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Ralser, M.

Publications and source records attributed to Ralser, M..

At least 37 records · Page 2Linked to original sources

Genetic and environmental determinants of multicellular-like phenotypes in fission yeast

Multicellular fungi have repeatedly given rise to primarily unicellular yeast species. Some of these, including Schizosaccharomyces pombe, are able to revert to multicellular-like phenotypes (MLP). Our bioinformatic analysis of existing data suggested that, besides some regulatory proteins, most proteins involved in MLP formation are not functionally conserved between S. pombe and budding yeast. We developed high-throughput assays for two types of MLP in S. pombe: flocculation and surface adhesion, which correlated in minimal medium, suggesting a common mechanism. Using a library of 57 natural S. pombe isolates, we found MLP formation to widely vary across different nutrient and drug conditions. Next, in a segregant S. pombe library generated from an adhesive natural isolate and the standard laboratory strain, MLP formation correlated with expression levels of the transcription-factor gene mbx2 and several flocculins. Quantitative trait locus mapping of MLP formation located a causal frameshift mutation in the srb11 gene encoding cyclin C, a part of the Cdk8 kinase module (CKM) of the Mediator complex. Other CKM deletions also resulted in MLP formation, consistently through upregulation of mbx2, and only in minimal media. We screened a library of 3721 gene-deletion strains, uncovering additional genes involved in surface adhesion on minimal media. We identified 31 high-confidence hits, including 19 genes that have not been associated with MLPs in fission or budding yeast. Notably, deletion of srb11, unlike deletions of the 31 hits, did not compromise cell growth, which might explain its natural occurrence as a QTL for MLP formation.

genetics↗

An enzyme activation network provides evidence for extensive regulatory crosstalk between metabolic pathways

Enzyme activation by cellular metabolites plays a pivotal role in regulating metabolic processes. Nevertheless, our comprehension of such activation events on a global network scale remains incomplete. In this study, we conducted a comprehensive investigation into the optimization of cell-intrinsic activation interactions within Saccharomyces cerevisiae. To achieve this, we integrated a genome-scale metabolic model with enzyme kinetic data sourced from the BRENDA database. Our objective was to map the distribution of enzyme activators throughout the cellular network. Our findings indicate that virtually all biochemical pathways encompass enzyme activators, frequently originating from disparate pathways, thus revealing extensive regulatory crosstalk between metabolic pathways. Indeed, activators have short pathway lengths, indicating they are activated quickly upon nutrient shifts, and in most instances, these activators target key enzymatic reactions to facilitate downstream metabolic processes. Interestingly, non-essential enzymes exhibit a significantly higher degree of activation compared to their essential counterparts. This observation suggests that cells employ enzyme activators to finely regulate secondary metabolic pathways that are only required under specific conditions. Conversely, the activator metabolites themselves are more likely to be essential components, and their activation levels surpass those of non-essential activators. In summary, our study unveils the widespread importance of enzymatic activators, and suggests that feed-forward activation of conditional metabolic pathways through essential metabolites mediates metabolic plasticity.

systems biology↗

Myeloperoxidase-dependent tyrosine halogenation potentiates alpha-defensins functions

Neutrophils are immune cells that eliminate microbes using a powerful arsenal of reactive oxygen species, hypohalous acids, proteases, and antimicrobial peptides -- yet how these cytotoxic effectors act in concert remains poorly understood. Here, we identify an unrecognized synergy between oxidative and non-oxidative neutrophil defenses. We show that myeloperoxidase-derived hypohalous acids selectively halogenate -defensins (HNP1-3) at conserved tyrosine residues. This post-translational modification occurs in both human and rat neutrophils and is prominent in diseases marked by neutrophil-rich inflammation, including cystic fibrosis, bacterial pneumonia, and Staphylococcus aureus abscesses. Halogenation increases HNP1 hydrophobicity without altering its structure, reprogramming these peptides into potent immunomodulatory mediators. Using single-cell transcriptomics and a in vivo peritonitis model, we demonstrate that halogenated HNP1s amplify immune signaling. Our analysis of the human haloproteome reveals a novel oxidative mechanism by which hypohalous acids rewire immune protein functions, uncovering an unexpected layer of cooperation between neutrophil effector systems. The discovery of halogenated HNP1s represents, to our knowledge, the first characterization of a protein halogenation that has biologically significance in human immunity.

biochemistry↗

The amino acid sequence determines protein abundance through its conformational stability and reduced synthesis cost.

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, the amino acid sequence is tailored to meet the required abundance of proteomes, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here, we demonstrate that the amino acid sequence predicts abundance by shaping a proteins conformational stability. We show that increasing the abundance provides metabolic cost benefits, underscoring the evolutionary advantage of maintaining a highly abundant and stable proteome. Specifically, using a deep learning model (BERT), we predict 56% of protein abundance variation in Saccharomyces cerevisiae solely based on amino acid sequence. The model reveals latent factors linking sequence features to protein stability. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations increasing abundance significantly alter protein polarity and hydrophobicity, underscoring a connection between protein stability and abundance. Through molecular dynamics simulations and in vivo experiments in yeast, we confirm that abundance-enhancing mutations result in longer-lasting and more stable protein expression. Importantly, these sequence changes also reduce metabolic costs of protein synthesis, elucidating the evolutionary advantage of cost-effective, high-abundance, stable proteomes. Our findings support the role of amino acid sequence as a pivotal determinant of protein abundance and stability, revealing an evolutionary optimization for metabolic efficiency.

evolutionary biology↗

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein co-expression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3.6%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship. HighlightsO_LIAt the level of individual genes, the abundance of transcripts and proteins is weakly correlated within a species ({rho} = 0.165). C_LIO_LIWhile the proteome is not imprinted by population structure, co-expression patterns recapitulate the cellular functional landscape C_LIO_LIWild populations exhibit a higher abundance of respiration-related proteins compared to domesticated populations C_LIO_LILoci that influence protein abundance differ from those that impact transcript levels, likely because of protein turnover C_LI

systems biology↗

Speedy-PASEF: Analytical flow rate chromatography and trapped ion mobility for deep high-throughput proteomics

Increased throughput in proteomic experiments can improve accessibility of proteomic platforms, reduce costs and facilitate new approaches in systems biology and biomedical research. Here we propose Speedy-PASEF, a combination of analytical flow rate chromatography with ion mobility separation of peptide ions, data-independent acquisition and data analysis with the DIA-NN software suite, for conducting fast, high-quality proteomic experiments that require only moderate sample amounts. For instance, using a 500-l/min flow rate and a 3-minute chromatographic gradient, Speedy-PASEF quantified 5,211 proteins from 2 g of a mammalian cell-line standard at high quantitative accuracy and precision. We further used Speedy-PASEF to analyze blood plasma samples from a cohort of COVID-19 inpatients, using a 3-minute chromatographic gradient and alternating column regeneration on a dual pump system, for processing 398 samples per day. Speedy-PASEF delivered a comprehensive view of the COVID-19 plasma proteome, allowing classification of the patients according to disease severity and revealing plasma biomarker candidates. Speedy-PASEF thus facilitates acquisition of high-quality proteomes in large numbers.

biochemistry↗

The yeast RNA methylation complex consists of conserved yet reconfigured components with m6A-dependent and independent roles

N6-methyladenosine (m6A), the most abundant mRNA modification, is deposited in mammals/insects/plants by m6A methyltransferase complexes (MTC) comprising a catalytic subunit and at least five additional proteins. The yeast MTC is critical for meiosis and was known to comprise three proteins, of which two were conserved. We uncover three novel MTC components (Kar4/Ygl036w-Vir1/Dyn2). All MTC subunits, except for Dyn2, are essential for m6A deposition and have corresponding mammalian MTC orthologs. Unlike the mammalian bipartite MTC, the yeast MTC is unipartite, yet multifunctional. The mRNA interacting module, comprising Ime4, Mum2, Vir1, and Kar4, exerts the MTCs m6A-independent function, while Slz1 enables the MTC catalytic function in m6A deposition. Both functions are critical for meiotic progression. Kar4 also has a mechanistically separate role from the MTC during mating. The yeast MTC constituents play distinguishable m6A-dependent, MTC-dependent and MTC-independent functions, highlighting their complexity and paving the path towards dissecting multi-layered MTC functions in mammals.

molecular biology↗

Slice-PASEF: fragmenting all ions for maximum sensitivity in proteomics

Quantitative mass spectrometry (MS)-based proteomics has become a streamlined technology with a wide range of usage. Many emerging applications, such as single-cell proteomics, spatial proteomics of tissue sections and the profiling of low-abundant posttranslational modifications, require the analysis of minimal sample amounts and are thus constrained by the sensitivity of the workflow. Here, we present Slice-PASEF, a mass spectrometry technology that leverages trapped ion mobility separation of ions to attain the theoretical maximum of tandem MS sensitivity. We implement Slice-PASEF using a new module in our DIA-NN software and show that Slice-PASEF uniquely enables precise quantitative proteomics of low sample amounts. We further demonstrate its utility towards a range of applications, including single cell proteomics and degrader drug screens via ubiquitinomics.

biochemistry↗

MSBooster: Improving Peptide Identification Rates using Deep Learning-Based Features

Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFragger. Here, we present a new tool, MSBooster, for rescoring peptide-to-spectrum matches using additional features incorporating deep learning-based predictions of peptide properties, such as LC retention time, ion mobility, and MS/MS spectra. We demonstrate the utility of MSBooster, in tandem with MSFragger and Percolator, in several different workflows, including nonspecific searches (immunopeptidomics), direct identification of peptides from data independent acquisition data, single-cell proteomics, and data generated on an ion mobility separation-enabled timsTOF MS platform. MSBooster is fast, robust, and fully integrated into the widely used FragPipe computational platform.

bioinformatics↗

OxoScan-MS: Oxonium ion scanning mass spectrometry facilitates plasma glycoproteomics in large scale

Protein glycosylation is a complex and heterogeneous post-translational modification. Specifically, the human plasma proteome is rich in glycoproteins, and as protein glycosylation is frequently dysregulated in disease, glycoproteomics is considered an underexplored resource for biomarker discovery. Here, we present OxoScan-MS, a data-independent mass spectrometric acquisition technology and data analysis software that facilitates sensitive, fast, and cost-effective glycoproteome profiling of plasma and serum samples in large cohort studies. OxoScan-MS quantifies glycosylated peptide features by exploiting a scanning quadrupole to assign precursors to oxonium ions, glycopeptide-specific fragments. OxoScan-MS reaches a high level of sensitivity and selectivity in untargeted glycopeptide profiling, such that it can be efficiently used with fast microflow chromatography without a need for experimental enrichment of glycopeptides from neat plasma. We apply OxoScan-MS to profile the plasma glycoproteomic in an inpatient cohort hospitalised due to severe COVID-19, and obtain precise quantities for 1,002 glycopeptide features. We reveal that severe COVID-19 induces differential glycosylation in disease-relevant plasma glycoproteins, including IgA, fibrinogen and alpha-1-antitrypsin. Thus, with OxoScan-MS we present a strategy for quantitatively mapping glycoproteomes that scales to hundreds and thousands of samples, and report glycoproteomic changes in severe COVID-19.

systems biology↗

The Proteomic Landscape of Genome-Wide Genetic Perturbations

Functional genomic strategies help to address the genotype phenotype problem by annotating gene function and regulatory networks. Here, we demonstrate that combining functional genomics with proteomics uncovers general principles of protein expression, and provides new avenues to annotate protein function. We recorded precise proteomes for all non-essential gene knock-outs in Saccharomyces cerevisiae. We find that protein abundance is driven by a complex interplay of i) general biological properties, including translation rate, turnover, and copy number variations, and ii) their genetic, metabolic and physical interactions, including membership in protein complexes. We further show that combining genetic perturbation with proteomics provides complementary dimensions of functional annotation: proteomic profiling, reverse proteomic profiling, profile similarity and protein covariation analysis. Thus, our study generates a resource in which nine million protein quantities are linked to 79% of the yeast coding genome, and shows that functional proteomics reveals principles that govern protein expression. Highlights- Nine million protein quantities recorded in ~4,600 non-essential gene deletions in S. cerevisiae reveal principles of how the proteome responds to genetic perturbation - Genome-scale protein expression is determined by both functional relationships between proteins, as well as common biological responses - Broad protein expression profiles in slow-growing strains can be explained by chromosomal aneuploidies - Protein half-life and ribosome occupancy are predictable from protein abundance changes across knock-outs - Functional proteomics annotates missing gene function in four complementary dimensions

systems biology↗

High-throughput proteomics of nanogram-scale samples with Zeno SWATH DIA

The ability to conduct high-quality proteomic experiments in high throughput has opened new avenues in clinical research, drug discovery, and systems biology. Next to an increase in quantitative precision, recent developments in high-throughput proteomics have also gained proteomic depth, to the extent that earlier gaps between classic and high-throughput experiments have significantly narrowed. Here we introduce and benchmark Zeno SWATH, a data-independent acquisition technique that employs a linear ion trap pulsing (Zeno trap pulsing) in order to increase proteomic depth and dynamic range in proteomic experiments. Combined with the high acquisition speed, these gains in sensitivity are particularly attractive for conducting high-throughput proteomics experiments with high chromatographic flow rates and fast gradients. We demonstrate that when combined with either micro-flow- or analytical-flow-rate chromatography, Zeno SWATH increases protein identification in complex samples 5- to 10-fold when compared to current SWATH acquisition methods on the same instrument. Using 20-min micro-flow chromatography, Zeno SWATH identified > 6,000 proteins from a 62.5 ng load of human cell lysate with more than 5,000 proteins consistently quantified in triplicate injections with a median CV of 6%. Using 5-min analytical-flow-rate chromatography (800 {micro}l/min), Zeno SWATH identified 4,907 proteins from a triplicate injection of 2 {micro}g of a human cell lysate; or more than 3,000 proteins from 250 ng tryptic digest. Zeno SWATH hence facilitates precise proteomic experiments with small sample amounts using a fast and robust high flow-rate chromatographic method, broadening the application space that requires precise proteomic experiments on a large scale.

biochemistry↗

The natural diversity of the yeast proteome reveals chromosome-wide dosage compensation in aneuploids

Aneuploidy, an imbalance in chromosome copy numbers, causes genetic disorders, and drives cancer progression, drug tolerance, and antimicrobial resistance. While aneuploidy can confer stress resistance, it is not well understood how cells overcome the fitness burden caused by aberrant chromosomal copy numbers. Studies using both systematically generated 1-5 and natural aneuploid yeasts 6-8 triggered an intense debate about the role of dosage compensation, concluding that aneuploidy is transmitted to the transcriptome and proteome without significant buffering at the chromosome-wide level, and is, at least in lab strains, associated with significant fitness costs. Conversely, systematic sequencing and phenotyping of large collections of natural isolates revealed that aneuploidy is frequent and has few - if any - fitness costs in nature 9. To address these discrepant findings at the proteomic level, we developed a platform that yields highly precise proteomic measurements across large numbers of genetically diverse samples, and applied it to natural isolates collected as part of the 1011 genomes project 9. For 613 of the isolates, we were able to match the proteomes to their corresponding transcriptomes and genomes, subsequently quantifying the effect of aneuploidy on gene expression by comparing 95 aneuploid with 518 euploid strains. We find, as in previous studies, that aneuploid gene dosage is not buffered chromosome-wide at the transcriptome level. Importantly, in the proteome, we detect an attenuation of aneuploidy by about 25% below the aneuploid gene dosage in natural yeast isolates. Furthermore, this chromosome-wide dosage compensation is associated with the ubiquitin-proteasome system (UPS), which is expressed at higher levels and has increased activity across natural aneuploid strains. Thus, through systematic exploration of the species-wide diversity of the yeast proteome, we shed light on a long-standing debate about the biology of aneuploids, revealing that aneuploidy tolerance is mediated through chromosome-wide dosage compensation at the proteome level.

systems biology↗

Occurrence and quantities of DNA modifications across the tree of life

Enzymatic DNA modifications like methylcytosine (5mdC), methyladenine (N6mdA), or hydroxymethylcytosine (5hmdC) are key for chromatin function, gene expression regulation, and antiviral defense, but they remain understudied in non-model organisms. We established a mass spectrometric method for the sensitive and accurate quantification of enzymatic DNA modifications, and analyzed 85 bacterial genomes, 19 plant samples, 41 tissues from 12 animal species, 6 yeast species, and two archaeal species. We report no or only very low concentrations of DNA modifications in yeast and insects, but find DNA modifications universal to both bacteria and higher eukaryotes. Specifically for prokaryotes, our dataset indicates that evolutionary relationships and host-pathogen interactions, but not the ecological niche in general, select for a similar degree of DNA modification. In higher eukaryotes, largest concentration differences between tissues are detected for 5hmdC. Our dataset further reveals unique biological cases that warrant attention in the study of DNA modifications. For instance, while our data shows that most species contain just one dominating DNA modification, we detect all dominianting DNA modifications (5mdC, N6mdA, and 5hmdC) to exist in parallel in Raphanus sativus. Other plant species, like onion, sunflower, or the grass big bluestem, can have more than 35% of cytosines methylated. Finally, 5hmdC, so far mostly studied in the vertebrate central nervous system, was identified to reach a concentration of up to 8% of all cytosines in the Oman garra brain, and was also detected in several plants, like Lepidium sativum. The present study underscores the exploitation of biological diversity for studying DNA modifications.

genomics↗

Inorganic sulfur fixation via a new homocysteine synthase allows yeast cells to cooperatively compensate for methionine auxotrophy

The assimilation, incorporation, and metabolism of sulfur is a fundamental process across all domains of life, yet how cells deal with varying sulfur availability is not well understood. We studied an unresolved conundrum of sulfur fixation in yeast, in which an organosulfur-auxotrophy caused by deletion of homocysteine synthase Met17p is overcome when cells are inoculated at high cell density. We discovered that an uncharacterized gene YLL058Wp, herein named Hydrogen sulfide utilizing-1 (HSU1), acts as a homocysteine synthase and allows the cells to substitute for Met17p by re-assimilating hydrosulfide ions leaked from met17{Delta} cells into O-acetyl-homoserine and forming homocysteine. Our results show that cells can cooperate to achieve sulfur fixation, indicating that the collective properties of microbial communities facilitate their basic metabolic capacity. SummarySulfur limitation activates a dormant hydrogen sulfide fixation route via a novel homocysteine synthase Hsu1p (YLL058Wp).

molecular biology↗

Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan

Metabolism is fundamentally intertwined with the ageing process. We here report that a key determinant of cellular lifespan is not only nutrient supply and intracellular metabolism, but also metabolite exchange interactions that occur between cells. Studying chronological ageing in yeast, we observed that metabolites exported by young, exponentially growing, cells are re- imported during the stationary phase when cells age chronologically, indicating the existence of cross-generational metabolic interactions. We then used self-establishing metabolically cooperating communities (SeMeCos) to boost cell-cell metabolic interactions and observed a significant lifespan extension. A search for the underlying mechanisms, coupling SeMeCos, metabolic profiling, proteomics and genome-scale metabolic modelling, attributed a specific role to methionine consumer cells. These cells were enriched over time, adopted glycolytic metabolism and increased export of protective metabolites. Glycerol, in particular, accumulated in the communal metabolic environment and extended the lifespan of all cells in the community in a paracrine fashion. Our results hence establish metabolite exchange interactions as a determinant of the ageing process and show that metabolically cooperating cells shape their metabolic environment to achieve lifespan extension.

biochemistry↗

m6A reader Pho92 is recruited co-transcriptionally and couples translation efficacy to mRNA decay to promote meiotic fitness in yeast

N6-methyladenosine (m6A) RNA modification impacts mRNA fate primarily via reader proteins, which dictate processes in development, stress, and disease. Yet little is known about m6A function in Saccharomyces cerevisiae, which occurs solely during early meiosis. Here we perform a multifaceted analysis of the m6A reader protein Pho92/Mrb1. Cross-linking immunoprecipitation analysis reveals that Pho92 associates with the 3end of meiotic mRNAs in both an m6A-dependent and independent manner. Within cells, Pho92 transitions from the nucleus to the cytoplasm, and associates with translating ribosomes. In the nucleus Pho92 associates with target loci through its interaction with transcriptional elongator Paf1C. Functionally, we show that Pho92 promotes and links protein synthesis to mRNA decay. As such, the Pho92-mediated m6A-mRNA decay is contingent on active translation and the CCR4-NOT complex. We propose that the m6A reader Pho92 is loaded co-transcriptionally to facilitate protein synthesis and subsequent decay of m6A modified transcripts, and thereby promotes meiosis.

biochemistry↗

Increasing the throughput of sensitive proteomics by plexDIA

Current mass-spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, plexDIA, for simultaneously multiplexing the analysis of both peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using 3-plex nonisobaric mass tags, plexDIA enables quantifying 3-fold more protein ratios among nanogram-level samples. Using 1 hour active gradients and first-generation Q Exactive, plexDIA quantified about 8,000 proteins in each sample of labeled 3-plex sets. plexDIA also increases data completeness, reducing missing data over 2-fold across samples. We applied plexDIA to quantify proteome dynamics during the cell division cycle in cells isolated based on their DNA content; plexDIA detected many classical cell cycle proteins and discovered new ones. When applied to single human cells, plexDIA quantified about 1,000 proteins per cell and achieved 98 % data completeness within a plexDIA set while using about 5 min of active chromatography per cell. These results establish a general framework for increasing the throughput of sensitive and quantitative protein analysis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/467007v2_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@144bba6org.highwire.dtl.DTLVardef@17bbf20org.highwire.dtl.DTLVardef@140f497org.highwire.dtl.DTLVardef@179faa9_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗