Biology subjects

Shroff, H.

Publications and source records attributed to Shroff, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Organelle Volume Facilitates Spindle Positioning During C. elegans Female Meiosis

Cortical positioning of oocyte meiotic spindles is required for reducing chromosome number by segregating chromosomes into polar bodies. In C. elegans, kinesin-1 transports membrane-bound organelles inward into a central ball that is hypothesized to push the meiotic spindle outward. Using focused ion beam scanning electron microscopy, we found that the percent volume occupied by membrane-bound organelles was 28% in a mature oocyte that has completed endocytosis of the yolk precursor, vitellogenin, compared to 17% in a less mature oocyte that has not yet endocytosed vitellogenin. We therefore hypothesized that blocking endocytosis of vitellogenin would reduce the size of the central ball of organelles packed inward by kinesin-1 and limit outward movement of the spindle. Depletion of vitellogenin or proteins required for endocytosis resulted in a smaller central volume of kinesin-coated organelles and defective spindle positioning. A computer simulation of a simple exclusion model faithfully recapitulated wildtype and mutant spindle position phenotypes. These results support a volume exclusion model for positioning acentriolar meiotic spindles.

cell biology↗

bioRxiv2026

Transient morphogenetic constraints organize self-assembling axon neighborhoods for robust yet flexible wiring

Nervous systems form wiring patterns that are reproducible across individuals. This reproducibility is thought to emerge from molecular encoding and developmental events, but their relative contributions remain unclear. We address this question in the C. elegans neuropil, where embryonic developmental dynamics and adult anatomy are resolved at single-cell resolution. We find that transient morphogenetic structures -- rosettes, corridor cells, pioneer axon scaffold -- restrict which axons make contact, shaping the neuropil into overlapping neighborhoods. This demonstrates how early events constrain wiring choices, but not whether they explain the resulting reproducibility. To explain, we use an agent-based model of stochastic innervation that recapitulates macro- and micro-level reproducibility, revealing a trade-off between physical constraint and molecular specificity that limits neighborhood size. Counterintuitively, less selective axons produce more reproducible wiring when constrained within neighborhoods. This trade-off lets nervous systems maximize reproducibility without having to molecularly encode every axon-contact, a strategy for robust yet flexible wiring.

neuroscience↗

bioRxiv2026

WHaloForce enables chemigenetic imaging of molecular tension in living cells and animals

Piconewton forces borne by individual proteins within complex assemblies underlie cell adhesion, migration, and tissue morphogenesis, yet remain difficult to image in living systems. Here, we introduce WHaloForce, a chemigenetic HaloTag-based tension sensor that converts force-dependent relief of tryptophan-mediated dye quenching into a fluorescence lifetime change. Optical tweezers revealed a switch-like unquenching transition near 5 pN, and the sensor responded reversibly to force changes in cells. WHaloForce enabled quantitative tension imaging of diverse force-bearing proteins (vinculin, E-cadherin, -catenin, and laminin) in mammalian cells, mouse tissue, and C. elegans. Bright synthetic dyes made tension measurements possible at endogenous expression levels. In C. elegans, vinculin and laminin showed opposite tension patterns between tissues, revealing distinct force-transmission routes through adhesions and the extracellular matrix. During ovulation, laminin tension accumulated over repeated stretch-relaxation cycles, scaling with cumulative loading history. WHaloForce thus offers a modular platform for imaging spatiotemporal tension patterns in living systems.

cell biology↗

bioRxiv2026

Experience-Dependent Gain Modulation Drives Thermosensory Responses in Behavior

Sensory neurons must extract behaviorally relevant features from dynamic environments while maintaining sensitivity across wide stimulus ranges. To understand how sensory encoding adapts to experience during behavior, we combine long-duration calcium imaging in freely moving C. elegans with a temperature-trajectory playback paradigm to determine how the thermosensory neuron AFD extracts behaviorally relevant sensory features during navigation. We observe that AFD functions as a leaky integrator of recently experienced temperature changes, accumulating thermal inputs over a rolling window of tens of seconds, resulting in calcium levels that represent recent temperature dynamics during runs. Importantly, we determine that AFD selectively amplifies responses to temperature changes near its learned preferred temperature. This experience-dependent gain control aligns encoding with the navigational goal, providing a mechanism for representing temperature preference within a derivative-based sensory system. A minimal mathematical model incorporating derivative detection, leaky integration, and temperature-dependent gain captures the calcium dynamics over a range of stimuli, and a simulation based on the mathematical model predicts goal-oriented locomotor strategies across stimulus regimes. Together, these findings show how gain control allows a derivative-based sensory code to represent an absolute goal and guide locomotory strategies during navigation. HighlightsO_LIAFD encodes recent temperature changes over behaviorally relevant timescales. C_LIO_LIAFD amplifies temperature-change responses within a learned temperature-centered gain window. C_LIO_LIGain control provides a mechanism for representing distance to temperature preference within the derivative-based sensory system. C_LIO_LIA mathematical model and simulation of derivative sensing, leaky integration, and gain control predicts AFD calcium responses and goal-oriented locomotory strategies across stimulus regimes. C_LI

neuroscience↗

bioRxiv2025

The CENP-A chaperone complex spatially organizes centromeres

Centromeres, defined by CENP-A-containing nucleosomes, direct the assembly of kinetochores for spindle attachment. In mitosis, CENP-A and the constitutive centromere-associated network (CCAN) of the inner kinetochore are arranged into bipartite subdomains within clearings of chromatin. However, it remains unclear whether any of these features exist before mitosis. We show that in interphase, CENP-A and the CCAN assemble [~]200-300 nm shell-like structures that enclose a chromatin-poor central cavity. Strikingly, this cavity is occupied by the interphase-specific CENP-A chaperone complex, which promotes CENP-A assembly once per cell cycle. However, chaperone presence, but not CENP-A incorporation, is required to generate both the shell architecture and the chromatin clearing. The CCAN scaffold CENP-C, which links CENP-A nucleosomes to the chaperone complex, exhibits radial organization spanning the entire structure and is essential for its formation. These data uncover a previously unrecognized structural role for the CENP-A chaperone machinery in establishing interphase centromere architecture and suggest a mechanism by which this machinery configures centromeres for faithful kinetochore assembly and genome stability.

cell biology↗

bioRxiv2025

Observing biological spatio-angular structures and dynamics with statistical image reconstruction and polarized fluorescence microscopy

Understanding molecular orientation and density distributions is essential for exploring biological structure and function. Polarized fluorescence microscopy (PFM) provides insights into molecular architecture but struggles to resolve three-dimensional (3D) molecular orientation distributions, particularly in densely labeled or structurally complex specimens. To address this, we introduce the efficient generalized Richardson-Lucy (eGRL) algorithm, a robust framework for reconstructing 3D molecular density and orientation (spatio-angular) distributions from PFM data. By modeling the imaging process in spatio-angular hyperspace, we propose a maximum-likelihood solution enhanced by dimensionality reduction and angular domain transformation to overcome computational challenges. eGRL improves accuracy and efficiency across different PFM implementations, enabling use on standard platforms. We utilize our methods to resolve biological spatio-angular structures and dynamics otherwise impossible to resolve, including the tangential alignment of actin filaments in U2OS cells, nanowire-guided cytoskeletal organization in NIH3T3 cells, rotational actin patterns in live HeLa protrusions, and membrane tension-induced anisotropy in live macrophages.

bioengineering↗

bioRxiv2025

HD2Net: A Deep Learning Framework for Simultaneous Denoising and Deaberration in Fluorescence Microscopy

Fluorescence microscopy is essential for biological research, offering high-contrast imaging of microscopic structures. However, the quality of these images is often compromised by optical aberrations and noise, particularly in low signal-to-noise ratio (SNR) conditions. While adaptive optics (AO) can correct aberrations, it requires costly hardware and slows down imaging; whereas current denoising approaches boost the SNR but leave out the aberration compensation. To address these limitations, we introduce HD2Net, a deep learning framework that enhances image quality by simultaneously denoising and suppressing the effect of aberrations without the need for additional hardware. Building on our previous work, HD2Net incorporates noise estimation and aberration removal modules, effectively restoring images degraded by noise and aberrations. Through comprehensive evaluation of synthetic phantoms and biological data, we demonstrate that HD2Net outperforms existing methods, significantly improving image resolution and contrast. This framework offers a promising solution for enhancing biological imaging, particularly in challenging aberrating and low-light conditions.

bioengineering↗

bioRxiv2024

Imaging the extracellular matrix in live tissues and organisms with a glycan-binding fluorophore

All multicellular systems produce and dynamically regulate extracellular matrices (ECM) that play important roles in both biochemical and mechanical signaling. Though the spatial arrangement of these extracellular assemblies is critical to their biological functions, visualization of ECM structure is challenging, in part because the biomolecules that compose the ECM are difficult to fluorescently label individually and collectively. Here, we present a cell-impermeable small molecule fluorophore, termed Rhobo6, that turns on and red shifts upon reversible binding to glycans. Given that most ECM components are densely glycosylated, the dye enables wash-free visualization of ECM, in systems ranging from in vitro substrates to in vivo mouse mammary tumors. Relative to existing techniques, Rhobo6 provides a broad substrate profile, superior tissue penetration, nonperturbative labeling, and negligible photobleaching. This work establishes a straightforward method for imaging the distribution of ECM in live tissues and organisms, lowering barriers for investigation of extracellular biology.

biochemistry↗

bioRxiv2024

Live-cell single-molecule fluorescence microscopy for protruding organelles reveals regulatory mechanisms of MYO7A-driven cargo transport in stereocilia of inner ear hair cells

Stereocilia are unidirectional F-actin-based cylindrical protrusions on the apical surface of inner ear hair cells and function as biological mechanosensors of sound and acceleration. Development of functional stereocilia requires motor activities of unconventional myosins to transport proteins necessary for elongating the F-actin cores and to assemble the mechanoelectrical transduction (MET) channel complex. However, how each myosin localizes in stereocilia using the energy from ATP hydrolysis is only partially understood. In this study, we develop a methodology for live-cell single-molecule fluorescence microscopy of organelles protruding from the apical surface using a dual-view light-sheet microscope, diSPIM. We demonstrate that MYO7A, a component of the MET machinery, traffics as a dimer in stereocilia. Movements of MYO7A are restricted when scaffolded by the plasma membrane and F-actin as mediated by MYO7As interacting partners. Here, we discuss the technical details of our methodology and its future applications including analyses of cargo transportation in various organelles.

cell biology↗

bioRxiv2024

Altruistic feeding and cell-cell signaling during bacterial differentiation actively enhance phenotypic heterogeneity

Starvation triggers bacterial spore formation, a committed differentiation program that transforms a vegetative cell into a dormant spore. Cells in a population enter sporulation non-uniformly to secure against the possibility that favorable growth conditions, which puts sporulation-committed cells at a disadvantage, may resume. This heterogeneous behavior is initiated by a passive mechanism: stochastic activation of a master transcriptional regulator. Here, we identify a cell-cell communication pathway that actively promotes phenotypic heterogeneity, wherein Bacillus subtilis cells that start sporulating early utilize a calcineurin-like phosphoesterase to release glycerol, which simultaneously acts as a signaling molecule and a nutrient to delay non-sporulating cells from entering sporulation. This produced a more diverse population that was better poised to exploit a sudden influx of nutrients compared to those generating heterogeneity via stochastic gene expression alone. Although conflict systems are prevalent among microbes, genetically encoded cooperative behavior in unicellular organisms can evidently also boost inclusive fitness.

microbiology↗

bioRxiv2024

Three-dimensional spatio-angular fluorescence microscopy with a polarized dual-view inverted selective-plane illumination microscope (pol-diSPIM)

Polarized fluorescence microscopy is a valuable tool for measuring molecular orientations, but techniques for recovering three-dimensional orientations and positions of fluorescent ensembles are limited. We report a polarized dual-view light-sheet system for determining the three-dimensional orientations and diffraction-limited positions of ensembles of fluorescent dipoles that label biological structures, and we share a set of visualization, histogram, and profiling tools for interpreting these positions and orientations. We model our samples, their excitation, and their detection using coarse-grained representations we call orientation distribution functions (ODFs). We apply ODFs to create physics-informed models of image formation with spatio-angular point-spread and transfer functions. We use theory and experiment to conclude that light-sheet tilting is a necessary part of our design for recovering all three-dimensional orientations. We use our system to extend known two-dimensional results to three dimensions in FM1-43-labelled giant unilamellar vesicles, fast-scarlet-labelled cellulose in xylem cells, and phalloidin-labelled actin in U2OS cells. Additionally, we observe phalloidin-labelled actin in mouse fibroblasts grown on grids of labelled nanowires and identify correlations between local actin alignment and global cell-scale orientation, indicating cellular coordination across length scales.

biophysics↗

bioRxiv2023

Phase diversity-based wavefront sensing for fluorescence microscopy

Fluorescence microscopy is an invaluable tool in biology, yet its performance is compromised when the wavefront of light is distorted due to optical imperfections or the refractile nature of the sample. Such optical aberrations can dramatically lower the information content of images by degrading image contrast, resolution, and signal. Adaptive optics (AO) methods can sense and subsequently cancel the aberrated wavefront, but are too complex, inefficient, slow, or expensive for routine adoption by most labs. Here we introduce a rapid, sensitive, and robust wavefront sensing scheme based on phase diversity, a method successfully deployed in astronomy but underused in microscopy. Our method enables accurate wavefront sensing to less than {lambda}/35 root mean square (RMS) error with few measurements, and AO with no additional hardware besides a corrective element. After validating the method with simulations, we demonstrate calibration of a deformable mirror > 100-fold faster than comparable methods (corresponding to wavefront sensing on the ~100 ms scale), and sensing and subsequent correction of severe aberrations (RMS wavefront distortion exceeding {lambda}/2), restoring diffraction-limited imaging on extended biological samples.

bioengineering↗

bioRxiv2023

Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics into the imaging path. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations. We use simulations and experiments to show that applying the trained de-aberration networks outperforms alternative methods, providing restoration on par with adaptive optics techniques; and subsequently apply the networks to diverse datasets captured with confocal, light-sheet, multi-photon, and super-resolution microscopy. In all cases, the improved quality of the restored data facilitates qualitative image inspection and improves downstream image quantitation, including orientational analysis of blood vessels in mouse tissue and improved membrane and nuclear segmentation in C. elegans embryos.

bioengineering↗

bioRxiv2023

Cell division machinery drives cell-specific gene activation during bacterial differentiation

When faced with starvation, the bacterium Bacillus subtilis transforms itself into a dormant cell type called a "spore". Sporulation initiates with an asymmetric division event, which requires the relocation of the core divisome components FtsA and FtsZ, after which the sigma factor {sigma}F is exclusively activated in the smaller daughter cell. Compartment specific activation of {sigma}F requires the SpoIIE phosphatase, which displays a biased localization on one side of the asymmetric division septum and associates with the structural protein DivIVA, but the mechanism by which this preferential localization is achieved is unclear. Here, we isolated a variant of DivIVA that indiscriminately activates {sigma}F in both daughter cells due to promiscuous localization of SpoIIE, which was corrected by overproduction of FtsA and FtsZ. We propose that a unique feature of the sporulation septum, defined by the cell division machinery, drives the asymmetric localization of DivIVA and SpoIIE to trigger the initiation of the sporulation program.

microbiology↗

bioRxiv2022

Label-free cleared tissue microscopy and machine learning for 3D histopathology of biomaterial implants

Tissue clearing of whole intact organs has enhanced imaging by enabling the exploration of tissue structure at a subcellular level in three-dimensional space. Although clearing and imaging of the whole organ have been used to study tissue biology, the microenvironment in which cells evolve to adapt to biomaterial implants or allografts in the body is poorly understood. Obtaining high-resolution information from complex cell-biomaterial interactions with volumetric landscapes represents a key challenge in the fields of biomaterials and regenerative medicine. To provide a new approach to examine how tissue responds to biomaterial implants, we apply cleared tissue light-sheet microscopy and three-dimensional reconstruction to utilize the wealth of autofluorescence information for visualizing and contrasting anatomical structures. This study demonstrates the adaptability of the clearing and imaging technique to provide sub-cellular resolution (0.6m isotropic) 3D maps of various tissue types, using samples from fully intact peritoneal organs to volumetric muscle loss injury specimens, with and without biomaterials implants. We further apply computational-driven image classification to analyze the autofluorescence spectrum at multiple emission wavelengths to categorize tissue types in the tissue-biomaterial microenvironment.

bioengineering↗

bioRxiv2022

Three-dimensional structured illumination microscopy with enhanced axial resolution

We present two distinct, complementary methods for improving axial resolution in three-dimensional structured illumination microscopy (3D SIM) with minimal or no modification to the optical system. First, we show that placing a mirror directly opposite the sample enables 4-beam interference with higher spatial frequency content than 3D SIM illumination, offering near-isotropic imaging with [~]120 nm lateral and 160 nm axial resolution. Second, we develop an improved deep learning method that can be directly applied to 3D SIM data, obviating the need for additional hardware. This procedure results in [~]120 nm isotropic resolution and can be combined with denoising to facilitate volumetric imaging spanning dozens of time points. We demonstrate the potential of these advances by imaging a variety of cellular samples, delineating the nanoscale distribution of vimentin and microtubule filaments, observing the relative positions of caveolar coat proteins and lysosomal markers, and visualizing rich cytoskeletal dynamics within T-cells in the early stages of immune synapse formation.

cell biology↗

bioRxiv2022

Coiling of cellular protrusions around extracellular fibers

Protrusions at the leading-edge of a cell play an important role in sensing the extracellular cues, during cellular spreading and motility. Recent studies provided indications that these protrusions wrap (coil) around the extra-cellular fibers. The details of this coiling process, and the mechanisms that drive it, are not well understood. We present a combined theoretical and experimental study of the coiling of cellular protrusions on fibers of different geometry. Our theoretical model describes membrane protrusions that are produced by curved membrane proteins that recruit the protrusive forces of actin polymerization, and identifies the role of bending and adhesion energies in orienting the leading-edges of the protrusions along the azimuthal (coiling) direction. Our model predicts that the cells leading-edge coils on round fibers, but the coiling ceases for a fiber of elliptical (flat) cross-section. These predictions are verified by 3D visualization and quantitation of coiling on suspended fibers using Dual-View light-sheet microscopy (diSPIM). Overall, we provide a theoretical framework supported by high spatiotemporal resolution experiments capable of resolving coiling of cellular protrusions around extracellular fibers of varying diameters. Significance StatementCells adhere and migrate in environments that are composed of fibrous structures, such as the thin filaments of the extracellular matrix, or the wider axons and dendrites of neurons. In recent experiments, cells have been observed to form leading edge protrusions on such surfaces, that seem to coil around the extracellular fibers. However, the mechanism responsible for the formation of such coiling protrusions is not understood. Here, we provide a combined experimental and theoretical approach to explain the emergence of coiling protrusions. Our model is based on the self-organization of curved proteins that recruit actin polymerization at the leading edge of the cell, when spreading over an adhesive fiber.

biophysics↗

bioRxiv2022

Incorporating the image formation process into deep learning improves network performance in deconvolution applications

We present Richardson-Lucy Network (RLN), a fast and lightweight deep learning method for 3D fluorescence microscopy deconvolution. RLN combines the traditional Richardson-Lucy iteration with a fully convolutional network structure, improving network interpretability and robustness. Containing only [~]16 thousand parameters, RLN enables 4- to 50-fold faster processing than purely data-driven networks with many more parameters. By visual and quantitative analysis, we show that RLN provides better deconvolution, better generalizability, and fewer artifacts than other networks, especially along the axial dimension. RLN outperforms Richardson-Lucy deconvolution on volumes contaminated with severe out of focus fluorescence or noise and provides 4- to 6-fold faster reconstructions of large, cleared tissue datasets than classic multi-view pipelines. We demonstrate RLNs performance on cells, tissues, and embryos imaged with widefield-, light sheet-, and structured illumination microscopy.

biophysics↗