Epithelial cell plasticity: breaking boundaries and changing landscapes

Epithelial tissues respond to a wide variety of environmental and genotoxic stresses. As an adaptive mechanism, cells can deviate from their natural paths to acquire new identities, both within and across lineages. Under extreme conditions, epithelial tissues can utilize “shape‐shifting” mechanisms whereby they alter their form and function at a tissue‐wide scale. Mounting evidence suggests that in order to acquire these alternate tissue identities, cells follow a core set of “tissue logic” principles based on developmental paradigms. Here, we review the terminology and the concepts that have been put forward to describe cell plasticity. We also provide insights into various cell intrinsic and extrinsic factors, including genetic mutations, inflammation, microbiota, and therapeutic agents that contribute to cell plasticity. Additionally, we discuss recent studies that have sought to decode the “syntax” of plasticity—i.e., the cellular and molecular principles through which cells acquire new identities in both homeostatic and malignant epithelial tissues—and how these processes can be manipulated for developing novel cancer therapeutics.     

An “elite hacker”: Breast tumors exploit the normal microenvironment program to instruct their progression and biological diversity

The year 2011 marked the 40 year anniversary of Richard Nixon signing the National Cancer Act, thus declaring the beginning of the “War on Cancer” in the United States. Whereas we have made tremendous progress toward understanding the genetics of tumors in the past four decades, and in developing enabling technology to dissect the molecular underpinnings of cancer at unprecedented resolution, it is only recently that the important role of the stromal microenvironment has been studied in detail. Cancer is a tissue-specific disease, and it is becoming clear that much of what we know about breast cancer progression parallels the biology of the normal breast differentiation, of which there is still much to learn. In particular, the normal breast and breast tumors share molecular, cellular, systemic and microenvironmental influences necessary for their progression. It is therefore enticing to consider a tumor to be a “rogue hacker”—one who exploits the weaknesses of a normal program for personal benefit. Understanding normal mammary gland biology and its “security vulnerabilities” may thus leave us better equipped to target breast cancer. In this review, we will provide a brief overview of the heterotypic cellular and molecular interactions within the microenvironment of the developing mammary gland that are necessary for functional differentiation, provide evidence suggesting that similar biology—albeit imbalanced and exaggerated—is observed in breast cancer progression particularly during the transition from carcinoma in situ to invasive disease. Lastly we will present evidence suggesting that the multigene signatures currently used to model cancer heterogeneity and clinical outcome largely reflect signaling from a heterogeneous microenvironment—a recurring theme that could potentially be exploited therapeutically.     

Effect of cellular rearrangement time delays on the rheology of vertex models for confluent tissues

Large-scale tissue deformation during biological processes such as morphogenesis requires cellular rearrangements. The simplest rearrangement in confluent cellular monolayers involves neighbor exchanges among four cells, called a T1 transition, in analogy to foams. But unlike foams, cells must execute a sequence of molecular processes, such as endocytosis of adhesion molecules, to complete a T1 transition. Such processes could take a long time compared to other timescales in the tissue. In this work, we incorporate this idea by augmenting vertex models to require a fixed, finite time for T1 transitions, which we call the “T1 delay time”. We study how variations in T1 delay time affect tissue mechanics, by quantifying the relaxation time of tissues in the presence of T1 delays and comparing that to the cell-shape based timescale that characterizes fluidity in the absence of any T1 delays. We show that the molecular-scale T1 delay timescale dominates over the cell shape-scale collective response timescale when the T1 delay time is the larger of the two. We extend this analysis to tissues that become anisotropic under convergent extension, finding similar results. Moreover, we find that increasing the T1 delay time increases the percentage of higher-fold coordinated vertices and rosettes, and decreases the overall number of successful T1s, contributing to a more elastic-like—and less fluid-like—tissue response. Our work suggests that molecular mechanisms that act as a brake on T1 transitions could stiffen global tissue mechanics and enhance rosette formation during morphogenesis.     

Model-Based Deconvolution of Cell Cycle Time-Series Data Reveals Gene Expression Details at High Resolution

In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure “just-in-time” assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract “single-cell”-like information from population-level time-series expression data. This method removes the effects of 1) variance in growth rate and 2) variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell.     

Impact of Natural Genetic Variation on Gene Expression Dynamics

DNA sequence variation causes changes in gene expression, which in turn has profound effects on cellular states. These variations affect tissue development and may ultimately lead to pathological phenotypes. A genetic locus containing a sequence variation that affects gene expression is called an “expression quantitative trait locus” (eQTL). Whereas the impact of cellular context on expression levels in general is well established, a lot less is known about the cell-state specificity of eQTL. Previous studies differed with respect to how “dynamic eQTL” were defined. Here, we propose a unified framework distinguishing static, conditional and dynamic eQTL and suggest strategies for mapping these eQTL classes. Further, we introduce a new approach to simultaneously infer eQTL from different cell types. By using murine mRNA expression data from four stages of hematopoiesis and 14 related cellular traits, we demonstrate that static, conditional and dynamic eQTL, although derived from the same expression data, represent functionally distinct types of eQTL. While static eQTL affect generic cellular processes, non-static eQTL are more often involved in hematopoiesis and immune response. Our analysis revealed substantial effects of individual genetic variation on cell type-specific expression regulation. Among a total number of 3,941 eQTL we detected 2,729 static eQTL, 1,187 eQTL were conditionally active in one or several cell types, and 70 eQTL affected expression changes during cell type transitions. We also found evidence for feedback control mechanisms reverting the effect of an eQTL specifically in certain cell types. Loci correlated with hematological traits were enriched for conditional eQTL, thus, demonstrating the importance of conditional eQTL for understanding molecular mechanisms underlying physiological trait variation. The classification proposed here has the potential to streamline and unify future analysis of conditional and dynamic eQTL as well as many other kinds of QTL data.     

On Leukocytes in Mammary Development and Cancer

During metastasis, tumor cells may be copying a program that is executed by hematopoietic stem cells during development.That cancer is development gone awry is not a new concept. Most of the “hallmarks” ascribed to cancer—proliferation, invasion and induction of blood vessel growth—also occur during organogenesis and development. Therefore, tumors are not necessarily learning new tricks during their development, but how about when they metastasize? In colonizing a new organ, often with some degree of specificity, tumor cells may simply be copying a program that is executed during development by hematopoietic stem cells (HSCs)—the stem cells that ultimately generate all of the cells in our blood and maintain its homeostasis. One family of cells generated by HSCs—leukocytes—is the focus of the work by Coussens and Pollard (2012). These two scientists have woven together several studies that revolutionized the way we think of immune cells. As pointed out by the investigators (whose respective laboratories are responsible for much of the seminal work on this subject), immune cells also have a variety of trophic functions, and it is these functions that are used rationally during development, and recklessly during tumor growth.This leads us back to metastasis. There is so much to learn about why a tumor travels from one organ to another, how it does so, and the manner by which it adapts to and ultimately flourishes (or fails) in a foreign microenvironment. And as stated above, immune cell precursors, HSCs, do the same. In the mouse, HSCs have originated in one tissue (the dorsal aorta), traveled to another (the placenta) via the circulation, and matured somewhere else (the liver)—all before birth. Finally, HSCs make their way to the bone marrow, where they reside postnatally. Specialized niches in the bone marrow are thought to mediate HSC dormancy as a means to preserve the “stemness” of this population, and there are mechanisms in place that allow these cells to rapidly exit these environs and proliferate in response to injury. Therefore, it should not come as a surprise that a common site where micrometastases are found is the bone marrow for many cancers (including that of the breast).Uncovering whether the same niches that control HSC expansion in the bone marrow are also responsible for maintaining quiescence of tumor cell populations is an exciting prospect, as is deciphering the precise components of these niches. Such work could explain the seemingly incongruous observation that despite an absence of clinically detectable disease, circulating tumor cells are present in the blood of post-treatment cancer patients sometimes even decades later! Perhaps the niches that regulate prolonged dormancy of tumors are dynamic and inhibit tumor proliferation while allowing them to mobilize periodically, much like for HSCs. It also stands to reason that loss of the same controls that prevent HSC expansion until systemic damage occurs could awaken dormant tumors.Shiozawa et al. (2011) have demonstrated that prostate cancer cells do in fact compete with HSCs for niches within the bone marrow, and that tumor cells are mobilized from HSC niches by similar mechanisms as for HSCs. Whether this is the case for other cancers and whether these similarities can be exploited therapeutically remain to be seen.So what more is there to be learned about immune cells? By furthering our understanding of how solid cancers mimic and hijack components of our immune system, we may not “cure” cancer, but we very well may uncover a means to suppress some cancers into a state of permanent dormancy.     

Drosophila Protein interaction Map (DPiM): A paradigm for metazoan protein complex interactions

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein—especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex “map” provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.     

Cooperation and Shared Beliefs about Trust in the Assurance Game

Determinants of cooperation include ingroup vs. outgroup membership, and individual traits, such as prosociality and trust. We investigated whether these factors can be overridden by beliefs about people’s trust. We manipulated the information players received about each other’s level of general trust, “high” or “low”. These levels were either measured (Experiment 1) or just arbitrarily assigned labels (Experiment 2). Players’ choices whether to cooperate or defect in a stag hunt (or an assurance game)—where it is mutually beneficial to cooperate, but costly if the partner should fail to do so—were strongly predicted by what they were told about the other player’s trust label, as well as by what they were told that the other player was told about their own label. Our findings demonstrate the importance for cooperation in a risky coordination game of both first- and second-order beliefs about how much people trust each other. This supports the idea that institutions can influence cooperation simply by influencing beliefs.     

Cell groups reveal structure of stimulus space

An important task of the brain is to represent the outside world. It is unclear how the brain may do this, however, as it can only rely on neural responses and has no independent access to external stimuli in order to “decode” what those responses mean. We investigate what can be learned about a space of stimuli using only the action potentials (spikes) of cells with stereotyped—but unknown—receptive fields. Using hippocampal place cells as a model system, we show that one can (1) extract global features of the environment and (2) construct an accurate representation of space, up to an overall scale factor, that can be used to track the animal's position. Unlike previous approaches to reconstructing position from place cell activity, this information is derived without knowing place fields or any other functions relating neural responses to position. We find that simply knowing which groups of cells fire together reveals a surprising amount of structure in the underlying stimulus space; this may enable the brain to construct its own internal representations.     

Pulsed feedback defers cellular differentiation

Environmental signals induce diverse cellular differentiation programs. In certain systems, cells defer differentiation for extended time periods after the signal appears, proliferating through multiple rounds of cell division before committing to a new fate. How can cells set a deferral time much longer than the cell cycle? Here we study Bacillus subtilis cells that respond to sudden nutrient limitation with multiple rounds of growth and division before differentiating into spores. A well-characterized genetic circuit controls the concentration and phosphorylation of the master regulator Spo0A, which rises to a critical concentration to initiate sporulation. However, it remains unclear how this circuit enables cells to defer sporulation for multiple cell cycles. Using quantitative time-lapse fluorescence microscopy of Spo0A dynamics in individual cells, we observed pulses of Spo0A phosphorylation at a characteristic cell cycle phase. Pulse amplitudes grew systematically and cell-autonomously over multiple cell cycles leading up to sporulation. This pulse growth required a key positive feedback loop involving the sporulation kinases, without which the deferral of sporulation became ultrasensitive to kinase expression. Thus, deferral is controlled by a pulsed positive feedback loop in which kinase expression is activated by pulses of Spo0A phosphorylation. This pulsed positive feedback architecture provides a more robust mechanism for setting deferral times than constitutive kinase expression. Finally, using mathematical modeling, we show how pulsing and time delays together enable “polyphasic” positive feedback, in which different parts of a feedback loop are active at different times. Polyphasic feedback can enable more accurate tuning of long deferral times. Together, these results suggest that Bacillus subtilis uses a pulsed positive feedback loop to implement a “timer” that operates over timescales much longer than a cell cycle.     

Fifteen compelling open questions in plant cell biology

As scientists, we are at least as excited about the open questions—the things we do not know—as the discoveries. Here, we asked 15 experts to describe the most compelling open questions in plant cell biology. These are their questions: How are organelle identity, domains, and boundaries maintained under the continuous flux of vesicle trafficking and membrane remodeling? Is the plant cortical microtubule cytoskeleton a mechanosensory apparatus? How are the cellular pathways of cell wall synthesis, assembly, modification, and integrity sensing linked in plants? Why do plasmodesmata open and close? Is there retrograde signaling from vacuoles to the nucleus? How do root cells accommodate fungal endosymbionts? What is the role of cell edges in plant morphogenesis? How is the cell division site determined? What are the emergent effects of polyploidy on the biology of the cell, and how are any such “rules” conditioned by cell type? Can mechanical forces trigger new cell fates in plants? How does a single differentiated somatic cell reprogram and gain pluripotency? How does polarity develop de-novo in isolated plant cells? What is the spectrum of cellular functions for membraneless organelles and intrinsically disordered proteins? How do plants deal with internal noise? How does order emerge in cells and propagate to organs and organisms from complex dynamical processes? We hope you find the discussions of these questions thought provoking and inspiring.

We asked 15 experts to address what they consider to be the most compelling open questions in plant cell biology and these are their questions.     

Suspended animation,diapause and quiescence: Arresting the cell cycle in C. elegans

Developing organisms require nutrients to support cell division vital for growth and development. An adaptation to stress, used by many organisms, is to reversibly enter an arrested state by reducing energy-requiring processes, such as development and cell division. This “wait it out” approach to survive stress until the environment is conductive for growth and development is used by many metazoans. Much is known about the molecular regulation of cell division, metazoan development and responses to environmental stress. However, how these biological processes intersect is less understood. Here, we review studies conducted in Caenorhabditis elegans that investigate how stresses such as oxygen deprivation (hypoxia and anoxia), exogenous chemicals or starvation affect cellular processes in the embryo, larvae or adult germline. Using C. elegans to identify how stress signals biological arrest can help in our understanding of evolutionary pressures as well as human health-related issues.     

Transition to quorum sensing in an Agrobacterium population: A stochastic model

Understanding of the intracellular molecular machinery that is responsible for the complex collective behavior of multicellular populations is an exigent problem of modern biology. Quorum sensing, which allows bacteria to activate genetic programs cooperatively, provides an instructive and tractable example illuminating the causal relationships between the molecular organization of gene networks and the complex phenotypes they control. In this work we—to our knowledge for the first time—present a detailed model of the population-wide transition to quorum sensing using the example of Agrobacterium tumefaciens. We construct a model describing the Ti plasmid quorum-sensing gene network and demonstrate that it behaves as an “on–off” gene expression switch that is robust to molecular noise and that activates the plasmid conjugation program in response to the increase in autoinducer concentration. This intracellular model is then incorporated into an agent-based stochastic population model that also describes bacterial motion, cell division, and chemical communication. Simulating the transition to quorum sensing in a liquid medium and biofilm, we explain the experimentally observed gradual manifestation of the quorum-sensing phenotype by showing that the transition of individual model cells into the “on” state is spread stochastically over a broad range of autoinducer concentrations. At the same time, the population-averaged values of critical autoinducer concentration and the threshold population density are shown to be robust to variability between individual cells, predictable and specific to particular growth conditions. Our modeling approach connects intracellular and population scales of the quorum-sensing phenomenon and provides plausible answers to the long-standing questions regarding the ecological and evolutionary significance of the phenomenon. Thus, we demonstrate that the transition to quorum sensing requires a much higher threshold cell density in liquid medium than in biofilm, and on this basis we hypothesize that in Agrobacterium quorum sensing serves as the detector of biofilm formation.     

Focus: The Aging Brain: Neural stem/progenitor cells in Alzheimer’s disease

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease and a worldwide health challenge. Different therapeutic approaches are being developed to reverse or slow the loss of affected neurons. Another plausible therapeutic way that may complement the studies is to increase the survival of existing neurons by mobilizing the existing neural stem/progenitor cells (NSPCs) — i.e. “induce their plasticity” — to regenerate lost neurons despite the existing pathology and unfavorable environment. However, there is controversy about how NSPCs are affected by the unfavorable toxic environment during AD. In this review, we will discuss the use of stem cells in neurodegenerative diseases and in particular how NSPCs affect the AD pathology and how neurodegeneration affects NSPCs. In the end of this review, we will discuss how zebrafish as a useful model organism with extensive regenerative ability in the brain might help to address the molecular programs needed for NSPCs to respond to neurodegeneration by enhanced neurogenesis.     

Elda Grabocka: Stress-buffering comes in granules

Elda Grabocka investigates the role of stress granules in obesity and cancer.

When one thinks of high school, sharing hallways with students from 80 different countries is not the usual image that springs to mind. This was indeed Elda Grabocka’s experience. She grew up in Pogradec, a remote town in Albania—her parents, both physicians, were assigned to this location by the state. Elda won one of the two spots available for Albanian students in a national competition to attend the United World College of the Adriatic in Trieste, Italy, a high school focused on social change that brings together students from around the globe to promote intercultural understanding. Elda still remembers, with a smile on her face, the first glimpse at the laboratories as the senior students were working on their thesis projects: “That was exactly what I wanted to do!” She barely spoke English at the time and had to catch up to the level of her peers, but her perseverance and passion prevailed, and she obtained the International Baccalaureate Diploma (IBD). For the independent study of the IBD program, she submitted a research project in chemistry, which ended up being an important learning and life lesson: “That helped me understand that I was more suited to biology! In hindsight, it was great to have that experience so early; I certainly had no awareness then how essential failing and then learning from your failures is to science, but having a level of comfort with it from the beginning was probably a bonus.”Elda Grabocka. Photo courtesy of Chris Hamilton Photography.But science was not the only professional option Elda contemplated—her volunteering experience with relief organizations in various refugee camps made her consider a career in public health and humanitarian relief efforts. She finally sought a PhD degree in molecular pharmacology and structural biology in the laboratory of Phil Wedegaertner at Thomas Jefferson University. After studying heterotrimeric G-proteins and how the subcellular localization of their exchange factors regulates function, Elda felt the need to seek greener pastures. She went on to do a postdoc on one of longest-studied oncogenes, RAS—her choice wasn’t motivated by the field, but by the mentor, Dafna Bar-Sagi. Elda’s admiration for Dafna is notable when she speaks about her time at the New York University Langone Medical Center: “It’s remarkable how many novel aspects of RAS biology that have shaped and then re-shaped our thinking about this oncogene have come out of her lab; I felt there was a depth and breadth to her approach to scientific research that if I could learn, I’d be able to see more of the angles, so to speak, ask better questions; she has really expanded my mind in all those aspects.” Elda’s work focused on the interplay between the mutated forms of RAS and the wild-type isoforms, which she and others have shown is context dependent, with the wild-type isoforms acting as both tumor suppressors and tumor promoters (1). While still in Dafna’s laboratory, Elda pursued a more independent scientific interest: the role of stress granules in mutant KRAS cells. In 2016, Elda returned to her alma mater, joining the Department of Cancer Biology at the Sidney Kimmel Cancer Center at Jefferson as an assistant professor, with stress granules in cancer as the focus of her laboratory. We contacted her to learn more about her research journey.What interested you about stress granules and their connection with obesity and cancer?I became interested in stress granules and their potential role in cancer early in my postdoc. I read a review by Stephen Elledge’s group where they described the “stress phenotype” of cancer as an important player in tumorigenesis. I realized that cancer cells exist mostly in a state of stress—for example, mutated genes, like oncogenic RAS, are potent inducers of many types of cellular stresses. I was working on a RAS ubiquitination project, and one of the candidates for a RAS de-ubiquitinating enzyme we were looking at was implicated in stress granule formation. Little was known about stress granules at the time—they are induced by types of stresses associated with tumors (hypoxia, oxidative stress, osmotic pressure, proteotoxic stress, metabolic stress, etc.), so the question I asked was whether stress granules could function as a stress coping/adaptation mechanism in cancer. Indeed, I found that stress granules are prevalent in tissues from patients with pancreatic cancer and mouse models of pancreatic cancer. Remarkably, not all cancer cells are the same in their capacity to form stress granules—all cells will make stress granules under stress, but KRAS mutant cancer cells have a heightened ability to do so because signaling from mutant KRAS enhances the levels of a critical molecule to stress granule formation, 15-deoxy-prostaglandin J2 (2). This enhanced capacity to make stress granules, in turn, renders KRAS mutant cells more resistant to stress and more dependent on stress granules; inhibition of stress granules leads to increased cell death in KRAS mutant versus KRAS wild-type cancer cells.Immunofluorescence staining of pancreatic ductal adenocarcinoma tissue showing cancer cells in red, stress granules in green, and nuclei in blue. Image courtesy of the Grabocka laboratory.The work establishing this dependence was in vitro, so the primary goal when I started my laboratory was to determine their relevance in tumorigenesis, which led me to explore their connection to obesity and cancer for several reasons. First, obesity is a major predisposing factor for several cancers, including pancreatic and colon, which are prevalent KRAS-driven cancers for which treatment options are limited. Second, obesity is a complex pathology which likely impacts the pathobiology, the therapy response, and even the evolution of cancers that arise in this setting. Given that cell stress and inflammation are key features in obesity, this would make the ideal background to study the contribution of stress granules in tumorigenesis. I think this pre-existing stress [obesity] might necessitate the engagement of stress adaptive mechanisms from the early stages of tumorigenesis and may also lead to a high dependence on these processes.What are you currently working on, and what is up next for you?It’s a very exciting time to be working on stress granules! The field has grown significantly over the past 10 yr or so, especially with the renewed interest in phase separation. As organelles that form via phase separation when a cell is under stress, stress granules are perhaps one of the best examples of phase separation in vivo and a great platform to understand its relevance. The recent advances in defining the composition, as well as key molecular drivers and their functional domains in stress granule assembly, have been of great benefit. We are now better positioned to define the stress granule–specific functions in health and disease. Because stress granules are induced by various types of stresses, they could function as a pan-stress adaptation mechanism in cancer. This is a very appealing angle, as if we can solve how stress granules enable stress adaptation, which is a major focus of my laboratory, we could have better anti-cancer therapies.The composition of stress granules, comprising hundreds of proteins and mRNAs involved in several aspects of cell biology, prompted me to ask whether cytoprotection under stress is their main and/or only function. What other cellular processes stress granules regulate, whether these vary with the type of stress, and how such processes are integrated into the stress response of cancer cells are burning questions we are currently working on, as the answers will advance our understanding of the role of stress granules in cancer. The “chronic stress” of cancer is heterogenous in both spatial and temporal terms, as well as in the type of stress and intensity. I am also very curious to see if and how heterogeneity in stress stimuli impact the composition of stress granules and the processes they regulate, and how this may affect tumor evolution. Also, cancer cells are not the only cells in the tumor that make stress granules. As a matter of fact, we reported that KRAS mutant cells can stimulate stress granule formation in a paracrine manner. An ongoing project in the laboratory that I’m very excited about is focused on understanding the contribution of stress granules to the pro-tumorigenic microenvironment.What kind of approach do you bring to your work?My approach is very hypothesis and observation driven; the latter in the sense that it can often be that initial spark that inspires an idea, draws connections, and looks for context and meaning. I also find that sometimes the answer to my next question or the question I don’t know to ask yet is hidden right in front of my eyes, so paying careful attention to the data is key. It is also where objective and critical evaluation of experimental results starts. There’s one line that’s firmly ingrained in my mind from my postdoctoral training, which is “Science is self-correcting.” It’s a note of caution that if you don’t pay attention and see only what you want to see, it will still eventually prove you wrong, and you’d have wasted a lot of time in the process. So I try to minimize that waste as much as possible—unavoidable entirely, having a favorite hypothesis is part of the scientific thinking process, but crucial to remember to follow the data and not just convince yourself.What has been the biggest accomplishment in your career so far?I’m still quite early in my career to start listing accomplishments. I feel privileged to do the work I do; I essentially get funded to pursue ideas that I find interesting. So I have a hard time with this question because it has a hint of pride, and when you start adding pride to privilege, as a junior principal investigator especially, it gets a bit too self-serving. I hope that the work we are doing stands the test of time and leads to or helps lead to a meaningful impact on patients’ lives—that would be a great accomplishment.What has been the biggest challenge in your career so far?The past two years of COVID have certainly been a different reality, and a constantly shifting one at that. From a career perspective, so much of a scientific career happens at the bench: experiments happen at the bench, we train at the bench, animal work is long and requires multiple dedicated essential personnel and facilities, so inevitably, remote work, or shift work, limited occupancy, and the shortages we are now seeing in the supply chain have been a major challenge for everyone. I do think junior laboratories like mine experience that a bit harder. The bandwidth to absorb these challenges is much smaller if you’re just starting out, or if you’ve had a laboratory for a couple of years and are just ramping up. I must say though that it has made for stronger teamwork in the laboratory, and we’ve had to be really focused and efficient—so there’s an upside!Out for a paddle. Photo courtesy of Elda Grabocka.Any tips for a successful research career?Hard to say, because certainly it means different things to different people. The only tip I would give perhaps is to define what that means, what that success looks like for oneself, and be true to that. I expect how each one defines it also changes with time and experience, but I do think it’s very important to identify what success means as early as possible and let that be what you measure your efforts against. It’s easy to get distracted, overwhelmed, or even disheartened otherwise. My own definition is quite simple: success is doing what I love to do, working toward answering a meaningful scientific question, and enabling/supporting my trainees to reach their potential—keeping that in mind has been very important and helpful.     

Plasticity is a locally adapted trait with consequences for ecological dynamics in novel environments

Phenotypic plasticity is predicted to evolve in more variable environments, conferring an advantage on individual lifetime fitness. It is less clear what the potential consequences of that plasticity will have on ecological population dynamics. Here, we use an invertebrate model system to examine the effects of environmental variation (resource availability) on the evolution of phenotypic plasticity in two life history traits—age and size at maturation—in long‐running, experimental density‐dependent environments. Specifically, we then explore the feedback from evolution of life history plasticity to subsequent ecological dynamics in novel conditions. Plasticity in both traits initially declined in all microcosm environments, but then evolved increased plasticity for age‐at‐maturation, significantly so in more environmentally variable environments. We also demonstrate how plasticity affects ecological dynamics by creating founder populations of different plastic phenotypes into new microcosms that had either familiar or novel environments. Populations originating from periodically variable environments that had evolved greatest plasticity had lowest variability in population size when introduced to novel environments than those from constant or random environments. This suggests that while plasticity may be costly it can confer benefits by reducing the likelihood that offspring will experience low survival through competitive bottlenecks in variable environments. In this study, we demonstrate how plasticity evolves in response to environmental variation and can alter population dynamics—demonstrating an eco‐evolutionary feedback loop in a complex animal moderated by plasticity in growth.     

Shootin1–cortactin interaction mediates signal–force transduction for axon outgrowth

Motile cells transduce environmental chemical signals into mechanical forces to achieve properly controlled migration. This signal–force transduction is thought to require regulated mechanical coupling between actin filaments (F-actins), which undergo retrograde flow at the cellular leading edge, and cell adhesions via linker “clutch” molecules. However, the molecular machinery mediating this regulatory coupling remains unclear. Here we show that the F-actin binding molecule cortactin directly interacts with a clutch molecule, shootin1, in axonal growth cones, thereby mediating the linkage between F-actin retrograde flow and cell adhesions through L1-CAM. Shootin1–cortactin interaction was enhanced by shootin1 phosphorylation by Pak1, which is activated by the axonal chemoattractant netrin-1. We provide evidence that shootin1–cortactin interaction participates in netrin-1–induced F-actin adhesion coupling and in the promotion of traction forces for axon outgrowth. Under cell signaling, this regulatory F-actin adhesion coupling in growth cones cooperates with actin polymerization for efficient cellular motility.     

Learning the rules of collective cell migration using deep attention networks

Collective, coordinated cellular motions underpin key processes in all multicellular organisms, yet it has been difficult to simultaneously express the ‘rules’ behind these motions in clear, interpretable forms that effectively capture high-dimensional cell-cell interaction dynamics in a manner that is intuitive to the researcher. Here we apply deep attention networks to analyze several canonical living tissues systems and present the underlying collective migration rules for each tissue type using only cell migration trajectory data. We use these networks to learn the behaviors of key tissue types with distinct collective behaviors—epithelial, endothelial, and metastatic breast cancer cells—and show how the results complement traditional biophysical approaches. In particular, we present attention maps indicating the relative influence of neighboring cells to the learned turning decisions of a ‘focal cell’–the primary cell of interest in a collective setting. Colloquially, we refer to this learned relative influence as ‘attention’, as it serves as a proxy for the physical parameters modifying the focal cell’s future motion as a function of each neighbor cell. These attention networks reveal distinct patterns of influence and attention unique to each model tissue. Endothelial cells exhibit tightly focused attention on their immediate forward-most neighbors, while cells in more expansile epithelial tissues are more broadly influenced by neighbors in a relatively large forward sector. Attention maps of ensembles of more mesenchymal, metastatic cells reveal completely symmetric attention patterns, indicating the lack of any particular coordination or direction of interest. Moreover, we show how attention networks are capable of detecting and learning how these rules change based on biophysical context, such as location within the tissue and cellular crowding. That these results require only cellular trajectories and no modeling assumptions highlights the potential of attention networks for providing further biological insights into complex cellular systems.