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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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 127 records · Page 7Linked to original sources

bioRxiv2026

ProNotch converts extracellular protease activity into programmable transcriptional outputs

Synthetic receptors that convert extracellular protease activity into programmable transcriptional outputs would expand the toolkit of mammalian cell biology and cell engineering, yet modular platforms for directly coupling extracellular proteolysis to gene expression remain limited. Here we introduce ProNotch, a receptor architecture that harnesses protease-gated derepression of a mutant Notch1 negative regulatory region (NRR) to drive user-defined gene expression. ProNotch tethers destabilized NRR mutants to inhibitory anti-NRR single-chain variable fragments (scFvs) via protease-cleavable linkers. NRR engagement by high-affinity scFvs simultaneously rescues surface trafficking of mutant receptors and suppresses basal signaling until linker cleavage releases the inhibitory scFv module, permitting the destabilized NRR to initiate ligand-independent signaling. Linker substitution reprogrammed protease specificity across diverse enzymes, and tandem substrate repeats enhanced sensitivity without increasing basal activity. Single-chain receptor designs enabled OR and AND logic gates, allowing integration of multi-protease inputs into a single transcriptional output. ProNotch detected endogenous MMP-14 activity from cancer cell lines in cis and in trans and drove protease-dependent cell-state transitions in C3H/10T1/2 fibroblasts. The scFv-NRR module also functioned as a protease-activated pro-antibody that conditionally inhibited DLL4-dependent signaling and ligand-independent activation of mutant NOTCH1 in the T cell acute lymphoblastic leukemia cell line HPB-ALL. Together, these results establish ProNotch as a modular platform for engineering protease-responsive cells and demonstrate that its regulatory module can be extended to a soluble, conditionally activated inhibitor of NOTCH1 signaling.

synthetic biology↗

bioRxiv2022

Longitudinal single cell transcriptional and epigenetic mapping of effector, memory, and exhausted CD8 T cells reveals shared biological circuits across distinct cell fates

Naive CD8 T cells can differentiate into effector (TEFF), memory (TMEM), or exhausted (TEX) CD8 T cells. These developmental pathways are associated with distinct transcriptional and epigenetic changes that endow cells with different functional capacities and therefore therapeutic potential. The molecular circuitry underlying these developmental trajectories and the extent of heterogeneity within TEFF, TMEM, TEX populations remain poorly understood. Here, we used the lymphocytic choriomeningitis virus model of acutely-resolved and chronic infection and addressed these gaps by applying longitudinal scRNA-seq and scATAC-seq analysis. These analyses uncovered new subsets, including a subpopulation of TEX expressing NK cell-associated genes, as well as multiple distinct TCF1+ stem/progenitor-like subsets in acute and chronic infection. These data also revealed insights into the reshaping of TEX subsets following PD1 pathway blockade and identified a key role for the cell stress regulator, Btg1, in TEX differentiation. Finally, these results highlighted how the same biological circuits such as cytotoxicity or stem/progenitor pathways can be used by CD8 T cells with highly divergent underlying chromatin landscapes. Thus, this transcriptional and chromatin accessibility landscape map elucidates developmental biology and underlying mechanisms governing TEFF, TMEM, and TEX differentiation.

immunology↗

bioRxiv2016

Cell reprogramming modelled as transitions in a hierarchy of cell cycles

We construct a model of cell reprogramming (the conversion of fully differentiated cells to a state of pluripotency, known as induced pluripotent stem cells, or iPSCs) which builds on key elements of cell biology viz. cell cycles and cell lineages. Although reprogramming has been demonstrated experimentally, much of the underlying processes governing cell fate decisions remain unknown. This work aims to bridge this gap by modelling cell types as a set of hierarchically related dynamical attractors representing cell cycles. Stages of the cell cycle are characterised by the configuration of gene expression levels, and reprogramming corresponds to triggering transitions between such configurations. Two mechanisms were found for reprogramming in a two level hierarchy: cycle specific perturbations and a noise induced switching. The former corresponds to a directed perturbation that induces a transition into a cycle-state of a different cell type in the potency hierarchy (mainly a stem cell) whilst the latter is a priori undirected and could be induced, e.g., by a (stochastic) change in the cellular environment. These reprogramming protocols were found to be effective in large regimes of the parameter space and make specific predictions concerning reprogramming dynamics which are broadly in line with experimental findings.

genetics↗

bioRxiv2022

Genome-wide subcellular protein localisation in the flagellate parasite Trypanosoma brucei

Trypanosoma brucei is a prototypical trypanosomatid, an important group of human, animal and plant unicellular parasites. Understanding their complex cell architecture and life cycle is hindered since, as with most eukaryotic microbes, [~]50% of the proteins encoded in the genome have completely unknown function. Using fluorescence microscopy and cell lines expressing endogenously tagged proteins we mapped the subcellular localisation of 89% of the proteome, giving clues to function, defining the lineage-specific organelle adaptations for obligate parasitism and mapping the ultra-conserved cellular architecture of eukaryotes. This includes the single flagellum, vital for morphogenesis and pathology: the first comprehensive cartographic analysis of the flagellum in any organism. To demonstrate the power of this resource, we identify novel specialisation of organelle molecular composition through the cell cycle and in specialised subdomains. This is a transformative resource, important for hypothesis generation for both eukaryotic evolutionary molecular cell biology and fundamental parasite cell biology.

microbiology↗

bioRxiv2023

Ensemble Processing and Synthetic Image Generation For Abnormally Shaped Nuclei Segmentation

Abnormalities in biological cell nuclei morphology are correlated with cell cycle stages, disease states, and various external stimuli. There have been many deep learning approaches that have described nuclei segmentation and analysis of nuclear morphology. One problem with many deep learning methods is acquiring large amounts of annotated nuclei data, which is generally expensive to obtain. In this paper, we propose a system to segment abnormally shaped nuclei with a limited amount of training data. We first generate specific shapes of synthetic nuclei groundtruth. We randomly sample these synthetic groundtruth images into training sets to train several Mask R-CNNs. We design an ensemble strategy to combine or fuse segmentation results from the Mask R-CNNs. We also design an oval nuclei removal by StarDist to reduce the false positives and improve the overall segmentation performance. Our experiments indicate that our method outperforms other methods in segmenting abnormally shaped nuclei.

cell biology↗

bioRxiv2018

A comprehensive reference transcriptome resource for the Iberian ribbed newt Pleurodeles waltl, an emerging model for developmental and regeneration biology

Urodele amphibian newts have unique biological properties, notably including prominent regeneration ability. Iberian ribbed newt, Pleurodeles waltl, is a promising model newt along with the successful development of the easy breeding system and efficient transgenic and genome editing methods. However, genetic information of P. waltl was limited. In the present study, we conducted an intensive transcriptome analysis of P. waltl using RNA-sequencing to build gene models and annotate them. We generated 1.2 billion Illumina reads from a wide variety of samples across 11 different tissues and 9 time points during embryogenesis. They were assembled into 202,788 non-redundant contigs that appear to cover nearly complete (~98%) P. waltl protein-coding genes. Using the gene set as a reference, our gene network analysis identified regeneration-, developmental-stage-, and tissue-specific co-expressed gene modules. Ortholog analyses with other vertebrates revealed the gene repertoire evolution of amphibians which includes urodele-specific loss of bmp4 and duplications of wnt11b. Our transcriptome resource will enhance future research employing this emerging model animal for regeneration research as well as other areas such as developmental biology, stem cell biology, cancer research, ethology and toxico-genomics. These data are available via our portal website, iNewt (http://www.nibb.ac.jp/imori/main/).

genomics↗

bioRxiv2019

Fully automated, sequential focused ion beam milling for cryo-electron tomography

Cryo-electron tomography (cryoET) has become a powerful technique at the interface of structural biology and cell biology, with the unique ability to determine structures of macromolecular complexes in their cellular context. A major limitation of cryoET is its restriction to relatively thin samples. Sample thinning by cryo-focused ion beam (cryoFIB) milling has significantly expanded the range of samples that can be analyzed by cryoET. Unfortunately, cryoFIB milling is low-throughput, time-consuming and manual. Here we report a method for fully automated sequential cryoFIB preparation of high-quality lamellae, including rough milling and polishing. We reproducibly applied this method to eukaryotic and bacterial model organisms, and show that the resulting lamellae are suitable for cryoET imaging and subtomogram averaging. Since our method reduces the time required for lamella preparation and minimizes the need for user input, we envision the technique will render previously inaccessible projects feasible.

molecular biology↗

bioRxiv2020

Robust Optical Flow Algorithm for General, Label-free Cell Segmentation

Cell segmentation is crucial to the field of cell biology, as the accurate extraction of cell morphology, migration, and ultimately behavior from time-lapse live cell imagery are of paramount importance to elucidate and understand basic cellular processes. Here, we introduce a novel segmentation approach centered around optical flow and show that it achieves robust segmentation by validating it on multiple cell types, phenotypes, optical modalities, and in-vitro environments without the need of labels. By leveraging cell movement in time-lapse imagery as a means to distinguish cells from their background and augmenting the output with machine vision operations, our algorithm reduces the number of adjustable parameters needed for optimization to two. The code is packaged within a MATLAB executable file, offering an accessible means for general cell segmentation typically unavailable in most cell biology laboratories.

cell biology↗

bioRxiv2023

Quantitative Determination of Protein Concentration in Living Cells

Biological systems are regulated by molecular interactions which are tuned by the concentrations of each of the molecules involved. Cells exploit this feature by regulating protein expression, to adapt their responses to overstimulation. Correlating events in single cells to the concentrations of proteins involved can therefore provide important mechanistic insight into cell behavior. Unfortunately, quantification of molecular densities by fluorescence imaging becomes non-trivial due to the diffraction limited resolution of the imaged volume. We show here an alternative approach to overcome this limitation in optical quantification of protein concentrations which is based on calibrating protein volume and surface densities in a model membrane system. We exploit the ability of fluorescently labeled annexin V to bind membranes in presence of calcium. By encapsulating known concentrations of annexin V, we can directly infer the membrane density of annexin V after addition of Ca2+ and correlate the density with the measured fluorescence signal. Our method, named Calmet, enables quantitative determination of the concentration of cytosolic and membrane associated proteins. The applicability of Calmet is demonstrated by quantification of a transmembrane protein receptor (beta 1 adrenergic receptor) labeled by SNAP tagged fluorophores and expressed in HEK293 cells. Calmet is a generic method suitable for the determination of a broad range of concentrations and densities and can be used on regular fluorescence images captured by confocal laser scanning microscopy.

biophysics↗

bioRxiv2023

Atlas of Plasmodium falciparum intraerythrocytic development using expansion microscopy

Apicomplexan parasites exhibit tremendous diversity in much of their fundamental cell biology, but study of these organisms using light microscopy is often hindered by their small size. Ultrastructural expansion microscopy (U-ExM) is a microscopy preparation method that physically expands the sample [~]4.5x. Here, we apply U-ExM to the human malaria parasite Plasmodium falciparum during the asexual blood stage of its lifecycle to understand how this parasite is organized in three-dimensions. Using a combination of dye-conjugated reagents and immunostaining, we have catalogued 13 different P. falciparum structures or organelles across the intraerythrocytic development of this parasite and made multiple observations about fundamental parasite cell biology. We describe that the outer centriolar plaque and its associated proteins anchor the nucleus to the parasite plasma membrane during mitosis. Furthermore, the rhoptries, Golgi, basal complex, and inner membrane complex, which form around this anchoring site while nuclei are still dividing, are concurrently segregated and maintain an association to the outer centriolar plaque until the start of segmentation. We also show that the mitochondrion and apicoplast undergo sequential fission events while maintaining an association with the outer centriolar plaque during cytokinesis. Collectively, this study represents the most detailed ultrastructural analysis of P. falciparum during its intraerythrocytic development to date, and sheds light on multiple poorly understood aspects of its organelle biogenesis and fundamental cell biology. IMPACT STATEMENTUsing ultrastructure-expansion microscopy we explore the fundamental cell biology of malaria parasites, providing new insights into processes including establishment of cell polarity and organelle fission.

cell biology↗

bioRxiv2017

Degeneracy in the robust expression of spectral selectivity, subthreshold oscillations and intrinsic excitability of entorhinal stellate cells

Biological heterogeneities are ubiquitous and play critical roles in the emergence of physiology at multiple scales. Although neurons in layer II (LII) of the medial entorhinal cortex (MEC) express heterogeneities in their channel properties, the impact of such heterogeneities on the robustness of cellular-scale physiology has not been assessed. Here, we performed a 55-parameter stochastic search spanning 9 voltage- or calcium-activated channels to assess the impact of channel heterogeneities on the concomitant emergence of 10 electrophysiological characteristics of LII stellate cells (SCs). We generated 50,000 models and found a heterogeneous subpopulation of 155 valid models to robustly match all electrophysiological signatures. We employed this heterogeneous population to demonstrate the emergence of cellular-scale degeneracy in LII SCs, whereby disparate parametric combinations expressing weak pairwise correlations resulted in similar models. We then assessed the impact of virtually knocking out each channel from all valid models and demonstrate that the mapping between channels and measurements was many-to-many, a critical requirement for the expression of degeneracy. Finally, we quantitatively predict that the spike-triggered average of LII SCs should be endowed with theta-frequency spectral selectivity and coincidence detection capabilities in the fast gamma-band. We postulate this fast gamma-band coincidence detection as an instance of cellular-scale efficient coding, whereby SC response characteristics match the dominant oscillatory signals in LII MEC. The heterogeneous population of valid SC models built here unveils the robust emergence of cellular-scale physiology despite significant channel heterogeneities, and forms an efficacious substrate for evaluating the impact of biological heterogeneities on entorhinal network function.\n\nKEY POINTSO_LIStellate cells (SC) in layer II (LII) of the medial entorhinal cortex express cellular-scale degeneracy in the concomitant manifestation of several of their unique physiological signatures.\nC_LIO_LISeveral disparate parametric combinations expressing weak pairwise correlations resulted in models with very similar physiological characteristics, including robust theta-frequency membrane potential oscillations spanning several levels of subthreshold depolarization.\nC_LIO_LIElectrophysiological measurements of LII SCs exhibited differential and variable dependencies on underlying channels, and the mapping between channels and measurements was many-to-many.\nC_LIO_LIQuantitative predictions point to theta-frequency spectral selectivity and fast gamma-range coincidence detection capabilities in class II/III spike-triggered average of LII SCs, with the postulate for this to be an instance of cellular-scale efficient coding.\nC_LIO_LIA heterogeneous cell population that accounts for both channel and intrinsic heterogeneities in LII SCs, which could be employed by network models of entorhinal function to probe the impact of several biological heterogeneities on spatial navigation circuits.\nC_LI

neuroscience↗

bioRxiv2022

Filter inference: A scalable nonlinear mixed effects inference approach for snapshot time series data

Variability is an intrinsic property of biological systems and is often at the heart of their complex behaviour. Examples range from cell-to-cell variability in cell signalling pathways to variability in the response to treatment across patients. A popular approach to model and understand this variability is nonlinear mixed effects (NLME) modelling. However, estimating the parameters of NLME models from measurements quickly becomes computationally expensive as the number of measured individuals grows, making NLME inference intractable for datasets with thousands of measured individuals. This shortcoming is particularly limiting for snapshot datasets, common e.g. in cell biology, where high-throughput measurement techniques provide large numbers of single cell measurements. We extend earlier work by Hasenauer et al (2011) to introduce a novel approach for the estimation of NLME model parameters from snapshot measurements, which we call filter inference. Filter inference is a new variant of approximate Bayesian computation, with dominant computational costs that do not increase with the number of measured individuals, making efficient inferences from snapshot measurements possible. Filter inference also scales well with the number of model parameters, using state-of-the-art gradient-based MCMC algorithms, such as the No-U-Turn Sampler (NUTS). We demonstrate the properties of filter inference using examples from early cancer growth modelling and from epidermal growth factor signalling pathway modelling. Author summaryNonlinear mixed effects (NLME) models are widely used to model differences between individuals in a population. In pharmacology, for example, they are used to model the treatment response variability across patients, and in cell biology they are used to model the cell-to-cell variability in cell signalling pathways. However, NLME models introduce parameters, which typically need to be estimated from data. This estimation becomes computationally intractable when the number of measured individuals - be they patients or cells - is too large. But, the more individuals are measured in a population, the better the variability can be understood. This is especially true when individuals are measured only once. Such snapshot measurements are particularly common in cell biology, where high-throughput measurement techniques provide large numbers of single cell measurements. In clinical pharmacology, datasets consisting of many snapshot measurements are less common but are easier and cheaper to obtain than detailed time series measurements across patients. Our approach can be used to estimate the parameters of NLME models from snapshot time series data with thousands of measured individuals.

bioinformatics↗

bioRxiv2026

Live-cell imaging and ultrastructure expansion microscopy reveal the dynamic intracellular life cycle of Encephalitozoon intestinalis

Microsporidia are divergent fungal pathogens that infect a wide range of hosts. Microsporidia have evolved highly reduced genomes, resulting in the loss of many metabolic pathways. Encephalitozoon intestinalis is a human-infecting microsporidian species with the smallest known eukaryotic genome (2.3 Mbp). As an obligate intracellular parasite, E. intestinalis is dependent on its host for replication. Our current understanding of E. intestinalis cell biology remains limited. This is largely due to genetic intractability, which has made live-cell imaging challenging, and its small size (~2 m), which is within the diffraction limit of conventional microscopy. Here we develop a live-cell imaging technique, "silhouette microscopy", that does not rely on genetic manipulation of microsporidia, and enables us to study the live cell dynamics of E. intestinalis replication in host cells, from entry to exit. We report the timing of cell division, kinetics of the parasite life cycle, and dynamics of the parasitophorous vacuole within which E. intestinalis resides. The parasitophorous vacuole undergoes frequent fission and fusion, and ultimately ruptures to facilitate parasite release from the host cell. To gain a higher resolution understanding into the cell biology of E. intestinalis development, we performed ultrastructure expansion microscopy (U-ExM) on infected cells. U-ExM reveals the organization of the E. intestinalis cytoskeleton and development of the specialized invasion organelle, the polar tube. The combination of live-cell imaging and U-ExM provide a platform to study the E. intestinalis life cycle, and sheds light on the dynamics and cell biology of E. intestinalis in host cells.

microbiology↗

bioRxiv2019

Chytrid rhizoid morphogenesis is adaptive and resembles hyphal development in ‘higher’ fungi

Fungi are major components of the Earths biosphere [1], sustaining many critical ecosystem processes [2, 3]. Key to fungal prominence is their characteristic cell biology, our understanding of which has been principally based on higher dikaryan hyphal and yeast forms [4-6]. The early-diverging Chytridiomycota (chytrids) are ecologically important [2, 7, 8] and a significant component of fungal diversity [9-11], yet their cell biology remains poorly understood. Unlike dikaryan hyphae, chytrids typically attach to substrates and feed osmotrophically via anucleate rhizoids [12]. The evolution of fungal hyphae appears to have occurred from lineages exhibiting rhizoidal growth [13] and it has been hypothesised that a rhizoid-like structure was the precursor to multicellular hyphae and mycelial feeding in fungi [14]. Here we show in a unicellular chytrid, Rhizoclosmatium globosum, that rhizoid development has equivalent features to dikaryan hyphae and is adaptive to resource availability. Rhizoid morphogenesis exhibits analogous properties with growth in hyphal forms, including tip production, branching and decreasing fractal geometry towards the growing edge, and is controlled by {beta}-glucan-dependent cell wall synthesis and actin polymerisation. Chytrid rhizoids from individual cells also demonstrate adaptive morphological plasticity in response to substrate availability, developing a searching phenotype when carbon starved and exhibiting spatial differentiation when interacting with particulate substrates. Our results show striking similarities between unicellular early-diverging and dikaryan fungi, providing insights into chytrid cell biology, ecological prevalence and fungal evolution. We demonstrate that the sophisticated cell biology and developmental plasticity previously considered characteristic of hyphal fungi are shared more widely across the Kingdom Fungi and therefore could be conserved from their most recent common ancestor.

developmental biology↗

bioRxiv2017

Transcriptomic characterization of 20 organs and tissues from mouse at single cell resolution creates a Tabula Muris

The Tabula Muris ConsortiumWe have created a compendium of single cell transcriptome data from the model organism Mus musculus comprising more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, revealing gene expression in poorly characterized cell populations and allowing for direct and controlled comparison of gene expression in cell types shared between tissues, such as T-lymphocytes and endothelial cells from distinct anatomical locations. Two distinct technical approaches were used for most tissues: one approach, microfluidic droplet-based 3-end counting, enabled the survey of thousands of cells at relatively low coverage, while the other, FACS-based full length transcript analysis, enabled characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.

cell biology↗

bioRxiv2021

Ratiometric RNA labeling allows dynamic multiplexed analysis of gene circuits in single cells

Biological processes are highly dynamic and are regulated by genes that connect with one and another, forming regulatory circuits and networks. Understanding how gene regulatory circuits operate dynamically requires monitoring the expression of multiple genes in the same cell. However, it is limited by the relatively few distinguishable fluorescent proteins. Here, we developed a multiplexed real-time transcriptional imaging method based on two RNA stem-loop binding proteins, and employed it to analyze the temporal dynamics of synthetic gene circuits. By incorporating different ratios of MS2 and PP7 stem-loops, we were able to monitor the real-time nascent transcriptional activities of up to five genes in the same cell using only two fluorescent proteins. Applying this multiplexing capability to synthetic linear or branched gene regulatory cascades revealed that propagation of transcriptional dynamics is enhanced by non-stationary dynamics and is dictated by the slowest regulatory branch in the presence of combinatorial regulation. Mathematical modeling provided further insight into temporal multi-gene interactions and helped to understand potential challenges in regulatory inference using snapshot single-cell data. Ratiometric multiplexing should scale exponentially with additional labelling channels, providing a way to track the dynamics of larger circuits.

systems biology↗

bioRxiv2017

Systematic gene tagging using CRISPR/Cas9 in human stem cells to illuminate cell organization

We present a CRISPR/Cas9 genome editing strategy to systematically tag endogenous proteins with fluorescent tags in human inducible pluripotent stem cells. To date we have generated multiple human iPSC lines with GFP tags for 10 proteins representing key cellular structures. The tagged proteins include alpha tubulin, beta actin, desmoplakin, fibrillarin, lamin B1, non-muscle myosin heavy chain IIB, paxillin, Sec61 beta, tight junction protein ZO1, and Tom20. Our genome editing methodology using Cas9 ribonuclear protein electroporation and fluorescence-based enrichment of edited cells resulted in <0.1-24% HDR across all experiments. Clones were generated from each edited population and screened for precise editing. [~]25% of the clones contained precise mono-allelic edits at the targeted locus. Furthermore, 92% (36/39) of expanded clonal lines satisfied key quality control criteria including genomic stability, appropriate expression and localization of the tagged protein, and pluripotency. Final clonal lines corresponding to each of the 10 cellular structures are now available to the research community. The data described here, including our editing protocol, genetic screening, quality control assays, and imaging observations, can serve as an initial resource for genome editing in cell biology and stem cell research.

cell biology↗

bioRxiv2020

Comparing Lifeact and Phalloidin for Super-resolution Imaging of Actin in Fixed Cells

Visualizing actin filaments in fixed cells is of great interest for a variety of topics in cell biology such as cell division, cell movement, and cell signaling. We investigated the possibility of replacing phalloidin, the standard reagent for super-resolution imaging of F-actin in fixed cells, with the actin binding peptide lifeact. We compared the labels for use in single molecule based super-resolution microscopy, where AlexaFluor 647 labeled phalloidin was used in a (d)STORM modality and Atto 655 labeled lifeact was used in a single molecule imaging, reversible binding modality. We found that imaging with lifeact had a comparable resolution in reconstructed images and provided several advantages over phalloidin including lower costs, the ability to image multiple regions of interest on a coverslip without degradation, simplified sequential super-resolution imaging, and more continuous labeling of thin filaments.

cell biology↗