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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 307 records · Page 17Linked to original sources

bioRxiv2018

Microinjection into the Caenorhabditis elegans embryo using an uncoated glass needle enables cell lineage visualization and reveals cell-non-autonomous adhesion control

Microinjection is a useful method in cell biology, with which exogenous substances are introduced into a cell in a location- and time-specific manner. The Caenorhabditis elegans embryo is an important model system for cell and developmental biology. Applying microinjection to the C. elegans embryo had been difficult due to the rigid eggshell surrounding the embryo. In 2013, microinjection method using a carbon-coated quartz needle for the C. elegans embryo was reported. To prepare the needle, unfortunately, special equipment is required and thus a limited number of researchers can use this method. In this study, we established a method for the microinjection of drugs, dyes, and microbeads into the C. elegans embryo using an uncoated glass needle that can be produced in a general laboratory. This method enabled us to easily detect cell lineage up to adult stages by injecting a fluorescent dye into a blastomere. We also found a cell-non-autonomous control mechanism of cell adhesion; specifically, the injection of an actin inhibitor into one cell at the 2-cell stage enhanced adhesion between daughter cells of the other cell. Our microinjection method is expected to be used for broad studies and could facilitate various discoveries using C. elegans.

cell biology↗

bioRxiv2019

3D imaging of colorectal cancer organoids identifies responses to Tankyrase inhibitors

Aberrant activation of the Wnt signalling pathway is required for tumour initiation and survival in the majority of colorectal cancers. The development of inhibitors of Wnt signalling has been the focus of multiple drug discovery programs targeting colorectal cancer and other malignancies associated with aberrant pathway activation. However, progression of new clinical entities targeting the Wnt pathway has been slow. One challenge lies with the limited predictive power of 2D cancer cell lines because they fail to fully recapitulate intratumoural phenotypic heterogeneity. In particular, the relationship between 2D cancer cell biology and cancer stem cell function is poorly understood. By contrast, 3D tumour organoids provide a platform in which complex cell-cell interactions can be studied. However, complex 3D models provide a challenging platform for the quantitative analysis of drug responses of therapies that have differential effects on tumour cell subpopulations. Here, we generated tumour organoids from colorectal cancer patients and tested their responses to inhibitors of Tankyrase (TNKSi) which are known to modulate Wnt signalling. Using compounds with 3 orders of magnitude difference in cellular mechanistic potency together with image-based assays, we demonstrate that morphometric analyses can capture subtle alterations in organoid responses to Wnt inhibitors that are consistent with activity against a cancer stem cell subpopulation. Overall our study highlights the value of phenotypic readouts as a quantitative method to asses drug-induced effects in a relevant preclinical model.

cancer biology↗

bioRxiv2018

KH-type splicing regulatory protein controls colorectal cancer cell growth and modulates the tumor microenvironment

KH-type splicing regulatory protein (KHSRP) is a multifunctional nucleic acid binding protein implicated in key aspects of cancer cell biology: inflammation and cell-fate determination. However, the role KHSRP plays in colorectal cancer (CRC) tumorigenesis remains largely unknown. Using a combination of in silico analysis of large datasets, ex vivo analysis of protein expression in patients, and mechanistic studies using in vitro models of CRC, we investigated the oncogenic role of KHSRP. We demonstrated KHSRP expression in the epithelial and stromal compartments of both primary and metastatic tumors. Elevated expression was found in tumor versus matched normal tissue, and we validated these findings in larger independent cohorts in silico. KHSRP expression was a prognostic indicator of worse overall survival (HR=3.74, 95% CI = 1.43-22.97, p=0.0138). Mechanistic data in CRC cell line models supported a role of KHSRP in driving epithelial cell proliferation in both a primary and metastatic setting, through control of the G1/S transition. Additionally, KHSRP promoted a pro-angiogenic extracellular environment by regulating the secretion of oncogenic proteins involved in diverse cellular processes such as migration and response to cellular stress. Our study provides novel mechanistic insight into the tumor-promoting effects of KHSRP in CRC.

cancer biology↗

bioRxiv2020

Evidence that polyploidy in esophageal adenocarcinoma originates from mitotic slippage caused by defective chromosome attachments

Polyploidy is present in many cancer types and is increasingly recognized as an important factor in promoting chromosomal instability, genome evolution, and heterogeneity in cancer cells. However, the mechanisms that trigger polyploidy in cancer cells are largely unknown. In this study, we investigated the origin of polyploidy in esophageal adenocarcinoma (EAC), a highly heterogenous cancer, using a combination of genomics and cell biology approaches in EAC cell lines, organoids, and tumors. We found the EAC cells and organoids present specific mitotic defects consistent with problems in the attachment of chromosomes to the microtubules of the mitotic spindle. Time-lapse analyses confirmed that EAC cells have problems in congressing and aligning their chromosomes, which can ultimately culminate in mitotic slippage and polyploidy. Furthermore, whole-genome sequencing, RNA-seq, and quantitative immunofluorescence analyses revealed alterations in the copy number, expression, and cellular distribution of several proteins known to be involved in the mechanics and regulation of chromosome dynamics during mitosis. Together, these results provide evidence that an imbalance in the amount of proteins implicated in the attachment of chromosomes to spindle microtubules is the molecular mechanism underlying mitotic slippage in EAC. Our findings that the likely origin of polyploidy in EAC is mitotic failure caused by problems in chromosomal attachments not only improves our understanding of cancer evolution and diversification, but may also aid in the classification and treatment of EAC and possibly other highly heterogeneous cancers.

cancer biology↗

bioRxiv2026

Learning activator-inhibitor dynamics at the cell cortex with neural likelihood ratio estimation

A key question in cell biology is how cell-scale organization emerges from a given set of molecular players and rules of interaction. Given its multiscale nature, addressing this question requires a combination of experimental perturbation, mathematical modeling, and parameter inference. We leverage recent advances in each of these fields, focusing in particular on neural-network methods for simulation-based inference, to study how cell-scale patterns of Rho GTPase activity are defined by molecular-scale activator-inhibitor interactions with filamentous actin. Using an existing model of this interaction, we demonstrate that an over-expressive, regularized classification neural network can approximate the likelihood of data arising from a particular parameter set. We show that variations in F-actin assembly dynamics can be inferred directly from experimental data, but only if the network is made less sensitive to model misspecification. We use our approach to interpret perturbation experiments in which increasing RhoGAP coexpression increases the frequency and coherence of Rho activity waves in frog eggs. After showing that the known functions of RhoGAP are insufficient to explain experimentally-observed dynamics, we use neural methods to suggest an alternative pathway by which RhoGAP could decrease filament nucleation rates to sustain waves. Our work yields specific, experimentally-testable predictions and illustrates how a combination of traditional forward models and modern inference tools can aid in unraveling mechanisms of self-organization.

systems biology↗

bioRxiv2020

Cadherin clustering controls heterogeneous, asymmetric junction dynamics during vertebrate axis elongation

Morphogenesis is governed by the interplay of molecular signals and mechanical forces across multiple length scales. The last decade has seen tremendous advances in our understanding of the dynamics of protein localization and turnover at sub-cellular length scales, and at the other end of the spectrum, of mechanics at tissue-level length scales. Integrating the two remains a challenge, however, because we lack a detailed understanding of the subcellular patterns of mechanical properties of cells within tissues. Here, in the context of the elongating body axis of a vertebrate embryo, we combine tools from cell biology and physics to demonstrate that individual cell-cell junctions display finely-patterned local mechanical heterogeneity along their length. We show that such local mechanical patterning is essential for the cell movements of convergent extension and is imparted by locally patterned clustering of a classical cadherin. Finally, the patterning of cadherins and thus local mechanics along cell-cell junctions are controlled by Planar Cell Polarity signaling, a key genetic module for CE that is mutated in diverse human birth defects.

cell biology↗

bioRxiv2020

Cytonemes with complex geometries and composition extend into invaginations of target cells

Cytonemes are specialized filopodia that mediate paracrine signaling in Drosophila and other animals. Studies using fluorescence confocal microscopy (CM) established their general paths, cell targets, and essential roles in signaling. To investigate details unresolvable by CM, we used high pressure freezing and electron microscopy to visualize cytoneme structures, paths, contents, and contacts. We observed cytonemes previously seen by CM in the Drosophila wing imaginal disc system, including in disc, tracheal air sac primordium (ASP), and myoblast cytonemes, and identified cytonemes extending into invaginations of target cells and cytonemes connecting ASP cells and connecting myoblasts. Diameters of cytoneme shafts vary between wide (206 {+/-} 51.8 nm) and thin (55.9 {+/-}16.2 nm) segments at regular intervals. Actin, ribosomes, and membranous compartments are present throughout; rough endoplasmic reticulum and mitochondria are in wider proximal sections. These results reveal novel structural features of filopodia and provide a basis for understanding cytoneme cell biology and function. SummaryCytoneme signaling filopodia of Drosophila cells have regions defined by oscillating diameters, and contents that include ER, mitochondria and ribosomes, and form contacts along invaginations of target cell membranes.

cell biology↗

bioRxiv2022

scHumanNet: a single-cell network analysis platform for the study of cell-type specificity of disease genes

A major challenge in single-cell biology is identifying cell-type-specific gene functions, which may substantially improve precision medicine. Differential expression analysis of genes is a popular, yet insufficient approach, and complementary methods that associate function with cell type are required. Here, we describe scHumanNet (https://github.com/netbiolab/scHumanNet), a single-cell network analysis platform for resolving cellular heterogeneity across gene functions in humans. Based on cell-type-specific networks (CSNs) constructed under the guidance of the HumanNet reference interactome, scHumanNet displayed higher functional relevance to the cellular context than CSNs built by other methods on single-cell transcriptome data. Cellular deconvolution of gene signatures based on network compactness across cell types revealed breast cancer prognostic markers associated with T cells. scHumanNet could also prioritize genes associated with particular cell types using CSN centrality and identified the differential hubness of CSNs between disease and healthy conditions. We demonstrated the usefulness of scHumanNet by uncovering T-cell-specific functional effects of GITR, a prognostic gene for breast cancer, and functional defects in autism spectrum disorder genes specific for inhibitory neurons. These results suggest that scHumanNet will advance our understanding of cell-type specificity across human disease genes.

bioinformatics↗

bioRxiv2023

Experiments in micro-patterned model membranes support the narrow escape theory

The narrow escape theory (NET) predicts the escape time distribution of Brownian particles confined to a domain with reflecting borders except for one small window. Applications include molecular activation events in cell biology and biophysics. Specifically, the mean first passage time [Formula] can be analytically calculated from the size of the domain, the escape window, and the diffusion coefficient of the particles. In this study, we systematically tested the NET in a disc by variation of the escape opening. Our model system consisted of micro-patterned lipid bilayers. For the measurement of [Formula], we imaged diffusing fluorescently-labeled lipids using single-molecule fluorescence microscopy. We overcame the lifetime limitation of fluorescent probes by re-scaling the measured time with the fraction of escaped particles. Experiments were complemented by matching stochastic numerical simulations. To conclude, we confirmed the NET prediction in vitro and in silico for the disc geometry in the limit of small escape openings. Significance StatementIn the biological context of a cell, a multitude of reactions are facilitated by diffusion. It is astonishing how Brownian motion as a cost-efficient but random process is mediating especially fast reactions. The formalism of the narrow escape theory is a tool to determine the average timescale of such processes to be completed (mean first passage time, MFPT) from the reaction space and diffusion coefficient. We present the systematic proof of this formalism experimentally in a bio-mimetic model system and by random walk simulations. Further, we demonstrate a straightforward solution to determine the MFPT from incomplete experimental traces. This will be beneficial for measurements of the MFPT, reliant on fluorescent probes, that have prior been inaccessible.

biophysics↗

bioRxiv2023

Self-referencing rates in biological disciplines

The use of citation counts (among other bibliometrics) as a facet of academic research evaluation can influence citation behavior in scientific publications. One possible unintended consequence of this bibliometric is excessive self-referencing, where an author favors referencing their own publications over related publications from different research groups. Peer reviewers are often prompted by journals to examine whether references listed in the manuscript under review are unbiased, but there is no consensus on what is considered "excessive" self-referencing. Here, self-referencing rates are estimated across multiple journals in the fields of biology, genetics, computational biology, medicine, pathology, and cell biology. Median self-referencing rates are between 8-13% across a range of journals within these subdisciplines. However, self-referencing rates vary as a function of total number of references, number of authors, author status/rank, author position, and total number publications for each author. These results may serve as useful statistical guidelines for authors, editors, reviewers, and journals when considering referencing practices for individual publications.

scientific communication and education↗

bioRxiv2023

Unraveling cellular complexity with unlimited multiplexed super-resolution imaging

Mapping the intricate spatial relationships between the many different molecules inside a cell is essential to understanding cellular functions in all their complexity. Super-resolution fluorescence microscopy offers the required spatial resolution but struggles to reveal more than four different targets simultaneously. Exchanging labels in subsequent imaging rounds for multiplexed imaging extends this number but is limited by its low throughput. Here we present a novel imaging method for rapid multiplexed super-resolution microscopy of a nearly unlimited number of molecular targets by leveraging fluorogenic labeling in conjunction with Transient Adapter-mediated switching for high-throughput DNA-PAINT (FLASH-PAINT). We demonstrate the cell biological versatility of FLASH-PAINT in mammalian cells in four applications: i) mapping nine proteins in a single mammalian cell, ii) elucidating the functional organization of primary cilia by nine-target imaging, iii) revealing the changes in proximity of twelve different targets in unperturbed and dissociated Golgi stacks and iv) investigating inter-organelle contacts at 3D super-resolution.

cell biology↗

bioRxiv2024

Tumor suppressor p53 controls thymic NKT17 development

The tumor suppressor p53 antagonizes tumorigenesis, notably including the suppression of T cell lymphomas while its role on physiological T cell biology including thymic T cell development has not been fully understood. Invariant natural killer T (iNKT) cells develop in the thymus as innate-like {beta}-T cells which consist of NKT1, NKT2 and NKT17 subsets. We found that the tumor suppressor p53 regulates specifically thymic NKT17 development. p53 is highly expressed in NKT17 relative to other T cell populations. Loss of p53 in the T cell lineage resulted in increased thymic NKT17 cell number with retention of lineage specific cytokine production, while development of NKT1, NKT2 and conventional T cells was not affected. Of interest, {gamma}H2AX expression was higher in NKT17 than NKT1 and NKT2 at steady state, and it was further increased in p53-deficient NKT17, suggesting that NKT17 development involves selectively greater DNA damage or genomic instability and that p53 expression might be in response to these damage signals. Taken together, our results indicated that the tumor suppressor p53 is active in selectively controlling thymic NKT17 development, with absence of p53 leading to an increase in thymic NKT17 cells expressing high levels of DNA damage response.

immunology↗

bioRxiv2025

Isolation of individual natural killer cells from deep, high-aspect ratio microwell arrays - an evaluative study

Immune cells exhibit functional heterogeneity beyond what is resolved by classical definitions of subpopulations based on cell surface expression of receptors. To develop efficient and personalized cell-based immunotherapies, we need to resolve this heterogeneity and understand the underlying parameters that dictate cellular responses to specific target cells. For this, new methods are required that can identify and harvest immune cells with specific functions, e.g., high cytotoxic potential, to form clonally expanded cells or to assess molecular or genetic signatures. In this study, we evaluate a system for non-destructive, live cell picking and release in deep, high-aspect ratio microwells and test it for isolation of individual natural killer (NK) cells. We assess its performance at retrieving and releasing beads from microwells and demonstrate its potential for single NK cell isolation with intact viability. We also implement a semi-automated workflow for functional single-cell screening of NK cell behavior in microwell arrays followed by single-cell identification and isolation, demonstrating the potential for functional screening and isolation of serial killing immune cells. Our evaluation concludes that this cell isolation system, in combination with microwell arrays, offers opportunities for improved understanding of NK cell biology with applications towards cell therapy. However, its limited throughput hinders large-scale applicability.

immunology↗

bioRxiv2026

Towards automated gating of clinical flow cytometry data

Flow cytometry analysis is widespread practice in cell biology, immunology and hematology. Cell populations of interest are typically identified by consecutively examining the expression levels of antigen marker pairs. Since this manual gating process lacks standardization and is time-consuming, several machine learning (ML) methods for automated gating of flow cytometry data have been proposed in recent years. However, their translation into routine workflows has been limited. To address this, we developed the Python package FLAG-X ("flow cytometry automated gating toolbox"), which supports two novel workflows that integrate manual with ML-based gating, using labeled and unlabeled training data. We selected state-of-the-art ML methods developed for automated gating for inclusion in FLAG-X, based on their gating performance in comparison to manual expert annotations. FLAG-X provides a unified interface for top-performing methods and enables seamless integration with standard software for manual gating by exporting results as FCS files. To demonstrate its practical utility, we applied FLAG-X to representative cases from clinical practice. FLAG-X is available at https://anaconda.org/channels/bioconda/packages/flagx/overview. Author summaryIn our research, we work with flow cytometry data, a common laboratory technique to measure the expression of specific antigens in individual cells of a patient sample. In everyday clinical diagnostics or research, experts use dedicated software tools to "manually" inspect these data and often select a subset of cells for further analysis, e.g. B cells for Lymphoma subtype classification. However, this manual procedure, known as gating, can be time-consuming and is not standardized such that outcomes may vary based on the clinician carrying out the cell selection. Automated, machine learning-based methods developed to mitigate those problems are rarely used in routine clinical work. In this study, we set out to close this gap by developing novel workflows that allow clinicians to more easily integrate (semi-)automated approaches into their existing workflows. To do this, we we developed a software package that brings together top-performing methods, functionality to handle clinical flow cytometry data and is designed to be compatible with with existing tools for manual analysis. We evaluated our workflows and toolbox using realistic clinical scenarios and considered practical requirements for their use. By integrating automation into familiar workflows, we strive to make flow cytometry gating both faster and more consistent to support wider use of computational methods in clinical diagnostics.

bioinformatics↗

bioRxiv2026

Unraveling a fine balance between ferroptosis, lipid metabolism, and hormonal protection in Leydig cell steroidogenesis

Leydig cells (LCs) are essential for male reproductive function due to their role in testosterone synthesis, a process critically dependent on mitochondrial cholesterol transport mediated by the Steroidogenic Acute Regulatory protein (StAR). Despite their importance, LCs are highly sensitive to metabolic and exogenous stressors. Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation, has emerged as a key link between cellular metabolism and cell fate; however, its role in LCs and steroidogenesis remains poorly understood. In this study, we investigated the induction of ferroptosis in LCs and its impact on their steroidogenic capacity. We evaluated cellular responses to canonical ferroptosis inducers (Erastin and RSL3) alongside the transcriptional regulation of key genes. Our results demonstrate that LCs are vulnerable to ferroptotic stress, which significantly downregulates Star expression. Notably, we uncovered a novel endocrine-metabolic crosstalk: hormonal stimulation via hCG effectively rescues LCs from Erastin-induced toxicity and fully sustains maximal steroidogenesis. However, this hormone-driven cytoprotection fails against direct GPX4 inhibition by RSL3, indicating an absolute reliance on functional GPX4. These mechanistic findings highlight the paradoxical dual role of ACSL4 in Leydig cell biology and are further supported by single-cell transcriptomic analysis of human testis, which reveals an imbalance in the ACSL4/GPX4 axis within the Leydig-cell compartment of infertile patients. Together, our data position ferroptosis as a critical disruptor of male endocrine function and reveal a hormone-mediated metabolic adaptation that could inform novel therapeutic strategies against oxidative stress in the testis. Highlights- Leydig cells exhibit a strong vulnerability to ferroptotic cell death. - Ferroptosis disrupts StAR expression and halts Leydig cell steroidogenesis. - hCG signaling promotes metabolic adaptation against Erastin-induced ferroptosis.

cell biology↗

bioRxiv2023

Design principles of Cdr2 node patterns in fission yeast cells

Pattern forming networks have diverse roles in cell biology. Rod-shaped fission yeast cells use pattern formation to control the localization of mitotic signaling proteins and the cytokinetic ring. During interphase, the kinase Cdr2 forms membrane-bound multiprotein complexes termed nodes, which are positioned in the cell middle due in part to the node inhibitor Pom1 enriched at cell tips. Node positioning is important for timely cell cycle progression and positioning of the cytokinetic ring. Here, we combined experimental and modeling approaches to investigate pattern formation by the Pom1-Cdr2 system. We found that Cdr2 nodes accumulate near the nucleus, and Cdr2 undergoes nucleocytoplasmic shuttling when cortical anchoring is reduced. We generated particle-based simulations based on tip inhibition, nuclear positioning, and cortical anchoring. We tested model predictions by investigating Pom1-Cdr2 localization patterns after perturbing each positioning mechanism, including in both anucleate and multinucleated cells. Experiments show that tip inhibition and cortical anchoring alone are sufficient for the assembly and positioning of nodes in the absence of the nucleus, but that the nucleus and Pom1 facilitate the formation of unexpected node patterns in multinucleated cells. These findings have implications for spatial control of cytokinesis by nodes and for spatial patterning in other biological systems.

cell biology↗

bioRxiv2026

ILK binding to β1 Integrin is indirectly mediated by Kindlin-2

Integrin-linked kinase (ILK) and kindlin-2 (K2) are key components of focal adhesions (FAs) that regulate cell-matrix adhesion and integrin signaling. Both proteins directly bind each other, but how they influence each others localization to FAs and binding to integrins remains a subject of ongoing debate. Here, we establish a sensitive workflow to study protein-protein interactions in cells by combining methods from biochemistry, cell biology and super-resolution microscopy. Together with an analytical framework this approach allowed us to distinguish direct from indirect molecular interactions and construct detailed interaction networks. Disrupting the ILK-K2 interaction reduced ILK localization to FAs and compromised integrin function, whereas K2 recruitment was unaffected. Our interdisciplinary approach also revealed that ILK does not directly bind {beta}1-integrin cytosolic domains in vitro and in cells. Instead, ILK was recruited to integrins exclusively through a K2-dependent mechanism, primarily via K2 bridging ILK and {beta}1 integrins. These findings define the hierarchical relationship between ILK and K2 in FAs and highlight the essential role of K2-mediated ILK recruitment for integrin adhesion and signaling. Significance StatementHow cells anchor to their environment is a fundamental question in biology. Integrins provide such a connection by bridging the extracellular matrix and the cytoskeleton. A central regulator of the integrin machine is Integrin-linked kinase (ILK). How ILK is recruited to {beta}1 integrins is hotly debated since its discovery more than 30 years ago. By integrating cell biology and biochemistry with super-resolution DNA-PAINT microscopy and a novel spatial analysis framework, we demonstrate that ILK does not bind directly to integrin cytoplasmic tails. Instead, we found that ILK is recruited by kindlin-2 (K2) to active, adhesion plaque-resident integrins. This work resolves a long-standing controversy in cell biology and establishes a versatile workflow for distinguishing direct from indirect protein-protein interactions in situ.

cell biology↗

bioRxiv2020

Pathway-guided deep neural network toward interpretable and predictive modeling of drug sensitivity

MotivationTo efficiently save cost and reduce risk in drug research and development, there is a pressing demand to develop in-silico methods to predict drug sensitivity to cancer cells. With the exponentially increasing number of multi-omics data derived from high-throughput techniques, machine learning-based methods have been applied to the prediction of drug sensitivities. However, these methods have drawbacks either in the interpretability of mechanism of drug action or limited performance in modeling drug sensitivity. ResultsIn this paper, we presented a pathway-guided deep neural network model, referred to as pathDNN, to predict the drug sensitivity to cancer cells. Biological pathways describe a group of molecules in a cell that collaborates to control various biological functions like cell proliferation and death, thereby abnormal function of pathways can result in disease. To make advantage of both the excellent predictive ability of deep neural network and the biological knowledge of pathways, we reshape the canonical DNN structure by incorporating a layer of pathway nodes and their connections to input gene nodes, which makes the DNN model more interpretable and predictive compared to canonical DNN. We have conducted extensive performance evaluations on multiple independent drug sensitivity data sets, and demonstrate that pathDNN significantly outperformed canonical DNN model and seven other classical regression models. Most importantly, we observed remarkable activity decreases of disease-related pathway nodes during forward propagation upon inputs of drug targets, which implicitly corresponds to the inhibition effect of disease-related pathways induced by drug treatment on cancer cells. Our empirical experiments show that pathDNN achieves pharmacological interpretability and predictive ability in modeling drug sensitivity to cancer cells. AvailabilityThe web server, as well as the processed data sets and source codes for reproducing our work, is available at http://pathdnn.denglab.org

bioinformatics↗