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Results for “cell biology”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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

Spatial mapping of DNA synthesis reveals dynamics and geometry of human replication nanostructures

DNA replication is essential to life and ensures the accurate transmission of genetic information, which is significantly disturbed during cancer development and chemotherapy. While DNA replication is tightly controlled in time and space, methods to visualise and quantify replication dynamics within 3D human cells are lacking. Here, we introduce 3D-Spatial Assay for Replication Kinetics (3D-SPARK), an approach enabling nanoscale analysis of DNA synthesis dynamics in situ. 3D-SPARK integrates optimised nucleotide analogue pulse labelling with super-resolution microscopy to detect, classify, and quantify replication nanostructures in single cells. By combining immunofluorescence techniques with click chemistry-based nascent DNA labelling and transfection of fluorescent nucleotide derivatives, we map multi-colour DNA synthesis events in relation to established replication proteins, local RNA-protein condensates or large subnuclear domains. We demonstrate quantitative changes in size, relative abundance and spatial arrangement of nanoscale DNA synthesis events upon chemotherapeutic treatment, CDC6 oncogene expression and loss of chromatin organiser RIF1. The flexibility, precision and modular design of 3D-SPARK helps bridging the gap between spatial cell biology, genomics, and 2D fibre-based replication studies in health and disease.

cell biology↗

bioRxiv2017

A computational modelling framework to quantify the effects of passaging cell lines

In vitro cell culture is routinely used to grow and supply a sufficiently large number of cells for various types of cell biology experiments. Previous experimental studies report that cell characteristics evolve as the passage number increases, and various cell lines can behave differently at high passage numbers. To provide insight into the putative mechanisms that might give rise to these differences, we perform in silico experiments using a random walk model to mimic the in vitro cell culture process. Our results show that it is possible for the average proliferation rate to either increase or decrease as the passaging process takes place, and this is due to a competition between the initial heterogeneity and the degree to which passaging damages the cells. We also simulate a suite of scratch assays with cells from near-homogeneous and heterogeneous cell lines, at both high and low passage numbers. Although it is common in the literature to report experimental results without disclosing the passage number, our results show that we obtain significantly different closure rates when performing in silico scratch assays using cells with different passage numbers. Therefore, we suggest that the passage number should always be reported to ensure that the experiment is as reproducible as possible. Furthermore, our modelling also suggests some avenues for further experimental examination that could be used to validate or refine our simulation results.

biophysics↗

bioRxiv2021

Multiple RSV strains infecting HEp-2 and A549 cells reveal cell line-dependent differences in resistance to RSV infection.

Respiratory syncytial virus (RSV) is a leading cause of pediatric acute respiratory infection worldwide. There are currently no approved vaccines or antivirals to combat RSV disease. A few transformed cell lines and two historic strains have been extensively used to study RSV. Here we report a thorough molecular and cell biological characterization of HEp-2 and A549 cells infected with four strains of RSV representing both major subgroups as well as historic and more contemporaneous genotypes -- [RSV/A/Tracy (GA1), RSV/A/Ontario (ON), RSV/B/18537 (GB1), RSV/B/Buenos Aires (BA)] -- via measurements of viral replication kinetics and viral gene expression, immunofluorescence-based imaging of gross cellular morphology and cell-associated RSV, and measurements of host response including transcriptional changes and levels of secreted cytokines and growth factors. Our findings strongly suggest 1) the existence of a conserved difference in gene expression between RSV subgroups A and B; 2) the A549 cell line is a more stringent and natural host of replicating RSV than the HEp-2 cell line; and 3) consistent with previous studies, determining the full effects of viral genetic variation in RSV pathogenesis requires model systems as tractable as transformed cell lines but better representative of the human host. IMPORTANCEInfection with respiratory syncytial virus (RSV) early in life is essentially guaranteed and can lead to severe disease. In vitro data from two historic RSV/A strains and two cell lines, HEp-2 and A549, constitute most of our knowledge; but RSV contains ample variation from two evolving subgroups (A and B) showing recent convergent evolution. Here we measure viral action and host response in HEp-2 and A549 cells infected with four RSV strains from both subgroups and representing both historic and more contemporaneous strains. We discover a subgroup-dependent difference in viral gene expression and find A549 cells are more potently antiviral and more sensitive, albeit subtly, to viral variation. Our findings reveal important differences between RSV subgroups and two widely used cell lines and provide baseline data for experiments with model systems better representative of natural RSV infection.

microbiology↗

bioRxiv2023

FocA: A deep learning tool for reliable, near-real-time imaging focus analysis in automated cell assay pipelines

The increasing use of automation in cellular assays and cell culture presents significant opportunities to enhance the scale and throughput of imaging assays, but to do so, reliable data quality and consistency are critical. Realizing the full potential of automation will thus require the design of robust analysis pipelines that span the entire workflow in question. Here we present FocA, a deep learning tool that, in near real-time, identifies in-focus and out-of-focus images generated on a fully automated cell biology research platform, the NYSCF Global Stem Cell Array(R). The tool is trained on small patches of downsampled images to maximize computational efficiency without compromising accuracy, and optimized to make sure no sub-quality images are stored and used in downstream analyses. The tool automatically generates balanced and maximally diverse training sets to avoid bias. The resulting model correctly identifies 100% of out-of-focus and 98% of in-focus images in under 4 seconds per 96-well plate, and achieves this result even in heavily downsampled data ([~]30 times smaller than native resolution). Integrating the tool into automated workflows minimizes the need for human verification as well as the collection and usage of low-quality data. FocA thus offers a solution to ensure reliable image data hygiene and improve the efficiency of automated imaging workflows using minimal computational resources.

bioinformatics↗

bioRxiv2024

Somatic epigenetic drift during shoot branching: a cell lineage-based model

Plant architecture is shaped by the continuous production of new organs, most of which emerge post-embryonically. This process includes the formation of new lateral branches along existing shoots. Shoot branching is fundamental to plant development, plant-environment interactions, and vegetative propagation. Current empirical evidence supports a "detached meristem" model as the cellular basis of lateral shoot initiation. In this model, a small number of undifferentiated cells are "sampled" from the periphery of the shoot apical meristem (SAM) to act as precursors for axillary buds, which eventually develop into new shoots. Repeated branching thus creates a series of cellular bottlenecks (i.e. somatic drift) that affect how de novo genetic and epigenetic mutations propagate through the plant body during development. Somatic drift could be particularly relevant for epigenetic changes in the form of stochastic DNA methylation gains and losses (i.e. spontaneous epimutations), as they have been shown to arise rapidly with each cell division. Here, we formalize a special case of the "detached meristem" model, where pre-cursor cells are randomly sampled from the SAM periphery in a way that maximizes cell lineage independence. By following a population of SAM cells through repeated branching processes, we show that somatic drift gives rise to a complex mixture of cellular phylogenies, which shape the evolution of cell-to-cell DNA methylation heterogeneity within the SAM over time. This process is dependent on the number of branch points, the strength of somatic drift as well as the epimutation rate. For many realistic cell biological settings, our model predicts that cell-to-cell DNA methylation heterogeneity in the SAM converges to non-zero states during development, suggesting that epigenetic variation is an inherent property of the SAM cell population. Our insights have direct implications for empirical studies of somatic (epi)genomic diversity in long-lived perennial and clonal species using bulk or single-cell sequencing approaches.

genetics↗

bioRxiv2024

Single-cell transcriptomics highlights sexual cues among reproductive life stages of uncultivated Acantharia (Radiolaria)

As an innate property of life, the ability to reproduce is a key process for the perpetuation of organisms. Along the evolution of protist reproductive strategies, the molecular machinery of sexual recombination is estimated to have been inherited from the last eukaryotic common ancestor (LECA). Nevertheless, unraveling the sexual cycles of extant free-living protist lineages remains challenging, given the enigmatic roles of many uncultivated life stages. Among the uncultivated planktonic group of Acantharia (Radiolaria), a hypothetical sexual cycle has been proposed since the late 19th century, including the existence of a gamete-like life stage of undetermined ploidy, referred to as swarmers. In order to investigate the sexual nature of acantharian reproductive stages, we conducted single-cell transcriptomic analysis across various acantharian life stages. Our results show distinct functional profiles for reproductive and vegetative life stages, while revealing the expression of the reference eukaryotic genes involved in gamete fusion, HAP2/GCS1 and GEX1-KAR5, in swarmers and pre-swarmer stages. Annotation of differentially expressed life stage-specific genes, also highlights putative meiosis-related functions among swarmers, while suggesting the existence of a potential swarmer/vegetative intermediate stage expressing putative growth-related genes. This original life stage-specific genetic data is coherent with morphological evidence supporting the existence of an acantharian sexual cycle, with swarmers acting as gametes. Moreover, it paves the way for a deeper understanding of radiolarian cell biology and ecology at a single-cell scale. HighlightsO_LIAcantharia demonstrate both morphological and genetic evidence of a sexual cycle C_LIO_LIAcantharian reproductive stages are enriched in functions related to cell division C_LIO_LINuclear fusion gene family GEX1-KAR5 is up-regulated in putative acantharian gametes C_LIO_LIMost expressed genes specific to acantharian reproductive stages are unassigned C_LIO_LIReproduction-specific unassigned genes include putative sex-related functions C_LI

microbiology↗

bioRxiv2025

transfactor: Transcription factor activity estimation via probabilistic gene expression deconvolution

Gene expression is the primary modality being studied to differentiate between biological cells. Contemporary single-cell studies simultaneously measure genome-wide transcription levels for thousands of individual cells in a single experiment. While the characterization of cell population differences has often occurred through differential expression analysis, tiny effect sizes become statistically significant when thousands of cells are available for each population, compromising biological interpretation. Moreover, these large studies have spurred the development of methods to infer gene regulatory networks (GRNs) directly from the data, and GRN databases are becoming more comprehensive. In this work, we propose a statistical model for gene expression measures and an inference method that leverage GRNs to deconvolve transcription factor (TF) activity from gene expression, by probabilistically assigning mRNA molecules to TFs. This shifts the paradigm from investigating gene expression differences to regulatory differences at the level of TF activity, aiding interpretation and allowing prioritization of a limited number of TFs responsible for significant contributions to the observed gene expression differences. The inferred TF activities result in intuitive prioritization of TFs in terms of the (difference in) estimated number of molecules they produce, in contrast to other widely-used methods relying on arbitrary enrichment scores. Our model allows the incorporation of prior information on the regulatory potential between each TF and target gene through prior distributions, and is able to deal with both repressing and activating interactions. We compare our approach to other TF activity estimation methods using two simulation experiments and two case studies.

bioinformatics↗

bioRxiv2025

Inference of multi-enhancer interactions in T lymphocytes using Hi-Cociety

AbstractsThree-dimensional (3D) enhancer communities are key regulators of gene expression, shaping cell fate decisions and contributing to disease pathogenesis. Assays such as H3K27ac HiChIP have been used to map enhancer-enhancer interactions and define enhancer communities; however, their reliance on antibody-based enrichment restricts scalability and cross-cell-type applicability. In contrast, Hi-C provides an unbiased, genome-wide view of chromatin architecture but lacks direct annotation of regulatory elements, limiting its utility for enhancer-focused analyses. To bridge this gap, we introduce Hi-Cociety--a graph-based computational framework and accompanying R package that infers 3D enhancer communities directly from Hi-C data, without relying on histone modification or chromatin accessibility measurements. Hi-Cociety constructs a network of significant interactions and applies clustering algorithms to define chromatin interaction modules. Applying Hi-Cociety to Hi-C measurements in T lymphocytes, we identified highly connected modules enriched for active transcription, chromatin accessibility, and histone acetylation. Notably, modules identified in T cells pinpoint critical genes central to T cell biology. Hi-Cociety also detects cell-type-specific differences in chromatin organization, highlighting dynamic regulatory rewiring across T cell states. Our findings underscore the importance of network properties-- connectivity, transitivity, and centrality--in shaping gene regulation through 3D genome organization. Hi-Cociety provides a scalable and versatile tool for mapping enhancer communities at scale, advancing our understanding of immune cell identity and the regulatory logic encoded in 3D chromatin structure.

bioinformatics↗

bioRxiv2025

Formation of extracellular vesicles depends on mechanical feedback of the cortex and the glycocalyx

Cell-secreted extracellular vesicles (EVs) play a pivotal role in local and distant cell-to-cell communication by delivering specific cargoes to other cells or to the extracellular space. In many cells, the glycocalyx, a thick sugar-rich layer at the cell surface, and the membrane-cortex attachment are crucially linked to the formation of EVs, yet it is unclear what determines the successful formation of EVs when multiple physical factors are involved. In this work, we developed a model for glycocalyx-membrane-cortex composite to investigate the effects of gly-cocalyx and membrane-cortex adhesion on the formation of EVs by combining polymer physics-based theory and Helfrich membrane theory. By performing linear stability analysis, we show that modulating the mechanical feedback among the glycocalyx, membrane-cortex attachment, and membrane curvature can give rise to two types of instabilities: a conserved Turing-type instability and a Cahn-Hilliard-type instability. Furthermore, using an equilibrium model, we identified two critical conditions for EV formation: an initial detachment of the membrane from the underlying cortex and then a sufficient driving force to induce membrane deformation for successful EV formation. We further demonstrated that there exists an optimal glycocalyx coating area at which the formation of EVs is most favorable. Finally, we use our model to predict that a heterogeneous size distribution of EVs can be generated through the regulation of glycocalyx properties, shedding insight into how EVs of different radii may be generated. Significance StatementExtracellular vesicles (EVs) are important for cell biology because they facilitate active communication between cells. Understanding the governing factors that control the formation of EVs is crucial to many cellular processes ranging from tumor progression and metastasis evolution to the disposal of unwanted biomolecules. However, whether EV secretion is a consequence of the glycocalyx and the role of membrane-cortex adhesion in the formation of EVs are still elusive. To address these issues, here we develop a biophysical model for EV formation that couples the presence of glycocalyx and membrane-cortex adhesion. We find that the glycocalyx-membrane-cortex composite system exhibits two types of instabilities utilizing stability analysis - a Turing instability and a Cahn-Hilliard type instability. Based on our proposed equilibrium model, we identified that for the initiation of membrane detachment and the formation of EVs each need to meet a critical threshold. In addition, our model predicts that the formation of EVs is most favorable when an optimal glycocalyx coating area reaches and a heterogeneous distribution EV sizes can be produced by regulating glycocalyx properties.

biophysics↗

bioRxiv2025

Rapid thermoforming of polycarbonate cell culture accessories from 3D printed molds

Bespoke cell culture devices are essential for tissue engineering applications. Traditional manufacturing methods for cell culture accessories involve injection molding and machining, which are too costly and time-consuming to implement for producing custom designs in small batches, and/or while testing the usefulness of a new design before mass producing it. Materials typically used for rapid design iteration, like poly(dimethylsiloxane) (PDMS) elastomers, surmount this issue but present new challenges of affinity for hydrophobic small molecules and sub-optimal interactions with sensitive cell types. Here, we propose polycarbonate (PC) thermoforming as a solution for creating customized transparent and autoclavable accessories. We demonstrate that optimized preheating of PC overcomes issues with bubbling during thermoforming. The use of high heat deflection temperature (HDT) resins allows these PC devices to be thermoformed off molds created by Digital Light Processing (DLP) 3D prints, enabling rapid prototyping of the PC. Using this approach, we fabricated custom PC well plate inserts. These inserts combine many advantages of tissue culture polystyrene (negligible absorption of hydrophobic molecules, transparency, rigidity) and elastomers (ease of creating bespoke devices, ability to be sterilized by autoclaving) and are compatible with a variety of cell biology applications, including human induced pluripotent stem cells (iPSC) culture. PC inserts also supported iPSC differentiation into cardiomyocytes (iPS-CM) and micro-patterning of iPS-CM into cardiospheres. This low cost, customizable approach holds promise for a variety of bioengineering applications.

bioengineering↗

bioRxiv2025

Vertically Integrated System for Tracking and Assessing cell-cycle aware phenotypes under confinement

Quantitative cell biology often studies migration and the cell-cycle (CC) in separate assays, limiting mechanistic insights, particularly under geometric confinement. Here, we introduce a vertically integrated platform for simultaneously tracking single-cell migration and assessing CC under confinement. Our system integrates cell engineering via multiplexed sensors for cell-cycle, actin, and tubulin, as well as photopatterned engineered extracellular matrix (ECM) islands of defined sizes. It also features an automated, high-throughput pattern-aware imaging pipeline (Fab2Mic) that enables on-pattern, joint migration-CC assessment in the same live cells. Since the local microenvironment plays a critical role in metastasis by constraining cell behaviors within spatial boundaries, we used an HT1080 fibrosarcoma model as an illustrative case. Where static phenotyping yielded 40% G1 and 60% S/G2/M, with larger cell areas and tubulin spread in the S/G2/M phase, dynamic phenotyping via live-cell imaging confirmed CC-linked motility, with faster instantaneous velocities in G1, exemplifying the CC-migration correlations. These phenotypes were modulated by the spatial confinement imposed by the engineered ECM islands. Stronger confinement reduced cell area and tubulin spread and increased the frequency of abnormal CC events, particularly Long G1 states on smaller engineered ECM islands. It also induced a confinement-specific S/G2/M-G1 mitotic slippage, observed only under our confined conditions. Together, this vertically integrated system suggests that confinement may continuously tune migration-CC coupling and provides a deployable pipeline for CC-aware mechanobiology and screening. Moreover, we stress how dynamic imaging provides access to variables that are difficult or impossible to infer from static snapshots, including velocity and CC timing.

bioengineering↗

bioRxiv2018

Ex vivo dynamics of human glioblastoma cells in a microvasculature-on-a-chip system correlates with tumor heterogeneity and subtypes

The perivascular niche (PVN) plays an essential role in brain tumor stem-like cell (BTSC) fate control, tumor invasion, and therapeutic resistance. Herein we report on the use of a microvasculature-on-a-chip system as a PVN model to evaluate the dynamics of BTSCs ex vivo from 10 glioblastoma patients. We observed that BTSCs preferentially localize in the perivascular zone. Live cell tracking revealed that the cells residing in the vicinity of microvessels had the lowest motility, while a fraction of cells on the microvessels unexpectedly possessed the highest motility and migrated over the longest distance. These results indicate that the perivascular zone is a niche for BTSCs, while the microvascular tracks are also a path for long-distance tumor cell migration and invasion. Additionally, the degree of co-localization between tumor cells and microvessels varied significantly across patients. To validate the results from our microvasculature-on-a-chip system, we used single-cell transcriptome sequencing (10 patients and 21,750 single cells in total) to identify the subtype of each tumor cell. The co-localization coefficient was found to correlate positively with proneural (stem-like) or mesenchymal (invasive) but not classical (proliferative) tumor cells. Furthermore, we found that a gene signature profile including PDGFRA correlated strongly with the \"homing\" of brain tumor cells to the PVN. Our findings demonstrated that ex vivo dynamics of human brain tumor cells in a microvasculature-on-a-chip model can recapitulate in vivo tumor cell dynamics, heterogeneity, and subtypes, representing a new route to the study of human tumor cell biology and uncover patient-specific tumor cell functions.

bioengineering↗

bioRxiv2019

Efficient and robust NK-Cell transduction with Baboon Envelope pseudotyped lentivector: a major tool for immunotherapy

NK-cell resistance to transduction is a major technical hurdle for developing NK-cell immunotherapy. By using Baboon envelope pseudotyped lentiviral vectors (BaEV-LVs) encoding eGFP, we obtained a transduction rate of 23.0{+/-}6.6% in freshly-isolated NK-cells (FI-NK) and 83.4{+/-}10.1% in NK-cells obtained from the NK-cell Activation and Expansion System (NKAES), even at low MOI, with a sustained transgene expression for at least 21 days. BaEV-LVs outperformed Vesicular Stomatitis Virus type-G (VSV-G)-, RD114-and Measles Virus (MV)-pseudotyped LVs (p<0.001). mRNA expression of both BaEV receptors, ASCT1 and ASCT2, was detected in FI-NK and NKAES, with much higher expression in NKAES. Transduction with BaEV-LVs encoding for CAR-CD22 resulted in robust CAR-expression on 44.2%{+/-}14.2% of NKAES cells, which allowed the specific killing of the NK-resistant pre-B-ALL-RS4;11 cell line. Using a larger vector, encoding a dual CD19/CD22-CAR separated by T2A, we were able to transduce and re-expand dual-CAR-expressing NKAES, even with low viral titer. These dual-CAR-NK efficiently and specifically killed both CD19KO-and CD22KO-RS4;11 cells, which may overcome antigen-loss escape in the clinical setting. Our results suggest that BaEV-LVs may efficiently enable NK-cell biological studies and translation of NK-cell-based immunotherapy to the clinic.

immunology↗

bioRxiv2026

PAVR: High-Resolution Cellular Imaging via a Physics-Aware Volumetric Reconstruction Framework

The rapid convergence of advanced microscopy and deep learning is transforming cell biology by enabling imaging systems in which optical encoding and computational inference are jointly optimized for volumetric information capture and interpretation. However, broadly accessible three-dimensional imaging at high spatiotemporal resolution remains constrained by volumetric reconstruction throughput, susceptibility to artifacts, and the burden of collecting modality-matched training data. Here, we introduce PAVR, a physics-aware light-field imaging platform that integrates single-shot volumetric acquisition with fast, end-to-end volumetric reconstruction. PAVR is trained entirely using in silico system responses, avoiding reliance on external high-resolution ground-truth modalities and enabling sample-independent reconstruction across diverse biological contexts. Using fixed and live mammalian cells, we demonstrate multicolor volumetric imaging of subcellular organelles, three-dimensional tracking of autofluorescent particles, and high-speed visualization of organelle remodeling and interactions. We further extend PAVR to quantify coupled morphological and functional dynamics in beating human induced pluripotent stem cell-derived cardiomyocytes under pharmacological perturbation. Together, PAVR establishes a scalable hardware-software platform for high-throughput volumetric imaging and quantitative analysis of dynamic cellular systems in both basic and translational settings.

bioengineering↗

bioRxiv2026

Tirzepatide attenuates atherosclerosis through weight loss-independent anti-inflammatory mechanisms

BackgroundAtherosclerosis is a chronic inflammatory vascular disorder with persistent residual inflammation even after standard lipid-lowering therapy. Mounting evidence from bench to bedside suggests that diabetes and obesity accelerate atherosclerosis development. Tirzepatide (TZP), a dual Glucagon-Like Peptide-1 Receptor/Glucose-Dependent Insulinotropic Polypeptide Receptor (GLP-1R/GIPR) agonist approved for treating diabetes and obesity, has demonstrated proven cardiometabolic efficacy in large cardiovascular outcome trials. However, it remains largely uncertain whether TZP attenuates atherosclerosis independent of its anti-diabetic and anti-obese effects through direct actions on the vasculature. MethodsWe established atherosclerotic mouse models under diabetic, obese, and non-diabetic/non-obese conditions. Analysis of covariance (ANCOVA) and pair-feeding experiments were applied to experimentally decouple weight-dependent metabolic improvement from intrinsic vasculoprotection. Molecular and cell biological assays in human umbilical vein endothelial cells (HUVECs) and human aortic endothelial cells (HAECs) were performed to dissect the underlying signaling mechanisms. ResultsTZP markedly reduced aortic plaque burden and inflammation, restrained necrotic core enlargement, and improved plaque stability across all experimental mouse models. Both ANCOVA and pair-feeding experiments confirmed that these atheroprotective effects were independent of food intake and body weight loss. Furthermore, TZP attenuated systemic and vascular inflammation in Tumor Necrosis Factor- (TNF)-treated C57BL/6J mice, and this protection occurred without changes in body weight or blood glucose levels. Mechanistically, TZP directly targeted endothelial cells and activated the cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA)/endothelial nitric oxide synthase (eNOS) pathway, increased eNOS phosphorylation and nitric oxide bioavailability, consequently downregulating the expression of the pro-inflammatory adhesion molecules Vascular Cell Adhesion Molecule-1 (VCAM-1) and Intercellular Adhesion Molecule-1 (ICAM-1). ConclusionsTZP arrests atherosclerosis progression through weight loss-independent anti-inflammatory mechanisms. These findings implicate TZP as a promising therapeutic drug for mitigating residual vascular inflammation in patients with atherosclerotic cardiovascular disease (ASCVD), irrespective of glycemic status or obesity. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LITirzepatide exerts direct anti-atherosclerotic effects in preclinical mouse models of atherosclerosis under diabetic, obese, and non-obese conditions. C_LIO_LITirzepatide directly targets endothelial GLP-1R/GIPR and downstream cAMP/PKA/eNOS signaling pathway to suppress NF-{kappa}B-driven vascular inflammation, thereby uncovering a previously unrecognized vasculoprotective mechanism underlying its cardiovascular benefits C_LI What Are the Clinical Implications?O_LITirzepatide exerts direct vascular protective effects independent of body weight reduction, suggesting that its cardiovascular benefits may extend beyond glycemic control and obesity management. C_LIO_LITirzepatide may represent a promising therapeutic drug for addressing residual vascular inflammation in ASCVD patients, including those without overt diabetes or obesity C_LI

physiology↗

bioRxiv2025

TRAP seq in 3D Angiogenesis Assays Reveals a Distinct Endothelial Translatome Associated with Early and Late Stages of Morphogenesis.

Endothelial cells (ECs) are often a minority cell type in a tissue, limiting the utility of bulk sequencing approaches. Single cell sequencing lacks sensitivity and requires disruptive tissue digestion techniques. TRAP seq (Translating Ribosome Affinity Purification) or "RiboTag" has been used to overcome these limitations. Multicellular co-culture systems allow primary ECs to differentiate and undergo tubular morphogenesis in cell culture, however similar limitations exist with these in vitro assays, as ECs are under-represented by as much as a factor of 10 in many assays. We sought to use TRAP seq to better understand the gene expression landscapes that drive these morphogenic events. We found TRAP seq selectively enriches for endothelial RNA in two distinct co-culture paradigms, in both the planar and fibrin bead co-culture assays. Intriguingly, the use of this technology in vitro, revealed distinct gene expression changes in blood vessel development and in the mitotic cell cycle, with genes unique to early and late phases of morphogenesis. It is widely accepted that expression of the NOTCH signaling pathway is a regulator of angiogenesis in vivo. Correspondingly, we found that a large number of NOTCH related genes relevant to endothelial cell biology, were changing across this morphogenic process, underpinning the importance and utility of this technology in 3D multicellular cultures that model in vivo environments.

cell biology↗

bioRxiv2024

Dual roles of IQCG, a novel microtubule nucleation factor rapidly evolving in humans

The centrosome serves as the main microtubule-organizing structure, playing crucial roles in animal development. Uncovering new components and elucidating their functions helps to understand the regulation of cell maintenance and division by the centrosome. In this study, through a combination of genetic analyses and cell biological characterizations, we identify IQ Motif Containing G (IQCG) as a novel microtubule nucleation factor with a dual role involved in both centrosomal microtubule organization and mitotic spindle formation. IQCG interacts with GSK3{beta} via its N2 region, enhancing its centrosomal accumulation in interphase; subsequently, IQCG disperses into the spindle to promote microtubule generation during mitosis and ensure robust cell division. Furthermore, our analyses indicate that the IQCG gene has undergone accelerated evolution within the human lineage, with positive selection acting on the variable N2 region. This adaptation may confer advantages to human cells by augmenting central regulatory control over cellular activities through the centrosome. Our findings offer novel insights into the functional mechanisms and evolutionary significance of the human centrosome associated with human evolution. Summary blurbThe cellular functions of the novel microtubule nucleation factor IQCG, which enhances centrosomal microtubule organization and cell division robustness, are implicated in human evolution.

cell biology↗

bioRxiv2026

Cellquant: a vibecoder's guide to image analysis

Quantitative fluorescence microscopy is central to modern cell biology, yet extracting reproducible measurements from images remains a bottleneck for biologists without programming experience. Here we present cellquant, a single-script command line pipeline for multi-channel fluorescence images that performs cell segmentation, puncta quantification, colocalization analysis, and spatial proximity measurements. Because the interface is entirely text based, the exact command used to generate any result can be recorded and re-executed. We validate cellquant on two biological systems. In human HCT116 cells, the pipeline quantified arsenite-induced stress granule formation. In budding yeast, simultaneous measurement of nucleolar morphology, colocalization, and spatial proximity across a temperature gradient revealed a coordinated sequence of nucleolar reorganization. Applying PCA and UMAP to the multi-parameter output of cellquant resolved a continuous cell state transition across the temperature gradient, with condensate redistribution and nucleolar morphology defining orthogonal axes. The pipeline produces publication-ready quantification with visual quality control and statistically rigorous replicate analysis. All code, documentation, and example datasets are freely available.

cell biology↗