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 pka1Δ cells. Supplementation of aspartate, on the other hand, shortens the lifespan of pka1Δ 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

Co-regulation map of the human proteome enables identification of protein functions

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: All mass spectrometry raw files generated in-house have been deposited in the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository36 with the dataset identifier PXD008888. The co-regulation map is hosted on our website at www.proteomeHD.net, and pair-wise co-regulation scores are available through STRING (https://string-db.org). A network of the top 0.5% co-regulated protein pairs can be explored interactively on NDEx (https://doi.org/10.18119/N9N30Q).Code availability: Data analysis was performed in R 3.5.1. R scripts and input files required to reproduce the results of this manuscript are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/ProteomeHD. R scripts related specifically to the benchmarking of the treeClust algorithm using synthetic data are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/treeClust-benchmarking. The R package data.table was used for fast data processing. Figures were prepared using ggplot2, gridExtra, cowplot and viridis.Note that the title of the AAM is different from the published versionThe annotation of protein function is a longstanding challenge of cell biology that suffers from the sheer magnitude of the task. Here we present ProteomeHD, which documents the response of 10,323 human proteins to 294 biological perturbations, measured by isotope-labelling mass spectrometry. We reveal functional associations between human proteins using the treeClust machine learning algorithm, which we show to improve protein co-regulation analysis due to robust selectivity for close linear relationships. Our co-regulation map identifies a functional context for many uncharacterized proteins, including microproteins that are difficult to study with traditional methods. Co-regulation also captures relationships between proteins which do not physically interact or co-localize. For example, co-regulation of the peroxisomal membrane protein PEX11β with mitochondrial respiration factors led us to discover a novel organelle interface between peroxisomes and mitochondria in mammalian cells. The co-regulation map can be explored at www.proteomeHD.net .Biotechnology & Biological Sciences Research Council (BBSRC)European Commissio

A proteomic survival predictor for COVID-19 patients in intensive care

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care

Fighting post-COVID and ME/CFS - development of curative therapies

The sequela of COVID-19 include a broad spectrum of symptoms that fall under the umbrella term post-COVID-19 condition or syndrome (PCS). Immune dysregulation, autoimmunity, endothelial dysfunction, viral persistence, and viral reactivation have been identified as potential mechanisms. However, there is heterogeneity in expression of biomarkers, and it is unknown yet whether these distinguish different clinical subgroups of PCS. There is an overlap of symptoms and pathomechanisms of PCS with postinfectious myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). No curative therapies are available for ME/CFS or PCS. The mechanisms identified so far provide targets for therapeutic interventions. To accelerate the development of therapies, we propose evaluating drugs targeting different mechanisms in clinical trial networks using harmonized diagnostic and outcome criteria and subgrouping patients based on a thorough clinical profiling including a comprehensive diagnostic and biomarker phenotyping

ISG15 blocks cardiac glycolysis and ensures sufficient mitochondrial energy production during Coxsackievirus B3 infection

AIMS: Virus infection triggers inflammation and, may impose nutrient shortage to the heart. Supported by type I interferon (IFN) signaling, cardiomyocytes counteract infection by various effector processes, with the IFN-stimulated gene of 15 kDa (ISG15) system being intensively regulated and protein modification with ISG15 protecting mice Coxsackievirus B3 (CVB3) infection. The underlying molecular aspects how the ISG15 system affects the functional properties of respective protein substrates in the heart are unknown. METHODS AND RESULTS: Based on the protective properties due to protein ISGylation, we set out a study investigating CVB3-infected mice in depth and found cardiac atrophy with lower cardiac output in ISG15-/- mice. By mass spectrometry, we identified the protein targets of the ISG15 conjugation machinery in heart tissue and explored how ISGylation affects their function. The cardiac ISGylome showed a strong enrichment of ISGylation substrates within glycolytic metabolic processes. Two control enzymes of the glycolytic pathway, hexokinase 2 (HK2) and phosphofructokinase muscle form (PFK1), were identified as bona fide ISGylation targets during infection. In an integrative approach complemented with enzymatic functional testing and structural modeling, we demonstrate that protein ISGylation obstructs the activity of HK2 and PFK1. Seahorse-based investigation of glycolysis in cardiomyocytes revealed that, by conjugating proteins, the ISG15 system prevents the infection-/IFN-induced upregulation of glycolysis. We complemented our analysis with proteomics-based advanced computational modeling of cardiac energy metabolism. Our calculations revealed an ISG15-dependent preservation of the metabolic capacity in cardiac tissue during CVB3 infection. Functional profiling of mitochondrial respiration in cardiomyocytes and mouse heart tissue by Seahorse technology showed an enhanced oxidative activity in cells with a competent ISG15 system. CONCLUSIONS: Our study demonstrates that ISG15 controls critical nodes in cardiac metabolism. ISG15 reduces the glucose demand, supports higher ATP production capacity in the heart, despite nutrient shortage in infection, and counteracts cardiac atrophy and dysfunction

Natural proteome diversity links aneuploidy tolerance to protein turnover

Accessing the natural genetic diversity of species unveils hidden genetic traits, clarifies gene functions and allows the generalizability of laboratory findings to be assessed. One notable discovery made in natural isolates of Saccharomyces cerevisiae is that aneuploidy—an imbalance in chromosome copy numbers—is frequent (around 20%), which seems to contradict the substantial fitness costs and transient nature of aneuploidy when it is engineered in the laboratory. Here we generate a proteomic resource and merge it with genomic and transcriptomic data for 796 euploid and aneuploid natural isolates. We find that natural and lab-generated aneuploids differ specifically at the proteome. In lab-generated aneuploids, some proteins—especially subunits of protein complexes—show reduced expression, but the overall protein levels correspond to the aneuploid gene dosage. By contrast, in natural isolates, more than 70% of proteins encoded on aneuploid chromosomes are dosage compensated, and average protein levels are shifted towards the euploid state chromosome-wide. At the molecular level, we detect an induction of structural components of the proteasome, increased levels of ubiquitination, and reveal an interdependency of protein turnover rates and attenuation. Our study thus highlights the role of protein turnover in mediating aneuploidy tolerance, and shows the utility of exploiting the natural diversity of species to attain generalizable molecular insights into complex biological processes