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Ralser, M.

Publications and source records attributed to Ralser, M..

At least 55 records · Page 3Linked to original sources

SIGNR1 promotes immune dysfunction in systemic candidiasis by modulating neutrophil lifespan via T cell-derived histones and G-CSF

The mechanisms regulating immune dysfunction during sepsis are poorly understood. Here, we show that neutrophil-derived myeloperoxidase delays the onset of immune dysfunction during systemic candidiasis by controlling microbes captured by splenic marginal zone (MZ) macrophages. In contrast, SIGNR1-mediated microbe capture accelerates MZ colonization and immune dysfunction by triggering T cell death, T cell-dependent chromatin release and the synergistic induction of G-CSF by histones and fungi. Histones and G-CSF promote the prevalence of immature Ly6Glow neutrophils with defective oxidative burst, by selectively shortening the lifespan of mature Ly6Ghigh neutrophils. Consistently, T cell deficiency, or blocking SIGNR1, G-CSF or histones delayed neutrophil dysfunction. Furthermore, histones and G-CSF in the plasma of sepsis patients, shortened neutrophil lifespan and correlated with neutrophil mortality markers associated with a poor prognosis. Hence, the compromise of internal antimicrobial barrier sites drives neutrophil dysfunction by selectively modulating neutrophil lifespan via pathogenic T cell death, extracellular histones, and G-CSF.

immunology↗

Functional profiling of long intergenic non-coding RNAs in fission yeast

Eukaryotic genomes express numerous long intergenic non-coding RNAs (lincRNAs) that do not overlap any coding genes. Some lincRNAs function in various aspects of gene regulation, but it is not clear in general to what extent lincRNAs contribute to the information flow from genotype to phenotype. To explore this question, we systematically analyzed cellular roles of lincRNAs in Schizosaccharomyces pombe. Using seamless CRISPR/Cas9-based genome editing, we deleted 141 lincRNA genes to broadly phenotype these mutants, together with 238 diverse coding-gene mutants for functional context. We applied high-throughput colony-based assays to determine mutant growth and viability in benign conditions and in response to 145 different nutrient, drug and stress conditions. These analyses uncovered phenotypes for 47.5% of the lincRNAs and 96% of the protein-coding genes. For 110 lincRNA mutants, we also performed high-throughput microscopy and flow-cytometry assays, linking 37% of these lincRNAs with cell-size and/or cell-cycle control. With all assays combined, we detected phenotypes for 84 (59.6%) of all lincRNA deletion mutants tested. For complementary functional inference, we analyzed colony growth of strains ectopically overexpressing 113 lincRNA genes under 47 different conditions. Of these overexpression strains, 102 (90.3%) showed altered growth under certain conditions. Clustering analyses provided further functional clues and relationships for some of the lincRNAs. These rich phenomics datasets associate lincRNA mutants with hundreds of phenotypes, indicating that most of the lincRNAs analyzed exert cellular functions in specific environmental or physiological contexts. This study provides groundwork to further dissect the roles of these lincRNAs in the relevant conditions.

genetics↗

High sensitivity dia-PASEF proteomics with DIA-NN and FragPipe

The dia-PASEF technology exploits ion mobility separation for high-sensitivity analysis of complex proteomes. Here, we demonstrate neural network-based processing of the ion mobility data, which we implement in the DIA-NN software suite. Using spectral libraries generated with the MSFragger-based FragPipe computational platform, the DIA-NN analysis of dia-PASEF raw data increases the proteomic depth by up to 69% compared to the originally published dia-PASEF workflow. For example, we quantify over 5200 proteins from 10ng of HeLa peptides separated with a 95-minute nanoflow gradient, and over 5000 proteins from 200ng using a 4.8-minute separation with an Evosep One system. In complex samples, featuring a mix of human and yeast lysates, the workflow detects over 11700 proteins in single runs acquired with a 100-minute nanoflow gradient, while demonstrating quantitative precision. Hence, the combination of FragPipe and DIA-NN provides a simple-to-use software platform for dia-PASEF data analysis, yielding significant gains in high-sensitivity proteomics.

bioinformatics↗

Barcode Sequencing and a High-throughput Assay for Chronological Lifespan Uncover Ageing-associated Genes in Fission Yeast

Ageing-related processes are largely conserved, with simple organisms remaining the main platform to discover and dissect new ageing-associated genes. Yeasts provide potent model systems to study cellular ageing owing their amenability to systematic functional assays under controlled conditions. Even with yeast cells, however, ageing assays can be laborious and resource-intensive. Here we present improved experimental and computational methods to study chronological lifespan in Schizosaccharomyces pombe. We decoded the barcodes for 3206 mutants of the latest gene-deletion library, enabling the parallel profiling of [~]700 additional mutants compared to previous screens. We then applied a refined method of barcode sequencing (Bar-seq), addressing technical and statistical issues raised by persisting DNA in dead cells and sampling bottlenecks in aged cultures, to screen for mutants showing altered lifespan during stationary phase. This screen identified 341 long-lived mutants and 1246 short-lived mutants which point to many previously unknown ageing-associated genes, including 51 conserved but entirely uncharacterized genes. The ageing-associated genes showed coherent enrichments in processes also associated with human ageing, particularly with respect to ageing in non-proliferative brain cells. We also developed an automated colony-forming unit assay for chronological lifespan to facilitate medium- to high-throughput ageing studies by saving time and resources compared to the traditional assay. Results from the Bar-seq screen showed good agreement with this new assay, validating 33 genes not previously associated with cellular ageing. This study provides an effective methodological platform and identifies many new ageing-associated genes as a framework for analysing cellular ageing in yeast and beyond.

genomics↗

Longitudinal omics in Syrian hamsters integrated with human data unravel complexity of moderate immune responses to SARS-CoV-2

In COVID-19, the immune response largely determines disease severity and is key to therapeutic strategies. Cellular mechanisms contributing to inflammatory lung injury and tissue repair in SARS-CoV-2 infection, particularly endothelial cell involvement, remain ill-defined. We performed detailed spatiotemporal analyses of cellular and molecular processes in SARS-CoV-2 infected Syrian hamsters. Comparison of hamster single-cell sequencing and proteomics with data sets from COVID-19 patients demonstrated inter-species concordance of cellular and molecular host-pathogen interactions. In depth vascular and pulmonary compartment analyses (i) supported the hypothesis that monocyte-derived macrophages dominate inflammation, (ii) revealed endothelial inflammation status and T-cell attraction, and (iii) showed that CD4+ and CD8+ cytotoxic T-cell responses precede viral elimination. Using the Syrian hamster model of self-limited moderate COVID-19, we defined the specific roles of endothelial and epithelial cells, among other myeloid and non-myeloid lung cell subtypes, for determining the disease course.

immunology↗

Amino acids whose intracellular levels change most during aging alter chronological lifespan of fission yeast

Amino acid deprivation or supplementation can affect cellular and organismal lifespan, but we know little about the role of concentration changes in free, intracellular amino acids during aging. Here, we determine free amino-acid levels during chronological aging of non-dividing fission yeast cells. We compare wild-type with long-lived mutant cells that lack the Pka1 protein of the protein kinase A signalling pathway. In wild-type cells, total amino-acid levels decrease during aging, but much less so in pka1 mutants. Two amino acids strongly change as a function of age: glutamine decreases, especially in wild-type cells, while aspartate increases, especially in pka1 mutants. Supplementation of glutamine is sufficient to extend the chronological lifespan of wild-type but not of pka1{Delta} cells. Supplementation of aspartate, on the other hand, shortens the lifespan of pka1{Delta} but not of wild-type cells. Our results raise the possibility that certain amino acids are biomarkers of aging, and their concentrations during aging can promote or limit cellular lifespan.

physiology↗

Single amino acid-promoted reactions link a non-enzymatic chemical network to the early evolution of enzymatic pentose phosphate pathway

How metabolic pathways emerged in early evolution remains largely unknown. Recently discovered chemical networks driven by iron and sulfur resemble reaction sequences found within glycolysis, gluconeogenesis, the oxidative and reductive Krebs cycle, the Wood Ljungdahl as well as the S-adenosylmethionine pathways, components of the core cellular metabolic network. These findings suggest that the evolution of central metabolism was primed by environmental chemical reactions, implying that non-enzymatic reaction networks served as a "template" in the evolution of enzymatic activities. We speculated that the turning point for this transition would depend on the catalytic properties of the simplest structural components of proteins, single amino acids. Here, we systematically combine constituents of Fe(II)-driven non-enzymatic reactions resembling glycolysis and pentose phosphate pathway (PPP), with single proteinogenic amino acids. Multiple reaction rates are enhanced by amino acids. In particular, cysteine is able to replace (and/or complement) the metal ion Fe(II) in driving the non-enzymatic formation of the RNA-backbone metabolite ribose 5-phosphate from 6-phosphogluconate, a rate-limiting reaction of the oxidative PPP. In the presence of both Fe(II) and cysteine, a complex is formed, enabling the non-enzymatic reaction to proceed at a wide range of temperatures. At mundane temperatures, this minimal enzyme-like complex achieves a much higher specificity in the formation of ribose 5-phosphate than the Fe(II)-driven reaction at high temperatures. Hence, simple amino acids can accelerate key steps within metal-promoted metabolism-like chemical networks. Our results imply a stepwise scenario, in which environmental chemical networks served as primers in the early evolution of the metabolic network structure. Significance StatementThe evolutionary roots of metabolic pathways are barely understood. Here we show results consistent with a stepwise scenario during the evolution of (enzymatic) metabolism, starting from non-enzymatic chemical networks. By systematic screening of metabolic-like reactivities in vitro, and using high-throughput analytical techniques, we identify an iron/cysteine complex to act as a minimal enzymelike complex, which consists of a metal ion, an amino acid, and a sugar phosphate ligand. Integrated in a metal-driven, non-enzymatic pentose phosphate pathway, it promotes the formation of the RNA-backbone precursor ribose 5-phosphate at ambient temperature.

biochemistry↗

Genetic architecture of host proteins interacting with SARS-CoV-2

Strategies to develop therapeutics for SARS-CoV-2 infection may be informed by experimental identification of viral-host protein interactions in cellular assays and measurement of host response proteins in COVID-19 patients. Identification of genetic variants that influence the level or activity of these proteins in the host could enable rapid in silico assessment in human genetic studies of their causal relevance as molecular targets for new or repurposed drugs to treat COVID-19. We integrated large-scale genomic and aptamer-based plasma proteomic data from 10,708 individuals to characterize the genetic architecture of 179 host proteins reported to interact with SARS-CoV-2 proteins or to participate in the host response to COVID-19. We identified 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links, evidence that putative viral interaction partners such as MARK3 affect immune response, and establish the first link between a recently reported variant for respiratory failure of COVID-19 patients at the ABO locus and hypercoagulation, i.e. maladaptive host response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and dynamic and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/).

genomics↗

Ribosome profiling reveals ribosome stalling on tryptophan codons upon oxidative stress in fission yeast

Modulation of translation is an essential response to stress conditions. We have investigated the translational programmes launched by the fission yeast Schizosaccharomyces pombe subject to five environmental stresses: oxidative stress, heavy metal, heat shock, osmotic shock and DNA damage. We also explored the contribution of two major defence pathways to these programmes: The Integrated Stress Response, which directly regulates translation initiation, and the stress-response MAPK pathway. To obtain a genome-wide and high-resolution view of this phenomenon, we performed ribosome profiling of control cells and of cells subject to each of the five stresses mentioned above, both in wild type background and in cells in which the Integrated Stress Response or the MAPK pathway were inactivated. Translational changes were partially dependent on the integrity of both signalling pathways. Interestingly, we found that the transcription factor Fil1, a functional homologue of the Gcn4 and Atf4 proteins (from budding yeast and mammals, respectively), was highly upregulated in most stresses. Consistent with this result, Fil1 was required for the normal response to most stresses. A large group of mRNAs were translationally downregulated, including many required for ribosome biogenesis. Overall, our data suggest that severe stresses lead to the implementation of a universal translational response, which includes energy-saving measures (reduction of ribosome production) and induction of a Fil1-mediated transcriptional programme. Surprisingly, ribosomes stalled on tryptophan codons specifically upon oxidative stress, a phenomenon that is likely caused by a decrease in charged tRNA-Tryptophan. Tryptophan stalling led to a mild translation elongation reduction and contributed to the inhibition of initiation by the Integrated Stress Response. Taken together, our results show that different stresses elicit common and specific translational responses, revealing a special and so far unknown role in Tryptophan-tRNA availability.

molecular biology↗

Cooperative molecular networks drive a mammalian cell state transition

In the mammalian embryo, epiblast cells must exit their naive state and acquire formative pluripotency. This cell state transition is recapitulated by mouse embryonic stem cells (ESCs), which undergo pluripotency progression in defined conditions in vitro. However, our understanding of the molecular cascades and gene-networks involved in the exit from naive pluripotency remains fragmented. Here we employed a combination of genetic screens in haploid ESCs, CRISPR/Cas9 gene disruption, large-scale transcriptomics and computational systems-biology to delineate the regulatory circuits governing naive state exit. Transcriptome profiles for 73 knockout ESC lines predominantly manifest delays on the trajectory from naive to formative epiblast. We find that gene networks operative in ESCs are active during transition from pre- to post-implantation epiblast in utero. We identified 374 naive-associated genes tightly connected to epiblast state and largely conserved in human ESCs and primate embryos. Integrated analysis of mutant transcriptomes revealed funneling of multiple gene activities into discrete regulatory modules. Finally, we delineate how intersections with signaling pathways direct this pivotal mammalian cell state transition.

systems biology↗

Mitochondrial respiration is required to provide amino acids during fermentative proliferation of fission yeast

When glucose is available, many organisms repress mitochondrial respiration in favour of aerobic glycolysis, or fermentation in yeast, that suffices for ATP production. Fission yeast cells, however, rely partially on respiration for rapid proliferation under fermentative conditions. Here we determined the limiting factors that require respiratory function during fermentation. When the electron transport chain was inhibited, supplementation with arginine was necessary and sufficient to restore rapid cell proliferation. Accordingly, a systematic screen for mutants growing poorly without arginine identified not only mutants defective in arginine synthesis but also mutants defective in mitochondrial oxidative metabolism. Genetic or pharmacological inhibition of respiration triggered a drop in intracellular levels of arginine and amino acids derived from the Krebs-cycle metabolite alpha-ketoglutarate: glutamine, lysine and glutamic acid. Conversion of arginine into these amino acids was required for rapid proliferation when the respiratory chain was blocked. The respiratory block triggered an immediate gene-expression response diagnostic of TOR inhibition, which was muted by arginine supplementation or without the AMPK-activating kinase Ssp1. The TOR-controlled proteins featured biased composition of amino acids reflecting their shortage after respiratory inhibition. We conclude that respiration supports rapid proliferation in fermenting cells of fission yeast by boosting the supply of Krebs-cycle derived amino acids.

genetics↗

Pyphe: A python toolbox for assessing microbial growth and cell viability in high-throughput colony screens

Microbial fitness screens are a key technique in functional genomics. We present an all-in-one solution, pyphe, for automating and improving data analysis pipelines associated with large-scale fitness screens, including image acquisition and quantification, data normalisation, and statistical analysis. Pyphe is versatile and processes fitness data from colony sizes, viability scores from phloxine B staining or colony growth curves, all obtained with inexpensive transilluminating flatbed scanners. We apply pyphe to show that the fitness information contained in late endpoint measurements of colony sizes is similar to maximum growth slopes from time series. We phenotype gene-deletion strains of fission yeast in 59,350 individual fitness assays in 70 conditions, revealing that colony size and viability provide complementary, independent information. Viability scores obtained from quantifying the redness of phloxine-stained colonies accurately reflect the fraction of live cells within colonies. Pyphe is user-friendly, open-source and fully-documented, illustrated by applications to diverse fitness analysis scenarios.

genomics↗

A natural variant of the sole pyruvate kinase of fission yeast lowers glycolytic flux triggering increased respiration and oxidative-stress resistance but decreased growth

Cells balance glycolysis with respiration to support their energetic and biosynthetic needs in different environmental or physiological contexts. With abundant glucose, many cells prefer to grow by aerobic glycolysis, or fermentation in yeast. Using 161 natural isolates of fission yeast, we investigated the genetic basis and phenotypic effects of the fermentation-respiration balance. The laboratory and a few other strains were more dependent on respiration. This trait was associated with a missense variant in a highly conserved region of Pyk1. Pyk1 is the single pyruvate kinase in fission yeast, while most organisms possess isoforms with different activity. This variant reduced Pyk1 activity and glycolytic flux. Replacing the low-activity pyk1 allele in the laboratory strain with the common high-activity allele was sufficient to increase fermentation and decrease respiration. This metabolic reprogramming triggered systems-level adaptations in the transcriptome and proteome, and in cellular phenotypes, including increased growth and chronological lifespan, but decreased resistance to oxidative stress. Thus, low Pyk1 activity provided no growth advantage but stress tolerance, despite increased respiration. The genetic tuning of glycolytic flux by a single-nucleotide change might reflect an adaptive trade-off in a species lacking pyruvate-kinase isoforms.

genetics↗

ScanningSWATH enables ultra-fast proteomics using high-flow chromatography and minute-scale gradients

Bridging genotype to phenotype, the proteome has increasingly become of major importance to generate large, longitudinal sample series for data-driven biology and personalized medicine. Major improvements in laboratory automation, chromatography and software have increased the scale and precision of proteomics. So far missing are however mass spectrometric acquisition techniques that could deal with very fast chromatographic gradients. Here we present scanning SWATH, a data-independent acquisition (DIA) method, in which the DIA-typical stepwise windowed acquisition is replaced by a continuous movement of the precursor isolation window. Scanning SWATH accelerates the duty cycles to a few hundreds of milliseconds, and enables precursor mass assignment to the MS2 fragment traces for improving true positive precursor identification in fast proteome experiments. In combination with 800 {micro}L/min high-flow chromatography, we report the quantification of 270 precursors per second, increasing the precursor identifications by 70% or more compared to previous methods. Scanning SWATH quantified 1,410 Human protein groups in conjunction with chromatographic gradients as fast as 30 seconds, 2,250 with 60-second gradients, and 4,586 in conjunction with 5-minute gradients. At high quantitative precision, our method hence increases the proteomic throughput to hundreds of samples per day per mass spectrometer. Scanning SWATH hence enables a broad range of new proteomic applications that depend on large numbers of cheap yet quantification precise proteomes.

systems biology↗

A multi-omic analysis of optineurin proteinopathy in a yeast model suggests the involvement of lipid metabolism in Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is an incurable fatal neurodegenerative disease for which the precise mechanisms of toxicity remain unclear despite some significant advances in our understanding of the underlying genetic basis. A holistic, integrated view of cellular changes will be critical to understanding the processes of neurodegeneration and the development of effective treatments. Mutant forms of optineurin (a ubiquitin-binding protein involved in autophagy, membrane trafficking, and NF-{kappa}B activation) are found associated with cytoplasmic inclusions containing TDP43 or SOD1 in some ALS patients. We have taken a multi-omics approach to understand the cellular response to OPTN overexpression in a yeast model of ALS. We found that genetic interaction screens and metabolomics provided parallel, highly complementary data on OPTN toxicity. Genetic enhancers of OPTN toxicity in yeast relate directly to the native function of OPTN in vesicular trafficking and intracellular transport, suggesting the human OPTN protein is functional when expressed in yeast even though there is no yeast ortholog. Crucially, we find that the genetic modifiers and the metabolic response are distinct for different ALS-linked genes expressed in yeast. This lends strong support to the use of yeast as a model system and omics platform to study ALS.

systems biology↗

MTA proteins act redundantly within the NuRD complex to ensure fidelity of ES cell lineage commitment

Multiprotein chromatin remodelling complexes show remarkable conservation of function amongst metazoans, even though components present in invertebrates are often present as multiple paralogous proteins in vertebrate complexes. In some cases these paralogues specify distinct biochemical and/or functional activities in vertebrate cells. Here we set out to define the biochemical and functional diversity encoded by one such group of proteins within the mammalian Nucleosome Remodelling and Deacetylation (NuRD) complex: Mta1, Mta2 and Mta3. We find that, in contrast to what has been described in somatic cells, MTA proteins are not mutually exclusive within ES cell NuRD and, despite subtle differences in chromatin binding and biochemical interactions, serve largely redundant functions. Nevertheless, ES cells lacking all three MTA proteins represent a complete NuRD null and are viable, allowing us to identify a previously undetected function for NuRD in maintaining differentiation trajectory during early stages of lineage commitment.

developmental biology↗

DIA-NN: Deep neural networks substantially improve the identification performance of Data-independent acquisition (DIA) in proteomics

Data-independent acquisition (DIA-MS) strategies, like SWATH-MS, have been developed to increase consistency, quantification precision and proteomic depth in label-free proteomic experiments. They aim to overcome stochasticity in the selection of precursor ions by utilising (mass-) windowed acquisition that is followed by computational reconstruction of the chromatograms. While DIA methods increasingly outperform typical data-dependent methods in identification consistency and precision specifically on large sample series, possibilities remain for further improvements. At present, only a fraction of the information recorded in the complex DIA spectra is extracted by the software analysis pipelines. Here we present a software tool (DIA-NN) that introduces artificial neural nets and a new quantification strategy to enhance signal processing in DIA-data. DIA-NN greatly improves identification of precursor ions and, as a consequence, protein quantification accuracy. The performance of DIA-NN demonstrates that deep learning provides opportunities to boost the analysis of data-independent acquisition workflows in proteomics.

bioinformatics↗

A Yeast Global Genetic Screen Reveals that Metformin Induces an Iron Deficiency-Like State

We report here a simple and global strategy to map out gene functions and target pathways of drugs, toxins or other small molecules based on \"homomer dynamics\" Protein-fragment Complementation Assays (hdPCA). hdPCA measures changes in self-association (homomerization) of over 3,500 yeast proteins in yeast grown under different conditions. hdPCA complements genetic interaction measurements while eliminating confounding effects of gene ablation. We demonstrate that hdPCA accurately predicts the effects of two longevity and health-span-affecting drugs, immunosuppressant rapamycin and type II diabetes drug metformin, on cellular pathways. We also discovered an unsuspected global cellular response to metformin that resembles iron deficiency. This discovery opens a new avenue to investigate molecular mechanisms for the prevention or treatments of diabetes, cancers and other chronic diseases of aging.

systems biology↗