Protein degradation and dynamic tRNA thiolation fine-tune translation at elevated temperatures

Maintenance of protein quality control has implications in various processes such as neurodegeneration and ageing. To investigate how environmental insults affect this process, we analysed the proteome of yeast continuously exposed to mild heat stress. In agreement with previous transcriptomics studies, amongst the most marked changes, we found up-regulation of cytoprotective factors; a shift from oxidative phosphorylation to fermentation; and down-regulation of translation. Importantly, we also identified a novel, post-translationally controlled, component of the heat shock response. The abundance of Ncs2p and Ncs6p, two members of the URM1 pathway responsible for the thiolation of wobble uridines in cytoplasmic tRNAs tKUUU, tQUUG and tEUUC, is down-regulated in a proteasomal dependent fashion. Using random forests we show that this results in differential translation of transcripts with a biased content for the corresponding codons. We propose that the role of this pathway in promoting catabolic and inhibiting anabolic processes, affords cells with additional time and resources needed to attain proper protein folding under periods of stres

Protein degradation and dynamic tRNA thiolation fine-tune translation at elevated temperatures

Maintenance of protein quality control has implications in various processes such as neurodegeneration and ageing. To investigate how environmental insults affect this process, we analysed the proteome of yeast continuously exposed to mild heat stress. In agreement with previous transcriptomics studies, amongst the most marked changes, we found up-regulation of cytoprotective factors; a shift from oxidative phosphorylation to fermentation; and down-regulation of translation. Importantly, we also identified a novel, post-translationally controlled, component of the heat shock response. The abundance of Ncs2p and Ncs6p, two members of the URM1 pathway responsible for the thiolation of wobble uridines in cytoplasmic tRNAs tKUUU, tQUUG and tEUUC, is down-regulated in a proteasomal dependent fashion. Using random forests we show that this results in differential translation of transcripts with a biased content for the corresponding codons. We propose that the role of this pathway in promoting catabolic and inhibiting anabolic processes, affords cells with additional time and resources needed to attain proper protein folding under periods of stress.ISSN:1362-4962ISSN:0301-561

PRAMEL7 and CUL2 decrease NuRD stability to establish ground-state pluripotency

Pluripotency is established in E4.5 preimplantation epiblast. Embryonic stem cells (ESCs) represent the immortalization of pluripotency, however, their gene expression signature only partially resembles that of developmental ground-state. Induced PRAMEL7 expression, a protein highly expressed in the ICM but lowly expressed in ESCs, reprograms developmentally advanced ESC+serum into ground-state pluripotency by inducing a gene expression signature close to developmental ground-state. However, how PRAMEL7 reprograms gene expression remains elusive. Here we show that PRAMEL7 associates with Cullin2 (CUL2) and this interaction is required to establish ground-state gene expression. PRAMEL7 recruits CUL2 to chromatin and targets regulators of repressive chromatin, including the NuRD complex, for proteasomal degradation. PRAMEL7 antagonizes NuRD-mediated repression of genes implicated in pluripotency by decreasing NuRD stability and promoter association in a CUL2-dependent manner. Our data link proteasome degradation pathways to ground-state gene expression, offering insights to generate in vitro models to reproduce the in vivo ground-state pluripotency.ISSN:1469-221XISSN:1469-317

Mitochondrial NAD+ Controls Nuclear ARTD1-Induced ADP-Ribosylation

In addition to its role as an electron transporter, mitochondrial nicotinamide adenine dinucleotide (NAD+) is an important co-factor for enzymatic reactions, including ADP-ribosylation. Although mitochondria harbor the most intra-cellular NAD+, mitochondrial ADP-ribosylation remains poorly understood. Here we provide evidence for mitochondrial ADP-ribosylation, which was identified using various methodologies including immunofluorescence, western blot, and mass spectrometry. We show that mitochondrial ADP-ribosylation reversibly increases in response to respiratory chain inhibition. Conversely, H2O2-induced oxidative stress reciprocally induces nuclear and reduces mitochondrial ADP-ribosylation. Elevated mitochondrial ADP-ribosylation, in turn, dampens H2O2-triggered nuclear ADP-ribosylation and increases MMS-induced ARTD1 chromatin retention. Interestingly, co-treatment of cells with the mitochondrial uncoupler FCCP decreases PARP inhibitor efficacy. Together, our results suggest that mitochondrial ADP-ribosylation is a dynamic cellular process that impacts nuclear ADP-ribosylation and provide evidence for a NAD+-mediated mitochondrial-nuclear crosstalk.ISSN:1097-2765ISSN:1097-416

Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial

Advancements in mass spectrometry-based proteomics have enabled experiments encompassing hundreds of samples. While these large sample sets deliver much-needed statistical power, handling them introduces technical variability known as batch effects. Here, we present a step-by-step protocol for the assessment, normalization, and batch correction of proteomic data. We review established methodologies from related fields and describe solutions specific to proteomic challenges, such as ion intensity drift and missing values in quantitative feature matrices. Finally, we compile a set of techniques that enable control of batch effect adjustment quality. We provide an R package, "proBatch", containing functions required for each step of the protocol. We demonstrate the utility of this methodology on five proteomic datasets each encompassing hundreds of samples and consisting of multiple experimental designs. In conclusion, we provide guidelines and tools to make the extraction of true biological signal from large proteomic studies more robust and transparent, ultimately facilitating reliable and reproducible research in clinical proteomics and systems biology.ISSN:1744-429

Proteogenetic drug response profiling elucidates targetable vulnerabilities of myelofibrosis

Myelofibrosis is a hematopoietic stem cell disorder belonging to the myeloproliferative neoplasms. Myelofibrosis patients frequently carry driver mutations in either JAK2 or Calreticulin (CALR) and have limited therapeutic options. Here, we integrate ex vivo drug response and proteotype analyses across myelofibrosis patient cohorts to discover targetable vulnerabilities and associated therapeutic strategies. Drug sensitivities of mutated and progenitor cells were measured in patient blood using high-content imaging and single-cell deep learning-based analyses. Integration with matched molecular profiling revealed three targetable vulnerabilities. First, CALR mutations drive BET and HDAC inhibitor sensitivity, particularly in the absence of high Ras pathway protein levels. Second, an MCM complex-high proliferative signature corresponds to advanced disease and sensitivity to drugs targeting pro-survival signaling and DNA replication. Third, homozygous CALR mutations result in high endoplasmic reticulum (ER) stress, responding to ER stressors and unfolded protein response inhibition. Overall, our integrated analyses provide a molecularly motivated roadmap for individualized myelofibrosis patient treatment.ISSN:2041-172

Integrated multi-omics reveals anaplerotic rewiring in methylmalonyl-CoA mutase deficiency

Methylmalonic aciduria (MMA) is an inborn error of metabolism with multiple monogenic causes and a poorly understood pathogenesis, leading to the absence of effective causal treatments. Here we employ multi-layered omics profiling combined with biochemical and clinical features of individuals with MMA to reveal a molecular diagnosis for 177 out of 210 (84%) cases, the majority (148) of whom display pathogenic variants in methylmalonyl-CoA mutase (MMUT). Stratification of these data layers by disease severity shows dysregulation of the tricarboxylic acid cycle and its replenishment (anaplerosis) by glutamine. The relevance of these disturbances is evidenced by multi-organ metabolomics of a hemizygous Mmut mouse model as well as through identification of physical interactions between MMUT and glutamine anaplerotic enzymes. Using stable-isotope tracing, we find that treatment with dimethyl-oxoglutarate restores deficient tricarboxylic acid cycling. Our work highlights glutamine anaplerosis as a potential therapeutic intervention point in MMA.ISSN:2522-581

Integrated multi-omics reveals anaplerotic insufficiency in methylmalonyl-CoA mutase deficiency

Multi-layered omics approaches can help define relationships between genetic factors, biochemical processes and phenotypes thus extending research of inherited diseases beyond identifying their monogenic cause 1. We implemented a multi-layered omics approach for the inherited metabolic disorder methylmalonic aciduria (MMA). We performed whole genome sequencing, transcriptomic sequencing, and mass spectrometry-based proteotyping from matched primary fibroblast samples of 230 individuals (210 affected, 20 controls) and related the molecular data to 105 phenotypic features. Integrative analysis identified a molecular diagnosis for 84% (177/210) of affected individuals, the majority (148) of whom had pathogenic variants in methylmalonyl-CoA mutase (MMUT). Untargeted analysis of all three omics layers revealed dysregulation of the TCA cycle and surrounding metabolic pathways, a finding that was further corroborated by multi-organ metabolomics of a hemizygous Mmut mouse model. Integration of phenotypic disease severity indicated downregulation of oxoglutarate dehydrogenase and upregulation of glutamate dehydrogenase, two proteins involved in glutamine anaplerosis of the TCA cycle. The relevance of disturbances in this pathway was supported by metabolomics and isotope tracing studies which showed decreased glutamine-derived anaplerosis in MMA. We further identified MMUT to physically interact with both, oxoglutarate dehydrogenase complex components and glutamate dehydrogenase providing evidence for a multi-protein metabolon that orchestrates TCA cycle anaplerosis. This study emphasizes the utility of a multi-modal omics approach to investigate metabolic diseases and highlights glutamine anaplerosis as a potential therapeutic intervention point in MMA.Take home message Combination of integrative multi-omics technologies with clinical and biochemical features leads to an increased diagnostic rate compared to genome sequencing alone and identifies anaplerotic rewiring as a targetable feature of the rare inborn error of metabolism methylmalonic aciduria.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis project was funded by the ETH domain strategic focus area Personalized Health and Related Technology (PHRT; https://www.sfa-phrt.ch).Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The Ethics Committee of the Canton of Zurich, Switzerland gave ethical approval for this work.I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced in the present study are available upon reasonable request to the authors

SCIM: Universal Single-Cell Matching with Unpaired Feature Sets

Motivation Recent technological advances have led to an increase in the production and availability of single-cell data. The ability to integrate a set of multi-technology measurements would allow the identification of biologically or clinically meaningful observations through the unification of the perspectives afforded by each technology. In most cases, however, profiling technologies consume the used cells and thus pairwise correspondences between datasets are lost. Due to the sheer size single-cell datasets can acquire, scalable algorithms that are able to universally match single-cell measurements carried out in one cell to its corresponding sibling in another technology are needed. Results We propose Single-Cell data Integration via Matching (SCIM), a scalable approach to recover such correspondences in two or more technologies. SCIM assumes that cells share a common (low-dimensional) underlying structure and that the underlying cell distribution is approximately constant across technologies. It constructs a technology-invariant latent space using an auto-encoder framework with an adversarial objective. Multi-modal datasets are integrated by pairing cells across technologies using a bipartite matching scheme that operates on the low-dimensional latent representations. We evaluate SCIM on a simulated cellular branching process and show that the cell-to-cell matches derived by SCIM reflect the same pseudotime on the simulated dataset. Moreover, we apply our method to two real-world scenarios, a melanoma tumor sample and a human bone marrow sample, where we pair cells from a scRNA dataset to their sibling cells in a CyTOF dataset achieving 93% and 84% cell-matching accuracy for each one of the samples respectively. Availability https://github.com/ratschlab/sci