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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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 19 recordsLinked to original sources

bioRxiv2014

Choosing an appropriate modelling framework for analysing multispecies co-culture cell biology experiments

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insufficient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Cell Biology↗

bioRxiv2018

BacStalk: a comprehensive and interactive image analysis software tool for bacterial cell biology

Prokaryotes display a remarkable spatiotemporal organization of processes within individual cells. Investigations of the underlying mechanisms rely extensively on the analysis of microscopy images. Advanced image analysis software has revolutionized the cell-biological studies of established model organisms with largely symmetric rod-like cell shapes. However algorithms suitable for analyzing features of morphologically more complex model species are lacking although such unusually shaped organisms have emerged as treasure-troves of new molecular mechanisms and diversity in prokaryotic cell biology. To address this problem we developed BacStalk a simple interactive and easy-to-use MatLab-based software tool for quantitatively analyzing images of commonly and uncommonly shaped bacteria including stalked (budding) bacteria. BacStalk automatically detects the separate parts of the cells (cell body stalk bud or appendage) as well as their connections thereby allowing in-depth analyses of the organization of morphologically complex bacteria over time. BacStalk features the generation and visualization of concatenated fluorescence profiles along cells stalks appendages and buds to trace the spatiotemporal dynamics of fluorescent markers. Cells are interactively linked to demographs kymographs cell lineage analyses and scatterplots which enables intuitive and fast data exploration and thus significantly speeds up the image analysis process. Furthermore BacStalk introduces a 2D representation of demo- and kymographs enabling data representations in which the two spatial dimensions of the cell are preserved. The software was developed to handle large data sets and to generate publication-grade figures that can be easily edited. BacStalk therefore provides an advanced image analysis platform that extends the spectrum of model organisms for prokaryotic cell biology to bacteria with multiple morphologies and life cycles.\n\nIMPORTANCEProkaryotic cells show a striking degree of subcellular organization. Studies of the underlying mechanisms and their variation among different species greatly enhance our understanding of prokaryotic cell biology. The image analysis software tool BacStalk extracts an unprecedented amount of information from images of stalked bacteria, by generating interactive demographs, kymographs, cell lineages, and scatter plots that aid fast and thorough data analysis and representation. Notably, BacStalk can preserve the two spatial dimensions of cells when generating demographs and kymographs to accurately and intuitively reflect the intracellular organization. BacStalk also performs well on established, non-stalked model organisms with common or uncommon shapes. BacStalk therefore contributes to the advancement of prokaryotic cell biology, as it widens the spectrum of easily accessible model organisms and enables a more intuitive and interactive data analysis and visualization.

microbiology↗

bioRxiv2018

A robust method for transfection in choanoflagellates illuminates their cell biology and the ancestry of animal septins

As the closest living relatives of animals, choanoflagellates offer unique insights into animal origins and core mechanisms underlying animal cell biology. However, unlike traditional model organisms, such as yeast, flies and worms, choanoflagellates have been refractory to DNA delivery methods for expressing foreign genes. Here we report the establishment of a robust method for expressing transgenes in the choanoflagellate Salpingoeca rosetta, overcoming barriers that have previously hampered DNA delivery and expression. To demonstrate how this method accelerates the study of S. rosetta cell biology, we engineered a panel of fluorescent protein markers that illuminate key features of choanoflagellate cells. We then investigated the localization of choanoflagellate septins, a family of GTP-binding cytoskeletal proteins that are hypothesized to regulate the multicellular rosette development in S. rosetta. Fluorescently tagged septins localized to the basal pole of S. rosetta single cells and rosettes in a pattern resembling septin localization in animal epithelia. The establishment of transfection in S. rosetta and its application to the study of septins represent critical advances in the growth of S. rosetta as an experimental model for investigating choanoflagellate cell biology, core mechanisms underlying animal cell biology, and the origin of animals.

cell biology↗

bioRxiv2016

Decoupling global biases and local interactions between cell biological variables

Analysis of coupled variables is a core concept of cell biological inference, with co-localization of two molecules as a proxy for protein interaction being a ubiquitous example. However, external effectors may influence the observed co-localization independently from the local interaction of two proteins. Such global bias, although biologically meaningful, is often neglected when interpreting co-localization. Here, we describe DeBias, a computational method to quantify and decouple global bias from local interactions between variables by modeling the observed co-localization as the cumulative contribution of a global and a local component. We showcase four applications of DeBias in different areas of cell biology, and demonstrate that the global bias encapsulates fundamental mechanistic information of cellular behavior. The DeBias software package is freely accessible online via a web-server at https://debias.biohpc.swmed.edu.

Cell Biology↗

bioRxiv2017

Unlocking the biological potential of Euglena gracilis: evolution, cell biology and significance to parasitism

Photosynthetic euglenids are major components of aquatic ecosystems and relatives of trypanosomes. Euglena gracilis has considerable biotechnological potential and great adaptability, but exploitation remains hampered by the absence of a comprehensive gene catalogue. We address this by genome, RNA and protein sequencing: the E. gracilis genome is >2Gb, with 36,526 predicted proteins. Large lineage-specific paralog families are present, with evidence for flexibility in environmental monitoring, divergent mechanisms for metabolic control, and novel solutions for adaptation to extreme environments. Contributions from photosynthetic eukaryotes to the nuclear genome, consistent with the shopping bag model are found, together with transitions between kinetoplastid and canonical systems. Control of protein expression is almost exclusively post-transcriptional. These data are a major advance in understanding the nuclear genomes of euglenids and provide a platform for investigating the contributions of E. gracilis and its relatives to the biosphere.

evolutionary biology↗

bioRxiv2016

Nanog fluctuations in ES cells highlight the problem of measurement in cell biology

A number of important pluripotency regulators, including the transcription factor Nanog, are observed to fluctuate stochastically in individual embryonic stem (ES) cells. By transiently priming cells for commitment to different lineages, these fluctuations are thought to be important to the maintenance of, and exit from, pluripotency. However, since temporal changes in intracellular protein abundances cannot be measured directly in live cells, these fluctuations are typically assessed using genetically engineered reporter cell lines that produce a fluorescent signal as a proxy for protein expression. Here, using a combination of mathematical modeling and experiment, we show that there are unforeseen ways in which widely used reporter strategies can systemically disturb the dynamics they are intended to monitor, sometimes giving profoundly misleading results. In the case of Nanog we show how genetic reporters can compromise the behavior of important pluripotency-sustaining positive feedback loops, and induce a bifurcation in the underlying dynamics that gives rise to heterogeneous Nanog expression patterns in reporter cell lines that are not representative of the wild-type. These findings help explain the range of published observations of Nanog variability and highlight a fundamental measurement problem in cell biology.

Cell Biology↗

bioRxiv2018

Four assessment methods to measure student gains in a graduate course on mathematical modeling in cell biology

The push for mathematics and quantitative skill development in biology is greater than ever before. The perceptions of these techniques are a barrier to their implementation on a grand scale. Methods to assess the efficacy of approaches to teaching quantitative skills are needed to determine if they effectively overcome social stereotypes and fears of math. In our project we study the effect of a mathematical modeling course in cell biology. We developed four assessments to understand if hands-on modeling increases student understanding of the concepts while simultaneously reducing fear of math. Two concept inventories track students learning gains both in general and specific knowledge to the course content. Two surveys quantify students quantitative confidence and opinions of the usefulness of these techniques in biology. We discuss the effectiveness of our methods and the implications for assessment development in mathematical biology education.

scientific communication and education↗

bioRxiv2018

Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology

High costs and technical limitations of cell sorting and single-cell techniques currently restrict the collection of large-scale, cell-type-specific DNA methylation data. This, in turn, impedes our ability to tackle key biological questions that pertain to variation within a population, such as identification of disease-associated genes at a cell-type-specific resolution. Here, we show mathematically and empirically that cell-type-specific methylation levels of an individual can be learned from its tissue-level bulk data, conceptually emulating the case where the individual has been profiled with a single-cell resolution and then signals were aggregated in each cell population separately. Provided with this unprecedented way to perform powerful large-scale epigenetic studies with cell-type-specific resolution, we revisit previous studies with tissue-level bulk methylation and reveal novel associations with leukocyte composition in blood and with rheumatoid arthritis. For the latter, we further show consistency with validation data collected from sorted leukocyte sub-types. Corresponding software is available from: https://github.com/cozygene/TCA.

bioinformatics↗

bioRxiv2017

Information Theory and Stem Cell Biology

Purpose of ReviewTo outline how ideas from Information Theory may be used to analyze single cell data and better understand stem cell behaviour.\n\nRecent findingsRecent technological breakthroughs in single cell profiling have made it possible to interrogate cell-to-cell variability in a multitude of contexts, including the role it plays in stem cell dynamics. Here we review how measures from information theory are being used to extract biological meaning from the complex, high-dimensional and noisy datasets that arise from single cell profiling experiments. We also discuss how concepts linking information theory and statistical mechanics are being used to provide insight into cellular identity, variability and dynamics.\n\nSummaryWe provide a brief introduction to some basic notions from information theory and how they may be used to understand stem cell identities at the single cell level. We also discuss how work in this area might develop in the near future.

cell biology↗

bioRxiv2017

Viral hijacking of the nucleolar DNA-damage response machinery: a novel mechanism to regulate host cell biology

Recent landmark studies indicate that nucleoli play critical roles in the DNA-damage response (DDR) via interaction of DDR machinery including NBS1 with nucleolar Treacle protein, a key mediator of ribosomal RNA (rRNA) transcription and processing, implicated in Treacher-Collins syndrome. Here, using proteomics, confocal/super-resolution imaging, and infection under BSL-4 containment, we present the first report that this nucleolar DDR pathway is targeted by infectious pathogens. We find that Treacle has antiviral activity, but that matrix protein of Henipaviruses and P3 protein of rabies virus, highly pathogenic viruses of the order Mononegavirales, interact with Treacle and inhibit its function, thereby silencing rRNA biogenesis, consistent with mimicking NBS1-Treacle interaction during a DDR. These data identify a novel mechanism for viral modulation of host cells by appropriating the nucleolar DDR; this appears to have developed independently in different viruses, and represents, to our knowledge, the first direct intra-nucleolar function for proteins of any mononegavirus.

microbiology↗

bioRxiv2018

Beating Swords into Ploughshares: Domestication of a Phage Lysin for Housekeeping Function

Temperate phages constitute a potentially beneficial genetic reservoir for bacterial innovation despite being selfish entities encoding an infection cycle inherently at odds with bacterial fitness. These phages integrate their genomes into the bacterial host during infection, donating new, but deleterious, genetic material: the phage genome encodes toxic genes, such as lysins, that kill the bacterium during the phage infection cycle. Remarkably, some bacteria have exploited the destructive properties of phage genes for their own benefit by co-opting them as toxins for functions related to bacterial warfare, virulence, and secretion. However, do toxic phage genes ever become raw material for functional innovation? Here we report on a toxic phage gene whose product has lost its toxicity and has become a domain of a core cellular factor, SpmX, throughout the bacterial order Caulobacterales. Using a combination of phylogenetics, bioinformatics, structural biology, cell biology, and biochemistry, we have investigated the origin and function of SpmX and determined that its occurrence is the result of the detoxification of a phage peptidoglycan hydrolase gene. We show that the retained, attenuated activity of the phage-derived domain plays an important role in proper cell morphology and developmental regulation in representatives of this large bacterial clade. To our knowledge, this is the first observation of phage gene domestication in which a toxic phage gene has been co-opted for a housekeeping function.

microbiology↗

bioRxiv2017

Quantitative hybrid modeling reveals predictable mechanical stress response of growing tumor spheroids

Model simulations indicate that the response of growing cell populations on mechanical stress follows the same functional relationship and is predictable over different cell lines and growth conditions despite the response curves look largely different. We develop a hybrid model strategy in which cells are represented by coarse-grained individual units calibrated with a high resolution cell model and parameterized measurable biophysical and cell-biological parameters. Cell cycle progression in our model is controlled by volumetric strain, the latter being derived from a bio-mechanical relation between applied pressure and cell compressibility. After parameter calibration from experiments with mouse colon carcinoma cells growing against the resistance of an elastic alginate capsule, the model adequately predicts the growth curve in i) soft and rigid capsules, ii) in different experimental conditions where the mechanical stress is generated by osmosis via a high molecular weight dextran solution, and iii) for other cell types with varying doubling times. Our model simulation results suggest that the growth response of cell population upon externally applied mechanical stress is the same, as it can be quantitatively predicted using the same growth progression function.\n\nAuthor summaryThe effect of mechanical resistance on the growth of tumor cells remains today largely unquantified. We studied data from two different experimental setups that monitor the growth of tumor cells under mechanical compression. The existing data in the first experiment examined growing CT26 cells in an elastic permeable capsule. In the second experiment, growth of tumor cells under osmotic stress of the same cell line as well as other cell lines were studied. We have developed and agent-based model with measurable biophysical and cell-biological parameters that can simulate both experiments. Cell cycle progression in our model is a Hill function of cell volumetric strain, derived from a bio-mechanical relation between applied pressure and cell compressibility. After calibration of the model parameters within the data of the first experiment, we are able predict the growth rates in the second experiment. We show that that the growth response of cell populations upon externally applied mechanical stress in the two different experiments and over different cell lines can be predicted using the same growth progression function once the growth kinetics of the cell lines in abscence of mechanical stress is known.

biophysics↗

bioRxiv2017

Microfluidic Transfection for High-Throughput Mammalian Protein Expression

Mammalian synthetic biology and cell biology would greatly benefit from improved methods for highly parallel transfection, culturing and interrogation of mammalian cells. Transfection is routinely performed on high-throughput microarrays, but this setup requires manual cell culturing and precludes precise control over the cell environment. As an alternative, microfluidic transfection devices streamline cell loading and culturing. Up to 280 transfections can be implemented on the chip at high efficiency. The culturing environment is tightly regulated and chambers physically separate the transfection reactions, preventing cross-contamination. Unlike typical biological assays that rely on end-point measurements, the microfluidic chip can be integrated with high-content imaging, enabling the evaluation of cellular behavior and protein expression dynamics over time.

molecular biology↗

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↗

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↗

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↗

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↗

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↗