Biology subjects

Marguerat, S.

Publications and source records attributed to Marguerat, S..

14 recordsLinked to original sources

bioRxiv2026

Denaturing purifications support direct interaction between PRC2 and RNA in cells

Polycomb Repressive Complex 2 (PRC2) maintains repression of genes specific for other cell differentiation states. PRC2 binds RNA in vitro with a preference for G-rich sequences. UV-based crosslinking coupled with immunoprecipitation (CLIP) experiments have shown that PRC2 also binds RNA in cells. Recently, Guo et al reported that a stringent denaturing variant of CLIP called CLAP did not detect PRC2 RNA binding in cells. We present a reanalysis of CLAP data that supports direct interaction of PRC2 with RNA in cells. CLAP for Halo-tagged PRC2 subunits from mixed populations of human and mouse cells specifically enriched for RNA from the species in which the proteins were tagged. The lack of apparent PRC2 RNA binding in Guo and colleagues analysis stems from a scaling step that deflates enrichment scores for low-complexity CLAP samples. Our findings pave the way for studies seeking to determine the physiological roles of PRC2 RNA binding activity.

genomics↗

bioRxiv2024

Aging-associated long non-coding RNA boosts longevity and reduces the ribosome content of non-dividing fission yeast cells

Genomes produce widespread long non-coding RNAs (lncRNAs) of largely unknown functions. We characterize aal1 (aging-associated lncRNA) which is induced in quiescent cells of fission yeast. Deletion of aal1 shortens the chronological lifespan of non-dividing cells, while ectopic overexpression of aal1 prolongs their lifespan, indicating that this lncRNA acts in trans. The overexpression of aal1 leads to the repression of ribosomal protein genes and inhibition of cell growth, and aal1 genetically interacts with coding genes functioning in protein translation. The aal1 RNA localizes to the cytoplasm and associates with ribosomes. Notably, aal1 deletion or overexpression is sufficient to increase or decrease the cellular ribosome content. The rpl1901 mRNA, encoding a ribosomal protein, is a binding target of aal1. The levels of rpl1901 are reduced [~]2-fold by aal1, which is critical and sufficient to extend the lifespan. Remarkably, the expression of aal1 lncRNA in Drosophila triggers an extension of fly lifespan. We propose that aal1 reduces the ribosome content by decreasing the levels of Rpl1901, thus attenuating protein translation and promoting longevity. Although the aal1 lncRNA itself is not conserved, its effect in flies raises the possibility that animals feature related mechanisms that modulate aging, based on the conserved translational machinery.

genetics↗

bioRxiv2023

Fission yeast obeys a linear size law under nutrient titration

Steady-state cell size and geometry depend on growth conditions. Here, we use an experimental setup based on continuous culture and single-cell imaging to study how cell volume, length, width and surface-to-volume ratio vary across a range of growth conditions including nitrogen and carbon titration, the choice of nitrogen source, and translation inhibition. Overall, we find cell geometry is not fully determined by growth rate and depends on the specific mode of growth rate modulation. However, under nitrogen and carbon titrations, we observe that the cell volume and the growth rate follow the same linear scaling. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/536544v1_fig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1d5c614org.highwire.dtl.DTLVardef@1bf877corg.highwire.dtl.DTLVardef@157f140org.highwire.dtl.DTLVardef@9fc243_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigureC_FLOATNO A. Graphical outline of the growth and imaging assays. B. Illustration of the procedure used to extract cell size and geometry data. C. Average surface-to-volume (S/V) ratio plotted as a function of average cell width across all steady-state cultures. The dark grey circle indicates the base growth medium, EMM2. Cultures limited in their growth by the concentration of ammonium, glucose, and cycloheximide in the medium are indicated with cyan lozenges, green triangles, and orange squares, respectively. Cultures limited by the choice of nitrogen source are indicated with light grey circles; the amino-acid nitrogen source used is labelled with its three-letter abbreviation, using Amm for the equivalent culture grown with ammonium chloride as its sole nitrogen source. D. Average cell volume plotted against the growth rate across all cultures, showing collapse for ammonium- and glucose-limited cultures and differing behaviour for nitrogen-source- and translation-limited cultures. Plotted in dark grey is a linear fit to the ammonium- and glucose-limited data, including the base medium, with 95% confidence interval; a similar fit (without CI) to the cycloheximide-limited cultures is indicated by a dashed orange line. E. Average surface-to-volume (S/V) ratio against growth rate across all cultures, with dashed lines for ammonium-, glucose-, and translation-limited cultures representing linear fits to the respective data, each including the base medium. Under ammonium limitation, the surface-to-volume ratio increases markedly as the growth rate decreases. A moderate increase is observed for glucose limitation and a moderate decrease is observed for protein synthesis inhibition with cycloheximide. There is no consistent trend with the growth rate when the quality of the nitrogen source is varied. F. Average surface area, G. cell length, H. cell width against growth rate, showing that ammonium-limited cells are thinner than glucose-limited cells at equivalent growth rates, consistent with their different surface-to-volume ratios and the relation between surface-to-volume ratio and cell width (see C). C_FIG

systems biology↗

bioRxiv2023

A coarse-grained resource allocation model of carbon and nitrogen metabolism in unicellular microbes

Coarse-grained resource allocation models (C-GRAMs) are simple mathematical models of whole cell physiology, where large components of the macromolecular composition are abstracted into single entities. The dynamics and steady-state behaviour of such models provides insights on optimal allocation of cellular resources and have explained experimentally observed cellular growth laws. Here, we formulate a minimal C-GRAM with nitrogen and carbon pathways converging on biomass production, with parameterizations accounting for respiro-fermentative and purely respiratory growth. The model describes the effects of the uptake of sugars, ammonium, and/or compound nutrients such as amino acids on the translational resource allocation towards proteome sectors that maximised the growth rate. It robustly recovers cellular growth laws including the Monod law and the ribosomal growth law. Furthermore, we show how the growth-maximizing balance between carbon uptake, recycling, and excretion depends on the nutrient environment. Lastly, we find a robust linear correlation between the ribosome fraction and the abundance of amino acid equivalents in the optimal cell, which supports the view that simple regulation of translational gene expression can enable cells to achieve an approximately optimal growth state.

systems biology↗

bioRxiv2023

Modelling capture efficiency of single cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics

Gene expression is characterised by stochastic bursts of transcription that occur at brief and random periods of promoter activity. The kinetics of gene expression burstiness differs across the genome and is dependent on the promoter sequence, among other factors. Single-cell RNA sequencing (scRNA-seq) has made it possible to quantify the cell-to-cell variability in transcription at a global genome-wide level. However, scRNA-seq data is prone to technical variability, including low and variable capture efficiency of transcripts from individual cells. Here, we propose a novel mathematical theory for the observed variability in scRNA-seq data. Our method captures burst kinetics and variability in both cell size and capture efficiency, which allows us to propose several likelihood-based and simulation-based methods for the inference of burst kinetics from scRNA-seq data. Using both synthetic and real data, we show that the simulation-based methods provide an accurate, robust and flexible tool for inferring burst kinetics from scRNA-seq data. In particular, in supervised manner, a simulation-based inference method based on neural networks proves to be accurate and useful in application to both allele and non-allele specific scRNA-seq data.

bioinformatics↗

bioRxiv2023

Size-Dependent Expression of the Fission Yeast Cdc13 Cyclin is Conferred by Translational Regulation

The major fission yeast cyclin, Cdc13, has been shown to increase in concentration in correlation with cell size, and has been proposed to thereby regulate cell size at division. However, the mechanism of its cell-size regulation has been unknown. Here, we show that Cdc13 is regulated post-transcriptionally. Its transcript is not expressed in a size-dependent manner, rather a size-dependent concentration of protein is expressed from a size-independent concentration of mRNA. Moreover, we show that the expression of Cdc13 is, in fact, size dependent, as opposed to simply size-correlated due to time-dependent expression. We identify a 20-amino-acid motif, which includes the APC D-box degron, as necessary and sufficient for size-dependent expression, which allowed us to construct a size-independent allele of cdc13. Using this allele, we show that size-dependent expression of Cdc13 is not required for size control in fission yeast cells.

cell biology↗

bioRxiv2022

Large-scale changes of molecular network states explain complex traits

The complexity of many cellular and organismal traits results from poorly understood mechanisms integrating genetic and environmental factors via molecular networks. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to large-scale adaptations of global network states. Integrating multi-omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single-dimensional axis, thereby modulating processes including energy- and amino acid metabolism, transcription, translation, cell cycle control and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/519111v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@18d3323org.highwire.dtl.DTLVardef@1185111org.highwire.dtl.DTLVardef@17238c7org.highwire.dtl.DTLVardef@1edc6e6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract:C_FLOATNO Genetic variants directly or indirectly affecting the activity of PKA and/or TOR signaling cause global changes of transcriptomic and proteomic network states by modulating the activity of diverse cellular functions and network modules. Using marker genes acting downstream of PKA and TOR signaling we are able to quantify the activity status of combined PKA and TOR signaling (PT Score). This PT Score correlates with major transcriptomic and proteomic changes in response to genetic variability. Those large-scale molecular adaptations correlate with and explain phenotypic consequences for multiple cellular traits. Variants affecting the stoichiometry of proteins within a specific module have regional effects that remain confined to smaller parts of the molecular network. Variants affecting only one or very few proteins change molecular networks only locally. The global reorganization of network states caused by variants of the first type result in consequences for many cellular traits (i.e. pleiotropic effects), such as growth on different carbon sources, stress response, energy metabolism and replicative lifespan. (Created with BioRender.com) C_FIG

systems biology↗

bioRxiv2022

Diet suppresses tumour initiation by maintaining quiescence of mutation-bearing neural stem cells

Glioblastoma is thought to originate from neural stem cells (NSCs) of the subventricular zone that acquire genetic alterations. In the adult brain, NSCs are largely quiescent, suggesting that deregulation of quiescence maintenance may be a pre-requisite for tumour initiation. Although inactivation of the tumour suppressor p53 is a frequent event in gliomagenesis, whether, or how, it affects quiescent NSCs (qNSCs) remains unclear. Here we show that p53 maintains quiescence by inducing fatty acid oxidation (FAO) and that acute p53 deletion in qNSCs results in their premature activation to a proliferative state. Mechanistically, this occurs through direct transcriptional induction of PPARGC1a, which in turn activates PPAR to upregulate FAO genes. Strikingly, dietary supplementation with fish oil containing omega-3 fatty acids, natural PPAR ligands, fully restores quiescence of p53-deficient NSCs and delays tumour initiation in a glioblastoma mouse model. Thus, diet can silence glioblastoma driver mutations, with important implications for cancer prevention.

cancer biology↗

bioRxiv2021

Growth-Rate Dependent And Nutrient-Specific Gene Expression Resource Allocation In Fission Yeast

Cellular resources are limited and their relative allocation to gene expression programmes determines physiological states and global properties such as the growth rate. Quantitative studies using various growth conditions have singled out growth rate as a major physiological variable explaining relative protein abundances. Here, we used the simple eukaryote Schizosaccharomyces pombe to determine the importance of growth rate in explaining relative changes in protein and mRNA levels during growth on a series of non-limiting nitrogen sources. Although half of fission yeast genes were significantly correlated with the growth rate, this came alongside wide-spread nutrient-specific regulation. Proteome and transcriptome often showed coordinated regulation but with notable exceptions, such as metabolic enzymes. Genes positively correlated with growth rate participated in every level of protein production with the notable exception of RNA polymerase II, whereas those negatively correlated mainly belonged to the environmental stress response programme. Critically, metabolic enzymes, which represent [~]55-70% of the proteome by mass, showed mainly condition-specific regulation. Specifically, many enzymes involved in glycolysis and NAD-dependent metabolism as well as the fermentative and respiratory pathways were condition-dependent and not consistently correlated with growth. In summary, we provide a rich account of resource allocation to gene expression in a simple eukaryote, advancing our basic understanding of the interplay between growth-rate dependent and nutrient-specific gene expression.

systems biology↗

bioRxiv2020

The white matter is a pro-differentiative microenvironment for glioblastoma

Glioblastomas are hierarchically organised tumours driven by glioma stem cells that retain partial differentiation potential. Glioma stem cells are maintained in specialised microenvironments, but how they undergo lineage progression outside of these niches remains unclear. Here we identify the white matter as a differentiative niche for glioblastomas with oligodendrocyte lineage competency. Tumour cells in contact with white matter acquire pre-oligodendrocyte-like fate, resulting in decreased proliferation and invasion. Differentiation is a response to white matter injury, which is caused by tumour infiltration itself in a tumoursuppressive feedback loop. Mechanistically, tumour cell differentiation is driven by selective white matter upregulation of SOX10, a master regulator of normal oligodendrogenesis. SOX10 overexpression or treatment with myelination-promoting agents that upregulate endogenous SOX10, mimic this response, leading to white matter-independent pre-oligodendrocyte-like differentiation and tumour suppression in vivo. Thus, glioblastoma recapitulates an injury response and exploiting this latent programme may offer treatment opportunities for a subset of patients.

cancer biology↗

bioRxiv2018

Condensin controls cellular RNA levels through the accurate segregation of chromosomes instead of directly regulating transcription

Condensins are genome organisers that shape chromosomes and promote their accurate transmission. Several studies have also implicated condensins in gene expression, although the mechanisms have remained enigmatic. Here, we report on the role of condensin in gene expression in fission and budding yeasts. In contrast to previous studies, we provide compelling evidence that condensin plays no direct role in the maintenance of the transcriptome, neither during interphase nor during mitosis. We further show that the changes in gene expression in post-mitotic fission yeast cells that result from condensin inactivation are largely a consequence of chromosome missegregation during anaphase, which notably depletes the RNA-exosome from daughter cells. Crucially, preventing karyotype abnormalities in daughter cells restores a normal transcriptome despite condensin inactivation. Thus, chromosome instability, rather than a direct role of condensin in the transcription process, changes gene expression. This knowledge challenges the concept of gene regulation by canonical condensin complexes.

molecular biology↗

bioRxiv2018

Single-cell phenotyping and RNA sequencing reveal novel patterns of gene expression heterogeneity and regulation during growth and stress adaptation in a unicellular eukaryote

Cell-to-cell variability is central for microbial populations and contributes to cell function, stress adaptation and drug resistance. Gene-expression heterogeneity underpins this variability, but has been challenging to study genome-wide. Here, we report an integrated approach for imaging of individual fission yeast cells followed by single-cell RNA sequencing (scRNA-seq) and novel Bayesian normalisation. We analyse >2000 single cells and >700 matching RNA controls in various environmental conditions and identify sets of highly variable genes. Combining scRNA-seq with cell-size measurements provides unique insights into genes regulated during cell growth and division in single cells, including genes whose expression does not scale with cell size. We further analyse the heterogeneity and dynamics of gene expression during adaptive and acute responses to changing environments. Entry into stationary phase is preceded by a gradual, synchronised adaptation in gene regulation, followed by highly variable gene expression when growth decreases. Conversely, a sudden and acute heat-shock leads to a stronger and coordinated response and adaptation across cells. This analysis reveals that the extent and dynamics of global gene-expression heterogeneity is regulated in response to different physiological conditions within populations of a unicellular eukaryote. In summary, this works illustrates the potential of combined transcriptomics and imaging analysis in single cells to provide comprehensive and unbiased mechanistic understanding of cell-to-cell variability in microbial communities.

genomics↗

bioRxiv2017

Impact of division rate and cell size on gene expression noise

The cell division rate, size, and gene expression programmes change in response to external conditions. These global changes impact on average concentrations of biomolecule and their variability or noise. Gene expression is inherently stochastic, and noise levels of individual proteins depend on synthesis and degradation rates as well as on cell-cycle dynamics. We have modelled stochastic gene expression inside growing and dividing cells to study the effect of division rates on noise in mRNA and protein expression. We use assumptions and parameters relevant to Escherichia coli, for which abundant quantitative data are available. We find that coupling of transcription, but not translation rates to the rate of cell division can result in protein concentration and noise homeostasis across conditions. Interestingly, we find that the increased cell size at fast division rates, observed in E. coli d other unicellular organisms, buffers noise levels even for proteins with decreased expression at faster growth. We then investigate the functional importance of these regulations using gene regulatory networks that exhibit bi-stability and oscillations. We find that network topology affects robustness to changes in division rate in complex and unexpected ways. In particular, a simple model of persistence, based on global physiological feedback, predicts increased proportion of persistors cells at slow division rates. Altogether, our study reveals how cell size regulation in response to cell division rate could help controlling gene expression noise. It also highlights that understanding of circuits robustness across growth conditions is key for the effective design of synthetic biological systems.

systems biology↗

bioRxiv2017

Long non-coding RNA repertoire and regulation by nuclear exosome, cytoplasmic exonuclease and RNAi in fission yeast

Transcriptomes feature pervasive, but poorly defined long non-coding RNAs (lncRNAs). We identify 5775 novel lncRNAs in Schizosaccharomyces pombe, nearly 4-times the previously annotated lncRNAs. Most lncRNAs become derepressed under genetic and physiological perturbations, especially during late meiosis. These lncRNAs are targeted by three RNA-processing pathways: the nuclear exosome, cytoplasmic exonuclease and RNAi, with substantial coordination and redundancy among pathways. We classify lncRNAs into cryptic unstable transcripts (CUTs), Xrn1-sensitive unstable transcripts (XUTs), and Dicer-sensitive unstable transcripts (DUTs). XUTs and DUTs are enriched for antisense lncRNAs, while CUTs are often bidirectional and actively translated. The cytoplasmic exonuclease and RNAi repress thousands of meiotically induced RNAs. Antisense lncRNA and sense mRNA expression often negatively correlate in the physiological, but not the genetic conditions. Intergenic and bidirectional lncRNAs emerge from nucleosome-depleted regions, upstream of positioned nucleosomes. This broad survey of the S. pombe lncRNA repertoire and characteristics provides a rich resource for functional analyses.

genomics↗