Biology subjects

Mann, M.

Publications and source records attributed to Mann, M..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

Ultra-high sensitivity mass spectrometry quantifies single-cell proteome changes upon perturbation

Single-cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing1-3. However, proteins are the main drivers of cellular function and in-depth characterization of individual cells by mass spectrometry (MS)-based proteomics would thus be highly valuable and complementary4,5. Chemical labeling-based single-cell approaches introduce hundreds of cells into the MS, but direct analysis of single cells has not yet reached the necessary sensitivity, robustness and quantitative accuracy to answer biological questions6,7. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow-rate chromatography and a novel trapped ion mobility mass spectrometer, resulting in a more than ten-fold improved sensitivity. We accurately and robustly quantify proteomes and their changes in single, FACS-isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators such as CDK2NA, the E2 ubiquitin ligase UBE2S, DNA topoisomerases TOP2A/B and the chromatin regulator HMGA1. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single-cell proteomes to transcriptome data revealed a stable core proteome despite perturbation, while the transcriptome appears volatile. This emphasizes substantial regulation of translation and sets the stage for its elucidation at the single cell level. Our technology can readily be applied to ultra-high sensitivity analyses of tissue material8, posttranslational modifications and small molecule studies to gain unprecedented insights into cellular heterogeneity in health and disease.

systems biology↗

bioRxiv2020

Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories toward type 2 diabetes

Existing studies do not sufficiently describe the molecular changes of pancreatic islet beta cells leading to their deficient insulin secretion in type 2 diabetes (T2D). Here we address this deficiency with a comprehensive multi-omics analysis of metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum from normoglycemia to T2D. Islet pools isolated from surgical samples by laser-capture microdissection had remarkably heterogeneous transcriptomic and proteomic profiles in diabetics, but not in non-diabetic controls. Transcriptomics analysis of this unique cohort revealed islet genes already dysregulated in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive but disharmonic remodeling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or trans-differentiation stages in T2D. Further, integration of islet transcriptomics and pre-operative blood plasma lipidomics data enabled us to define the relative importance of gene co-expression modules and lipids positively or negatively associated with HbA1c levels, pointing to potential prognostic markers.

bioinformatics↗

bioRxiv2020

Identification of Covalent Modifications Regulating Immune Signaling Complex Composition and Phenotype

Cells signal through rearrangements of protein communities governed by covalent modifications and reversible interactions of distinct sets of proteins. A method that identifies those post-transcriptional modifications regulating signaling complex composition and functional phenotypes in one experimental setup would facilitate an efficient identification of novel molecular signaling checkpoints. Here we devised Modifications, Interactions and Phenotypes by Affinity Purification Mass Spectrometry (MIP-APMS), comprising the streamlined cloning and transduction of tagged proteins into functionalized reporter cells as well as affinity chromatography, followed by MS-based quantification. We report the time-resolved interplay of more than 50 previously undescribed modification and hundreds of protein-protein interactions of 19 immune protein complexes in monocytes. Validation of interdependecies between covalent, reversible and functional protein complex regulations by knock-out or site-specific mutation, revealed isgylation and phosphorylation of TRAF2 as well as ARHGEF18 interaction in Toll-like receptor 2 signaling. Moreover, we identify distinct mechanisms of action for small molecule inhibitors of p-38 (MAPK14). Our method provides a fast and cost-effective pipeline for the molecular interrogation of protein communities in diverse biological systems and primary cells. HighlightsO_LIExperimental framework to reveal dynamic signaling checkpoints in primary cells C_LIO_LIIdentification of crosstalk between protein modifications and interactions in signaling complexes C_LIO_LIDiscovery of TRAF2 isgylation, phosphorylation and ARHGEF18 interaction in monocytes C_LIO_LIDifferential drug mode of action for p-38 (MAPK14) kinase inhibitors C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/384750v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@1e833d3org.highwire.dtl.DTLVardef@1a2805forg.highwire.dtl.DTLVardef@199e1eaorg.highwire.dtl.DTLVardef@1becf99_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2020

Phosphoproteome profiling uncovers a key role for CDKs in TNF signaling

Tumor necrosis factor (TNF) is one of the few cytokines successfully targeted by therapies against inflammatory diseases. However, blocking this well studied and pleiotropic ligand can cause dramatic side-effects. We reasoned that a systems-level proteomic analysis of TNF signaling could dissect its diverse functions and offer a base for developing more targeted therapies. Combining phosphoproteomics time course experiments with subcellular localization and kinase inhibitor analysis identifies functional modules of phosphorylations. The majority of regulated phosphorylations could be assigned to an upstream kinase by inhibiting master kinases and spatial proteomics revealed phosphorylation-dependent translocations of hundreds of proteins upon TNF stimulation. Phosphoproteome analysis of TNF-induced apoptosis and necroptosis uncovered a key role for transcriptional cyclin-dependent kinase (CDK) activity to promote cytokine production and prevent excessive cell death downstream of the TNF signaling receptor. Our comprehensive interrogation of TNF induced pathways and sites can be explored at http://tnfviewer.biochem.mpg.de/. Highlights- Distinct phosphorylation events mark early and late TNF signaling - Inhibition of master kinases reveals TNF stimulation dependent kinase-substrate relations - TNF induces phosphorylation-dependent spatial rearrangement of hundreds of proteins - CDK kinase activity promotes TNF-induced cytokine expression and inhibits cell death - CDK12/13 inhibitors have potential as anti-inflammatory agents

systems biology↗

bioRxiv2020

A paired liver biopsy and plasma proteomics study reveals circulating biomarkers for alcohol-related liver disease

Existing tests for detecting liver fibrosis, inflammation and steatosis, three stages of liver disease that are still reversible are severely hampered by limited accuracy or invasive nature. Here, we present a paired liver-plasma proteomics approach to infer molecular pathophysiology and to identify biomarkers in a cross-sectional alcohol-related liver disease cohort of nearly 600 individuals. Metabolic functions were downregulated whereas fibrosis-associated signaling and novel immune responses were upregulated, but only half of tissue proteome changes were transmitted to the circulation. Machine learning models based on our biomarker panels outperformed existing tests, laying the foundation for a generic proteomic liver health assessment.

biochemistry↗

bioRxiv2020

The Hippo pathway controls myofibril assembly and muscle fiber growth by regulating sarcomeric gene expression

Skeletal muscles are composed of gigantic cells called muscle fibers, packed with force-producing myofibrils. During development the size of individual muscle fibers must dramatically enlarge to match with skeletal growth. How muscle growth is coordinated with growth of the contractile apparatus is not understood. Here, we use the large Drosophila flight muscles to mechanistically decipher how muscle fiber growth is controlled. We find that regulated activity of core members of the Hippo pathway is required to support flight muscle growth. Interestingly, we identify Dlg5 and Slmap as regulators of the STRIPAK phosphatase, which negatively regulates Hippo to enable post-mitotic muscle growth. Mechanistically, we show that the Hippo pathway controls timing and levels of sarcomeric gene expression during development and thus regulates the key components that physically mediate muscle growth. Since Dlg5, STRIPAK and the Hippo pathway are conserved a similar mechanism may contribute to muscle or cardiomyocyte growth in humans.

developmental biology↗

bioRxiv2020

DIA-based systems biology approach unveils novel E3-dependent responses to a metabolic shift

Yeast Saccharomyces cerevisiae is a powerful model system for systems-wide biology screens and large-scale proteomics methods. Nearly complete proteomics coverage has been achieved owing to advances in mass spectrometry. However, it remains challenging to scale this technology for rapid and high-throughput analysis of the yeast proteome to investigate biological pathways on a global scale. Here we describe a systems biology workflow employing plate-based sample preparation and rapid, single-run data independent mass spectrometry analysis (DIA). Our approach is straightforward, easy to implement and enables quantitative profiling and comparisons of hundreds of nearly complete yeast proteomes in only a few days. We evaluate its capability by characterizing changes in the yeast proteome in response to environmental perturbations, identifying distinct responses to each of them, and providing a comprehensive resource of these responses. Apart from rapidly recapitulating previously observed responses, we characterized carbon source dependent regulation of the GID E3 ligase, an important regulator of cellular metabolism during the switch between gluconeogenic and glycolytic growth conditions. This unveiled new regulatory targets of the GID ligase during a metabolic switch. Our comprehensive yeast system read-out pinpointed effects of a single deletion or point mutation in the GID complex on the global proteome, allowing the identification and validation novel targets of the GID E3 ligase. Moreover, our approach allowed the identification of targets from multiple cellular pathways that display distinct patterns of regulation. Although developed in yeast, rapid whole proteome-based readouts can serve as comprehensive systems-level assay in all cellular systems.

systems biology↗

bioRxiv2020

Defining the RBPome of T helper cells to study higher order post-transcriptional gene regulation

Post-transcriptional gene regulation is complex, dynamic and ensures proper T cell function. The targeted transcripts can simultaneously respond to various factors as evident for Icos, an mRNA regulated by several RNA binding proteins (RBPs), including Roquin. However, fundamental information about the entire RBPome involved in post-transcriptional gene regulation in T cells is lacking. Here, we applied global RNA interactome capture (RNA-IC) and orthogonal organic phase separation (OOPS) to human and mouse primary T cells and identified the core T cell RBPome. This defined 798 mouse and 801 human proteins as RBPs, unexpectedly containing signaling proteins like Stat1, Stat4 and Vav1. Based on the vicinity to Roquin-1 in proximity labeling experiments, we selected [~]50 RBPs for testing coregulation of Roquin targets. Induced expression of these candidate RBPs in wildtype and Roquin-deficient T cells unraveled several Roquin-independent contributions, but also revealed Celf1 as a new Roquin-1-dependent and target-specific coregulator of Icos. One sentence statementWe provide an atlas of RNA-binding proteins in human and mouse T helper cells as a resource for studying higher order post-transcriptional gene regulation.

immunology↗

bioRxiv2020

Urinary proteome profiling for stratifying patients with familial Parkinsons disease

The prevalence of Parkinsons disease (PD) is increasing but the development of novel treatment strategies and therapeutics altering the course of the disease would benefit from specific, sensitive and non-invasive biomarkers to detect PD early. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomic workflow for urinary proteome profiling. Our workflow enabled the reproducible quantification of more than 2,000 proteins in more than 200 urine samples using minimal volumes from two independent patient cohorts. The urinary proteome was significantly different between PD patients and healthy controls, as well as between LRRK2 G2019S carriers and non-carriers in both cohorts. Interestingly, our data revealed lysosomal dysregulation in individuals with the LRRK2 G2019S mutation. When combined with machine learning, the urinary proteome data alone was sufficient to classify mutation status and disease manifestation in mutation carriers remarkably well, identifying VGF, ENPEP and other PD-associated proteins as the most discriminating features. Taken together, our results validate urinary proteomics as a valuable strategy for biomarker discovery and patient stratification in PD.

systems biology↗

bioRxiv2020

Data-independent acquisition method for ubiquitinome analysis reveals regulation of circadian biology

Protein ubiquitination is involved in virtually all cellular processes. Enrichment strategies employing antibodies targeting ubiquitin-derived diGly remnants combined with mass spectrometry (MS) have enabled investigations of ubiquitin signaling at a large scale. However, so far the power of data independent acquisition (DIA) with regards to sensitivity in single run analysis and data completeness have not yet been explored. We developed a sensitive workflow combining diGly antibody-based enrichment and optimized Orbitrap-based DIA with comprehensive spectral libraries together containing more than 90,000 diGly peptides. This approach identified 35,000 diGly peptides in single measurements of proteasome inhibitor-treated cells - double the number and quantitative accuracy of data dependent acquisition. Applied to TNF-alpha signaling, the workflow comprehensively captured known sites while adding many novel ones. A first systems-wide investigation of ubiquitination of the circadian cycle uncovered hundreds of cycling ubiquitination sites and dozens of cycling ubiquitin clusters within individual membrane protein receptors and transporters, highlighting novel connections between metabolism and circadian regulation.

systems biology↗

bioRxiv2020

Spatially and cell-type resolved quantitative proteomic atlas of healthy human skin

Human skin provides both physical integrity and immunological protection from the external environment using functionally distinct layers, cell types and extracellular matrix. Despite its central role in human health and disease, the constituent proteins of skin have not been systematically characterized. Here, we combined advanced tissue dissection methods, flow cytometry and state-of-the-art proteomics to describe a spatially-resolved quantitative proteomic atlas of human skin. We quantified 10,701 proteins as a function of their spatial location and cellular origin. The resulting protein atlas and our initial data analyses demonstrate the value of proteomics for understanding cell-type diversity within the skin. We describe the quantitative distribution of structural proteins, known and novel proteins specific to cellular subsets and those with specialized immunological functions such as cytokines and chemokines. We anticipate that this proteomic atlas of human skin will become an essential community resource for basic and translational research (www.skin.science).

cell biology↗

bioRxiv2020

Multi-level proteomics reveals host-perturbation strategies of SARS-CoV-2 and SARS-CoV

The global emergence of SARS-CoV-2 urgently requires an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several individual omics studies have extended our knowledge of COVID-19 pathophysiology1-10. Integration of such datasets to obtain a holistic view of virus-host interactions and to define the pathogenic properties of SARS-CoV-2 is limited by the heterogeneity of the experimental systems. We therefore conducted a concurrent multi-omics study of SARS-CoV-2 and SARS-CoV. Using state-of-the-art proteomics, we profiled the interactome of both viruses, as well as their influence on transcriptome, proteome, ubiquitinome and phosphoproteome in a lung-derived human cell line. Projecting these data onto the global network of cellular interactions revealed crosstalk between the perturbations taking place upon SARS-CoV-2 and SARS-CoV infections at different layers and identified unique and common molecular mechanisms of these closely related coronaviruses. The TGF-{beta} pathway, known for its involvement in tissue fibrosis, was specifically dysregulated by SARS-CoV-2 ORF8 and autophagy by SARS-CoV-2 ORF3. The extensive dataset (available at https://covinet.innatelab.org) highlights many hotspots that can be targeted by existing drugs and it can guide rational design of virus- and host-directed therapies, which we exemplify by identifying kinase and MMPs inhibitors with potent antiviral effects against SARS-CoV-2.

systems biology↗

bioRxiv2020

Deep learning the collisional cross sections of the peptide universe from a million training samples

The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To explore the nature and utility of the entire peptide collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests of five organisms with trapped ion mobility spectrometry (TIMS) and parallel accumulation - serial fragmentation (PASEF). The scale and precision (CV <1%) of our data is sufficient to train a deep recurrent neural network that accurately predicts CCS values solely based on the peptide sequence. Cross section predictions for the synthetic ProteomeTools library validate the model within a 1.3% median relative error (R > 0.99). Hydrophobicity, position of prolines and histidines are main determinants of the cross sections in addition to sequence-specific interactions. CCS values can now be predicted for any peptide and organism, forming a basis for advanced proteomics workflows that make full use of the additional information.

systems biology↗

bioRxiv2020

Integrative proteomics reveals principles of dynamic phospho-signaling networks in human erythropoiesis

Human erythropoiesis is exquisitely controlled at multiple levels and its dysregulation leads to numerous human diseases. Despite many functional studies focused on classical regulators, we lack a global, system-wide understanding of post-translational mechanisms coordinating erythroid maturation. Using the latest advances in mass spectrometry (MS)-based proteomics we comprehensively investigate the dynamics of protein and post-translational regulation of in vitro reconstituted CD34+ HSPC-derived erythropoiesis. This quantifies and dynamically tracks 7,400 proteins and 27,000 phosphorylation sites. Our data reveals differential temporal protein expression encompassing most protein classes and numerous post-translational regulatory cascades. Drastic cell surface remodeling across erythropoiesis include numerous orchestrated changes in solute carriers, providing new stage-specific markers. The dynamic phosphoproteomes combined with a kinome-targeting CRISPR/Cas9 screen reveal coordinated networks of erythropoietic kinases and downregulation of MAPK signaling subsequent to c-Kit attenuation as key drivers of maturation. Our global view of erythropoiesis establishes a central role of post-translational regulation in terminal differentiation.

systems biology↗

bioRxiv2020

Clinical Knowledge Graph Integrates Proteomics Data into Clinical Decision-Making

The promise of precision medicine is to deliver personalized treatment based on the unique physiology of each patient. This concept was fueled by the genomic revolution, but it is now evident that integrating other types of omics data, like proteomics, into the clinical decision-making process will be essential to accomplish precision medicine goals. However, quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across myriad biomedical databases and publications makes this exceptionally difficult. To address this, we developed the Clinical Knowledge Graph (CKG), an open source platform currently comprised of more than 16 million nodes and 220 million relationships to represent relevant experimental data, public databases and the literature. The CKG also incorporates the latest statistical and machine learning algorithms, drastically accelerating analysis and interpretation of typical proteomics workflows. We use several biomarker studies to illustrate how the CKG may support, enrich and accelerate clinical decision-making. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/084897v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@433689org.highwire.dtl.DTLVardef@b18068org.highwire.dtl.DTLVardef@1656084org.highwire.dtl.DTLVardef@a38201_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2020

Identification of MAZ as a novel transcription factor regulating erythropoiesis

Erythropoiesis requires a combination of ubiquitous and tissue-specific transcription factors. Here, through DNA affinity purification followed by mass spectrometry, we have identified the widely expressed protein MAZ (Myc-associated zinc finger) as a transcription factor that binds to the promoter of the erythroid-specific human -globin gene. Genome-wide mapping in primary human erythroid cells revealed that MAZ also occupies active promoters as well as GATA1-bound enhancer elements of key erythroid genes. Consistent with an important role during erythropoiesis, knockdown of MAZ in primary human erythroid cells impairs erythroid differentiation, and genetic variants in the MAZ locus are associated with clinically important human erythroid traits. Taken together, these findings reveal the Zinc-finger transcription factor MAZ to be a previously unrecognised regulator of the erythroid differentiation program.

molecular biology↗

bioRxiv2020

Gain-of-function mutations amplify cytotoxic FAM111 protease activity in human genetic disorders

Dominant missense mutations in the human serine protease FAM111A underlie perinatally lethal gracile bone dysplasia and Kenny-Caffey syndrome 1-3, yet how FAM111A mutations lead to disease is not known. We show that FAM111A proteolytic activity suppresses DNA replication and transcription by displacing key effectors of these processes from chromatin, triggering rapid programmed cell death by Caspase-dependent apoptosis to potently undermine cell viability. Patient-associated point mutations in FAM111A exacerbate these phenotypes by hyperactivating its intrinsic protease activity. Moreover, FAM111A forms a complex with the uncharacterized homologous serine protease FAM111B, point mutations in which cause a hereditary fibrosing poikiloderma syndrome 4, and we demonstrate that disease-associated FAM111B mutants display amplified proteolytic activity and phenocopy the cellular impact of deregulated FAM111A catalytic activity. Thus, patient-associated FAM111A and FAM111B mutations may drive multisystem disorders via a common gain-of-function mechanism that relieves inhibitory constraints on their protease activities to powerfully undermine cellular fitness.

cell biology↗

bioRxiv2020

Limited Environmental Serine Confers Sensitivity to PHGDH Inhibition in Brain Metastasis

A hallmark of metastasis is the adaptation of tumor cells to new environments. Although it is well established that the metabolic milieu of the brain is severely deprived of nutrients, particularly the amino acids serine and its catabolite glycine, how brain metastases rewire their metabolism to survive in the nutrient-limited environment of the brain is poorly understood. Here we demonstrate that cell-intrinsic de novo serine synthesis is a major determinant of brain metastasis. Whole proteome comparison of triple-negative breast cancer (TNBC) cells that differ in their capacity to colonize the brain reveals that 3-phosphoglycerate dehydrogenase (PHGDH), which catalyzes the rate-limiting step of glucose-derived serine synthesis, is the most significantly upregulated protein in cells that efficiently metastasize to the brain. Genetic silencing or pharmacological inhibition of PHGDH attenuated brain metastasis and improved overall survival in mice, whereas expression of catalytically active PHGDH in a non-brain trophic cell line promoted brain metastasis. Collectively, these findings indicate that nutrient availability determines serine synthesis pathway dependence in brain metastasis, and suggest that PHGDH inhibitors may be useful in the treatment of patients with cancers that have spread to the brain. Statement of SignificanceOur study highlights how limited serine and glycine availability within the brain microenvironment potentiates tumor cell sensitivity to serine synthesis inhibition. This finding underscores the importance of studying cancer metabolism in physiologically-relevant contexts, and provides a rationale for using PHGDH inhibitors to treat brain metastasis.

cancer biology↗