Coordination of cellular force-generation during
Drosophila ventral furrow formation
by
Shicong Xie
B.A., Physics & Applied Mathematics,
University of California, Berkeley (2010)
Submitted to the Program in Computational & Systems Biology
in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
February 2016
Massachusetts Institute of Technology 2016. All rights reserved.
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Program in Computational & Systems Biology
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Adam C. Martin
Assistant Professor
Thesis Supervisor
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Christopher Burge
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Coordination of cellular force-generation during Drosophila
ventral furrow formation
by
Shicong Xie
Submitted to the Program in Computational & Systems Biology on December 4, 2015, in partial fulfillment of the
requirements for the degree of Doctor of Philosophy
Abstract
Spatiotemporally coordinated cell behavior is observed during morphogenesis, in both embryonic development as well as tissue regeneration. An open question is how individual cells collectively generate force to achieve the correct tissue architecture. This thesis examines how the apical forces generated by Drosophila ventral furrow cells undergoing collective apical constriction are coordinated to fold the tissue.
In Chapter 2, I investigate how discrete actomyosin contraction events are coor-dinated in time and between neighboring cells to yield tissue contraction and folding. I developed a computational pipeline to identify and classify contraction events from live images of ventral furrow formation. Using this framework, I found heterogeneity in contraction events, both in terms of contraction intensity as well as apical area behavior. I found that apical constricting cells transition in contractile behavior over time, from undergoing reversible contractions into a ratcheted state where contrac-tions are irreversible. High expression of the transcription factor Twist is required for the transition into this irreversible, ratcheted state, which is associated with more neighboring contractions as well as cooperative interactions between neighbors.
In Chapter 3, I examined how contractility is buffered against heterogeneity in cell apical area. I found that Cta-signaling is required to robustly maintain apical F-actin cortex that can support contrF-acting over larger apical distances. Without this buffering, apically larger cells progressively lose apical F-actin and exhibit delayed initiation of actomyosin contractions, leading to a lack of coordinated constriction.
Thesis Supervisor: Adam C. Martin Title: Assistant Professor
Acknowledgments
I would like to thank my advisor Adam Martin for his wonderful mentorship during my graduate studies. Without his deep knowledge and ceaseless excitement this thesis would not have been possible. I also thank all the members of the Martin lab, whose energy, intellect, and companionship I will always treasure. A special thank goes to Frank M. Mason for being an amazing collaborator, and for all his insightful suggestions stemming from our countless scientific discussions. I thank Doug Lauffenburger and Hazel Sive who served on my thesis committee for their invaluable guidance. Furthermore, I thank the brilliant people I have met in the MIT community, from my fellow CSB graduates to my housemates from pika and beyond, whose warmth and vibrance welcomed me to MIT from day one.
Lastly, I thank my partner William Mallard for always being there for me (and the cats), and my parents who have always loved, encouraged, and supported me.
Contents
1 Introduction 1
1.1 Force generation in cells . . . . 1
1.1.1 The actin cytoskeleton . . . . 2
1.1.2 Epithelia and cell-cell adhesion . . . . 6
1.2 Tissue morphogenesis . . . . 7
1.2.1 Epithelial folding . . . . 8
1.2.2 Actomyosin contractions in morphogenesis . . . . 10
1.3 Collective cell behavior . . . . 11
1.4 Chapter 2: Coordinating pulsed contraction events . . . . 13
1.5 Chapter 3: Cta signaling buffers contractility against cell heterogeneity 13 2 Intracellular signalling and intercellular coupling coordinate hetero-geneous contractile events to facilitate tissue folding 17 2.1 Introduction . . . . 18
2.2 R esults . . . . 19
2.2.1 Computational identification of contractile events . . . . 19
2.2.2 Three distinct classes of pulses during tissue invagination . . . 20
2.2.3 Ratcheted constrictions have higher myosin persistence . . . . 23
2.2.4 Ventral furrow cells constrict as a single population . . . . 25
2.2.5 Cells transition from unratcheted to ratcheted pulses . . . . . 27
2.2.6 Twist expression promotes biased transitions in pulse class . . 27
2.2.7 Twi promotes increased levels of stable medioapical Rok . . . 29 2.2.8 Ratcheting prevents competition between neighboring pulses . 31
2.2.9 Ratcheted pulses are enriched in neighboring contractions . 2.3 D iscussion . . . . 2.4 M ethods . . . .
2.4.1 Embryo preparation and imaging . . . . 2.4.2 Image and data analysis . . . . 2.4.3 Statistical analysis and testing . . . .
c)A A T- - -Q, _ _ 4 - -
-2.4.4 .Jensen-ShannoIivergenc . . . . . . . . . . . . .
2.4.5 Spatiotemporal pair correlation function (stPCF) 2.4.6 Pulse spatial randomization . . . . 2.5 Supplemental Figures and Tables . . . .
3 GPCR-signaling buffers apical constriction against cell ity during epithelial folding.
3.1 Introduction . . . . 3.2 R esults . . . . 3.2.1 Initial apical area predicts constriction behavior in
. . . . 41 . . . . 41 . . . . 42 . . . . 47 A 17 . . . . 48 . . . . 49 . . . . 51 heterogene-cta cells
3.2.2 Contractile pulse initiation is delayed in expanding cells. . . . 3.2.3 Aberrant nuclear position does not explain divergent cell be-havior in cta mutants. . . . . 3.2.4 Cta is required for maintaining apical F-actin in larger cells. . 3.3 D iscussion . . . . 3.4 M ethods . . . . 3.4.1 Embryo preparation and imaging . . . . 3.4.2 Image processing and data analysis . . . . 3.4.3 Statistics . . . . 3.5 Supplemental Information . . . .
4 Conclusion and outlook
4.1 Sum m ary . . . . 4.2 Future experiments . . . . 4.2.1 Mechano-chemical coupling between contracting cells . . . . .
61 62 64 64 65 68 71 73 79 79 81 82 83 87 87 88 88 33 37
4.2.2 Molecular mechanism of Cta-signaling . . . . 92
4.2.3 Improvement of the pulse-detection framework . . . . 94
4.3 Concluding remarks . . . . 95
A Vertex model and implementation details 97 A.1 Vertex model . . . . 97
A.1.1 Energy function . . . . 97
A.1.2 Equation of motion . . . . 99
A.1.3 Numerical solution . . . . 101
A.1.4 Data structures . . . . 102
A.1.5 Simulating the ventral furrow . . . . 102
A.2 Notes on pulse detection framework . . . . 104
A.2.1 Work flow . . . .. 104
List of Figures
1-1 The actin cytoskeleton. . . . . 3
1-2 Myosin II motor protein. . . . . 5
1-3 Cell-cell adhesion in an epithelium. . . . . 7
1-4 Epithelial folding. . . . . 8
1-5 Drosophila ventral furrow formation. . . . . 9
1-6 The Twist pathway during ventral furrow formation. . . . . 10
1-7 Actomyosin contraction driving apical constriction in Drosophila ven-tral furrow . . . . . 12
1-8 cta is required for coordinated apical constriction. . . . . 14
2-1 Image segmentation and pulse identification pipeline. . . . . 21
2-2 Pulse classification. . . . . 22
2-3 Ratcheting of contractile pulses correlates with persistent myosin struc-tures... ... 24
2-4 Ventral furrow cells initiate contraction as a single population. . . . . 26
2-5 Dynamic transitions in pulse behavior in wild-type embryos. . . . . . 28
2-6 Dynamic transitions in pulse behavior in wild-type embryos. . . . . . 30
2-7 Twi expression promotes the medioapical stabilization of Rok. . . . . 31
2-8 Ratcheting prevents mechanical competition between neighboring cells. 34 2-9 Ratcheting of contractile pulses correlates with enrichment in neigh-boring pulses. . . . . 35
2-10 Model for collective apical constriction. . . . . 39
2-12 Manual curation of computationally fitted myosin pulses. . . . . 52
2-12 Continued . . . . 53
2-13 Pulses exhibit heterogeneous behaviors that can be categorized to three classes: ratcheted, unratcheted, and unconstricting. . . . . 54
2-14 Principal component analysis of area responses to pulses from wild-type and twi-RNAi embryos supports the use of three clusters. . . . . 55
2-15 Pulses identified from twi-RNAi cells. . . . . 56
2-16 Tissue-level temporal dynamics. . . . . 57
2-17 Pulsing dynamics in control injected and twi-RNAi tissues. . . . . 58
2-18 Interactions between neighbouring contractions. . . . . 59
2-19 Spatial analysis of pulsing. . . . . 60
3-1 Schematic of Fog/Cta pathway. . . . . 63
3-2 Divergent area behavior in cta mutants is predicated by initial apical area. ... ... 66
3-3 Initiation of contraction differentiates constricting and expanding cta cells. . . . . 67
3-4 Delayed initiation of contractility is sufficient for area behavior hetero-geneity in silico. . . . . 69
3-5 Nuclear position does not explain divergent cta cell behavior. . . . . . 71
3-6 Nuclear position does not explain disruption to apical pulsing. . . . . 72
3-7 Large initial cell area leads to cortical fragmentation in the absence of C ta. . . . . 74
3-8 Model of Cta-dependent coordination of apical constriction. . . . . . 76
3-9 Area and myosin dynamics in wild-type and cta embryos. . . . . 83
3-10 Pulsing dynamics in cta cells. . . . . 84
3-11 Apical-basal nuclear position in cta and char-RNAi embryos. . . . . . 85
A-1 Schematic of the vertex model. . . . . 98
A-2 Gradient of cell area A, at vertex vi. . . . . 100
A-4 Gradient of interface length li. . . . . 101 A-5 Work flow for detecting myosin pulses from a ventral furrow movie. . 105
List of Tables
2.1 Ratcheted pulses do not compete with neighboring pulses. . . . . 33 2.2 Central pulse timing does not affect analysis of competition. . . . . . 53
Chapter 1
Introduction
Tissues in multicellular organisms need to be sculpted into precise shapes for their proper function. During morphogenesis, tissues acquire their shape through the ap-plication of mechanical force, often generated by a tissue's constituent cells, that changes tissue architecture by deforming individual cell shapes or rearranging inter-cellular connections [1]. Live-imaging of whole tissues has suggested that in vivo force-generation during morphogenesis is spatially organized and temporally dynamic, and an important unanswered question is how local forces generated by cells are co-ordinated across a tissue to achieve the global reconfiguration.
1.1
Force generation in cells
Force generation is a fundamental aspect of life, spanning the nanometer-scale move-ments of individual proteins to the meter-scale movemove-ments of a human muscle. I will focus on the mechanical force generated to achieve cell shape change. A variety of cellular structures and organelles contribute to cellular mechanical force genera-tion. Cytoskeletal networks govern the shape of animal cells; motor proteins actively generate internal force; adhesion molecules mechanically connect the cell to its sur-roundings. The interplay between these three components gives rise to cell motility and shape changes. Additionally, complex signaling systems integrate mechanical, chemical, and genetic information to modulate and regulate these components and
their interactions. In most eukaryotes, there are three cytoskeletal networks: actin, microtubule, and intermediate filaments [2]. The actin cytoskeleton and its associated proteins are the major contributors to cell shape and cell motion.
1.1.1
The actin cytoskeleton
The building block of the actin cytoskeleton is the small globular protein actin (G-actin), which is capable of polymerizing into filaments (F-actin) (Figure 1-1a). In a cell, the actin cytoskeleton consists of networks of F-actin, motor proteins which can bind and remodel these networks, and regulatory proteins which control the network geometry, topology, and mechanical properties [2]. A major structure formed by the actin cytoskeletal system is the actin cortex, a meshwork of crosslinked F-actin that underlies the plasma membrane of eukaryotic cells. The actin cortex is responsible for conferring shape and generating the movement of cells (Figure 1-1b).
Actin filaments are polarized, each with a plus-end and a minus-end (Figure 1-1a). Actin regulators-such as nucleating, severing, and capping proteins-control the location, polarity, and length of filaments, while crosslinking and bundling pro-teins change the interconnectivity across different filaments (Figure 1-1c-e) [3].
There are two main types of nucleating factors, the ARP2/3 complex which nucleates branched filaments, and formin family proteins which nucleate unbranched filaments and catalyze elongation. The nucleation of actin filaments is the rate-limiting step to actin polymerization and nucleation controls the location of F-actin in vivo [4]. Cells expend energy to maintain filament turnover at a much faster rate than observed in
vitro in the absence of regulatory proteins, allowing them to remodel their entire actin
cytoskeleton in as quickly as a few minutes and thus respond quickly to changes in their environment [3]. This constant turnover of actin monomers ensures that the cor-tex is viscoelastic, behaving like an elastic spring under short time-scale perturbations
G-actin
Asser,
F-actin D
Formin ARP2/3 complex
Assembly
d
Cofilin
*
e
n-natininDisassembly
Figure 1-1: Structure of the actin cytoskeleton. a. Monomeric G-actin poly-merizes into F-actin, which is polarized. b. Scanning electron micrograph of the actin cortex in a bleb from a M2 cell. Image from Bovellan et al (2014) [ ]. c. Actin nucleation factors promote F-actin formation. Formin polymerizes unbranched actin filaments while the ARP2/3 complex polymerizes branched F-actin from exist-ing filaments. d. Actin depolymerization factors (e.g. cofilin) can destabilize F-actin to promote disassembly. e. Crosslinkers can bind multiple filaments and promote trans-filament linkage.
C
b
a
Myosin motors
An important class of actin interacting proteins is the myosin motor protein, which utilizes ATP hydrolysis to drive energy-dependent translocation and remodeling of actin filaments [21. In this work I will focus on non-muscle type II myosin (myosin), which is an important driver of many morphogenetic processes [1].
Myosin also polymerizes into higher-order structures. The monomeric unit of myosin is a hexamer, consisting of two heavy chains (MHC), two essential light chains, and two regulatory light chains (Figure 1-2a) [7]. The MHC has a motor domain head and a long coiled-coil tail. The head domain binds F-actin and hydrolyzes ATP to translocate along F-actin towards its plus-end, moving 5nm and exerting a few pN per cycle [8] (Figure 1-2b). The coiled-coil tail domain facilitates the assembly of monomeric myosin into myosin minifilaments, composed of 10 - 50 monomers arranged in a bipolar fashion such that the MHC head domains are exposed on both ends (Figure 1-2c) [9]. The exposed heads of the bipolar minifilament can bind to multiple actin filaments and crosslink them. Moreover, if the F-actin filaments are arranged in an antiparallel manner, the collective motor activity of the actin-bound minifilament heads can result in an overall contraction force on the F-actin filaments [2] (Figure 1-2d).
Regulators of actin and myosin
The main signaling network that controls the spatiotemporal dynamics of the actin cytoskeleton is the Rho-family small G-protein system. G-proteins are GTPases that act as switches, existing between a GDP-bound "off" state and a GTP-bound "on" state. They require a guanine nucleotide exchange factor (GEF) to transition from the GDP-bound state to the GTP-bound state, and a GTPase-activating protein (GAP) to activate their intrinsic GTP-hydrolysis [2]. In their active, GTP-bound state, Rho G-proteins can bind and activate downstream effectors, the most well-studied of which control the actin cytoskeleton.
a
b P werroke C Hydro lysi +4 d ++Figure 1-2: Myosin II motor protein. a. The myosin II monomer is composed of 6 subunits: 2 heavy chains, 2 essential light chains, and 2 regulatory light chains. b. The ATPase motor cycle of myosin. ATP binding and ATP hydrolysis lead to a plus-end (red to cyan in schematic) directed translocation of the myosin heavy chain motor head. The powerstroke associated with ADP release returns the motor head into the original conformation, generating mechanical force. c. The myosin monomer can assemble into bipolar minifilaments. d. Myosin minifilaments can bind two antiparallel actin filaments. The collective motor activity of the individual bound heads leads to a contraction force (arrows).
Heavy chain Monomer
Regulatory light chain
Essential light chain
010
Racl-GTP and Cdc42-GTP both activate nucleation co-factors of the ARP2/3 com-plex to nucleate branched F-actin. RhoA, on the other hand, activates formins to nucleate unbranched F-actin. RhoA's effector Rho-associated kinase (ROCK) ac-tivates myosin 4r-*gh~ by promote1the phosphorylation of the myosin regulatory light chain (MRLC), through both direct phosphorylation but alsoinhibiting the myosin phosphatase [11]. Phosphorylated MRLC promotes the assembly of myosin monomers into minifilaments and activates the head domain's ATPase activity. This phosphorylation serves as the major regulator of myosin activity in non-muscle cells.
1.1.2
Epithelia and cell-cell adhesion
In vivo, cells are organized into tissues like the epithelium, broadly defined as a sheet
(or multiple sheets) of cells tightly connected to each other. Mature epithelial cells have a defined apical-basal polarity, with the basal surface attached to a basement membrane and extracellular matrix, while the apical margins of the cell have adhesive structures, allowing them to connect to each other mechanically [2]. In embryonic epithelia, this mechanical connectivity is crucial for changes in cell shapes to sculpt tissue architecture [12].
One important adhesion structure for an epithelial tissue undergoing morphogene-sis is the adherens junctions, a cell-cell adhesion complex (Figure 1-3a) [2]. Adherens junctions are found at the apical margins of the cell and span the intracellular space between neighboring cells to mechanically couple the cells to each other. Further-more, adherens junctions are also bound to the F-actin cortex on their intracellular side, allowing them to transmit mechanical tension between cells. Adherens junctions are composed of clusters of the cadherin-catenin complex, consisting of E-cadherin,
#-catenin,
and a-catenin molecules [1: ]. E-cadherin is a transmembrane protein withlong extracellular domains capable of Ca2+-dependent homophilic interactions, which provides cell-cell adhesion [t 4]. The cytoplasmic domain of E-cadherin can bind -catenin, which binds a-catenin, which can finally bind cortical F-actin. The qua-ternary complex of cadherin-catenins-F-actin is stabilized by external mechanical tension (Figure 1-3b) [t5, 1(]. Therefore, adherens junctions transmit contractile
tension from one cell to the next
[
]. Within an epithelial sheet, adherens junctions are important for propagating tensile forces across the entire tissue, and loss of ad-herens junctions can lead to loss of epithelial architecture during morphogenesis I ]. In addition to adherens junctions, epithelia are also connected by tight junctions and desmosomes. Tight junctions control the permeability of macromolecules across the epithelial sheet, as well as regulate membrane diffusion across the apical-basal axis [ ]. In vertebrates, tight junctions are localized apical to adherens junctions. In insects, an analogous class of junctions, called septate junctions, are found basal to adherens junctions.a
b
Apical
Basal
C
Adherens junction
-E-cadherin
F-actin
4
P-catenin
-
Myosin
w
a-catenin
Figure 1-3: Cell-cell adhesion in an epithelium. a. Schematic of an epithelium with apical-basal polarity. Epithelial cells are connected apically by adherens junc-tions. b. Schematic of a single adherens junction. The F-actin cortex is bound to a a-catenin, #-catenin, E-cadherin complex in a tension-dependent manner [ ]. The extracellular domains of E-cadherin molecules across multiple cells can bind to each other through homophilic interactions.
1.2
Tissue morphogenesis
One fundamental aspect of embryonic development is the formation of 2D and 3D shapes required for the organism's functions later in life. Moreover, these morpho-genetic processes are seen again in the regeneration of damaged tissues and are often
co-opted during cancer progression [ , ]. In this thesis I will focus on epithelial
folding, a fundamental morphogenetic event.
1.2.1
Epithelial folding
One way organisms generate 3D structures from a 2D epithelial sheet is to bend the planar epithelium (Figure 1-4) 12]. As such, tissue folding is seen across metazoan embryogenesis to archive a variety of architectures, from tube-formation in vertebrate neurulation [, to Drosophila joint morphogenesis [ ], to the generation of multiple cell layers during the gastrulation movements of the Drosophila embryo [
I.
A universal mechanism of epithelial folding is for cells to undergo apical con-traction by narrowing their apical surfaces. When a collection of connected cells all apically constrict, they bend the tissue. The ubiquitous force-generating mecha-nism driving apical constriction is the contraction of an apical actin-myosin cortex interconnected to neighboring cells by adherens junctions [2.
Figure 1-4: Epithelial folding.
Schematic of folding a simple epithe-lium.
Drosophila ventral furrow formation
One of the most well-studied examples of epithelial folding and apical constriction is the formation of the ventral furrow during Drosophila gastrulation. Prior to gastru-lation, the Drosophila embryo is an ellipsoid consisting of a simple layer of columnar epithelial cells surrounding an interior yolk (Figure 1-5a) [i ]. The cells' basal sides
face the yolk, while their apical sides face the exterior of the embryo (Figure 1-5b). During gastrulation, the large ventral surface of the embryo, composed of >1,000
cells, will fold into a furrow-like feature and then internalize into the embryo, forming the future mesoderm of the larva. The main driving force of this folding process is the collective apical constriction of the ventral furrow cells, which transition from being column-shaped into being wedge-shaped (Figure 1-5b,c) [ ]. This is thought to lead to an out-of-plane deformation of the tissue, driving epithelial folding.
a b
A yolk P aa
Presumptive ventral furrow
c
d
Apical
DI
Columnar Basal
Wedge
Figure 1-5: Drosophila ventral furrow formation. a. Schematic of the
pre-gastrulation Drosophila embryo showing the presumptive ventral furrow location. b.
Cross-section schematic showing apical-basal polarity of the epithelium. c. Electron micrographs of cross-sectioned Drosophila early embryo undergoing tissue folding to form the ventral furrow. Individual cell shapes are highlighted in yellow. Images are
adapted from Sweeton et al. (1991) [A. d. Apical constriction observed during
ventral furrow folding where cells change shape from columnar to wedge-shaped.
The key signaling system governing ventral morphogenesis is controlled by the Twist transcription program [p. Twist is a transcription factor expressed specifically in the ventral domain. Among the targets of Twist are
folded
gastrulatio (fog) andsubunit of a heterotrimeric G-protein
[
, ]. T48 is a transmembrane protein[
I.
Expression of both Fog and T48 leads to the activation of RhoGEF2, a GEF activator of RhoA. RhoA can activate ROCK and Diaphanous (Dia), a member of the formin family of actin nucleators. The activation of MRLC by ROCK phosphorylation is thought to drive force-generation during apical constriction
[
,J.
T48
SF-actin GPCR RhoGEF2*o-GPR+
Dia
RhoA::GDP RhoA::GTP-- ROCK Myosin activation
Figure 1-6: The Twist pathway during ventral furrow formation. Schematic of the Twist pathway. Twist transcriptional targets fog and t48 activate RhoA, stimulate F-actin formation and myosin activity.
1.2.2
Actomyosin contractions in morphogenesis
The myosin-induced contraction of an F-actin meshwork (actomyosin contraction) is a key force-generator for many tissue morphogenetic events, including ventral furrow formation [ _]. During ventral furrow formation, live imaging of collectively apically constricting cells using functional fluorescent myosin constructs shows that an acto-myosin network spanning the entire medial apical surface drives apical constriction (Figure 1-7a) [ ]. Myosin contractions are highly dynamic, where myosin rapidly coalesces in the apical surface and then dissipates (Figure 1-7b). The rapid accu-mulation of apical myosin (termed a myosin or contraction pulse) is associated with phases of acute apical area reduction (Figure 1-7b,c) [ ]. Between phases of con-traction, when the myosin pulse dissipates from the apical surface, cell shapes stabilize and retain their new contracted shape (Figure 1-7b,c). After a few rounds of con-traction, ventral furrow cells establish a supracellular meshwork of actomyosin across the ventral domain, connected to each other through adherens junctions (Figure 1-7d) [ ]. Both the stabilization of contracted cell shapes (called ratcheting) as well as
the formation of the supracellular meshwork depend on high Twist expression [ , Similar pulsatile actin-myosin networks have been observed across many contexts, both during development and in homeostasis [31, 3-]. Developmental examples in-clude other apically constricting cells like the Drosophila amnioserosa [36], cell-cell rearrangement in both Drosophila and Xenopus convergent-extension [37-41], basal constriction during Drosophila oogenesis [12], and tissue compaction in early mouse embryongenesis [1 I]. In cultured homeostatic tissues, pulses of actomyosin contrac-tions have been observed to maintain lateral junctional complexes [35].
1.3
Collective cell behavior
Since tissue morphogenesis requires the collective force generation of many cells, it is important to understand how individual behavior is coordinated through time and across a spatially extensive tissue, and how the multiple cells comprising the tissue interact with each other.
Studies of collective apical constriction in the Drosophila ventral furrow have suggested that coordination depends on the Fog pathway downstream of Twist tran-scriptional control (Figure 1-6) [25, 2, 14]. Mutants in the secreted ligand fog or the G, subunit cta exhibit uncoordinated apical constriction. In these mutant tis-sues, a subpopulation of cells are constricting next to other cells that are abnormally expanding, leading to defects in tissue folding (Figure 1-8) [25]. Since ectopic Fog expression is sufficient to induce contractility in both the early Drosophila embryo as well as Drosophila S2R+ cells [2), 45], a model was proposed where there are two sub-populations of cells. One subset of cells requires Fog to activate contractility while the remaining cells can activate contractility through Fog-independent means. These Fog-independent cells will constrict, then upregulate contractility in their neighbors via the Fog pathway, either through secretion of the Fog ligand or through mechan-ical upregulation of Cta activity, thus leading to coherent contraction across the tissue [2>, 1]. Theoretical models have found that a neighbor-activating mechanism
a Pulse 0 Adherens junction F-actin - Myosin + Force
b Contraction pulse Stabilization C
s 12 s 24s 60s 96s E 30 20 T CL 00 2 4 6 Time (min) e d Cadherin Cadherin
(subapical) (apical) Myosin Merge Threshold
Pulse
Stabilize
Figure 1-7: Actomyosin contraction driving apical constriction in Drosophila ventral furrow a. A contracting meshwork of actomyosin drives apical constriction in ventral furrow cells. b. Representative images of an apically constricting ventral furrow cell with labeled myosin and cell membrane. Images adapted from Martin et al. (2009) [)]. c. Quantification of a ventral furrow cell's apical area and apical myosin intensity showing pulses of myosin (green) driving phases of rapid apical constriction. Data adapted from Martin et al. (2009) [ J. d. Example images of E-cadherin and apical myosin. Arrows highlight the formation of a supracellular network spanning across spot adherens junctions. Images adapted from Martin et al. (2010) [a]. e. Rounds of pulsed contractions are interspersed by phases of stabilization.
Although this model has been useful, it relies on images of static cell shapes in fixed embryos, without any live imaging of the force-generating machinery. It is now apparent that apical constriction is dynamic, with force generation mounted by discrete pulses of actomyosin contractions (Figure 1-7) [33]. This highly dy-namic contractility complicates the inference of cell behavior from fixed images of cell shapes. Therefore, it is crucial to study the coordinated behavior of the ventral furrow with live imaging of cell shapes as well as actomyosin contractility, using quan-titative analysis to directly examine how dynamic and heterogeneous cell behaviors are coordinated over space and time.
1.4
Chapter 2: Coordinating pulsed contraction events
Understanding how apical constriction is coordinated requires examining the contrac-tion events which generate morphogenetic force. Currently, it is not well understood how discrete contractile pulses are coordinated to produce a smooth tissue contrac-tion. Are the characteristics of pulsed contractions changing over time, and how are neighboring contraction events affecting each other? I investigated how discrete contraction events are coordinated to facilitate smooth tissue folding. To do this, I de-veloped a computational framework to identify and classify heterogeneous contraction events. Using statistical analysis of thousands of contraction events, I found that high Twist expression is required for cells to transition from undergoing reversible contrac-tions into a ratcheted state where contraccontrac-tions become irreversible. The ratcheted state is associated with cooperative interactions between neighboring contractions, and could be important for eliciting coordinated cell behavior.
1.5
Chapter 3: Cta signaling buffers contractility
against cell heterogeneity
The uncoordinated phenotype of fog and cta mutants can yield crucial insight into one mechanism underlying collective apical constriction in the ventral furrow. In this
Myosin Membrane
a
0.b
CLI
Fog-independent cells Fog signalingFigure 1-8: cta is required for coordinated apical constriction. a. Wild-type ventral furrow. Cells constrict relatively evenly, and start to invaginate out of the plane of imaging at 3.7 minutes from the first observed myosin pulses. Arrow b.
cta ventral furrow. cta embryos exhibit uncoordinated apical constriction, where constricting cells (arrowheads) are found next to expanded cells (arrows), as well as delayed tissue folding. c. Neighbor activation model. In this model, there are mosaic subset of cells that do not require Fog signaling to activate contractility, but will upregulate the Fog-pathway, either through secretion of Fog or by upregulating GPCR activity, to activate neighboring cells, inducing the rest of the tissue to contract
chapter, I used the tools developed in Chapter 2 to quantitatively characterize the behavior of uncoordinated cta cells. I uncovered a hitherto unseen dependence of the constriction defect on initial apical area, with larger initial apical area predicting a failure to robustly constrict. These larger cta cells progressively lose apical F-actin density, form holes in the apical meshwork, and initiate actomyosin contractions later than cells with smaller initial area. Crucially, the incoordination in constriction is not seen in embryos with heterogeneous initial apical area but intact Cta-signaling. There-fore, Cta-signaling buffers the apical contractile machinery against length-dependent defects, possibly through the robust maintenance of the apical F-actin meshwork within individual cells.
Chapter 2
Intracellular signalling and
intercellular coupling coordinate
heterogeneous contractile events to
facilitate tissue folding
This chapter is based on:
Intracellular signalling and intercellular coupling coordinate heterogeneous contractile events to facilitate tissue folding
Shicong Xie and Adam C. Martin
Nature Communications (2015) DOI: http://doi.org/10.1038/ncomms8161
Cellular forces generated in the apical domain of epithelial cells reshape tissues. Re-cent studies highlighted an important role for dynamic actomyosin contractions, called pulses, that change cell and tissue shape. Net cell shape change depends on whether cell shape is stabilized, or ratcheted, between pulses. Whether there are different classes of contractile pulses in wild-type embryos and how pulses are spatiotemporally coordinated is unknown. Here, we develop a computational framework to identify and classify pulses and determine how pulses are coordinated during invagination of the
where weak or unratcheted pulses transition to ratcheted pulses. The transcription factor Twist directs this transition, with cells in Twist-depleted embryos exhibiting ab-normal reversed transitions in pulse behavior. We demonstrate that ratcheted pulses have higher probability of having neighbouring contractions and that ratcheting of pulses prevents competition between neighboring contractions, allowing collective be-havior.
2.1
Introduction
Tissue morphogenesis results from forces generated by myosin II (myosin) motors that contract networks of actin filaments (F-actin) [1, 32], often occurring in discrete force-generating events, called pulses or pulsed contractions, that acutely change cell shape [ 17, 48]. One model system for studying tissue morphogenesis is Drosophila gas-trulation, where the collective apical constriction of the presumptive mesoderm drives the folding of the embryo along its ventral side (ventral furrow) [25, 271]. Pulsed con-tractions of the actin-myosin cortex drive apical constriction in individual cells; these contraction events can be stabilized in a ratchet-like manner, a process dependent on high expression of the transcription factor Twist (Twi) [331. In order for the overall tissue to fold effectively, ventral furrow cells must collectively apically constrict. A widespread model of collective cell constriction is that a subset of cells initiates con-striction, which triggers a population-level constriction [24, 27 2, 14, 146]. Given that cell shape change can occur in steps, it is unclear whether changes in the properties of dynamic cell events can promote the transition to collective cell constriction. A systematic and quantitative characterization of transient, dynamic cell behaviors is necessary to investigate how pulsed contractions are temporally organized to constrict the tissue, as well as how pulses are spatially coordinated between neighboring cells. Here, we develop a quantitative approach to identify and classify thousands of contractile events, showing that during wild-type Drosophila gastrulation, cells ex-hibit three predominant classes of contractile events: unconstricting, unratcheted, and ratcheted. We show that Twi expression drives the biased transition in
individ-ual cells from a weak and unratcheted contraction state into a strong and ratcheted state. We also find that neighboring cells are more likely to contract next to ratcheted pulses, and that ratcheting prevents competition between neighboring pulses. These results demonstrate that dynamic transitions in individual cell behavior promotes collective cell behavior in the ventral furrow. Quantitatively defining different classes of contractile events is important to understand how cells interact within a tissue. Contractile pulses are observed in a wide variety of morphogenetic events [32,; ,41, and our findings suggest that the dynamic engagement of a ratcheting mechanism is a key event in eliciting collective behavior in these systems.
2.2
Results
2.2.1
Computational identification of contractile events
In the Drosophila ventral furrow, myosin pulses generate force by rapidly contracting the apical F-actin cortex of a cell [ I)-51]; 9, in addition to the acute assembly and disassembly seen during a pulse, apical myosin also increases over time to form a supracellular meshwork [18]. However, contractility generated by the cortex might not always result in a productive deformation of the cell apex, for example if the cortex is not coupled to the apical margin, if the deformation is not stabilized, or if there are external forces that counteract the generated force [3, .3 1,5 2. While differ-ent types of contractile evdiffer-ents during vdiffer-entral furrow formation have been described qualitatively, understanding the basis for how these events elicit tissue shape change requires a quantitative approach for classifying contractile events and assessing their coordination across the tissue. Using myosin intensity as a proxy for force-generation, we developed a computational framework to identify contractile pulses, classify each pulse according to the behavior of the resulting change in cell area, and determine spa-tiotemporal relationships between pulses. We developed an iterative multi-Gaussian fitting approach to identify pulses from the myosin intensity signal, using an exponen-tial function to model the background increase in apical myosin levels (Figure 2-1a,
Supplemental Figure 2-11). To stringently verify this set of extracted pulses, we curated each putative pulse against a set of manually tracked pulses from the same embryo, yielding a set of validated myosin pulses from wild-type embryos (822 pulses, 277 cells, 5 embryos; Figure 2-2a, Supplemental Figure 2-12, see Methods 2.4.2). Our set of 822 pulses included all computationally and manually identified pulses that have been inspected and verified. The Gaussian parameters, mean and
amplitude7 were used to determine the timing of a pulse's peak and its maximum
myosin intensity, respectively (Figure 2-2a,c). We aligned all identified pulses by their Gaussian means to visualize the mean-centered cell area response to a pulse (Figure 2-1b). Sorting pulses by their amplitudes, we saw that the concomitant area responses also exhibited a gradient in the extent of constriction (Figure 2-2d-e). Because raw intensities cannot be compared across individual movies, we binned pulses of the same percentile-ranking within their respective embryos, termed the amplitude-bin (see Methods 2.4.2). By averaging pulses within each amplitude-bin, we found a correlation between the rank of myosin pulses, and thus pulse magnitude, and the reduction in apical area (Figure 2-2f-g). Taken together, these results show that there is a continuum of myosin pulse magnitudes within individual embryos dur-ing ventral furrow formation. Furthermore, we uncovered a dose-dependence of apical constriction on myosin pulse amplitude, which validates the use of myosin intensity as a proxy measurement for force generation.
2.2.2
Three distinct classes of pulses during tissue
invagina-tion
To determine whether wild-type embryos exhibit different classes of pulses that lead to different area responses, we used fuzzy c-means (FCM), an unsupervised cluster-ing method, to group pulses with similar area response behaviors (Figure 2-1c, see Methods 2.4.2) [7 i, j. FCM clustering not only classifies pulses, but also quanti-tatively assesses the degree of membership of a pulse in a given class (Figure 2-2c, degree of membership, left). We co-clustered the area responses of wild-type pulses
a
Myosin Cell outline
b
Myosin intensity (a.u.) X1 04
1.8
.14(
0.6r
-20 0 20 40 Pulse time (sec)
x10 40> 30 c 20 10 0 - _J 3 0 100 200 Developmental time (sec)
Area responses (pm2) 8
4
0
-20 0 20 40 Pulse time (sec)
-20 01 2O X1040 > 2x1 30 0 1 20 CD 10 0 100 200 Developmental time (sec)
5,
Figure 2-1: Image segmentation and pulse identification pipeline. a. Cell outlines were segmented and tracked to measure cell area (magenta) and apical myosin intensity (green) [ ]. Myosin intensity peaks (pulses) and background exponential increase (black) were identified by a multiple Gaussian fitting algorithm and subject to manual curation. The final curated Gaussian fits are show shown in grey (right). b. Pulses identified from the example cell in (a) were aligned by their centers (dotted line) to simultaneously quantify myosin intensity and area response.
a Myosin intensity (a.u.) Area responses (pm2 ) C Area responses (pm2 ) 800 4 X104 8 8 6 6 E Ratcheted 3 4 4 U Unratcheted O Unconstricting 2 a E 750.8 2 0 0.6 -2002040 2020 40 00.2440
Pulse time (sec) Pulse time (sec) Pulse time (sec)
b b' d d' d
x Stn* Unconstrictin Unratcheted Ratcheted
- 4perc 44 4
-o0 2- -8h .-- 4 4 -4044 4
-20 0 20 40 -20 0 20 40 percent e
Pulse time (sec) Pulse time (sec) weakest Pulse time (sec)
Figure 2-2: Pulse classification. a-b. Heatmaps of wild-type pulses identified
and used in this study. Myosin intensity (a) and area response (a') of all pulses
(ri= 822) identified from wild-type embryos (n= 5) and sorted by pulse intensity.
b-b'. Magnitude of apical constriction depends on the amplitude of myosin pulses.
Average mean-centred myosin intensity
(b)
and average mean-centered area response (b') of pulses in various amplitude-bins. Colors denote the percentile-ranking in pulse amplitude (m > 80 for each color). c. Pulses were clustered into three categories according to their area response behaviors. Heatmap shows the area responses to pulses (n= 720) clustered by FCM into ratcheted (blue), unratcheted (magenta), and unconstricting classes (red). Within each class, pulses were also sorted by the degree of membership (D.M.) of each area response within their respective category (left). Pulses with missing data points were not categorized and not shown (n =102). d-d". Average area response within each behaviour class. (d) Unconstricting pulses display no or minimal constriction (nr= 171). (d') Unratcheted pulses display unstabilized constrictions (rn = 205). (d") Ratcheted pulses display stabilized constrictions (n =344). Shaded areas represent standard deviations. e. Fraction of pulses with given behavior in wild-type ('r= 5) and twi-RNAi embryos (n = 5).
alongside validated pulses from twi-RNAi embryos, which are known to exhibit un-ratcheted pulses (Supplemental Figure 2-15a-b; 1127 pulses, 381 cells, 5 em-bryos)
[:J.
Pulses clustered into three behavior classes, which we termed: ratcheted,unratcheted, and unconstricting pulses (Figure 2-2e). On average, ratcheted pulses exhibited apical constrictions that did not relax (Figure 2-2d, Supplemental Fig-ure 2-13a). Unratcheted pulses also showed apical constriction, but the constricted area was not stabilized and the apical domain subsequently expanded (Figure 2-2d', Supplemental Figure 2-13b). In contrast, unconstricting pulses did not display measurable apical constriction (Figure 2-2d", Supplemental Figure 2-13c). To validate the use of three clusters, we used principal component analysis (PCA) to show that 3 principal components captured >90% of the total variance (Supplemental Figure 2-14a, c). Additionally, PCA reveals that these clusters do not represent discrete, well-separated clusters but rather different parts of a continuum of dynamic cell behaviors (Supplemental Figure 2-14b, d, see Methods 2.4.2). Consistent with previous reports, we observed that ratcheted pulses comprise the largest frac-tion of wild-type pulse behavior, while pulses in twi-RNAi embryos were enriched in the unratcheted behavior (Figure 2-2e) [13]. Next, we asked if the unconstricting behavior reflects different myosin pulse amplitudes. The unconstricting pulses could represent contractile events in which the apical actin-myosin meshwork is not me-chanically coupled to junctions at the apical margin [T1]; however, our quantitative analysis of pulse amplitudes demonstrates that unconstricting pulses are significantly enriched in pulses of the lowest ranked amplitude-bins (Figure 2-3a), suggesting the alternative possibility that this class represents weak pulses that fail to change cell shape. Both ratcheted and unratcheted pulses have a significantly higher probability of being higher amplitude pulses than unconstricting pulses (Figure 2-3a).
2.2.3
Ratcheted constrictions have higher myosin persistence
Previous models of the ratchet mechanism posited that ratcheting is caused by myosin structures persisting after a contractile pulse; however, we did not previously have a quantitative metric of ratchet engagement [12, 18]. To test our model, we measured
a
Cui M 0 CL 1 -0.8 0.6- 0.4-0.2 0 -C 0.8 CL 04 -0.4 -0.8 b Strongest 100th percentile 10Oth "J percentile Weakest Pulse time d Myosin persistence mean d9 Ratcheted Unratcheted 0.5 0.5 C') )0 0 0 R 0.101 - R= -0.301 * P>0.05 P<10' * 0 0.5 1 0 0.5 1 Degree of membership Degree of membershipe
a: C -1 Myosin MembraneI.E
I.
Figure 2-3: Ratcheting of contractile pulses correlates with persistent
myosin structures. a. Unconstricting pulses are enriched in low-amplitude myosin
pulses. Distributions of pulse amplitude-bin for each pulse behaviour class are shown.
b. Schematic for the myosin persistence measurement. Myosin persistence is defined
as the difference between the before-peak and after-peak myosin intensity minima
(AI) normalized by the average intensity (Imean) during the pulse. c. Ratcheted
pulses display more persistent myosin after the pulse measured for wild-type cells. Myosin persistence measured for wild-type ratcheted and unratcheted pulses reveal the lack of persistent myosin intensity in unratcheted pulses (P < 10-, unpaired T-test). Red bars represent sample medians and boxes demarcate the 25th and 75th percentiles. d-e. Myosin persistence is associated with pulse ratcheting. The de-gree of membership in the ratcheted class (d) correlates with myosin persistence
(R = 0.101,P > 0.05), while the degree of membership in the unratcheted class (e)
significantly anti-correlates with myosin persistence (R = -0.301,P < 10-4). Lines represent best-fit lines. f-g. Representative images of a ratcheted pulse (f, arrow-head) shows persistent myosin structures (f, arrow), while an unratcheted pulse (g, arrowhead) does not. Scale bars are 5pm.
myosin persistence for each pulse, defined as the normalized difference between the minimal myosin intensity before and after the pulse peak (Figure 2-3b). Supporting our model, we found that myosin was more persistent in ratcheted pulses compared to unratcheted pulses; furthermore, unratcheted pulses had average persistence close to zero, suggesting a lack of residual myosin structures after the dissipation of the pulse (Figure 2-3c, f-g, arrows). Additionally, when we examined the degree of member-ship of pulses in a particular behavior class as given by FCM, we saw that membermember-ship in the unratcheted class anti-correlates with myosin persistence, demonstrating that the most unratcheted constrictions tend to lack myosin persistence (Figure 2-3e). The correlation between membership in the ratcheted class and myosin persistence was positive although not significant (Figure 2-3d). These results support a ratchet mechanism in which persistent apical myosin structures help to stabilize pulsed con-tractions. In addition, we show that lower Twi levels increase the prevalence of an
unratcheted behavior already present in the wild-type system.
2.2.4
Ventral furrow cells constrict as a single population
We next investigated how collective apical constriction occurs in the ventral furrow. Previous research, mostly on fixed embryos, resulted in a model that a sub-population of cells initiates constriction, termed the stochastic phase of constriction, which trig-gers the coherent constriction of the remaining cells, resulting in tissue contraction and folding [1, ),
[J.
We examined whether we could detect cell populations withdistinct contractile dynamics. To compare the timing of ventral furrow formation across wild-type embryos, we temporally aligned movies using the onset of net tissue contraction as a reference point, set to t = 0 (Supplemental Figure 2-16a, see Methods 2.4.2). We quantified the timing of pulse initiation in wild-type cells, and found that it exhibits a unimodal distribution in time (Figure 2-4a; P > 0.9 Har-tigan's dip-test for non-unimodality [)(i]). Similarly, the timing of the first ratcheted pulse is unimodal (Figure 2-4b; P > 0.8). In addition, cell apical areas change as a unimodal distribution in time (Figure 2-4c,d; P > 0.1), suggesting that there are not distinct sub-populations of cells that differentially initiate constriction.
a
0.12 C .2 (n 60 =3 0.08 E _I 6 0.04 0L2 -200 -100 0 100 200 300 -600 -400 -200 0 200 Developmental time (sec) Developmental time (sec)b 0 d 0.2 td. = -23s (0 t.1 = 37s 0.1 Cz0.1 =t", = 97s Q) 2= td, = 157S 00 -200 -100 0 100 200 300 0 20 40 60 80
Developmental time (sec) Apical area (pm2
)
Figure 2-4: Ventral furrow cells initiate contraction as a single population. a. Distribution of timing of the initial pulse is unimodal. The timing of the first pulse from each wild-type cell is quantified and exhibits a single mode in density. b. Distribution of timing of the first ratcheted pulse is unimodal. The timing of the first pulse from each wild-type cell that was ratcheted is quantified. c. Apical area decreases smoothly as a single population. The probability distributions of apical areas is quantified across temporal bins in developmental time, and shows that cells constrict as a single population. Dotted lines refer to plots in (d). *P > 0.1, Hartigan's dip-test for non-unimodality [ ]. d. The distribution of apical area is shown for four time points during ventral furrow formation. Colours correspond to dotted lines in (c).
2.2.5
Cells transition from unratcheted to ratcheted pulses
We found that while contractile pulses initiate before net tissue contraction, there is not a distinct sub-population of "initiator" cells. Therefore, we asked whether changes in the dynamic behavior of individual cells could explain the onset of collective cell behavior. We found that the amplitudes of myosin pulses increase progressively with respect to developmental time, with the weakest pulses occurring around or before
t = 0 and the strongest pulses occurring after t = 0 (Figure 2-5a). Furthermore, the time interval between consecutive pulses within a single cell displayed an anti-correlation with developmental time (R = -0.220,P < 10-7). The period decreases by 8s per minute from the average periodicity of 85s seen before the onset of constric-tion, suggesting that in addition to increasing in amplitude, pulses also become more frequent (Figure 2-5b). Finally, pulses become increasingly ratcheted over devel-opmental time. Before t=0, most pulses are unconstricting or unratcheted (Figure 5c), with only 15% of these pulses being ratcheted (Supplemental Figure 2-16d-e). In contrast, over 60% of pulses occurring after t = 0 are ratcheted (Figure 2-5c). This transition in pulse behavior occurs at the cell level, where individual cells are more likely to undergo transitions from unconstricting or unratcheted into ratcheted pulses than the reverse (Figure 2-6ff', Supplemental Figure 2-16c). These results show that there is a temporal program of increasing myosin pulse am-plitude, frequency, and ratcheting during ventral furrow formation, and that once in the ratcheted state, cells are more likely to continue to have ratcheted pulses.
2.2.6
Twist expression promotes biased transitions in pulse
class
We hypothesized that the kinetics of signaling events downstream of Twi expression may be required for cells to properly order contractile events during tissue folding. We examined twi-RNAi embryos and saw that the temporal coordination of pulses was disrupted in several aspects. First, pulses within individual embryos were no longer ordered over time from lower to higher amplitudes (Figure 2-6a,a', Supplemental
b Wild-type 100 0.2 -500 0.2 S0 R=-0.220 a I 80 44M P6 a)6 0.15 6 20 01 :3e3 ) .2 2 - Ratcheted
E 40 100 10 2.05I a.~ 0.05- -- UnratchetedUnconstricting
C -200 200 400 600 800 0 -200 0 200 400 600 80 -20 0 200 40 600 80
Developmental time (sec) Developmental time (sec) Developmental time (sec)
Figure 2-5: Dynamic transitions in pulse behavior in wild-type embryos. a. Wild-type pulses progressively increase in magnitude. Probability density functions of the timing of pulses of increasing amplitude-bins are shown. b. Wild-type pulses become increasingly frequent. The time interval between consecutive pulses is shown with respect to developmental time. Line shows best-fit. c. Wild-type pulses tran-sition from unconstricting and unratcheted pulses to ratcheted pulses. Probability density functions of the timing of different pulse behavior classes are shown. (In-set) Cumulative distribution function. Dotted lines demarcate the respective mean timing.
Figure 2-17c-f). In control embryos, pulses within a single pulse amplitude-bin occur on average within 70-120s of each other, whereas in twi-RNAi embryos, pulses within the same amplitude-bin occur over a broader time distribution of 160-200 seconds (Figure 2-6d). Additionally, while lower magnitude control pulses on av-erage precede higher ones, twi-RNAi-RNAi pulses of different magnitudes are not as well separated in time. We used Jensen-Shannon divergence (JSD, see Methods 2.4.4) to compare the timing of pulses of different amplitude-bins, where a value of zero denotes identical distributions and larger values denote increasing dissimilarity. We demonstrate that whereas low- and high-amplitude pulses in control cells occur with dissimilar timing (Figure 2-6e, upper right), those from twi-RNAi cells occur with much more similar timing (Figure 2-6e, lower left). The absolute magnitude of constriction rates are similar between Twi-depleted and control embryos pulses, suggesting that Twi does not simply alter the dynamic range of the magnitude of contractile pulses (compare Figure 2-2b-b' with Supplemental Figure 2-15b, d). However, we cannot rule out that the absolute levels of force are different be-tween embryos and that the dynamic range of contraction forces in twi-RNAi embryos is lower. Nevertheless, within individual embryos, twi-RNAi clearly disrupts the
dering of pulse amplitudes from weakest to strongest. Second, the temporal increase in pulse frequency is inhibited by twi-RNAi. Pulse period begins at an average value of 95s, decreasing by 2s per minute as opposed to the 8s per minute seen in wild-type (Figures 2-5b, 2-6b-b'). Finally, the tissue-level transition to predominantly ratcheted pulses is also abolished, with ratcheted, unratcheted, and unconstricting pulses co-occurring in developmental time (Figure 2-6c-c', Supplemental Figure 2-17g-h). This lack of transition to the ratcheted state occurred at the individual cell level, with cells having unratcheted pulses failing to proceed to ratcheted pulses and cells with ratcheted pulses abnormally reverting back to unratcheted pulses (Figure 2-6f-f'). Therefore, Twi expression promotes biased transitions between pulse classes, directing cells from weaker, less frequent, and unratcheted pulses to stronger, more frequent, and more ratcheted pulses.
2.2.7
Twi promotes increased levels of stable medioapical Rok
To elucidate the mechanism by which Twi expression temporally coordinates the tran-sition in contractile state, we imaged the dynamics of Rho-kinase (Rok) in twi-RNAi cells. In the ventral furrow, Rok acts downstream of Twi expression to phosphorylate and activate myosin [.), 1!, 9-]. Previous studies showed that Rok exhibits apical
pulses with spatiotemporal dynamics similar to those of myosin pulses, and eventu-ally forms a stable, concentrated medioapical focus [ P,
![Figure 2-1: Image segmentation and pulse identification pipeline. a. Cell outlines were segmented and tracked to measure cell area (magenta) and apical myosin intensity (green) [ ]](https://thumb-eu.123doks.com/thumbv2/123doknet/14492697.526176/37.918.140.765.271.746/figure-segmentation-identification-pipeline-outlines-segmented-tracked-intensity.webp)
