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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2025

Membrane-bound cargo carried by teams of motors with heterogeneous velocities go faster and further than rigid cargo

Intracellular transport by teams of molecular motors is an essential cell-biological process that ensures the proper distribution of organelles, and other materials within cells. These teams of motors cooperate and compete in complex ways to achieve desired transport velocity and runlength. In-vitro experiments have observed that coupling motors through a lipid membrane that mimics in vivo membrane-bound cargoes leads to a higher cargo velocity. However, the mechanisms behind this increase in lipid cargo velocity are unclear. Here we seek to understand these mechanisms using Brownian dynamics simulations. We show that an underlying heterogeneity in single motor velocity is essential for the increased velocity of lipid cargoes. Our simulations also show that while the runlengths of both rigid and lipid cargoes increase, and the velocities decrease, with an increase in the fraction of slower motors, lipid cargoes can travel faster and substantially further with the same degree of heterogeneity, suggesting functional advantages of motor velocity heterogeneity. Together, our work explains mechanisms behind previous experimental observations and generates new experimentally testable predictions on velocities and runlengths relevant for in vivo transport.

biophysics↗

bioRxiv2025

The ParA-like ATPase PldP influences the TatA dynamics in Corynebacterium glutamicum

In bacterial cells, precise localization of protein complexes is achieved by unique positioning systems. One of the examples of such positioning systems is the ParAB-parS which is responsible for plasmid and chromosome segregation. In Corynebacterium glutamicum, a parAB deletion results in cell division and growth defects, while deletion of an orphan ParA-like protein pldP results only in a moderate cell division phenotype. Having confirmed a basal ATPase activity of PldP, we aimed to explore if the {Delta}pldP-related phenotype could be a consequence of the mislocalized secreted proteins, as the loss of extracellular proteins involved in cell wall metabolism results in a similar phenotype characterized by disrupted separation of daughter cells. Putative peptidoglycan hydrolase Rv2525c from Mycobacterium tuberculosis and Rv2525c-like glycoside hydrolase-like domain-containing protein Cg0955 from C. glutamicum were previously shown to be transported outside of the cell by twin-arginine protein translocation machinery (Tat). Here, we found that although the deletion of pldP did not lead to the altered secretion of the putative hydrolase Cg0955 by the Tat system, it resulted in the reduction of the Tat dynamics. Our findings highlight the interplay between the ParA-like ATPase PldP and the Tat translocon and contribute to the studies of ParA-like proteins being essential in positioning various cargos in the bacterial cells. ImportancePrecise spatio-temporal localization of protein complexes within a bacterial cell is essential for the survival and proliferation of bacteria. ParA-like ATPases play a crucial role in protein positioning, as well as chromosome and plasmid segregation. Here, we characterize a novel ParA-like ATPase PldP in Corynebacterium glutamicum, a model organism for the cell biology of Mycobacteriales and a biotechnological workhorse. Deletion of pldP results in the cell division phenotypes and impacts the intracellular dynamics of TatA, a component of the twin-arginine protein transport. We suggest that the mislocalization of the Tat-secreted putative peptidoglycan hydrolase caused by the indirect influence of pldP deletion might account for the observed cell separation defect.

microbiology↗

bioRxiv2019

ADAMTS-family protease MIG-17 regulates synaptic allometry by modifying the extracellular matrix and modulating glia morphology during growth

Synapses are largely established during embryogenesis and maintained during growth. The mechanisms that regulate synaptic allometry--the maintenance of synaptic positions during growth--are largely unknown. We performed forward genetic screens in C. elegans for synaptic allometry mutants and identified mig-17, a secreted metalloprotease of the conserved ADAMTS family. Through proteomic mass spectrometry analyses, cell biological and genetic studies we determined that MIG-17 is expressed by muscle cells to modulate glia location and morphology. Glia are proximal to synapses, and the glial location and morphology determine synaptic position during growth. Mig-17 regulates synapse allometry by influencing epidermal-glia crosstalk through the regulation of basement membrane proteins, including collagen type IV, SPARC and fibulin. Our findings underscore the importance of glia location in the maintenance of synaptic allometry, and uncover a muscle-epidermal-glia signaling axis, mediated through the extracellular matrix, in the regulation of glia morphology and synaptic positions during growth.

neuroscience↗

bioRxiv2026

Periplasmic SacB as a robust counter-selection tool for genome engineering in the polyploid bacterium Zymomonas mobilis

The alpha-proteobacterium Zymomonas mobilis exhibits exceptional ethanologenic physiology, which makes it a traditional alcoholic beverage producer and a promising chassis for biofuel production. Although genetic tools for this organism have expanded in recent years, a fundamental aspect of its chromosome organization remains to be understood. In particular, Z. mobilis has been suggested to exhibit polyploidy, but this feature is not fully confirmed because of discrepancies among studies reporting the copy number of chromosomes. Here, we tagged the chromosome-partitioning protein ParB with a fluorescent marker to visualise its cellular localisation and estimate chromosome copy number in individual cells. Imaging showed that Z. mobilis exhibits several distinctive ParB foci throughout the cytoplasm and an accumulated focus at the pole, demonstrating that a single Z. mobilis cell contains at >5 copies of the chromosome at the oriC regions. After verifying its polyploidy, we sought to establish an efficient counter-selection system, which is crucial for engineering multiple copies of the chromosome. We assessed the efficacy of levan-sucrase (SacB) toxicity in Z. mobilis. We found that, despite Z. mobilis secreting a native extra-cellular sucrase SacB, heterologous periplasmically-localised Bacillus subtilis SacB rendered Z. mobilis cells sensitive to sucrose. We successfully used this effect for counter-selection when deleting and inserting targeted DNA sequences into the Z. mobilis genome. Together, this work provides important insights and tools for advancing Z. mobilis genetics and its biotechnological applications. ImportanceZymomonas mobilis is a promising industrial bacterium with capacity to convert sugars into ethanol at nearly maximum theoretical yield. With its expanding use in industrial applications, it is crucial to clarify if individual Z. mobilis cells carry multiple copies of chromosome as this has important implications for genome engineering. Two previous studies have used quantitative PCR to address this question, but their reported chromosome copy numbers varied widely from 20 to 100. Here, we used a cell biological approach to estimate the copy number and confirmed that single Z. mobilis cell possesses multiple copies. In addition, we show that a SacB-based counter-selection works in Z. mobilis, enabling efficient and complete mutation of all chromosome copies.

microbiology↗

bioRxiv2023

Alternating polarity integrates chemical and mechanical cues to drive tissue morphogenesis

The spatial patterning of molecules within a sheet of cells directs morphogenesis in many epithelial tissues. In Scaptodrosophila follicle cells, Par3/Bazooka and aPKC were previously shown to localize to a set of cell edges destined to elongate and form the base of each eggshell dorsal appendage. This study establishes that the mechanism underlying this localization pattern is an alternating, in-plane polarity of the cells. A candidate screen identified several potential molecular players, whose epistatic relationships were then examined using a custom culture assay. These experiments demonstrated that positive feedback between actin polymerization and PI4P production leads to polarization of these cells individually, while mechanical force coordinates polarization among these cells. This work adds to the growing evidence for a role of mechanics in cell polarity, and also provides an example where morphological differences between species can be understood at the level of changes in fundamental cell biological processes. SummaryIn Scaptodrosophila, the alternating (left, right, left) polarization in a row of cells drives the formation of up to eight eggshell respiratory filaments. This study uncovers the underlying pathway, which integrates chemical signaling through actin and PI4P with mechanical force.

developmental biology↗

bioRxiv2025

Development of charged nanobubble-containing media and their effects on iPSC-derived cell cultures

Nanobubbles (NBs) are gas-filled spherical structures less than 1 {micro}m in diameter, characterized by high surface charge, long-term stability, and the ability to generate bactericidal hydroxyl radicals upon collapse. Although these unique properties enable their extensive applications, including wastewater treatment, their cell biological applications at neutral pH remain limited by difficulties in maintaining stability and surface charge. Here, we succeeded in generating both positively and negatively charged NBs, achieving high zeta potentials in human iPSC-derived neural progenitor cell (NPC) and neuron culture media (pH 7.4). Similar to their bactericidal effects, NBs induced cell death in iPSC-derived cells, with positively charged NBs showing stronger cytotoxicity than negatively charged ones. This may be because the cell membrane carries a negative charge, making positively charged NBs more likely to approach and interact with the membrane, or because positively charged nanobubbles exhibit stronger radical generation. In future, we aim to elucidate the molecular biological mechanisms underlying NB-induced cell death and to contribute to the potential application of nanobubbles in regenerative medicine. This study will serve as an initial step toward that goal.

bioengineering↗

bioRxiv2025

Eukaryotic recombinases duplicated after divergence from known asgardarchaeal RadA: implications for the evolution of sex during eukaryogenesis

The origin of meiotic sex was a key milestone in the evolution of the eukaryotic cell. The DNA recombinases Rad51 and DMC1 have been used previously to trace the timing and origins of the meiotic machinery, and warrant revisiting in the face of the recent increased diversity of reported asgardarchaeal taxa. Here we perform comparative genomics and phylogenetic analyses of RadA protein sequences from a broad sampling of eukaryotic and archaeal taxa. We show that even with increased and new sampling, the eukaryotic Rad51 and DMC1 proteins still resolve separately from any archaeal RadA sequences. Taking into account recent evolutionary cell biological discoveries, our data are most consistent with a scenario whereby the asgardarchaeal host cell was evolving cytoskeletal and membrane-protein machinery that was later incorporated into eukaryotic endomembrane systems following the acquisition of mitochondria and the evolution of sex.

evolutionary biology↗

bioRxiv2023

An inducible tricolor reporter mouse for simultaneous imaging of lysosomes, mitochondria and microtubules

Cell-type-specific use of the same DNA blueprint generates diverse cell types. Such diversity must also be executed via differential deployment of the same subcellular machinery. However, our understanding of the size, distribution, and dynamics of subcellular machinery in native tissues, and their connection to cellular diversity, remain limited. We generate and characterize an inducible tricolor reporter mouse, dubbed "kaleidoscope", for simultaneous imaging of lysosomes, mitochondria and microtubules in any cell type and at a single cell resolution. The expected subcellular compartments are labeled in culture and in tissues with no impact on cellular and organismal viability. Quantitative and live imaging of the tricolor reporter captures cell-type-specific organelle features and kinetics in the lung, as well as their changes after Sendai virus infection. Yap/Taz mutant lung epithelial cells undergo accelerated lamellar body maturation, a subcellular manifestation of their molecular defects. A comprehensive toolbox of reporters for all subcellular structures is expected to transform our understanding of cell biology in tissues. SUMMARY STATEMENTOur understanding of subcellular machinery is often inferred from that in cultured cells. Hutchison et al. have generated a tricolor tunable reporter mouse for simultaneous imaging of lysosomes, mitochondria and microtubules in the native tissues at a single-cell resolution.

developmental biology↗

bioRxiv2020

Granzyme B skews CD4+ T cell differentiation resulting in increased intestinal pathogenicity

CD4+ T cell activation and differentiation are important events that set the stage for proper immune responses. Many factors are involved in the activation and differentiation of T cells, and these events are tightly controlled to prevent unwanted and/or exacerbated immune responses that may harm the host. It has been well documented that granzyme B, a potent serine protease involved in cell-mediated cytotoxicity, is readily expressed by certain CD4+ T cells, such as regulatory T cells and CD4+CD8+ intestinal intraepithelial lymphocytes, both of which display cytotoxicity associated with granzyme B. However, because not all CD4+ T cells expressing granzyme B are cytotoxic, additional roles for this protease in CD4+ T cell biology remain unknown. Here, using a combination of in vivo and in vitro approaches, we report that granzyme B-deficient CD4+ T cells display increased IL-17 production. In the adoptive transfer model of intestinal inflammation, granzyme B-deficient CD4+ T cells triggered a more rapid disease onset than their WT counterparts, and presented a differential transcription profile. Similar results were also observed in granzyme B-deficient mice infected with Citrobacter rodentium. Our results suggest that granzyme B modulates CD4+ T cell differentiation, providing a new perspective into the biology of this enzyme.

immunology↗

bioRxiv2025

Sensitivity based model agnostic scalable explanations of deep learning

Deep neural networks (DNNs) are powerful tools for data-driven predictive machine learning, but their complex architecture obscures mechanistic relations that they have learned from data. This information is critical to the scientific method of hypotheses development, experiment design, and model validation, especially when DNNs are used for biological and clinical predictions that affect human health. We design SensX, a model agnostic explainable AI (XAI) framework that outperformed current state-of-the-art XAI in accuracy (up to 52% higher) and computation time (up to 158 times faster), with higher consistency in all cases. It also determines an optimal subset of important input features, reducing dimensionality of further analyses. SensX scaled to explain vision transformer (ViT) models with more than 150, 000 features, which is computationally infeasible for current state-of-the-art XAI. SensX validated that ViT models learned justifiable features as important for different facial attributes of different human faces. SensX revealed biases inherent to the ViT architecture, an observation possible only when importance of each feature is explained. We trained DNNs to annotate biological cell types using single-cell RNA-seq data and SensX determined the sets of genes that the DNNs learned to be important to different cell types.

systems biology↗

bioRxiv2026

Selenium-enriched rapeseed extract synergizes with chemotherapy drug cisplatin in inhibiting proliferation and promoting apoptosis of colorectal cancer cells

Chemotherapy treatment of colorectal cancers (CRC) using cisplatin (CDDP) encounters problems of drug resistance by the cancer cells and cytotoxicity to normal cells, highlighting the urgent need for joint therapeutical strategies. Selenium-enriched rapeseed extracts exhibit anti-cancer effects but the bioactive components and mechanisms remain unclear. Here, we applied different solvents to fractionate the extracts from Selenium-enriched rapeseed and found that the water extract (WE) fraction significantly enhanced the cytotoxic effect of CDDP on cancer cells but no damage on normal cells. HPLC-ICP-MS analysis revealed that methylselenocysteine (MSC) and selenocystine (SeCys2) were the main selenium speciation in WE. Through cell biology and integrative multi-omics analysis, we found a synergistic anti-CRC cell effect when combining CDDP with MSC, sulforaphane (SFN), celastrol (Cel), Indole-3-carbinol (I3C), -linolenic acid (ALA) or linoleic acid (LA). We propose that the CDDP-WE combination treatment holds the promise for improving curative efficacy for chemo-refractory CRC patients in the future.

cancer biology↗

bioRxiv2019

A probabilistic framework for cellular lineage reconstruction using single-cell 5-hydroxymethylcytosine sequencing

Lineage reconstruction is central to understanding tissue development and maintenance. While powerful tools to infer cellular relationships have been developed, these methods typically have a clonal resolution that prevent the reconstruction of lineage trees at an individual cell division resolution. Moreover, these methods require a transgene, which poses a significant barrier in the study of human tissues. To overcome these limitations, we report scPECLR, a probabilistic algorithm to endogenously infer lineage trees at a single cell-division resolution using 5-hydroxymethylcytosine. When applied to 8-cell preimplantation mouse embryos, scPECLR predicts the full lineage tree with greater than 95% accuracy. Further, scPECLR can accurately extract lineage information for a majority of cells when reconstructing larger trees. Finally, we show that scPECLR can also be used to map chromosome strand segregation patterns during cell division, thereby providing a strategy to test the \"immortal strand\" hypothesis in stem cell biology. Thus, scPECLR provides a generalized method to endogenously reconstruct lineage trees at an individual cell-division resolution.

systems biology↗

bioRxiv2020

A common genetic architecture enables the lossy compression of large CRISPR libraries

There are thousands of ubiquitously expressed mammalian genes, yet a genetic knockout can be lethal to one cell, and harmless to another. This context specificity confounds our understanding of genetics and cell biology. 2 large collections of pooled CRISPR screens offer an exciting opportunity to explore cell specificity. One explanation, synthetic lethality, occurs when a single "private" mutation creates a unique genetic dependency. However, by fitting thousands of machine learning models across millions of omic and CRISPR features, we discovered a "public" genetic architecture that is common across cell lines and explains more context specificity than synthetic lethality. This common architecture is built on CRISPR loss-of-function phenotypes that are surprisingly predictive of other loss-of-function phenotypes. Using these insights and inspired by the in silico lossy compression of images, we use machine learning to identify small "lossy compression" sets of in vitro CRISPR constructs where reduced measurements produce genome-scale loss-of-function predictions.

systems biology↗

bioRxiv2026

PantheonOS: An Evolvable Multi-Agent Framework for Automatic Genomics Discovery

The convergence of large language model-powered autonomous agent systems and single-cell biology promises a paradigm shift in biomedical discovery. However, existing biological agent systems, building upon single-agent architectures, are narrowly specialized or overly general, limiting applications to routine analyses. We introduce PantheonOS (https://PantheonOS.stanford.edu), an evolvable, privacy-preserving multi-agent framework designed to reconcile generality with domain specificity. Critically, PantheonOS enables agentic code evolution, allowing evolving state-of-the-art batch correction and our reinforcement-learning augmented gene panel selection algorithms to achieve super-human performance. PantheonOS drives biological discoveries across systems: uncovering asymmetric paracrine Cer1-Nodal inhibition in proximal-distal axis formation of novel early mouse embryo 3D data; integrating human fetal heart multi-omics with whole-heart data to reveal molecular programs underpin heart diseases; and adaptively selecting virtual cell models to predict cardiac regulatory and perturbation effects. Together, PantheonOS points towards a future where scientific discoveries are increasingly driven by self-evolving AI systems across biology and beyond. Websitehttps://pantheonos.stanford.edu Ecosystemhttps://github.com/aristoteleo SummaryLarge language model-powered agent systems are driving a paradigm shift in scientific discovery by automating, scaling, and accelerating data analysis. This transformation is particularly profound in biology, where the rapid expansion of single-cell and spatial genomics has effectively reshaped the field into a data-intensive science. However, existing biological agent systems are typically constrained to single-agent designs, are narrowly specialized, or are overly general without sufficient domain expertise, limiting their applicability to routine or shallow analyses. Here, we introduce PantheonOS (https://pantheonos.stanford.edu), an evolvable, privacy-preserving, and general-purpose multi-agent framework designed to reconcile generality with deep domain specificity. PantheonOS provides an abstract, extensible architecture that enables customized agent composition and supports end-to-end single-cell and multi-omics analysis, spanning reinforcement-learning-augmented gene panel design, raw FASTQ processing, multimodal data integration, and three-dimensional spatial genomics reconstruction. Central to this framework, Pantheon-Evolve enables agentic code evolution, allowing the system to autonomously improve state-of-the-art batch-correction algorithms and new reinforcement-learning based gene panel design algorithms, achieving performance beyond manually designed baselines. We demonstrate the power of PantheonOS across multiple biological domains. In early mouse embryogenesis, PantheonOS automatically reconstructs three-dimensional spatial gene expression landscapes and resolves asymmetric Cer1 expression and paracrine Cer1-Nodal inhibition, revealing a robust proximal-distal axis at embryonic day six (E6.0). In human development, PantheonOS integrates fetal heart single-cell multi-omics with whole-heart 3D MERFISH+ data at post-conception week 12, uncovering spatially resolved molecular programs underlying heart disease ontogeny. Finally, an intelligent model-routing mechanism enables PantheonOS to adaptively select optimal virtual cell models across heterogeneous tasks, revealing minimal regulatory networks of cardiogenesis and predicting spatially resolved perturbation effects in the developing heart. Together, PantheonOS establishes a foundation for fully automated, evolvable, and domain-aware agentic analysis in genomics, and points toward a future in which scientific discovery is increasingly driven by self-improving AI systems across biology and beyond.

bioinformatics↗

bioRxiv2026

Built-in integrated living electronics: from biosynthesis tomodulation of neuronal function

Neuroelectronic interfaces hold great promise to restore functions in neurological disorders or motor dysfunctions, but current devices struggle to integrate seamlessly within living tissues. Here we report a transformative approach to create bionic neurons that autonomously build integrated fluorescent fibrils and demonstrate their role as neuromodulators. Using a combination of cell biology, ultrastructural, imaging and nanospectroscopical approaches, we deciphered the unique biosynthetic pathway employed by the cells to self-fabricate these nanoelectronics and uncover their hybrid structure. Importantly, patch clamp recordings revealed their neuromodulatory potential, through the perturbation of membrane electrical properties and the early rising phase of the action potential. Deciphering how basic molecular elements self-organize into complex architectures within biological environments could unlock the ability to engineer natural electroactive systems directly inside living organisms. This capability could be used to create conductive pathways between arbitrarily defined neurons, microcircuits, or nervous system regions, effectively writing connections into living brains.

synthetic biology↗

bioRxiv2024

Transport Cocktails for Cancer Therapeutics

Beyond biological cell heterogeneity, evidenced by different resistances to therapeutics, "delivery heterogeneity" crucially limits treatment efficacy for advanced solid tumors: variations in therapeutic drug delivery to different tumor areas (perivascular, perinecrotic) leading to nonuniform drug concentrations/doses and to unsuccessful treatment (cancer cell kill). Short-range (40-80 {micro}m), high energy (1-5 MeV) alpha-particles successfully address the biological heterogeneity: the double-strand DNA breaks they cause make them impervious to cell resistance mechanisms. Multiresponsive nanocarriers and/or engineered antibody-drug-conjugates are elegant approaches to delivering such alpha-particle emitters. Delivery heterogeneity, however, remains a challenge in established (i.e. large, vascularized) tumors. Remarkably, delivery properties enabling efficacy at the cell scale (targeting selectivity, affinity, cell drug uptake) may act against spatial delivery uniformity at the tumor scale (binding-site barrier effect1). We have previously demonstrated, in different mouse models, that spatial delivery uniformity, key to the effective killing of solid tumors, can be achieved utilizing combinations of different, distinct delivery carriers of the same emitter, but with different, complementary delivery properties, "leaving no cancer cell behind". We build first principles reaction-transport models (quantitatively informed by experiments) that explain the "geographically complementary" behaviors of such carrier cocktails, and help optimally design these cocktails and their delivery protocols.

cancer biology↗

bioRxiv2017

Spot-On: robust model-based analysis of single-particle tracking experiments

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce \"Spot-On\", an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants.\n\nIMPACT STATEMENTSpot-On is an easy-to-use website that makes a rigorous and bias-corrected modeling framework for analysis of single-molecule tracking experiments available to all.

biophysics↗

bioRxiv2020

Simultaneous deep generative modeling and clustering of single cell genomic data

Recent advances in single-cell technologies, including single-cell ATAC-seq (scATAC-seq), have enabled large-scale profiling of the chromatin accessibility landscape at the single cell level. However, the characteristics of scATAC-seq data, including high sparsity and high dimensionality, have greatly complicated the computational analysis. Here, we proposed scDEC, a computational tool for single cell ATAC-seq analysis with deep generative neural networks. scDEC is built on a pair of generative adversarial networks (GANs), and is capable of learning the latent representation and inferring the cell labels, simultaneously. In a series of experiments, scDEC demonstrates superior performance over other tools in scATAC-seq analysis across multiple datasets and experimental settings. In the downstream applications, we demonstrated that the generative power of scDEC helps to infer the trajectory and intermediate state of cells during differentiation and the latent features learned by scDEC can potentially reveal both biological cell types and within-cell-type variations.

bioinformatics↗