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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 1,675 records · Page 93Linked to original sources
bioRxiv2021

tiRNA signaling via stress-regulated vesicle transfer in the hematopoietic niche

Extracellular vesicles transfer complex biologic material between cells, whose role in in-vivo organismal physiology is poorly defined. Here, we demonstrate that osteoblastic cells in the bone marrow elaborate extracellular vesicles that are taken up by hematopoietic progenitor cells in vivo. Genotoxic or infectious stress rapidly increased stromal-derived extracellular vesicle transfer to granulocyte-monocyte progenitors. Stimulating osteoblastic cells with parathyroid hormone or activating its receptor enhanced extracellular vesicle transfer, myeloid recovery post radiation and improved animal survival from Candida sepsis. The extracellular vesicles contained tiRNAs known to modulate protein translation. 5-ti-Pro-CGG-1 was preferentially abundant in osteoblast-derived extracellular vesicles and when transferred to granulocyte macrophage progenitors, increased protein translation, cell proliferation and myeloid differentiation. Therefore, EV-mediated tiRNA transfer provides a stress modulated signaling axis distinct from conventional cytokine-driven stress responses. One sentence summaryStress regulated tiRNA transfer alters hematopoiesis

cell biology↗
bioRxiv2021

Fluorinated oil-surfactant mixtures with the density of water: artificial cells for synthetic biology

There is a rising interest in biotechnology for the compartmentalization of biochemical reactions in water droplets. Several applications, such as the widely used digital PCR, seek to encapsulate a single molecule in a droplet to be amplified. Directed evolution, another technology with growing popularity, seeks to replicate what happens in nature by encapsulating a single gene and the protein encoded by this gene, linking genotype with phenotype. Compartmentalizing reactions in droplets also allows the experimentalist to run millions of different reactions in parallel. Compartmentalization requires a fluid that is immiscible with water and a surfactant to stabilize the droplets. While there are fluids and surfactants on the market that have been used to accomplish encapsulation, there are reported concerns with these. Span(R) 80, for example, a commonly used surfactant, has contaminants that interfere with various biochemical reactions. Similarly, synthetic fluids distributed by the cosmetic industry allow some researchers to produce experimental results that can be published, but then other researchers fail to reproduce some of these protocols due to the unreliable nature of these products, which are not manufactured with the intent of being used in biotechnology. The most reliable fluids, immiscible with water and suitable for biochemical reactions, are fluorinated fluids. Fluorinated compounds have the peculiar characteristic of being immiscible with water while at the same time not mixing with hydrophobic molecules. This peculiar characteristic has made fluorinated fluids attractive because it seems to be the basis of their being biologically inert. However, commercially available fluorinated fluids have densities between 1.4 to 1.6 g/mL. The higher-than-water density of fluorinated oils complicates handling of the droplets since these would float on the fluid since the water droplets would be less dense. This can cause aggregation and coalescence of the droplets. Here, we report the synthesis, characterization, and use of fluorinated polysiloxane oils that have densities similar to the one of water at room temperature, and when mixed with non-ionic fluorinated surfactants, can produce droplets encapsulating biochemical reactions. We show how droplets in these emulsions can host many biological processes, including PCR, DNA origami, rolling circle amplification (RCA), and Taqman(R) assays. Some of these use unnatural DNA built from an Artificially Expanded Genetic Information System (AEGIS) with six nucleotide "letters".

synthetic biology↗
bioRxiv2021

Systematic discovery of receptor-ligand biology by engineered cell entry and single-cell genomics

Cells communicate with each other via receptor-ligand interactions on the cell surface. Here we describe a technology for lentiviral-mediated cell entry by engineered receptor-ligand interaction (ENTER) to decode receptor specificity. Engineered lentiviral particles displaying specific ligands deliver fluorescent proteins into target cells upon cognate receptor-ligand interaction, without genome integration or transgene transcription. We optimize ENTER to decode interactions between T cell receptor (TCR)-MHC peptides, antibody-antigen, and other receptor-ligand pairs. We develop an effective presentation strategy to capture interactions between B cell receptor (BCR) and intracellular antigen epitopes. Single-cell readout of ENTER by RNA sequencing (ENTER-seq) enables multiplexed enumeration of TCR-antigen specificities, clonality, cell type, and cell states of individual T cells. ENTER-seq of patient blood samples after CMV infection reveals the viral epitopes that drive human effector memory T cell differentiation and inter-clonal phenotypic diversity that targets the same epitope. ENTER enables systematic discovery of receptor specificity, linkage to cell fates, and cell-specific delivery of gene or protein payloads. HIGHLIGHTSO_LIENTER displays ligands, deliver cargos, and records receptor specificity. C_LIO_LIENTER deorphanizes antigen recognition of TCR and BCR. C_LIO_LIENTER-seq maps TCR specificity, clonality and cell state in single cells. C_LIO_LIENTER-seq of patient sample decodes antiviral T cell memory. C_LI

genomics↗
bioRxiv2022

Bioengineering multifunctional extracellular vesicles for targeted delivery of biologics to T cells

Genetically modifying T cells can enable applications ranging from cancer immunotherapy to HIV treatment, yet delivery of T cell-targeted therapeutics remains challenging. Extracellular vesicles (EVs) are nanoscale particles secreted by all cells that naturally encapsulate and transfer proteins and nucleic acids, making them an attractive and clinically-relevant platform for engineering biocompatible delivery vehicles. We report a suite of technologies for genetically engineering cells to produce multifunctional EV vehicles--without employing chemical modifications that complicate biomanufacturing. We display high affinity targeting domains on the EV surface to achieve specific, efficient binding to T cells, identify a protein tag to confer active cargo loading into EVs, and display fusogenic glycoproteins to increase EV uptake and fusion with recipient cells. We demonstrate integration of these technologies by delivering Cas9-sgRNA complexes to edit primary human T cells. These approaches could enable targeting vesicles to a range of cells for the efficient delivery of cargo.

bioengineering↗
bioRxiv2022

3D CentroidNet: Nuclei Centroid Detection With Vector Flow Voting

Automated microscope systems are increasingly used to collect large-scale 3D image volumes of biological tissues. Since cell boundaries are seldom delineated in these images, detection of nuclei is a critical step for identifying and analyzing individual cells. Due to the large intra-class variability in nuclei morphology and the difficulty of generating ground truth annotations, accurate nuclei detection remains a challenging task. We propose a 3D nuclei centroid detection method by estimating the "vector flow" volume where each voxel represents a 3D vector pointing to its nearest nuclei centroid in the corresponding microscopy volume. We then use a voting mechanism to estimate the 3D nuclei centroids from the "vector flow" volume. Our system is trained on synthetic microscopy volumes and tested on real microscopy volumes. The evaluation results indicate our method outperforms other methods both visually and quantitatively.

cell biology↗
bioRxiv2025

A Morpho-Proteomic Atlas of Mitosis at Sub-Minute Resolution

Precise spatiotemporal protein organization is critical for fundamental biological processes including cell division1,2. Indeed, aberrant mitosis and mitotic factors are involved in diverse diseases, including various cancers3,4, Alzheimers disease5, and rare diseases6. During mitosis, complex spatial rearrangements and regulation ensure the accurate separation of replicated sister chromatids to produce genetically identical daughter cells7-9. Previous studies employed high-throughput methodologies to follow specific proteins during mitosis10-15. Still a temporally refined systems-level approach capable of monitoring morphological and proteomic changes throughout mitosis has been lacking. Here, we achieved unprecedented resolution by phenotypically decomposing mitosis into 40 subsections of a regression plane for proteomic analysis using deep learning and regression techniques. Our deep visual proteomics (DVP) workflow16, revealed rapid, dynamic proteomic changes throughout mitosis. We quantified 4,350 proteins with high confidence, demonstrating that 147 show significant dynamic abundance changes during mitotic progression. Clustering revealed coordinated patterns of protein regulation, while network analysis uncovered tight regulation of core cell cycle proteins and a link between cell cycle and cancer-linked mutations. Immunofluorescence validated abundance changes and linked previously uncharacterised proteins, like C19orf53, to mitosis. To facilitate data navigation, we developed Mito-Omix, a user-friendly online platform that integrates intricate morphological and molecular data. Our morphological and proteomic dataset spans mitosis at high resolution, providing a rich resource for understanding healthy and aberrant cell division.

cell biology↗
bioRxiv2025

The copper chaperone ATOX1 exhibits differential protein-protein interactions and contributes to skeletal myoblast differentiation

Copper is an essential but potentially toxic nutrient required for a variety of biological functions. Mammalian cells use a complex network of copper transporters and metallochaperones to maintain copper homeostasis. Previous work investigating the role of copper in various disease states has highlighted the importance of copper transporters and metallochaperones. However, questions remain about how copper distribution changes under dynamic conditions like tissue differentiation. We previously reported that the copper exporter ATP7A is required for skeletal myoblast differentiation and that its expression changes in a differentiation dependent manner. Here, we sought to further understand the ATP7A-mediated copper export pathway by examining ATOX1, the copper chaperone that delivers copper to ATP7A. To investigate the role of ATOX1 in a dynamic cellular context, we characterized its binding partners during myoblast differentiation using the proximity labeling protein APEX2 to biotinylate proteins near ATOX1. We discovered that the ATOX1 interactome undergoes dramatic changes as myoblasts differentiate. These dynamic interactions correlate with distinct phenotypes of ATOX1 deficiency in proliferating and differentiated cells. Together, our results highlight the dynamic interactome of ATOX1 and its contribution to myoblast differentiation.

cell biology↗
bioRxiv2025

Inferring virtual cell environments using multi-agent reinforcement learning

1Single cells interact continuously to form a cell environment that drives key biological processes. Cells and cell environments are highly dynamic across time and space, fundamentally governed by molecular mechanisms, such as gene expression. Recent sequencing techniques measure single-cell-level gene expression under specific conditions, either temporally or spatially. Using these datasets, emerging works, such as virtual cells, can learn biologically useful representations of individual cells. However, these representations are typically static and overlook the underlying cell environment and its dynamics. To address this, we developed CellTRIP, a multi-agent reinforcement learning method that infers a virtual cell environment to simulate the cell dynamics and interactions underlying given single-cell data. Specifically, cells are modeled as individual agents with dynamic interactions, which can be learned through self-attention mechanisms via reinforcement learning. CellTRIP also applies novel truncated reward boot-strapping and adaptive input rescaling to stabilize training. We can in-silico manipulate any combination of cells and genes in our learned virtual cell environment, predict spatial and/or temporal cell changes, and prioritize corresponding genes at the single-cell level. We applied and benchmarked CellTRIP on various simulated and real gene expression datasets, including recapitulating cellular dynamic processes simulated by gene regulatory networks and stochastic models, imputing spatial organization of mouse cortical cells, predicting developmental gene expression changes after drug treatment in cancer cells, and spatiotemporal reconstruction of Drosophila embryonic development, demonstrating its outperformance and broad applicability. Interactive manipulation of those virtual cell environments, including in-silico perturbation, can prioritize spatial and developmental genes for single-cell-level changes, enabling the generation of new insights into cell dynamics over time and space. CellTRIP is open source as a general tool and available at github.com/daifengwanglab/CellTRIP.

bioinformatics↗
bioRxiv2025

Engineered Transdermal Peptide-Recombinant Type III Collagen Hydrogel with Biological Efficacy in Cell Proliferation and Wound Healing

Collagen, as a major structural protein in the extracellular matrix, plays a crucial role in tissue regeneration; however, traditional collagen sources often suffer from immunogenicity, poor stability, and batch-to-batch variability. In this study, a novel transdermal peptide-recombinant type III collagen hydrogel was developed, which has excellent biocompatibility, thermal stability, and skin repair effects. Transdermal peptide-recombinant type III collagen was expressed and purified by genetic engineering methods, and its potential for biomedical applications was further evaluated. The experimental results showed that the prepared collagen had a high purity (95%) and retained the unique secondary structure of collagen, showing good structural stability at different pH values. Through cell proliferation experiments and mouse wound healing experiments, we verified the superior effect of the collagen hydrogel in promoting wound healing and significantly accelerating wound healing at concentrations as low as 0.2 mg/mL. This achievement provides strong experimental support for its application in clinical skin wound repair.

biochemistry↗
bioRxiv2018

Prolyl Endopeptidase (PREP) is Involved in the Reproductive Functions and Cytoskeletal Organization in Rat Spermatogenesis and in Mammalian Sperm.

Prolyl endopeptidase (PREP) is an enzyme which cleaves several peptide hormones and neuropeptides at the carboxyl side of proline residues, involved in many biological processes, including cell proliferation and differentiation, glucose metabolism, learning, memory and cognitive disorders. Moreover, PREP was identified as binding partner of tubulin, suggesting that this endopeptidase may be involved in microtubule-associate processes, independent of its peptidase activity. Several reports have also suggested PREP participation in both male and female reproduction-associated processes. In this work, we assessed the possible association of PREP with the morphogenesis of rat testis, profiling its localization versus tubulin, during the first wave of spermatogenesis and in the adult gonad (from 7 to 60 dpp). Here we show that, in mitotic phases, PREP shares its localization with tubulin in Sertoli cells, gonocytes and spermatogonia. Later, during meiosis, both proteins are found in spermatocytes, and in the cytoplasm of Sertoli cells protrusions, which surround the germ cells, while, during spermiogenesis, they both localize in the cytoplasm of round and elongating spermatids. Finally, they are expressed in the flagellum of mature gametes, as corroborated by additional immunolocalization analysis on both rat and human sperm. Our data strongly support the hypothesis of a role of PREP in supporting a correct reproductive function and in cytoskeletal organization during Mammalian testis morphogenesis and gamete progression, while also hinting at its possible investigation as a morphological marker of germ cell and sperm physiology.\n\nSummary statementIn this paper we show the co-localization of the enzyme PREP with tubulin during the first wave of rat spermatogenesis and in mature gametes of rat and human.

cell biology↗
bioRxiv2026

AKIP1 is an inner scaffold component required for centriole integrity

Centrioles are microtubule-based organelles that play crucial roles in various biological processes, including cell division, ciliogenesis and flagellar assembly. These functions require the preservation of centriole structural integrity, yet the molecular mechanisms that maintain this integrity remain incompletely understood. In this study, through large-scale gene co-dependency analysis and ultrastructure expansion microscopy (U-ExM), we identified A-kinase interacting protein 1 (AKIP1) as a novel component of the centriole inner scaffold, a luminal structural framework that supports centriole integrity. Analysis of large-scale functional genomic data from DepMap placed AKIP1 in a functional cluster with the inner scaffold components POC1A, POC1B, and POC5. Consistently, AKIP1 colocalizes with these clustered inner scaffold components in the central core region of centrioles, forming a multicomponent interaction network. We further show that AKIP1 is recruited to centrioles during G2 phase, subsequent to the recruitment of other inner scaffold components, and that its centriolar localization depends on these components. AKIP1 depletion leads to defects in centriolar microtubules and abnormal centriole morphology. Together, our findings establish AKIP1 as a downstream component of the inner scaffold that contributes to the maintenance of centriole integrity.

cell biology↗
bioRxiv2018

Biology and Bias in Cell Type-Specific RNAseq of Nucleus Accumbens Medium Spiny Neurons

Isolation of cell populations is untangling complex biological interactions, but studies comparing methodologies lack in vivo complexity and draw limited conclusions about the types of transcripts identified by each technique. Furthermore, few studies compare FACS-based techniques to ribosomal affinity purification, and none do so genome-wide. We addressed this gap by systematically comparing nuclear-FACS, whole cell-FACS, and RiboTag affinity purification in the context of D1 or D2 dopamine receptor-expressing medium spiny neuron (MSN) subtypes of the nucleus accumbens (NAc), a key brain reward region. We find that nuclear-FACS-seq generates a substantially longer list of differentially expressed genes between these cell types, and a significantly larger number of neuropsychiatric GWAS hits than the other two methods. RiboTag-seq has much lower coverage of the transcriptome than the other methods, but very efficiently distinguishes D1- and D2-MSNs. We also demonstrate differences between D1- and D2-MSNs with respect to RNA localization, suggesting fundamental cell type differences in mechanisms of transcriptional regulation and subcellular transport of RNAs. Together, these findings guide the field in selecting the RNAseq method that best suits the scientific questions under investigation.

neuroscience↗
bioRxiv2019

Investigating the Central Dogma of Molecular Biology in the Context of Nuclear Architecture and Cell Cycle

Nuclear architecture is the organization of the genome within a cell nucleus with respect to different nuclear landmarks such as nuclear lamina, matrix or nucleoli. Lately it has emerged as a major regulator of gene expression in mammalian cells. The studies connecting nuclear architecture with gene expression are largely population-averaged and do not report on the heterogeneity in genome organization or in gene expression within a population. In this report we present a method for combining 3D DNA Fluorescence in situ Hybridization (FISH) with single molecule RNA FISH (smFISH) and immunofluorescence to study nuclear architecture-dependent gene regulation on a cell-by-cell basis. We further combine it with an imaging-based cell cycle staging to correlate nuclear architecture with gene expression across the cell cycle. We present this in the context of Cyclin A2 (CCNA2) gene for its known cell cycle-dependent expression. We show that, across the cell cycle, the expression of a CCNA2 gene copy is stochastic and depends neither on its sub-nuclear position--which usually lies close to nuclear lamina--nor on the expression from the other copies.

cell biology↗
bioRxiv2026

Systematic evaluation of integration methods and parameters on single-cell RNA-sequencing biological insights: a case study on cattle embryos.

BackgroundSingle-cell RNA sequencing (scRNA-seq) integration methods remove technical variation while preserving biological signal, yet systematic frameworks for evaluating how parameter choices influence biological interpretation remain limited. Traditional benchmarking approaches evaluate single-parameter configurations per method, potentially missing systematic patterns in functional outcomes and method convergence. A framework for systematic integration parameter evaluation was developed and applied to bovine embryo development. ResultsSix integration methods (FastMNN, CCA, RPCA, scVI, Harmony, STACAS) combined with multiple parameters, including those for neighbor identification and clustering, yielded 8232 combinations. The main outputs evaluated were specific cell counts and marker identification. After filtering for extremely poor cell and marker identification, 4,287 integration parameter combinations were retained for analysis. There were three major patterns (clusters) with integration methods distributed non-randomly across clusters and distinct biological outcomes. One pattern emerged, composed of scVI and STACAS integration, dominated by the lack of identification of epiblast cells. Cluster 2 (n=29), also composed of scVI and STACAS integration, identified the most epiblast markers (n=7, 8, or 9) but had a limited number of epiblast cells (median=10). Cluster 1 (n=4,120 combinations) had the highest method diversity. Across clusters, trophoblast and mesoderm showed high functional distinctness, while epiblast and hypoblast showed moderate overlap in gene ontology classes. ConclusionsThe approach reveals that parameter choices influence cell type classification, functional interpretation, and the degree of method convergence, with implications for identifying specific biological inferences for further orthogonal validation. A systematic approach to evaluating integration methods, along with other parameters, is advisable for accurate biological inference.

genomics↗
bioRxiv2026

Immediate transcriptional changes initiated by direct cell-cell contact between cytotoxic T cells and cancer cells

Many biological processes are regulated by the direct interaction between two or more cell types. However, our understanding of the immediate dynamic changes in gene transcription upon physical interaction between two cells has remained limited due to technical limitations. Here we address these limitations in a model system of cancer-specific T cell receptor (TCR)-modified CD8 T cells where single and cancer-interacting T cells were isolated by image-enabled cell sorting and transcripts from heterotypic cancer cell and T cell pairs were in silico assigned. This approach uncovers immediate, dynamic changes in gene expression following the specific interaction between TCR-modified CD8 T cells and cancer cells. In addition to dissecting transcriptional cascades dependent on the peptide sensitivity of the TCR, we for the first time directly compare these gene expression changes between single T cells and T cells in direct physical contact with cancer cells. Modeling of the observed transcriptomic activation signature identifies phenotypically distinct tumor infiltrating CD8 T cell subsets associated with reduced TCR diversity in in vivo datasets. Taken together, the paradigm developed here allows for future clonal identification of T cell receptors mediating ongoing effective cytotoxic responses in vivo.

immunology↗
bioRxiv2021

Reciprocal impacts of telomerase activity and tumor cell differentiation in neuroblastoma tumor biology

Telomere maintenance and tumor cell differentiation have been separately implicated in neuroblastoma malignancy. Their mechanistic connection is unclear. We analyzed neuroblastoma cell lines and morphologic subclones representing the adrenergic (ADRN) and mesenchymal (MES) differentiation states and uncovered sharp differences in their telomere protein and telomerase activity levels. Pharmacologic conversion of ADRN into MES cells elicited consistent and robust changes in the expression of telomere-related proteins. Conversely, stringent down-regulation of telomerase activity triggers the differentiation of ADRN into MES cells, which was reversible upon telomerase upregulation. Interestingly, the MES differentiation state is associated with elevated levels of innate immunity factors, including key components of the DNA-sensing pathway. Accordingly, MES but not ADRN cells can mount a robust response to viral infections in vitro. A gene expression signature based on telomere and cell lineage-related factors can cluster neuroblastoma tumor samples into predominantly ADRN or MES-like groups, with distinct clinical outcomes. Our findings establish a novel mechanistic connection between telomere and differentiation and suggest that manipulating telomeres may suppress malignancy not only by limiting the tumor growth potential but also by inducing tumor cell differentiation and altering its immunogenicity.

cancer biology↗
bioRxiv2017

Extended logistic growth model for heterogeneous populations

Cell proliferation is the most important cellular-level mechanism responsible for regulating cell population dynamics in living tissues. Modern experimental procedures show that the proliferation rates of individual cells can vary significantly within the same cell line. However, in the mathematical biology literature, cell proliferation is typically modelled using a classical logistic equation which neglects variations in the proliferation rate. In this work, we consider a discrete mathematical model of cell migration and cell proliferation, modulated by volume exclusion (crowding) effects, with variable rates of proliferation across the total population. We refer to this variability as heterogeneity. Constructing the continuum limit of the discrete model leads to a generalisation of the classical logistic growth model. Comparing numerical solutions of the model to averaged data from discrete simulations shows that the new model captures the key features of the discrete process. Applying the extended logistic model to simulate a proliferation assay using rates from recent experimental literature shows that neglecting the role of heterogeneity can, at times, lead to misleading results.

cell biology↗
bioRxiv2025

Programmable chronogenetic gene circuits for self-regulated circadian delivery of biologic drugs

Cells of the body rely on the circadian clock to orchestrate daily changes in physiology that impact both homeostatic and pathological conditions, such as the inflammatory autoimmune disease rheumatoid arthritis (RA). In RA, high levels of proinflammatory cytokines peak early in the morning hours, reflected by daily changes in joint stiffness. Chronotherapy (or circadian medicine) seeks to delivery drugs at optimal times to maximize their efficacy. However, chronotherapy remains a largely unexplored approach for disease modifying, antirheumatic treatment, particularly for cell-based therapies. In this study, we developed autonomous chronogenetic gene circuits that produce the biologic drug interleukin-1 receptor antagonist (IL-1Ra) with desired phase and amplitude. We compared expression of IL-1Ra from circuits that contained different circadian promoter elements (E-boxes, D-boxes, or RREs) and their ability to respond to inflammatory challenges in murine pre-differentiated induced pluripotent stem cells (PDiPSC) or engineered cartilage pellets. We confirmed that each circuit reliably peaked at a distinct circadian time over multiple days. Engineered cells generated significant amounts of IL-1Ra on a circadian basis, which protected them from circadian dysregulation and inflammatory damage. These programmable chronogenetic circuits have the potential to align with an individuals circadian rhythm for optimized, self-regulated daily drug delivery.

synthetic biology↗