Biology subjects

Banerjee, T.

Publications and source records attributed to Banerjee, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Autoregulation of RNase E synthesis: Predominant impact of a branched RNA stem-loop to which the nuclease binds

Due to its crucial role in proteobacterial RNA processing and degradation, the synthesis of the endonuclease RNase E is tightly controlled by a post-transcriptional autoregulatory mechanism governed by the 5' untranslated region of rne mRNA, the transcript that encodes it. Previous studies have identified one structural component of the rne 5' untranslated region (hp2) that helps to mediate this process in Escherichia coli by binding to RNase E. Here, we show that another component (hp3), a branched stem-loop, makes an even greater contribution to feedback regulation of RNase E synthesis and that the effects of hp2 and hp3 are additive, suggesting independent function. Despite the structural complexity of hp3, a single constituent branch appears to be the principal source of its regulatory activity. This branch also enables hp3 to bind RNase E with high affinity. The secondary structure of this branch, including the presence of two internal loops essential for its impact, is conserved in diverse Enterobacterales species, whereas the sequence of the internal loops is not. We propose that hp2 and hp3 mediate autoregulation by recruiting RNase E to the rne transcript.

molecular biology↗

bioRxiv2026

NanoCellAnnotator: Formalizing Expert Cell Type Annotation with Large Language Models

MotivationCell-type annotation in spatial transcriptomics is challenging due to sparse gene panels, spatial heterogeneity, and limited availability of tissue-matched reference atlases. Recent approaches have explored large language models (LLMs) for integrating biological knowledge during annotation, but unconstrained inference can produce biologically unsupported predictions and hallucinated cell types. In addition, many LLM-based pipelines rely on large cloud-hosted models that limit reproducibility and deployment in privacy-sensitive environments. ResultsWe introduce NanoCellAnnotator, a biologically constrained and confidence-aware framework for automated cell-type annotation in spatial transcriptomics. The framework de-couples spatial structure discovery, deterministic biological evidence construction, and language-model-based semantic inference. Spatial clusters are identified using hybrid spatially regularized non-negative matrix factorization (hSNMF), after which cluster-level marker genes are abstracted into ontology-derived functional programs using Gene Ontology enrichment and GO-slim projection. A lightweight locally executable language model performs constrained label selection within a curated admissible label space derived from PanglaoDB and CellMarker. Annotation confidence is estimated independently using marker support strength and lineage separation, enabling ambiguous or heterogeneous clusters to be explicitly flagged. We evaluate NanoCellAnnotator on Xenium spatial transcriptomics data from intrahepatic cholangiocarcinoma and an independent breast cancer spatial transcriptomics dataset. The framework recovers canonical cell populations with high confidence while identifying heterogeneous or transitional spatial domains as ambiguous. Agreement with manual annotations was evaluated using accuracy and adjusted Rand index. AvailabilityCode available at https://github.com/ishtyaqmahmud/NanoCellAnnotator.

bioinformatics↗

bioRxiv2026

Ambiguity-Aware Multi-Stage Cell-Type Annotation for Spatial Transcriptomics

Spatial transcriptomics enables characterization of cellular organization in intact tissue, but robust cell-type annotation remains challenging due to heterogeneous expression profiles, mixed populations, and transitional states. Existing methods often enforce a single label per cluster, obscuring biologically meaningful ambiguity and producing overconfident assignments. We propose an ambiguity-aware, multi-stage framework for spatial cell-type annotation. The method combines hybrid spatial-feature clustering with constrained language-model inference over curated label sets, and assigns confidence scores based on marker coverage, candidate separation, and entropy. Low-confidence clusters are selectively refined via local reclustering of ambiguous regions, while unresolved clusters are preserved as mixed rather than forcibly labeled. Applied to 10x Genomics Xenium spatial transcriptomics data from cholangiocarcinoma, the proposed refinement reduces cluster-level ambiguity from 16.1% to 2.27% and cell-level ambiguity from 18.4% to 0.86%, while improving confidence calibration. Spatial ablation confirms that topological integration resolves structural ambiguity over feature-only baselines, while constrained inference via a lightweight language model ensures scalable and biologically coherent annotations. These results highlight the importance of explicit ambiguity handling for reliable spatial annotation in heterogeneous tumors.

bioinformatics↗

bioRxiv2026

HyperNiche: Learning Heterophilic Cellular Niches with Hypergraph Neural Networks

We propose HyperNiche, a hypergraph-based framework for modeling higher-order, heterogeneous cellular niches from spatial transcriptomics data. Unlike conventional graph-based methods that rely on pairwise similarity and tend to produce homogeneous clusters, HyperNiche learns anchor-centered hyperedges through a compatibility-driven mechanism that captures both homophilic and heterophilic relationships among cells. By decoupling node roles into anchor and member representations and integrating spatial geometry into hyperedge construction, the model enables the discovery of multicellular niches that span diverse cell types. We evaluate HyperNiche on high-plex Xenium spatial transcriptomics datasets from breast and lung cancer tissue microarrays, demonstrating improvements over state-of-the-art graph-based baselines in clustering performance (ARI, NMI) and biological interpretability. Further analysis shows that HyperNiche produces hyperedges with significantly higher intra-edge feature diversity, indicating an enhanced ability to capture heterogeneous cellular niches compared to similarity-based models. These results highlight the importance of higher-order relational modeling for understanding complex spatial tissue organization and tumor microenvironments.

bioinformatics↗

bioRxiv2026

Counterfactual Modeling of Directional Cell Cell Influence in Spatial Transcriptomics

Understanding how neighboring cells influence cellular states is central to spatial transcriptomics, yet most existing methods rely on correlation or predefined ligand-receptor (LR) pairs and do not explicitly test directionality. We introduce a counterfactual, intervention-based framework for inferring directional cell-cell influence that is LR-agnostic and tests sender specificity. A neighborhood-conditioned graph model predicts receiver cell state from local spatial context. Directional influence is quantified by counterfactually replacing neighbors of a candidate sender type and measuring the resulting displacement in predicted receiver state. We define a Counterfactual Directionality Score (CDS) that quantifies directional influence, and compute pair-level CDS by aggregating across receiver cells and test cores for each ordered sender-receiver pair. Applied to Xenium cholangiocarcinoma tissue microarrays (38 cores), the framework identified reproducible, asymmetric interactions between tumor, immune, and stromal compartments, most prominently Tumor-EMT [->] Macrophage (CDS = 0.0828) and Fibroblast [->] Macrophage (CDS = 0.0582). Effects exceeded label-permutation and spatial-shuffle null models (p < 0.001, FDR-controlled) and remained stable under core-level bootstrap resampling. Inferred directional strengths correlated strongly with matched LR scores (r = 0.758, p = 0.0027), supporting biological concordance. These results demonstrate counterfactual testing as a statistically rigorous and scalable approach for directional cell-cell communication analysis in spatial transcriptomics.

cell biology↗

bioRxiv2026

Spatially Anchored Regulatory State Inference in Melanoma

Spatial transcriptomics (ST) captures gene expression within tissue architecture but lacks direct regulatory information, while single-cell multiome assays profile transcriptional and chromatin states without spatial context. We present a framework for spatially anchored regulatory inference that integrates Visium ST with single-cell multiome data to infer spatially resolved regulatory programs. Building upon GraphST, we introduce spatially regularized cell-to-spot mapping and propagate chromatin accessibility and transcription factor motif activity into tissue space. Regulatory analysis is performed at the spatial domain level via joint differential expression and accessibility testing, along with quantitative concordance assessment. Applied to melanoma tissue sections, the framework reveals spatially localized regulatory programs and shows that assignment strategy substantially affects downstream regulatory stability. This modular approach enables interpretable gene-, peak-, and transcription factor-level outputs for multimodal spatial analysis.

bioinformatics↗

bioRxiv2026

Membrane Kymograph Generator: A cross-platform GUI software for automated generation and analysis of kymographs along dynamic cell boundaries

SummaryThe plasma membrane and accompanying cortex serve as one of the major hubs of the signal transduction and cytoskeletal activities that collectively regulate numerous cell physiological processes such as migration, polarity, macropinocytosis, phagocytosis, cytokinesis, etc. Yet, dynamically tracking membrane-cortex associated protein or lipid kinetics over time from live-cell image series remains a challenging task, primarily due to the difficulty of accurately extracting and aligning the cell boundary between consecutive frames, as the cell continuously deforms and moves. Here, we present Membrane Kymograph Generator, a cross-platform software that accepts multichannel time-lapse live-cell fluorescent imaging datasets as input and automates the cumbersome, heuristic process of boundary tracking, inter-frame alignment, and intensity sampling along the boundary. The software implements a rotational offset minimization algorithm that circularly aligns boundaries across consecutive frames by exhaustively searching for the optimal angular shift that minimizes point-to-point distances, while handling variations in boundary point counts due to cell shape changes. The software outputs kymographs that represent spatiotemporal dynamics of different membrane-associated proteins or biosensors, allows users to fine-tune visualization parameters through an interactive interface, and provides built-in correlation analysis tools for multi-channel datasets. Furthermore, the software allows advanced programmatic usage for batch processing and further analysis via a native API. Our validation tests demonstrated that the Membrane Kymograph Generator can be used to accurately track, visualize, and quantitate the spatial kinetics of a wide array of membrane proteins and lipid biosensors over extended time periods, in a variety of cell types, including Dictyostelium amoeba, human neutrophils, mouse macrophages, and different mammalian cancer cells. The GUI-based software is user-friendly, does not require any technical expertise from users, and significantly reduces the manual effort and time required for kymograph generation and downstream analysis, while ensuring high accuracy and reproducibility. Availability and ImplementationMembrane Kymograph Generator is a free and open-source software, licensed under GNU General Public License 3.0 or later. This software is cross-platform: It can be graphically installed on both x86-64 and AArch64/ARM64 computers, running either Windows, macOS, or any standard Linux distribution. The software is distributed as single installer files (and portable executables) targeting specific hardware architectures and operating systems, and hence, it can be installed natively without any dependency resolution. The source code, detailed documentation, specific installers, portable binaries, and test data are freely available at https://github.com/tatsatb/membrane-kymograph-generator. Additionally, since the software is written in Python, it can also be installed inside any Python environment using PIP package manager (package ID: https://pypi.org/project/membrane-kymograph) and can also be interacted via a built-in Python API.

bioinformatics↗

bioRxiv2025

Spatial distribution of cytoskeleton-mediated feedback controls cell polarization: a computational study

In the social amoeba Dictyostelium, cell motility is regulated through a signal transduction excitable network that interfaces with the cytoskeleton to control actin polymerization patterns. In turn, the cytoskeleton influences the signaling machinery via several feedback loops, but the nature and function of this feedback remain poorly understood. In this study, we use computational models to discern the essential role of complementary positive and negative feedback loops in polarizing cells. We contrast two potential mechanisms for the negative feedback: local inhibition and global inhibition. Our results indicate that both mechanisms can stabilize the leading edge and inhibit actin polymerization in other sites, preventing multipolarity. While some experimental perturbations align more closely with the local inhibition model, statistical analyses reveal its limited polarization potential within a wide excitability range. Conversely, global inhibition more effectively suppresses secondary and tertiary leading-edge formation, making it a more robust polarization mechanism. This raises an intriguing question: if local inhibition better replicates experimental observations but is less effective for polarization than local excitation and global inhibition, could there be a supplementary mechanism enhancing its polarization potential? To address this, we propose a novel mechanism involving the dynamic partitioning of back molecules which enhances communication between the front and back of the cell and can be leveraged by local feedback interactions between the cytoskeleton and signal transduction to improve polarization efficiency.

cell biology↗

bioRxiv2024

Multiplexed functional analysis of TAP2 variants in regulating MHC-I cell surface abundance reveals overexpression of PLK1 downregulates antigen presentation.

The abundance of MHC-I on the cell surface depends on its association with antigenic peptides transported to the endoplasmic reticulum by the Transporter Associated with Antigen Processing (TAP), a peptide channel composed of TAP1 and TAP2. We functionally screened over 1400 TAP2 variants for effects on MHC-I cell surface abundance. Amino-acid substitutions of loss of function (LOF) variants clustered in the NTP-binding domain and along the TAP1-TAP2 binding interface, suggesting that these variants interfered with TAP conformational changes associated with peptide transport. Some LOF variants carried potential phosphomimetic substitutions; one such substitution at Ser251 was embedded in a sequence context consistent with the phosphorylation motif of PLK kinases. Inhibition of PLK kinases increased MHC-I surface expression, while overexpression of PLK1 in cells decreased MHC-I in wild type TAP2, but not in TAP2-S251A-expressing cells. Importantly, site-specific phosphorylation of TAP2 in human tumor samples correlated with alterations of gene expression in the cell cycle and antigen presentation pathways, consistent with the notion that phosphorylation downregulates antigenic peptide transport in human tumors. These data strongly support the hypothesis that in cancer cells, TAP2 phosphorylation by PLK1, and perhaps other kinases, can downregulate the antigen presentation process.

cancer biology↗

bioRxiv2024

PIP5K-Ras bistability initiates plasma membrane symmetry breaking to regulate cell polarity and migration

Symmetry breaking is a fundamental process that underlies key cellular behaviors such as cell polarity and migration, but the mechanism - how a uniform plasma membrane spontaneously transitions to an asymmetric state - is still unknown. Here in this study, using a combination of Dictyostelium amoeba, multiple mammalian leukocytes, and human cancer cells and 3D organoid systems, we monitored the localization dynamics of RasGTP and PIP5K, dissected the effects of eliminating, conditionally increasing, or optogenetically manipulating membrane PIP5K levels, screened for key regulators of Ras activation, and tracked single-molecules of PIP5K. Our data converge on a core biochemical circuit involving mutually inhibitory interactions between PIP5K and RasGTP that is both necessary and sufficient for symmetry breaking. The process is initiated by stochastic, localized Ras activation coupled with a decrease in the lifetime of the association of PIP5K with the membrane. A resulting localized reduction in PI(4,5)P2 facilitates the recruitment of a RasGEF to the corresponding domain, amplifying RasGTP production through a positive feedback loop. Dissociated PIP5K relocates to other membrane regions, where it suppresses Ras activation. These events separate the membrane into distinct active and inactive zones, even when receptor inputs or cytoskeletal activities are absent. This same core biochemical circuit controls the spatial organization of downstream PI3K/Akt/Rac signaling and actin/actomyosin activities, which generate the localized protrusions to define polarity and migration mode. While many models have been forwarded to explain polarity or symmetry breaking, the PIP5K-Ras mutually inhibitory bistable circuit we present here is the first universal molecular mechanism to explain the initiation of asymmetry as well as subsequent polarity and migration.

cell biology↗

bioRxiv2023

Ras-mediated homeostatic control of front-back signaling dictates cell polarity

Studies in the model systems, Dictyostelium amoebae and HL-60 neutrophils, have shown that local Ras activity directly regulates cell motility or polarity. Localized Ras activation on the membrane is spatiotemporally regulated by its activators, RasGEFs, and inhibitors, RasGAPs, which might be expected to create a stable front and back, respectively, in migrating cells. Focusing on C2GAPB in amoebae and RASAL3 in neutrophils, we investigated how Ras activity along the cortex controls polarity. Since existing gene knockout and overexpression studies can be circumvented, we chose optogenetic approaches to assess the immediate, local effects of these Ras regulators on the cell cortex. In both cellular systems, optically targeting the respective RasGAPs to the cell front extinguished existing protrusions and changed the direction of migration, as might be expected. However, when the expression of C2GAPB was induced globally, amoebae polarized within hours. Furthermore, within minutes of globally recruiting either C2GAPB in amoebae or RASAL3 in neutrophils, each cell type polarized and moved more rapidly. Targeting the RasGAPs to the cell backs exaggerated these effects on migration and polarity. Overall, in both cell types, RasGAP-mediated polarization was brought about by increased actomyosin contractility at the back and sustained, localized F-actin polymerization at the front. These experimental results were accurately captured by computational simulations in which Ras levels control front and back feedback loops. The discovery that context-dependent Ras activity on the cell cortex has counterintuitive, unanticipated effects on cell polarity can have important implications for future drug-design strategies targeting oncogenic Ras.

cell biology↗

bioRxiv2023

Chronic chemogenetic activation of hippocampal progenitors enhances adult neurogenesis and modulates anxiety-like behavior and fear extinction learning

Adult hippocampal neurogenesis is a lifelong process that involves the integration of newborn neurons into the hippocampal network, and plays a role in cognitive function and the modulation of mood-related behavior. Here, we sought to address the impact of chemogenetic activation of adult hippocampal progenitors on distinct stages of progenitor development, including quiescent stem cell activation, progenitor turnover, differentiation and morphological maturation. We find that hM3Dq-DREADD-mediated activation of nestin-positive adult hippocampal progenitors recruits quiescent stem cells, enhances progenitor proliferation, increases doublecortin-positive newborn neuron number, accompanied by an acceleration of differentiation and morphological maturation, associated with increased dendritic complexity. Behavioral analysis indicated anxiolytic behavioral responses in transgenic mice subjected to chemogenetic activation of adult hippocampal progenitors at timepoints when newborn neurons are predicted to integrate into the mature hippocampal network. Furthermore, we noted an enhanced fear memory extinction on a contextual fear memory learning task in transgenic mice subjected to chemogenetic activation of adult hippocampal progenitors. Our findings indicate that hM3Dq-DREAD-mediated chemogenetic activation of adult hippocampal progenitors impacts distinct aspects of hippocampal neurogenesis, associated with the regulation of anxiety-like behavior and fear memory extinction.

neuroscience↗

bioRxiv2023

DNA Repair Function Scores for 2172 Variants in the BRCA1 Amino-Terminus

Single nucleotide variants are the most frequent type of sequence changes detected in the genome and these are frequently variants of uncertain significance (VUS). VUS are changes in DNA for which disease risk association is unknown. Thus, methods that classify the functional impact of a VUS can be used as evidence for variant interpretation. In the case of the breast and ovarian cancer specific tumor suppressor protein, BRCA1, pathogenic missense variants frequently score as loss of function in an assay for homology-directed repair (HDR) of DNA double-strand breaks. We previously published functional results using a multiplexed assay for 1056 amino acid substitutions residues 2-192 in the amino terminus of BRCA1. In this study, we have re-assessed the data from this multiplexed assay using an improved analysis pipeline. These new analysis methods yield functional scores for more variants in the first 192 amino acids of BRCA1, plus we report new results for BRCA1 amino acid residues 193-302. We now present the functional classification of 2172 BRCA1 variants in BRCA1 residues 2-302 using the multiplexed HDR assay. Comparison of the functional determinations of the missense variants with clinically known benign or pathogenic variants indicated 93% sensitivity and 100% specificity for this assay. The results from BRCA1 variants tested in this assay are a resource for clinical geneticists for evidence to evaluate VUS in BRCA1. AUTHOR SUMMARYMost missense substitutions in BRCA1 are variants of unknown significance (VUS), and individuals with a VUS in BRCA1 cannot know from genetic information alone whether this variant predisposes to breast or ovarian cancer. We apply a multiplexed functional assay for homology directed repair of DNA double strand breaks to assess variant impact on this important BRCA1 protein function. We analyzed 2172 variants in the amino-terminus of BRCA1 and demonstrate that variants that are known as pathogenic have a loss of function in the DNA repair assay. Conversely, variants that are known to be benign are functionally normal in the multiplexed assay. We suggest that these functional determinations of BRCA1 variants can be used to augment the information that clinical cancer geneticists provide to patients who have a VUS in BRCA1.

cancer biology↗

bioRxiv2023

A dynamic partitioning mechanism polarizes membrane protein distribution

The plasma membrane is widely regarded as the hub of the signal transduction network activities that drives numerous physiological responses, including cell polarity and migration. Yet, the symmetry breaking process in the membrane, that leads to dynamic compartmentalization of different proteins, remains poorly understood. Using multimodal live-cell imaging, here we first show that multiple endogenous and synthetic lipid-anchored proteins, despite maintaining stable tight association with the inner leaflet of the plasma membrane, were unexpectedly depleted from the membrane domains where the signaling network was spontaneously activated such as in the new protrusions as well as within the propagating ventral waves. Although their asymmetric patterns resembled those of standard peripheral "back" proteins such as PTEN, unlike the latter, these lipidated proteins did not dissociate from the membrane upon global receptor activation. Our experiments not only discounted the possibility of recurrent reversible translocation from membrane to cytosol as it occurs for weakly bound peripheral membrane proteins, but also ruled out the necessity of directed vesicular trafficking and cytoskeletal supramolecular structure-based restrictions in driving these dynamic symmetry breaking events. Selective photoconversion-based protein tracking assays suggested that these asymmetric patterns instead originate from the inherent ability of these membrane proteins to "dynamically partition" into distinct domains within the plane of the membrane. Consistently, single-molecule measurements showed that these lipid-anchored molecules have substantially dissimilar diffusion profiles in different regions of the membrane. When these profiles were incorporated into an excitable network-based stochastic reaction-diffusion model of the system, simulations revealed that our proposed "dynamic partitioning" mechanism is sufficient to give rise to familiar asymmetric propagating wave patterns. Moreover, we demonstrated that normally uniform integral and lipid-anchored membrane proteins in Dictyostelium and mammalian neutrophil cells can be induced to partition spatiotemporally to form polarized patterns, by optogenetically recruiting membrane domain-specific peptides to these proteins. Together, our results indicate "dynamic partitioning" as a new mechanism of plasma membrane organization, that can account for large-scale compartmentalization of a wide array of lipid-anchored and integral membrane proteins in different physiological processes.

cell biology↗

bioRxiv2022

Direct activation of the Ras-Akt network mediates polarity and organizes protrusions in human neutrophil migration

Functions of Ras oncogenes and their downstream effectors are typically associated with cell proliferation and growth control while their role in immune cell migration has been largely unexplored. Although Ras-mediated signaling cascades have been implicated in immune response, there is no conclusive evidence to show local activation of these pathways on the plasma membrane directly regulates cell motility or polarity. Using spatiotemporally precise, cryptochrome-based optogenetic systems in human neutrophils, we abruptly altered protrusive activity, bypassing the chemoattractant-sensing receptor/G-protein network. First, global recruitment of active KRas4B/HRas isoforms or the guanine nucleotide exchange factor, RasGRP4, immediately increased spreading and random motility in neutrophils. Second, creating Ras activity at the cell rear generated new protrusions at the site and reversed pre-existing polarity, similar to the effects of steep chemoattractant gradients. Third, recruiting GTPase activating protein, RASAL3, at cell fronts abrogated existing protrusions and changed the direction of motility whereas dynamically inhibiting nascent fronts stopped migration completely. Fourth, combining pharmacological inhibition studies with optogenetics revealed that mTorC2 is more important than PI3K for Ras-mediated polarity and migration. Finally, local recruitment of Ras-mTorC2 effector, Akt, also generated new protrusions, rearranged pre-existing polarity, and triggered migration, even in absence of PI3K signaling. We propose that actin assembly, cell shape, and migration modes in immune cells are promptly controlled by rapid, local activities of established components of classical growth-control pathways independently of receptor activation.

immunology↗

bioRxiv2022

BindingSiteAugmentedDTA: Enabling A Next-Generation Pipeline for Interpretable Prediction Models in Drug-Repurposing

While research into Drug-Target Interaction (DTI) prediction is fairly mature, generalizability and interpretability are not always addressed in the existing works in this field. In this paper, we propose a deep learning-based framework, called BindingSite-AugmentedDTA, which improves Drug-Target Affinity (DTA) predictions by reducing the search space of potential binding sites of the protein, thus making the binding affinity prediction more efficient and accurate. Our BindingSite-AugmentedDTA is highly generalizable as it can be integrated with any DL-based regression model, while it significantly improves their prediction performance. Also, unlike many existing models, our model is highly interpretable due to its architecture and self-attention mechanism, which can provide a deeper understanding of its underlying prediction mechanism by mapping attention weights back to protein binding sites. The computational results confirm that our framework can enhance the prediction performance of seven state-of-the-art DTA prediction algorithms in terms of 4 widely used evaluation metrics, including Concordance Index (CI), Mean Squared Error (MSE), modified squared correlation coefficient [Formula], and the Area Under the Precision Curve (AUPC). We also contribute to the two most commonly used DTA benchmark datasets, namely Kiba and Davis, by including additional information on 3D structure of all proteins contained in these two datasets. We manually extracted this information from Protein Data Bank (PDB) files of proteins available at https://www.uniprot.org/. Furthermore, we experimentally validate the practical potential of our proposed framework through in-lab experiments. We measure the binding interaction between several drug candidate compounds for the inhibition of binding between (SARS-CoV-2 S-protein RBD) Spike and ACE-2 (host cell binding target) proteins. We then compare the computationally-predicted results against the ones experimentally-observed in the laboratory. The relatively high agreement between computationally-predicted and experimentally-observed binding interactions supports the potential of our framework as the next-generation pipeline for prediction models in drug repurposing.

bioinformatics↗

bioRxiv2022

Noise-induced symmetry breaking in a network of excitable ecological systems

Noise-induced symmetry breaking has barely been unveiled on the ecological grounds, though its occurrence may elucidate mechanisms responsible for maintaining biodiversity and ecosystem stability. Here, for a network of excitable consumer-resource systems, we show that the interplay of network structure and noise intensity manifests a transition from homogeneous steady state to inhomogeneous steady states, resulting in noise-induced symmetry breaking. On further increasing the noise intensity, there exist asynchronous oscillations, leading to heterogeneity crucial for maintaining a systems adaptive capacity. The observed collective dynamics can be understood analytically in the framework of linear stability analysis of the corresponding deterministic system.

ecology↗

bioRxiv2022

Spatiotemporal dynamics of membrane surface charge regulates cell polarity and migration

During cell migration and polarization, hundreds of signal transduction and cytoskeletal components self-organize to generate localized protrusions. Although biochemical and genetic analyses have delineated many specific interactions, how the activation and localization of so many different molecules are spatiotemporally orchestrated at the subcellular level has remained unclear. Here we show that the regulation of negative surface charge on the inner leaflet of the plasma membrane plays an integrative role in the molecular interactions. Surface charge, or zeta potential, is transiently lowered at new protrusions and within cortical waves of Ras/PI3K/TORC2/F-actin network activation. Rapid alterations of inner leaflet anionic phospholipids, such as PI(4,5)P2, PI(3,4)P2, phosphatidylserine, and phosphatidic acid, collectively contribute to the surface charge changes. Abruptly reducing the surface charge by recruiting positively charged optogenetic actuators was sufficient to trigger the entire biochemical network, initiate de novo protrusions, and abrogate pre-existing polarity. These effects were blocked by genetic or pharmacological inhibitions of key signaling components such as Akt and PI3K/TORC2. Conversely, increasing the negative surface deactivated the network and locally suppressed chemoattractant-induced protrusions or subverted EGF-induced ERK activation. Computational simulations involving excitable biochemical networks demonstrated that slight changes in feedback loops, induced by recruitment of the actuators, could lead to outsized effects on system activation. We propose that key signaling network components act on, and are in turn acted upon, by surface charge, closing feedback loops which bring about the global-scale molecular self-organization required for spontaneous protrusion formation, cell migration, and polarity establishment.

cell biology↗