Biology subjects

Mogre, S. S.

Publications and source records attributed to Mogre, S. S..

6 recordsLinked to original sources

bioRxiv2026

Dynamics of ML-based Morphological Features Indicate a Shear Stress-Dependent Bifurcation of hiPSC-Derived Endothelial Cell States

Cell states are increasingly conceptualized as attractors of high-dimensional dynamical systems, yet quantitative approaches for integrating phenotypic information into this framework remain limited. Here, we take an image-based approach that combines unsupervised machine learning (ML) with timelapse imaging to extract and characterize the temporal dynamics of morphological features. Using a cell line with endogenously tagged VE-cadherin, we acquired brightfield and fluorescence timelapse images of human induced pluripotent stem cell-derived endothelial cell (hiPSC-EC) monolayers, which adopt distinct phenotypes at two different magnitudes of shear stress in terms of their morphology, behavior, and VE-cadherin organization. To quantify these phenotypic cell states without segmentation, we trained a diffusion autoencoder to predict VE-cadherin signal from brightfield images. We identified interpretable ML-based features representing cell orientation, elongation, and local density. Treating these variables as dimensions of a morphological state space, we estimated a data-driven vector field and found that the two observed phenotypic cell states correspond to stable fixed points of the inferred dynamical system. Mapping measured cell migration coherence onto this space further distinguished the states. Imaging cells across intermediate shear stresses revealed a regime of bistability in which both states coexist, indicating that the shear-stress-dependent transition between endothelial cell states occurs as a bifurcation of the inferred dynamical system. Finally, we applied this method to study an N-terminal truncation of VE-cadherin, finding that mutated cells preserve alignment and coherent migration, but exhibit altered morphology and increased migration speed. This work demonstrates the applicability of a dynamical systems approach to quantitatively characterize morphological aspects of cell state from interpretable ML-based features.

biophysics↗

bioRxiv2024

Interpretable representation learning for 3D multi-piece intracellular structures using point clouds

A key challenge in understanding subcellular organization is quantifying interpretable measurements of intracellular structures with complex multi-piece morphologies in an objective, robust and generalizable manner. Here we introduce a morphology-appropriate representation learning framework that uses 3D rotation invariant autoencoders and point clouds. This framework is used to learn representations of complex multi-piece morphologies that are independent of orientation, compact, and easy to interpret. We apply our framework to intracellular structures with punctate morphologies (e.g. DNA replication foci) and polymorphic morphologies (e.g. nucleoli). We systematically compare our framework to image-based autoencoders across several intracellular structure datasets, including a synthetic dataset with pre-defined rules of organization. We explore the trade-offs in the performance of different models by performing multi-metric benchmarking across efficiency, generative capability, and representation expressivity metrics. We find that our framework, which embraces the underlying morphology of multi-piece structures, facilitates the unsupervised discovery of sub-clusters for each structure. We show how our approach can also be applied to phenotypic profiling using a dataset of nucleolar images following drug perturbations. We implement and provide all representation learning models using CytoDL, a python package for flexible and configurable deep learning experiments.

cell biology↗

bioRxiv2024

Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories

To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days, and developed open-source tools for image and data analysis and an interactive timelapse viewer for exploring quantitative features of nuclear size and shape. We performed a data-driven analysis of nuclear growth variations across timescales. We found that individual nuclear volume growth trajectories arise from short timescale variations attributable to their spatiotemporal context within the colony. We identified a strikingly time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited.

cell biology↗

bioRxiv2022

Spatiotemporal analysis of axonal autophagosome-lysosome dynamics reveals limited fusion events trigger two-step maturation

Macroautophagy is a homeostatic process required to clear cellular waste including aggregated proteins and dysfunctional organelles. Neuronal autophagosomes form constitutively in the distal tip of the axon and are actively transported toward the soma, with cargo degradation initiated en route. Cargo turnover requires autophagosomes to fuse with lysosomes to acquire degradative enzymes; however, the timing and number of these fusion events in the axon have proven difficult to detect using microscopy alone. Here we use a quantitative model, parameterized and validated using data from live and fixed imaging of primary hippocampal neurons, to explore the autophagosome maturation process on a cellular scale. We demonstrate that retrograde autophagosome motility is independent from lysosomal fusion, and that most autophagosomes fuse with only a few lysosomes by the time they reach the soma. Furthermore, our imaging and model results highlight the two-step maturation of the autophagosome: fusion with a lysosome or late endosome is followed by the slow degradation of the autophagosomal inner membrane before actual cargo degradation can occur. Together, rigorous quantitative measurements and mathematical modeling elucidate the dynamics of autophagosome-lysosome interaction and autophagosomal maturation in the axon.

cell biology↗

bioRxiv2021

Optimizing microtubule arrangements for rapid cargo capture

Cellular functions such as autophagy, cell signaling and vesicular trafficking involve the retrograde transport of motor-driven cargo along microtubules. Typically, newly formed cargo engages in slow diffusive movement from its point of origin before attaching to a microtubule. In some cell types, cargo destined for delivery to the perinuclear region relies on capture at dynein-enriched loading zones located near microtubule plus-ends. Such systems include extended cell regions of neurites and fungal hyphae, where the efficiency of the initial diffusive loading process depends on the axial distribution of microtubule plus-ends relative to the initial cargo position. We use analytic mean first passage time calculations and numerical simulations to model diffusive capture processes in tubular cells, exploring how the spatial arrangement of microtubule plus-ends affects the efficiency of retrograde cargo transport. Our model delineates the key features of optimal microtubule ar-rangements that minimize mean cargo capture times. Namely, we show that configurations with a single long microtubule and broad distribution of additional microtubule plus-ends allow for efficient capture in a variety of different scenarios for retrograde transport. Live-cell imaging of microtubule plus-ends in Aspergillus nidulans hyphae indicates that their distributions exhibit these optimal qualitative features. Our results highlight important coupling effects between microtubule length distribution and retrograde cargo transport, providing guiding principles for the spatial arrangement of microtubules within tubular cell regions.

biophysics↗

bioRxiv2019

Hitching a Ride: Mechanics of Organelle Transport Through Linker-Mediated Hitchhiking

In contrast to the canonical picture of transport by direct attachment to motor proteins, recent evidence shows that a number of intracellular cargos navigate the cytoplasm by hitchhiking on motor-driven carrier organelles. We describe a quantitative model of intracellular cargo transport via hitchhiking, examining the efficiency of hitchhiking initiation as a function of geometric and mechanical parameters. We focus specifically on the parameter regime relevant to the hitchhiking motion of peroxisome organelles in fungal hyphae. Our work predicts the dependence of transport initiation rates on the distribution of cytoskeletal tracks and carrier organelles, as well as the number, length and flexibility of the linker proteins that mediate contact between the carrier and the hitchhiking cargo. Furthermore, we demonstrate that attaching organelles to microtubules can result in a substantial enhancement of the hitchhiking initiation rate in tubular geometries such as those found in fungal hyphae. This enhancement is expected to increase the overall transport rate of hitchhiking organelles, and lead to greater efficiency in organelle dispersion. Our results leverage a quantitative physical model to highlight the importance of organelle encounter dynamics in non-canonical intracellular transport.\n\nSIGNIFICANCEA variety of cellular components are transported via hitchhiking by attaching to other motile organelles. Defects in the molecular machinery responsible for organelle hitchhiking may be linked with neurodegenerative disorders. To date, no comprehensive physical models of this non-canonical mode of transport have been developed. In particular, the connection between molecular- and organelle-scale properties of hitchhiking components and their effect on cellular-scale transport has remained unclear. Here, we investigate the mechanics of hitchhiking initiation and explore organelle interactions that can modulate the efficiency of this process.

biophysics↗