Biology subjects

Theriot, J. A.

Publications and source records attributed to Theriot, J. A..

34 records · Page 2Linked to original sources

bioRxiv2021

A comprehensive analysis of gene expression changes in a high replicate and open-source dataset of differentiating hiPSC-derived cardiomyocytes

We performed a comprehensive analysis of the transcriptional changes within and across cell populations during human induced pluripotent stem cell (hiPSC) differentiation to cardiomyocytes. Using the single cell RNA-seq combinatorial barcoding method SPLiT-seq, we sequenced >20,000 single cells from 55 independent samples representing two differentiation protocols and multiple hiPSC lines. Samples included experimental replicates ranging from undifferentiated hiPSCs to mixed populations of cells at D90 post-differentiation. As expected, differentiated cell populations clustered by time point, with differential expression analysis revealing markers of cardiomyocyte differentiation and maturation changing from D12 to D90. We next performed a complementary cluster-independent sparse regression analysis to identify and rank genes that best assigned cells to differentiation time points. The two highest ranked genes between D12 and D24 (MYH7 and MYH6) resulted in an accuracy of 0.84, and the three highest ranked genes between D24 and D90 (A2M, H19, IGF2) resulted in an accuracy of 0.94, revealing that low dimensional gene features can identify differentiation or maturation stages in differentiating cardiomyocytes. Expression levels of select genes were validated using RNA FISH. Finally, we interrogated differences in differentiation population composition and cardiac gene expression resulting from two differentiation protocols, experimental replicates, and three hiPSC lines in the WTC-11 background to identify sources of variation across these experimental variables.

cell biology↗

bioRxiv2021

Directional reorientation of migrating neutrophils is limited by suppression of receptor input signaling at the cell rear through myosin II activity

To migrate efficiently to target locations, cells must integrate receptor inputs while maintaining polarity: a distinct front that leads and a rear that follows. Here we investigate what is necessary to overwrite pre-existing front/rear polarity in neutrophil-like HL60 cells migrating inside straight microfluidic channels. Using subcellular optogenetic receptor activation, we show that receptor inputs can reorient weakly polarized cells, but the rear of strongly polarized cells is refractory to new inputs. Transient stimulation reveals a multi-step repolarization process, confirming that cell rear sensitivity to receptor input is the primary determinant of large-scale directional reversal. We demonstrate that the RhoA/ROCK/myosin II pathway limits the ability of receptor inputs to signal to Cdc42 and reorient migrating neutrophils. We discover that by tuning the phosphorylation of myosin regulatory light chain we can modulate the activity and localization of myosin II and thus the amenability of the cell rear to listen to receptor inputs and respond to directional reprogramming.

cell biology↗

bioRxiv2021

Phagocytic 'teeth' and myosin-II 'jaw' power target constriction during phagocytosis

Phagocytosis requires rapid actin reorganization and spatially controlled force generation to ingest targets ranging from pathogens to apoptotic cells. How actomyosin activity directs membrane extensions to engulf such diverse targets remains unclear. Here, we combine lattice light-sheet microscopy (LLSM) with microparticle traction force microscopy (MP-TFM) to quantify actin dynamics and subcellular forces during macrophage phagocytosis. We show that spatially localized forces leading to target constriction are prominent during phagocytosis of antibody-opsonized targets. This constriction is largely mediated by Arp2/3-mediated assembly of discrete actin protrusions containing myosin 1e and 1f ("teeth") that are interconnected in a ring-like organization. Contractile myosin-II activity contributes to late-stage phagocytic force generation and progression, suggesting a specific role in phagocytic cup closure. Observations of partial target eating attempts and sudden target release via a popping mechanism suggest that constriction may be critical for resolving complex in vivo target encounters. Overall, our findings suggest a phagocytic cup-shaping mechanism that is distinct from cytoskeletal remodeling in 2D cell motility and may contribute to mechanosensing and phagocytic plasticity.

cell biology↗

bioRxiv2020

Entropy-driven translocation of disordered proteins through the Gram-positive bacterial cell wall

Cells across all kingdoms of life actively partition molecules between discrete cellular compartments. In Gram-positive bacteria, a thick and highly cross-linked peptidoglycan cell wall separates the bacterial membrane from the extracellular space, imposing a barrier that must be crossed by proteins whose functions require that they be exposed on the bacterial cell surface1,2. Some surface-exposed proteins, such as the Listeria monocytogenes actin nucleation-promoting factor ActA3, remain associated with the bacterial membrane yet somehow thread through tens of nanometers of dense, cross-linked cell wall to expose their N-terminus on the outer surface4,5. Here, we show that entropy can drive the translocation of disordered transmembrane proteins through the Gram-positive cell wall. We develop a physical model predicting that the entropic constraint imposed by a thin periplasm is sufficient to drive translocation of an intrinsically disordered protein like ActA across a porous barrier similar to the cell wall. Consistent with this scenario, we demonstrate experimentally that translocation depends on both the dimensions of the cell envelope and the length of the disordered protein, and that translocation is reversible. We also show that disordered regions from eukaryotic nuclear pore complex proteins are capable of entropy-driven translocation through Gram-positive cell walls. These observations suggest that entropic forces alone, rather than chaperones or chemical energy, are sufficient to drive translocation of certain Gram-positive surface proteins for exposure on the outer surface of the cell wall.

biophysics↗

bioRxiv2020

Fundamental limits on the rate of bacterial growth

Recent years have seen an experimental deluge interrogating the relationship between bacterial growth rate, cell size, and protein content, quantifying the abundance of proteins across growth conditions with unprecedented resolution. However, we still lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we seek to quantitatively understand this relationship across a collection of Escherichia coli proteomic data covering {approx} 4000 proteins and 36 growth rates. We estimate the basic requirements for steady-state growth by considering key processes in nutrient transport, cell envelope biogenesis, energy generation, and the central dogma. From these estimates, ribosome biogenesis emerges as a primary determinant of growth rate. We expand on this assessment by exploring a model of proteomic regulation as a function of the nutrient supply, revealing a mechanism that ties cell size and growth rate to ribosomal content.

systems biology↗

bioRxiv2020

Leading edge stability in motile cells is an emergent property of branched actin network growth

Animal cell migration is predominantly driven by the coordinated, yet stochastic, polymerization of thousands of nanometer-scale actin filaments across micron-scale cell leading edges. It remains unclear how such inherently noisy processes generate robust cellular behavior. We employed high-speed imaging of migrating neutrophil-like HL-60 cells to explore the fine-scale shape fluctuations that emerge and relax throughout the process of leading edge maintenance. We then developed a minimal stochastic model of the leading edge that reproduces this stable relaxation behavior. Remarkably, we find lamellipodial stability naturally emerges from the interplay between branched actin network growth and leading edge shape - with no additional feedback required - based on a synergy between membrane-proximal branching and lateral spreading of filaments. These results thus demonstrate a novel biological noise-suppression mechanism based entirely on system geometry. Furthermore, our model suggests that the Arp2/3-mediated ~70-80{degrees} branching angle optimally smooths lamellipodial shape, addressing its long-mysterious conservation from protists to mammals. Significance StatementAll cellular functions are driven by the stochastic dynamics of macromolecules, and thus are subject to biological noise. Here, as a model system for noise-suppression in the context of cell migration, we investigate lamellipodial maintenance - where thousands of stochastically polymerizing filaments self-organize into a highly-stable, micron-scale leading edge. Combining experiment and computational modeling, we (1) establish lamellipodial stability is an emergent property of dendritically-branched actin network growth, (2) outline a noise-suppression mechanism based on the geometry of lamellipodial actin, and (3) determine the evolutionarily-conserved Arp2/3-mediated ~70-80{degrees} branching angle optimally suppresses stochastic fluctuations. Our results not only explain the essential role of Arp2/3-mediated branching in lamellipodial formation, but also address the decades-old question of why this specific geometry is so well-conserved.

cell biology↗

bioRxiv2020

Osmolarity-independent electrical cues guide rapid response to injury in zebrafish epidermis

The ability of epithelial tissues to heal after injury is essential for animal life, yet the mechanisms by which epithelial cells sense tissue damage are incompletely understood. In aquatic organisms such as zebrafish, osmotic shock following injury is believed to be an early and potent activator of a wound response. We find that, in addition to sensing osmolarity, basal skin cells in zebrafish larvae are also sensitive to changes in the particular ionic composition of their surroundings after wounding, specifically the concentration of sodium chloride in the immediate vicinity of the wound. This sodium chloride-specific wound detection mechanism is independent of cell swelling, and instead is suggestive of a mechanism by which cells sense changes in the transepithelial electrical potential generated by the transport of sodium and chloride ions across the skin. Consistent with this hypothesis, we show that electric fields directly applied within the skin are sufficient to initiate actin polarization and migration of basal cells in their native epithelial context in vivo, even overriding endogenous wound signaling. This suggests that, in order to mount a robust wound response, skin cells respond to both osmotic and electrical perturbations arising from tissue injury.

cell biology↗

bioRxiv2020

The Roles of Space and Stochasticity in Computational Simulations of Cellular Biochemistry: Quantitative Analysis and Qualitative Insights

Most of the fascinating phenomena studied in cell biology emerge from interactions among highly organized multi-molecular structures and rapidly propagating molecular signals embedded into complex and frequently dynamic cellular morphologies. For the exploration of such systems, computational simulation has proved to be an invaluable tool, and many researchers in this field have developed sophisticated computational models for application to specific cell biological questions. However it is often difficult to reconcile conflicting computational results that use different simulation approaches (for example partial differential equations versus particle-based stochastic methods) to describe the same phenomenon. Moreover, the details of the computational implementation of any particular algorithm may give rise to quantitatively or even qualitatively different results for the same set of starting assumptions and parameters. In an effort to address this issue systematically, we have defined a series of computational test cases ranging from very simple (bimolecular binding in solution) to moderately complex (spatial and temporal oscillations generated by proteins binding to membranes) that represent building blocks for comprehensive three-dimensional models of cellular function. Having used two or more distinct computational approaches to solve each of these test cases with consistent parameter sets, we generally find modest but measurable differences in the solutions of the same problem, and a few cases where significant deviations arise. We discuss the strengths and limitations of commonly used computational approaches for exploring cell biological questions and provide a framework for decision-making by researchers wishing to develop new models for cell biology. As computational power and speed continue to increase at a remarkable rate, the dream of a fully comprehensive computational model of a living cell may be drawing closer to reality, but our analysis demonstrates that it will be crucial to evaluate the accuracy of such models critically and systematically.

systems biology↗

bioRxiv2020

Quantitative comparison of principal component analysis and unsupervised deep learning using variational autoencoders for shape analysis of motile cells

Cell motility is a crucial biological function for many cell types, including the immune cells in our body that act as first responders to foreign agents. In this work we consider the amoeboid motility of human neutrophils, which show complex and continuous morphological changes during locomotion. We imaged live neutrophils migrating on a 2D plane and extracted unbiased shape representations using cell contours and binary masks. We were able to decompose these complex shapes into low-dimensional encodings with both principal component analysis (PCA) and an unsupervised deep learning technique using variational autoencoders (VAE), enhanced with generative adversarial networks (GANs). We found that the neural network architecture, the VAE-GAN, was able to encode complex cell shapes into a low-dimensional latent space that encodes the same shape variation information as PCA, but much more efficiently. Contrary to the conventional viewpoint that the latent space is a "black box", we demonstrated that the information learned and encoded within the latent space is consistent with PCA and is reproducible across independent training runs. Furthermore, by including cell speed into the training of the VAE-GAN, we were able to incorporate cell shape and speed into the same latent space. Our work provides a quantitative framework that connects biological form, through cell shape, to a biological function, cell movement. We believe that our quantitative approach to calculating a compact representation of cell shape using the VAE-GAN provides an important avenue that will support further mechanistic dissection of cell motility. AUTHOR SUMMARYDeep convolutional neural networks have recently enjoyed a surge in popularity, and have found useful applications in many fields, including biology. Supervised deep learning, which involves the training of neural networks using existing labeled data, has been especially popular in solving image classification problems. However, biological data is often highly complex and continuous in nature, where prior labeling is impractical, if not impossible. Unsupervised deep learning promises to discover trends in the data by reducing its complexity while retaining the most relevant information. At present, challenges in the extraction of meaningful human-interpretable information from the neural networks nonlinear discovery process have earned it a reputation of being a "black box" that can perform impressively well at prediction but cannot be used to shed any meaningful insight on underlying mechanisms of variation in biological data sets. Our goal in this paper is to establish unsupervised deep learning as a practical tool to gain scientific insight into biological data by first establishing the interpretability of our particular data set (images of the shapes of motile neutrophils) using more traditional techniques. Using the insight gained from this as a guide allows us to shine light into the "black box" of unsupervised deep learning.

cell biology↗

bioRxiv2020

Cell states beyond transcriptomics: integrating structural organization and gene expression in hiPSC-derived cardiomyocytes

We present a quantitative co-analysis of RNA abundance and sarcomere organization in single cells and an integrated framework to predict subcellular organization states from gene expression. We used human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes expressing mEGFP-tagged alpha-actinin-2 to develop quantitative image analysis tools for systematic and automated classification of subcellular organization. This captured a wide range of sarcomeric organization states within cell populations that were previously difficult to quantify. We performed RNA FISH targeting genes identified by single cell RNA sequencing to simultaneously assess the relationship between transcript abundance and structural states in single cells. Co-analysis of gene expression and sarcomeric patterns in the same cells revealed biologically meaningful correlations that could be used to predict organizational states. This study establishes a framework for multi-dimensional analysis of single cells to study the relationships between gene expression and subcellular organization and to develop a more nuanced description of cell states. Graphical AbstractTranscriptional profiling and structural classification was performed on human induced pluripotent stem cell-derived cardiomyocytes to characterize the relationship between transcript abundance and subcellular organization. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/081083v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@8f89c4org.highwire.dtl.DTLVardef@19dc813org.highwire.dtl.DTLVardef@1ba7c20org.highwire.dtl.DTLVardef@2b3daa_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2020

Mechanical competition triggered by innate immune signaling drives the collective extrusion of bacterially-infected epithelial cells

Multiple distinct types of intracellular bacterial pathogens have been shown to alter the mechanics of their mammalian host cells to promote cell-to-cell spread. Conversely, host cells may respond by altering their own mechanical behavior to limit infection. We monitored epithelial cell monolayers sparsely infected with the intracellular bacterial pathogens Listeria monocytogenes or Rickettsia parkeri over the course of several days. Under conditions where these pathogens were able to trigger innate immune signaling through the NF-{kappa}B pathway and to use actin-based motility to spread non-lytically from cell to cell, domains of infected cells formed enormous three-dimensional mounds, where uninfected cells surrounding the infected cells became stiffer and actively moved toward the site of infection, collectively squeezing the softer and weaker infected cells up and ejecting them from the epithelial monolayer. Bacteria in mounds were less able to spread laterally in the monolayer, limiting the growth of the focus, while mounded cells eventually underwent cell death. Cells in infected monolayers exhibited behavioral and molecular signatures of the epithelial to mesenchymal transition (EMT), such that coordinated forceful action by uninfected bystander cells actively eliminated large domains of infected cells, consistent with the hypothesis that this collective cell response represents an innate immune response.

microbiology↗

bioRxiv2018

Cell Mechanics at the Rear Act To Steer the Direction of Cell Migration

Motile cells navigate complex environments by changing their direction of travel, generating left-right asymmetries in their mechanical subsystems to physically turn. Currently little is known about how external directional cues are propagated along the length scale of the whole cell and integrated with its force-generating apparatus to steer migration mechanically. We examine the mechanics of spontaneous cell turning in fish epidermal keratocytes and find that the mechanical asymmetries responsible for turning behavior predominate at the rear of the cell, where there is asymmetric centripetal actin flow. Using experimental perturbations we identify two linked feedback loops connecting myosin II contractility, adhesion strength and actin network flow in turning cells that are sufficient to recreate observed cell shapes and trajectories in a computational model. Surprisingly, asymmetries in actin polymerization at the cell leading edge play only a minor role in the mechanics of cell turning - that is, cells steer from the rear.\n\nHighlightsO_LIFish keratocytes can migrate with persistent angular velocity, straight or in circles.\nC_LIO_LIAsymmetry in protrusion at the leading edge is not sufficient to generate persistent turning.\nC_LIO_LIAsymmetries in myosin II contraction, actin flow and adhesion at the cell rear cause turns.\nC_LIO_LIOur new computational model of migration predicts observed cell trajectories.\nC_LI

cell biology↗

bioRxiv2018

Superresolved and reference-free microparticle traction force microscopy (MP-TFM) reveals the complexity of the mechanical interaction in phagocytosis

Force exertion is an integral part of cellular behavior. Traction force microscopy (TFM) has been instrumental for studying such forces, providing both spatial and directional force measurements at subcellular resolution. However, the applications of classical TFM are restricted by the typical planar geometry. Here, we develop a particle-based force sensing strategy, specifically designed for studying ligand-dependent cellular interactions. We establish an accessible batch approach for synthesizing highly uniform, deformable and tunable hydrogel particles. In addition, they can be easily derivatized to trigger specific cellular behavior. The 3D shape of such particles can be resolved with superresolution (< 50 nm) accuracy using conventional confocal microscopy. We introduce a computational method that allows us to infer surface traction forces with high sensitivity (~ 10 Pa), directly from the particle shape without embedding tracers in the particle. We illustrate the potential and flexibility of this approach by measuring forces throughout phagocytic engulfment. This strategy can readily be adapted for studying cellular forces in a wide range of applications.

biophysics↗

bioRxiv2018

Listeria monocytogenes cell-to-cell spread in epithelia is heterogeneous and dominated by rare pioneer bacteria

L. monocytogenes hijacks host actin to promote its intracellular motility and intercellular spread. While L. monocytogenes virulence hinges on cell-to-cell spread, little is known about the dynamics of bacterial spread in epithelia at a population level. Here, we use live microscopy and statistical modeling to demonstrate that L. monocytogenes cell-to-cell spread proceeds anisotropically in an epithelial monolayer in culture. We show that boundaries of infection foci are irregular and dominated by rare pioneer bacteria that spread farther than the rest. We extend our quantitative model for bacterial spread to show that heterogeneous spreading behavior can improve the chances of creating a persistent L. monocytogenes infection in an actively extruding epithelium. Thus, our results indicate that L. monocytogenes cell-to-cell spread is heterogeneous, and that rare pioneer bacteria determine the frontier of infection foci and may promote bacterial infection persistence in dynamic epithelia.

microbiology↗

bioRxiv2018

Listeria monocytogenes InlP interacts with afadin and facilitates basement membrane crossing

During pregnancy, the placenta protects the fetus against the maternal immune response, as well as bacterial and viral pathogens. Bacterial pathogens that have evolved specific mechanisms of breaching this barrier, such as Listeria monocytogenes, present a unique opportunity for learning how the placenta carries out its protective function. We previously identified the L. monocytogenes protein Internalin P (InlP) as a secreted virulence factor critical for placental infection (1). Here, we show that InlP, but not the highly similar L. monocytogenes internalin Lmo2027, binds to human afadin (encoded by AF-6), a protein associated with cell-cell junctions. A crystal structure of InlP reveals several unique features, including an extended leucine-rich repeat (LRR) domain with a distinctive Ca2+-binding site. Despite afadins involvement in the formation of cell-cell junctions, MDCK epithelial cells expressing InlP displayed a decrease in the magnitude of the traction stresses they could exert on deformable substrates, similar to the decrease in traction exhibited by AF-6 knock-out MDCK cells. L. monocytogenes {Delta}inlP mutants were deficient in their ability to form actin-rich protrusions from the basal face of polarized epithelial monolayers, a necessary step in the crossing of such monolayers (transcytosis). A similar phenotype was observed for bacteria expressing an internal in-frame deletion in inlP (inlP DLRR5) that specifically disrupts its interaction with afadin. However, afadin deletion in the host cells did not rescue the transcytosis defect. We conclude that secreted InlP targets cytosolic afadin to specifically promote L. monocytogenes transcytosis across the basal face of epithelial monolayers, which may contribute to the crossing of the basement membrane during placental infection.

microbiology↗

bioRxiv2017

Cell surface vimentin is involved in matrix stiffness-dependent infection of endothelial cells by Listeria monocytogenes

Extracellular matrix (ECM) stiffness is one of many mechanical forces acting on mammalian adherent cells that influence cellular function. We have addressed the open question of how ECM stiffness might alter the susceptibility of host cells to infection by bacterial pathogens. We manufactured hydrogels of varying physiologically-relevant stiffness and seeded human microvascular endothelial cells (HMEC-1) on them. We then infected HMEC-1 with the bacterial pathogen Listeria monocytogenes (Lm) and found that adhesion of Lm onto host cells increases monotonically with increasing matrix stiffness, an effect that requires the activity of focal adhesion kinase (FAK). We identified cell surface vimentin as a candidate surface receptor mediating stiffness-dependent adhesion of Lm to HMEC-1, and demonstrated that bacterial infection of these host cells is decreased when surface vimentin is perturbed. Our results provide the first evidence that ECM stiffness can mediate the susceptibility of host cells to bacterial infection.

microbiology↗