Biology subjects

Bhowmick, D.

Publications and source records attributed to Bhowmick, D..

6 recordsLinked to original sources

bioRxiv2025

Compositional Analysis of Mouse Sperm Subpopulations During Capacitation In Vitro

Mammalian sperm must undergo capacitation to become competent for fertilization, yet this process is marked by substantial phenotypic heterogeneity among sperm cells. How such variability emerges and how it relates to fertilizing potential remain unresolved, in part because sperm subpopulations are typically analyzed independently despite being intrinsically interdependent. Here, we combine large-scale single-cell spectral flow cytometry with compositional statistical modeling to quantify how sperm population structure responds to controlled capacitation signals in vitro. Using cauda epididymal mouse sperm, we implemented a two-dimensional assay that systematically varies extracellular bicarbonate and free calcium--key regulators of capacitation--and classified millions of individual cells into four irreversible physiological states defined by cell viability and acrosome reaction status. We show that bicarbonate and calcium interact nonlinearly to redistribute sperm across these subpopulations, revealing structured responses that would be otherwise obscured in measurements lacking single-cell resolution. Elevated intracellular calcium was associated with increased cell death, while the highest proportions of live, acrosome-reacted sperm occurred under relatively low extracellular calcium conditions. To enable subpopulation-level analysis, we applied a hierarchical Dirichlet-multinomial regression model that accounts for multinomial sampling noise and between-male variability, yielding posterior probability surfaces that describe how sperm subpopulations reallocate across functional states as microenvironmental signaling conditions change. Together, these results demonstrate that capacitation is a stochastic, cell-population level process shaped by structured phenotypic heterogeneity. This framework provides a quantitative foundation for linking sperm subpopulation composition to measures of fertility competence and for improving existing interpretation of flow cytometry-based assessments of male fertility.

cell biology↗

bioRxiv2025

Protocol to optimize gain settings of Aurora for better data resolution

Full-spectrum flow cytometry has demonstrated clear advantages over conventional approach. Cyteks Aurora platform has played a pivotal role in popularizing this technology, even though SONY introduced a full-spectrum flow cytometer earlier. Full spectral cytometers can identify the autofluorescence and unmix the autofluorescence much better than conventional cytometers. The default gain setting for Aurora, known as the Cytek Assay Setting (CAS), is effective for its intended purpose. However, there is no clear evidence to confirm that CAS provides optimal data resolution. This technical note outlines a methodology for enhancing gain settings to achieve a two-to four-fold improvement in resolution on average.

cell biology↗

bioRxiv2025

Panel Perils: How Size, Fluorochrome Choices, and Unmixing Algorithms Shape Your Analysis Adventure!

IntroductionThe advent of full spectral flow cytometry has enabled the development of complex panels with over 35 colors, with the latest panels reaching 50 colors (1). This capability is made possible by cytometers equipped with numerous detectors beyond those in traditional cytometers and an expanded range of fluorochromes with emission peaks across the visible spectrum. However, our observations reveal significant challenges in the current unmixing, spread prediction, and panel design methodologies. Existing tools and guidelines, largely optimized for panels with up to 20+ colors, are limited in their ability to navigate this new ultra-high-color landscape. Without improvements in unmixing algorithms, predictive tools for spread, and design strategies, researchers risk creating suboptimal panels and obtaining inaccurate results. This article aims to highlight a range of emerging challenges associated with ultra-high parameter flow cytometry, particularly for practitioners accustomed to conventional panel design and analysis. As the field advances toward increasingly complex multiparameter experiments, novel issues have surfaced--many of which were previously unrecognized. Although this work does not provide comprehensive solutions to all of these observations, it underscores the need for continued methodological development. We anticipate that ongoing research by experts in the field will yield robust frameworks to address these challenges and advance best practices in high-dimensional cytometric analysis. Brief descriptionO_LIDifferent unmixing/compensation algorithms can result in different biological interpretations from the same raw dataset. C_LIO_LIA method to identify the optimal unmixing algorithm for accurate analysis is discussed. C_LIO_LIBoth panel size and specific fluorochrome combinations significantly impact population spread. C_LIO_LISSM (Spillover Spreading Matrix) values are influenced by panel size and fluorochrome combinations, which, if not carefully evaluated, may lead to misleading conclusions during panel design. C_LI

cell biology↗

bioRxiv2024

Modeling Diffusive Search by Non-Adaptive Sperm: Empirical and Computational Insights

During fertilization, mammalian sperm undergo a winnowing selection process that reduces the candidate pool of potential fertilizers from [~]106-1011 cells to 101-102 cells (depending on the species). Classical sperm competition theory addresses the positive or stabilizing selection acting on sperm phenotypes within populations of organisms but does not strictly address the developmental consequences of sperm traits among individual organisms that are under purifying selection during fertilization. It is the latter that is of utmost concern for improving assisted reproductive technologies (ART) because low fitness sperm may be inadvertently used for fertilization during interventions that rely heavily on artificial sperm selection, such as intracytoplasmic sperm injection (ICSI). Importantly, some form of sperm selection is used in nearly all forms of ART (e.g., differential centrifugation, swim-up, or hyaluronan binding assays, etc.). To date, there is no unifying quantitative framework (i.e., theory of sperm selection) that synthesizes causal mechanisms of selection with observed natural variation in individual sperm traits. In this report, we reframe the physiological function of sperm as a collective diffusive search process and develop multi-scale computational models to explore the causal dynamics that constrain sperm fitness during fertilization. Several experimentally useful concepts are developed, including a probabilistic measure of sperm fitness as well as an information theoretic measure of the magnitude of sperm selection, each of which are assessed under systematic increases in microenvironmental selective pressure acting on sperm motility patterns. Author SummaryFertilization in mammals requires many orders of magnitude more sperm than eggs to be fertilized. This study models collective sperm movement as a diffusive search process, combining experiments and simulations to explore how heterogeneity in motility patterns and microenvironmental complexity shape fertilization success. We introduce simple metrics to quantify sperm fitness and the magnitude of selection pressure imposed by the microenvironment, revealing that sperm phenotype distributions interact with environmental constraints to determine the range of sperm traits that ultimately support successful egg contact. These insights improve our understanding of sperm population dynamics and offer practical tools for optimizing assisted reproductive technologies in clinical and agricultural settings.

cell biology↗

bioRxiv2024

Mitochondria inside acute myeloid leukemia cells hydrolyze ATP to resist chemotherapy

Despite early optimism, therapeutics targeting oxidative phosphorylation (OxPhos) have faced clinical setbacks, stemming from their inability to distinguish healthy from cancerous mitochondria. Herein, we describe an actionable bioenergetic mechanism unique to cancerous mitochondria inside acute myeloid leukemia (AML) cells. Unlike healthy cells which couple respiration to the synthesis of ATP, AML mitochondria were discovered to support inner membrane polarization by consuming ATP. Because matrix ATP consumption allows cells to survive bioenergetic stress, we hypothesized that AML cells may resist cell death induced by OxPhos damaging chemotherapy by reversing the ATP synthase reaction. In support of this, targeted inhibition of BCL-2 with venetoclax abolished OxPhos flux without impacting mitochondrial membrane potential. In surviving AML cells, sustained polarization of the mitochondrial inner membrane was dependent on matrix ATP consumption. Mitochondrial ATP consumption was further enhanced in AML cells made refractory to venetoclax, consequential to downregulations in both the proton-pumping respiratory complexes, as well as the endogenous F1-ATPase inhibitor ATP5IF1. In treatment-naive AML, ATP5IF1 knockdown was sufficient to drive venetoclax resistance, while ATP5IF1 overexpression impaired F1-ATPase activity and heightened sensitivity to venetoclax. Collectively, our data identify matrix ATP consumption as a cancer-cell intrinsic bioenergetic vulnerability actionable in the context of mitochondrial damaging chemotherapy.

cancer biology↗

bioRxiv2020

'Range': A gain and dynamic range independent quantification of spread aiding in panel design

In conventional flowcytometry one detector (primary) is dedicated for one fluorochrome. However, photons usually end up in other detectors too (fluorescence spillover). Compensation is a process that corrects the spillover signal from all detectors except the primary detector. Post compensation, the photon counting error of spillover signals become evident as spreading of the data. The spreading induced by spillover impairs the ability to resolve stained cell population from the unstained one, potentially reducing or completely losing cell populations. For successful multi-color panel design, it is important to know the expected spillover to maximize the data resolution. The Spillover Spreading Matrix (SSM) can be used to estimate the spread, but the outcome is dependent on detector sensitivity. Simply, the same single stained sample produces different spillover spread values when detector(s) sensitivity is altered. Many researchers mistakenly use this artifact to "reduce" the spread by decreasing detector sensitivity. This can result in diminished capacity to resolve dimly expressing cell populations. Here, we introduce SQI (Spread Quantification Index), that can quantify the spillover spread independent of detector sensitivity and independent of dynamic range. This allows users to compare spillover spread between instruments having different types of detectors, which is not possible using SSM.

immunology↗