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.

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.

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.

PCfun: a hybrid computational framework for systematic characterization of protein complex function.

In molecular biology, it is a general assumption that the ensemble of expressed molecules, their activities and interactions determine biological function, cellular states and phenotypes. Stable protein complexes-or macromolecular machines-are, in turn, the key functional entities mediating and modulating most biological processes. Although identifying protein complexes and their subunit composition can now be done inexpensively and at scale, determining their function remains challenging and labor intensive. This study describes Protein Complex Function predictor (PCfun), the first computational framework for the systematic annotation of protein complex functions using Gene Ontology (GO) terms. PCfun is built upon a word embedding using natural language processing techniques based on 1 million open access PubMed Central articles. Specifically, PCfun leverages two approaches for accurately identifying protein complex function, including: (i) an unsupervised approach that obtains the nearest neighbor (NN) GO term word vectors for a protein complex query vector and (ii) a supervised approach using Random Forest (RF) models trained specifically for recovering the GO terms of protein complex queries described in the CORUM protein complex database. PCfun consolidates both approaches by performing a hypergeometric statistical test to enrich the top NN GO terms within the child terms of the GO terms predicted by the RF models. The documentation and implementation of the PCfun package are available at https://github.com/sharmavaruns/PCfun. We anticipate that PCfun will serve as a useful tool and novel paradigm for the large-scale characterization of protein complex function.

Reproducible Determination of High-Density Lipoprotein Proteotypes.

High-density lipoprotein (HDL) is a heterogeneous mixture of blood-circulating multimolecular particles containing many different proteins, lipids, and RNAs. Recent advancements in mass spectrometry-based proteotype analysis show promise for the analysis of proteoforms across large patient cohorts. In order to create the required spectral libraries enabling these data-independent acquisition (DIA) strategies, HDL was isolated from the plasma of more than 300 patients with a multiplicity of physiological HDL states. HDL proteome spectral libraries consisting of 296 protein groups and more than 786 peptidoforms were established, and the performance of the DIA strategy was benchmarked for the detection of HDL proteotype differences between healthy individuals and a cohort of patients suffering from diabetes mellitus type 2 and/or coronary heart disease. Bioinformatic interrogation of the data using the generated spectral libraries showed that the DIA approach enabled robust HDL proteotype determination. HDL peptidoform analysis enabled by using spectral libraries allowed for the identification of post-translational modifications, such as in APOA1, which could affect HDL functionality. From a technical point of view, data analysis further shows that protein and peptide quantities are currently more discriminative between different HDL proteotypes than peptidoforms without further enrichment. Together, DIA-based HDL proteotyping enables the robust digitization of HDL proteotypes as a basis for the analysis of larger clinical cohorts.

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.

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.

Author Correction: Surfaceome dynamics reveal proteostasis-independent reorganization of neuronal surface proteins during development and synaptic plasticity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Surfaceome dynamics reveal proteostasis-independent reorganization of neuronal surface proteins during development and synaptic plasticity.

Neurons are highly compartmentalized cells with tightly controlled subcellular protein organization. While brain transcriptome, connectome and global proteome maps are being generated, system-wide analysis of temporal protein dynamics at the subcellular level are currently lacking. Here, we perform a temporally-resolved surfaceome analysis of primary neuron cultures and reveal dynamic surface protein clusters that reflect the functional requirements during distinct stages of neuronal development. Direct comparison of surface and total protein pools during development and homeostatic synaptic scaling demonstrates system-wide proteostasis-independent remodeling of the neuronal surface, illustrating widespread regulation on the level of surface trafficking. Finally, quantitative analysis of the neuronal surface during chemical long-term potentiation (cLTP) reveals fast externalization of diverse classes of surface proteins beyond the AMPA receptor, providing avenues to investigate the requirement of exocytosis for LTP. Our resource (neurosurfaceome.ethz.ch) highlights the importance of subcellular resolution for systems-level understanding of cellular processes.

The SysteMHC Atlas: a Computational Pipeline, a Website, and a Data Repository for Immunopeptidomic Analyses.

Mass spectrometry has emerged as the method of choice for the exploration of the immunopeptidome. Insights from the immunopeptidome promise novel cancer therapeutic approaches and a better understanding of the basic mechanisms of our immune system. To meet the computational demands from the steady gain in popularity and reach of mass spectrometry-based immunopeptidomics analysis, we created the SysteMHC Atlas project, a first-of-its-kind computational pipeline and resource repository dedicated to standardizing data analysis and public dissemination of immunopeptidomic datasets.

Review of Batch Effects Prevention, Diagnostics, and Correction Approaches.

Systematic technical variation in high-throughput studies consisting of the serial measurement of large sample cohorts is known as batch effects. Batch effects reduce the sensitivity of biological signal extraction and can cause significant artifacts. The systematic bias in the data caused by batch effects is more common in studies in which logistical considerations restrict the number of samples that can be prepared or profiled in a single experiment, thus necessitating the arrangement of subsets of study samples in batches. To mitigate the negative impact of batch effects, statistical approaches for batch correction are used at the stage of experimental design and data processing. Whereas in genomics batch effects and possible remedies have been extensively discussed, they are a relatively new challenge in proteomics because methods with sufficient throughput to systematically measure through large sample cohorts have only recently become available. Here we provide general recommendations to mitigate batch effects: we discuss the design of large-scale proteomic studies, review the most commonly used tools for batch effect correction and overview their application in proteomics.

Classification of mouse B cell types using surfaceome proteotype maps.

System-wide quantification of the cell surface proteotype and identification of extracellular glycosylation sites is challenging when samples are limited. Here, we miniaturize and automate the previously described Cell Surface Capture (CSC) technology, increasing sensitivity, reproducibility and throughput. We use this technology, which we call autoCSC, to create population-specific surfaceome maps of developing mouse B cells and use targeted flow cytometry to uncover developmental cell subpopulations.

A tissue-based draft map of the murine MHC class I immunopeptidome.

The large array of peptides presented to CD8+ T cells by major histocompatibility complex (MHC) class I molecules is referred to as the MHC class I immunopeptidome. Although the MHC class I immunopeptidome is ubiquitous in mammals and represents a critical component of the immune system, very little is known, in any species, about its composition across most tissues and organs in vivo. We applied mass spectrometry (MS) technologies to draft the first tissue-based atlas of the murine MHC class I immunopeptidome in health. Peptides were extracted from 19 normal tissues from C57BL/6 mice and prepared for MS injections, resulting in a total number of 28,448 high-confidence H2Db/Kb-associated peptides identified and annotated in the atlas. This atlas provides initial qualitative data to explore the tissue-specificity of the immunopeptidome and serves as a guide to identify potential tumor-associated antigens from various cancer models. Our data were shared via PRIDE (PXD008733), SysteMHC Atlas (SYSMHC00018) and SWATH Atlas. We anticipate that this unique dataset will be expanded in the future and will find wide applications in basic and translational immunology.

Methodology for Urine Peptidome Analysis Based on Nano-HPLC Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry.

Urine is a sample of choice for noninvasive biomarkers search because it is easily available in large amounts and its molecular composition provides information on processes in the organism. The high potential of urine peptidomics has been demonstrated for clinical purpose. Several mass spectrometry based approaches have been successfully applied for urine peptidome analysis and potential biomarkers search. Summarizing literature data and our own experience we developed a protocol for comprehensive urine peptidome analysis. The technology includes several stages and consists of urine sample preparation by size exclusion chromatography and identification of featured peptides by nano-HPLC coupled to Fourier transform ion cyclotron resonance mass spectrometry, semiquantitative and statistical data analysis.

The SysteMHC Atlas project.

Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts.

Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses.

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the main method for high-throughput identification and quantification of peptides and inferred proteins. Within this field, data-independent acquisition (DIA) combined with peptide-centric scoring, as exemplified by the technique SWATH-MS, has emerged as a scalable method to achieve deep and consistent proteome coverage across large-scale data sets. We demonstrate that statistical concepts developed for discovery proteomics based on spectrum-centric scoring can be adapted to large-scale DIA experiments that have been analyzed with peptide-centric scoring strategies, and we provide guidance on their application. We show that optimal tradeoffs between sensitivity and specificity require careful considerations of the relationship between proteins in the samples and proteins represented in the spectral library. We propose the application of a global analyte constraint to prevent the accumulation of false positives across large-scale data sets. Furthermore, to increase the quality and reproducibility of published proteomic results, well-established confidence criteria should be reported for the detected peptide queries, peptides and inferred proteins.

In Vivo and in Vitro Proteome Analysis of Human Immunodeficiency Virus (HIV)-1-infected, Human CD4+ T Cells.

Host-directed therapies against HIV-1 are thought to be critical for long term containment of the HIV-1 pandemic but remain elusive. Because HIV-1 infects and manipulates important effectors of both the innate and adaptive immune system, identifying modulations of the host cell systems in humans during HIV-1 infection may be crucial for the development of immune based therapies. Here, we quantified the changes of the proteome in human CD4+ T cells upon HIV-1 infection, both in vitro and in vivo A SWATH-MS approach was used to measure the proteome of human primary CD4+ T cells infected with HIV-1 in vitro as well as CD4+ T cells from HIV-1-infected patients with paired samples on and off antiretroviral treatment. In the in vitro experiment, the proteome of CD4+ T cells was quantified over a time course following HIV-1 infection. 1,725 host cell proteins and 4 HIV-1 proteins were quantified, with 145 proteins changing significantly during the time course. Changes in the proteome peaked 24 h after infection, concomitantly with significant HIV-1 protein production. In the in vivo branch of the study, CD4+ T cells from viremic patients and those with no detectable viral load after treatment were sorted, and the proteomes were quantified. We consistently detected 895 proteins, 172 of which were considered to be significantly different between the viremic patients and patients undergoing successful treatment. The proteome of the in vitro-infected CD4+ T cells was modulated on multiple functional levels, including TLR-4 signaling and the type 1 interferon signaling pathway. Perturbations in the type 1 interferon signaling pathway were recapitulated in CD4+ T cells from patients. The study shows that proteome maps generated by SWATH-MS indicate a range of functionally significant changes in the proteome of HIV-infected human CD4+ T cells. Exploring these perturbations in more detail may help identify new targets for immune based interventions.

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 tK(UUU), tQ(UUG) and tE(UUC), 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.

VAPB/ALS8 interacts with FFAT-like proteins including the p97 cofactor FAF1 and the ASNA1 ATPase.

BACKGROUND: FAF1 is a ubiquitin-binding adaptor for the p97 ATPase and belongs to the UBA-UBX family of p97 cofactors. p97 converts the energy derived from ATP hydrolysis into conformational changes of the p97 hexamer, which allows the dissociation of its targets from cellular structures or from larger protein complexes to facilitate their ubiquitin-dependent degradation. VAPB and the related protein VAPA form homo- and heterodimers that are anchored in the endoplasmic reticulum membrane and can interact with protein partners carrying a FFAT motif. Mutations in either VAPB or p97 can cause amyotrophic lateral sclerosis, a neurodegenerative disorder that affects upper and lower motor neurons. RESULTS: We show that FAF1 contains a non-canonical FFAT motif that allows it to interact directly with the MSP domain of VAPB and, thereby, to mediate VAPB interaction with p97. This finding establishes a link between two proteins that can cause amyotrophic lateral sclerosis when mutated, VAPB/ALS8 and p97/ALS14. Subsequently, we identified a similar FFAT-like motif in the ASNA1 subunit of the transmembrane-domain recognition complex (TRC), which in turn mediates ASNA1 interaction with the MSP domain of VAPB. Proteasome inhibition leads to the accumulation of ubiquitinated species in VAPB immunoprecipitates and this correlates with an increase in FAF1 and p97 binding. We found that VAPB interaction with ubiquitinated proteins is strongly reduced in cells treated with FAF1 siRNA. Our efforts to determine the identity of the ubiquitinated targets common to VAPB and FAF1 led to the identification of RPN2, a subunit of an oligosaccharyl-transferase located at the endoplasmic reticulum, which may be regulated by ubiquitin-mediated degradation. CONCLUSIONS: The FFAT-like motifs we identified in FAF1 and ASNA1 demonstrate that sequences containing a single phenylalanine residue with the consensus (D/E)(D/E)FEDAx(D/E) are also proficient to mediate interaction with VAPB. Our findings indicate that the repertoire of VAPB interactors is more diverse than previously anticipated and link VAPB to the function of ATPase complexes such as p97/FAF1 and ASNA1/TRC.

Phosphorylation of Parkin at Serine65 is essential for activation: elaboration of a Miro1 substrate-based assay of Parkin E3 ligase activity.

Mutations in PINK1 and Parkin are associated with early-onset Parkinson's disease. We recently discovered that PINK1 phosphorylates Parkin at serine65 (Ser(65)) within its Ubl domain, leading to its activation in a substrate-free activity assay. We now demonstrate the critical requirement of Ser(65) phosphorylation for substrate ubiquitylation through elaboration of a novel in vitro E3 ligase activity assay using full-length untagged Parkin and its putative substrate, the mitochondrial GTPase Miro1. We observe that Parkin efficiently ubiquitylates Miro1 at highly conserved lysine residues, 153, 230, 235, 330 and 572, upon phosphorylation by PINK1. We have further established an E2-ubiquitin discharge assay to assess Parkin activity and observe robust discharge of ubiquitin-loaded UbcH7 E2 ligase upon phosphorylation of Parkin at Ser(65) by wild-type, but not kinase-inactive PINK1 or a Parkin Ser65Ala mutant, suggesting a possible mechanism of how Ser(65) phosphorylation may activate Parkin E3 ligase activity. For the first time, to the best of our knowledge, we report the effect of Parkin disease-associated mutations in substrate-based assays using full-length untagged recombinant Parkin. Our mutation analysis indicates an essential role for the catalytic cysteine Cys431 and reveals fundamental new knowledge on how mutations may confer pathogenicity via disruption of Miro1 ubiquitylation, free ubiquitin chain formation or by impacting Parkin's ability to discharge ubiquitin from a loaded E2. This study provides further evidence that phosphorylation of Parkin at Ser(65) is critical for its activation. It also provides evidence that Miro1 is a direct Parkin substrate. The assays and reagents developed in this study will be important to uncover new insights into Parkin biology as well as aid in the development of screens to identify small molecule Parkin activators for the treatment of Parkinson's disease.