pol III product.

Concentrations of α‐amanitin or actinomycin D as indicated were added during

the transcription reaction. The low sensitivity of our product to both inhibitors

indicates that it is likely a Pol III transcript. The purified RNA was incubated with

DNase, inactive RNase H‐D10A, RNase H, RNase III, or RNase A and showed the

greatest sensitivity to RNase A indicating that the product is likely single

stranded, and comparisons with non‐radiolabeled RNA ladder suggest it is a

transcript between 180‐220 nt long.


Figure S3. Inhibitory activity can be removed from extract‐treated DNA. DNA‐beads

were exposed to crude extract and then boiled or left on ice. DNA‐beads that had

been boiled regained their ability to titrate out factor in a fresh extract indicating

that boiling removed the inhibitory factor.


Figure S4. Intermediate gels during biochemical purification. a. Titration of DNA

beads treated with buffer, crude extract, or high speed extract shows that both


crude and high‐speed extract are able to inhibit the ability of beads to induce

transcription in a fresh extract. b. Flow through and elute of dilute high speed

extract from Q‐ and S‐columns bound in 20mM KCl and eluted with 1M KCl

indicates that under these conditions the inhibitory factor binds the S‐column but

not the Q‐column. c. Flow through from Q‐column in 20mM KCl directly bound by

S‐column. Fractions result from an 8‐fraction linear gradient from 20mM to 1M

KCl elution and the same Q‐column eluted with 1M KCl. These results indicate

that the inhibitory factor does not come off the S‐column until high KCl

concentrations and does not bind the Q‐column. d. Similar to (c), flow through

from Q‐column in 20mM KCl directly bound by S‐column and was then washed

with 400mM KCl. Fractions result from an 8‐fraction linear gradient from 400mM

to 1M KCl elution. The fractions marked with an asterisk were collected, pooled,

concentrated, and run over a gel filtration column as in (f). e. Schematic of the

final resulting biochemical purification used to isolate the inhibitory factor. f. The

final output of the total purification protocol resulting from running fractions

prepared as in (d) over a gel filtration column.


Figure S5. H3/H4 inhibits transcription. a. H3/H4 tetramers are able to inhibit

transcription from Xenopus U6 plasmid DNA indicating that the observed effect is


not specific to sperm DNA. b. H2A/H2B dimers were also able to inhibit

transcription, but not as efficiently as H3/H4 tetramers.

Figure S6. H3 Morpholinos reduce H3 concentrations at the MBT. Dilution series of

control injected and H3 morphant embryos for the three experiments shown in

Fig. S7. Embryos produced 56, 41, and 40% reduction in H3 normalized to

tubulin loading controls compared to control injected embryos respectively.


Figure S7. H3 Morphant embryos display early MBT in multiple independent

experiments. Three independent clutches with 2‐3 control embryos and 3‐4 H3

morphant embryos. A minimum of 15 cells were counted from each embryo. All

experiments show an early cell cycle lengthening in the morphant embryos as

compared to controls from the same clutch. Experiment 1 is also displayed in Fig.

3.4.


Band Protein ID Type Number of hits

1 H4_XENLA H4 14

1 H32_XENLA H3 6

1 H2B11_XENLA H2B 3

1 H33_XENLA H3 3

1 H2AV_XENLA H2A 2

1 A2BDA0_XENLA H4 2

1 H2AZL_XENLA H2A 1

1 H2A1_XENLA H2A 1

2 H32_XENLA H3 16

2 H4_XENLA H4 12

2 H2B11_XENLA H2B 7

2 CENPA_XENLA H3 5

2 Q6PH89_XENLA H2A 3

2 H33_XENLA H3 3

2 UBIQP_XENLA Ubiquitin 3

2 Q6DKE3_XENLA H2A 2

2 H2A1_XENLA H2A 2

2 A2BDA0_XENLA H4 1

2 Q3KQC9_XENLA Ribosomal 1

3 H4_XENLA H4 11

3 1433T_XENLA 12‐3‐3 theta 4

3 Q7T0R9_XENLA Ribonuclear 4



3 H32_XENLA H3 3

3 RAN_XENLA Ran GTPase 3

3 RS8_XENLA Ribosomal 3

3 H33_XENLA H3 2

3 RL10A_XENLA Ribosomal 2

3 A2BDA0_XENLA H4 1

3 PSA7A_XENLA Proteasome subunit 1

3 Q6AZR7_XENLA Proteasome subunit 1

3 Q8AVT2_XENLA Ribonuclear 1

4 H4_XENLA H4 10

4 Q7T0R9_XENLA Ribonuclear 5

4 H32_XENLA H3 3


4 EF1B_XENLA Elongation fact (translation) 1

4 A2BDA0_XENLA H4 1

4 Q68A88_XENLA Proteasome subunit 1

Table of mass spectrometry results: Total results from mass spectrometry of

bands shown in Fig. 3b, including the number of unique reads identified for each

protein.

CHAPTER IV: METHODS 51

Chapter IV: Methods

Transcription assay: 32P‐α‐UTP was added to interphase extracts or without

DNA and bacterially purified histones as indicated. RNAs were extracted using

either Qiagen RNAeasy kits or Tripure (Roche). RNA samples were run on a 5%

acrylamide, 8M urea gel and exposed to a phosphor screen overnight. Pixel

intensity within the band denoted in Fig. 3.1c was quantified after background

subtraction using ImageJ (NIH). Background subtraction was preformed using an

identical region below the end of the same lane. All titration series were

normalized to a reaction lacking DNA. The threshold for transcriptional

activation was defined as the first point 1.5 fold above the no DNA sample.

H3 Morpholinos: H3 (which target both H3.2 and H3.3) and control morpholinos

(previously described(Szenker et al.)) were injected four times distributed

equally around the animal cap with ~5nl of 1mM morpholino per injection.

Measurement of histone levels: Equal protein concentrations were separated

by SDS‐PAGE and transferred to polyvinylidenefluoride membrane in CAPS

transfer buffer. Membranes were incubated in rabbit anti‐H3 (1:1000; Millipore:

04‐928), 2 μg/ml rabbit anti‐H4 (Abcam: ab7311), or 0.25 μg/ml mouse anti‐

tubulin (Sigma‐Aldrich: T9026), washed and then incubated for a minimum of

one hour in Alexa Fluor 488– or Alexa Fluor 647–conjugated goat anti–rabbit or


anti–mouse antibodies (1:2,500; Invitrogen). Fluorescence was quantified in

Image J. Histone concentrations were normalized to tubulin loading controls.

Xenopus egg extract and sperm chromatin: Preparation of extracts was

performed as previously described(Desai et al., 1999). 750µM CaCl2 was added

to release the extracts into interphase. To monitor new transcription, 50nl/µl of

10mCi/ml or 12.5nl/µl of 40mCi/ml 32P‐α‐UTP (Perkin Elmer BLU507H or

BLU507Z) was added to each extract. Clarified extracts were prepared as in

ref.(Desai et al., 1997). Briefly, crude extracts not containing 32P‐α‐UTP or CaCl2

were spun for a second time at 50,000RPM in a Beckman SW55Ti rotor for 2

hours at 4°C. The clear middle layer was extracted using a 22g needle.

DNA immobilization: pBluescript DNA was cut using EcoRI and BamHI (New

England Biolabs) and end filled using klenow (NEB) and biotin‐dATP

(Invitrogen). DNA was coupled to streptavadin dynabeads (Invitrogen: Cat#

65305) following the protocol outlined in (Hannak and Heald, 2006). For factor

and histone depletion assays, ~250ng/µl DNA on beads was incubated in

interphase extract at 4°C for 1‐2 hours and then removed. In assays that transfer

the factor(s) from one extract or fraction to another, DNA‐beads were first

incubated in an excess of extract or fraction for 1‐2 hours, and then added to a

fresh extract at ~50ng/µl.

Transcription assay: Interphase extracts containing 32P‐α‐UTP were prepared

as described above and distributed into 20µl aliquots with or without DNA and


bacterially purified histones as indicated. Histones were purified as previously

described (Guse et al., 2012; Luger et al., 1997). In cases where sperm chrom

histone titration by dna sets the threshold for the mid‐blastulact021wp7863/amodeo thesis... ·...

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