The proteome landscape of the kingdoms of life.

Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported1, advances in mass-spectrometry-based proteomics2 have enabled increasingly comprehensive identification and quantification of the human proteome3-6. However, there have been few comparisons across species7,8, in stark contrast with genomics initiatives9. Here we use an advanced proteomics workflow-in which the peptide separation step is performed by a microstructured and extremely reproducible chromatographic system-for the in-depth study of 100 taxonomically diverse organisms. With two million peptide and 340,000 stringent protein identifications obtained in a standardized manner, we double the number of proteins with solid experimental evidence known to the scientific community. The data also provide a large-scale case study for sequence-based machine learning, as we demonstrate by experimentally confirming the predicted properties of peptides from Bacteroides uniformis. Our results offer a comparative view of the functional organization of organisms across the entire evolutionary range. A remarkably high fraction of the total proteome mass in all kingdoms is dedicated to protein homeostasis and folding, highlighting the biological challenge of maintaining protein structure in all branches of life. Likewise, a universally high fraction is involved in supplying energy resources, although these pathways range from photosynthesis through iron sulfur metabolism to carbohydrate metabolism. Generally, however, proteins and proteomes are remarkably diverse between organisms, and they can readily be explored and functionally compared at www.proteomesoflife.org.

Transparent Exploration of Machine Learning for Biomarker Discovery from Proteomics and Omics Data.

Biomarkers are of central importance for assessing the health state and to guide medical interventions and their efficacy; still, they are lacking for most diseases. Mass spectrometry (MS)-based proteomics is a powerful technology for biomarker discovery but requires sophisticated bioinformatics to identify robust patterns. Machine learning (ML) has become a promising tool for this purpose. However, it is sometimes applied in an opaque manner and generally requires specialized knowledge. To enable easy access to ML for biomarker discovery without any programming or bioinformatics skills, we developed "OmicLearn" (http://OmicLearn.org), an open-source browser-based ML tool using the latest advances in the Python ML ecosystem. Data matrices from omics experiments are easily uploaded to an online or a locally installed web server. OmicLearn enables rapid exploration of the suitability of various ML algorithms for the experimental data sets. It fosters open science via transparent assessment of state-of-the-art algorithms in a standardized format for proteomics and other omics sciences.

Accurate MS-based Rab10 Phosphorylation Stoichiometry Determination as Readout for LRRK2 Activity in Parkinson's Disease.

Pathogenic mutations in the Leucine-rich repeat kinase 2 (LRRK2) are the predominant genetic cause of Parkinson's disease (PD). They increase its activity, resulting in augmented Rab10-Thr73 phosphorylation and conversely, LRRK2 inhibition decreases pRab10 levels. Currently, there is no assay to quantify pRab10 levels for drug target engagement or patient stratification. To meet this challenge, we developed an high accuracy and sensitivity targeted mass spectrometry (MS)-based assay for determining Rab10-Thr73 phosphorylation stoichiometry in human samples. It uses synthetic stable isotope-labeled (SIL) analogues for both phosphorylated and nonphosphorylated tryptic peptides surrounding Rab10-Thr73 to directly derive the percentage of Rab10 phosphorylation from attomole amounts of the endogenous phosphopeptide. The SIL and the endogenous phosphopeptides are separately admitted into an Orbitrap analyzer with the appropriate injection times. We test the reproducibility of our assay by determining Rab10-Thr73 phosphorylation stoichiometry in neutrophils of LRRK2 mutation carriers before and after LRRK2 inhibition. Compared with healthy controls, the PD predisposing mutation carriers LRRK2 G2019S and VPS35 D620N display 1.9-fold and 3.7-fold increased pRab10 levels, respectively. Our generic MS-based assay further establishes the relevance of pRab10 as a prognostic PD marker and is a powerful tool for determining LRRK2 inhibitor efficacy and for stratifying PD patients for LRRK2 inhibitor treatment.

BoxCar acquisition method enables single-shot proteomics at a depth of 10,000 proteins in 100 minutes.

Great advances have been made in sensitivity and acquisition speed on the Orbitrap mass analyzer, enabling increasingly deep proteome coverage. However, these advances have been mainly limited to the MS2 level, whereas ion beam sampling for the MS1 scans remains extremely inefficient. Here we report a data-acquisition method, termed BoxCar, in which filling multiple narrow mass-to-charge segments increases the mean ion injection time more than tenfold as compared to that of a standard full scan. In 1-h analyses, the method provided MS1-level evidence for more than 90% of the proteome of a human cancer cell line that had previously been identified in 24 fractions, and it quantified more than 6,200 proteins in ten of ten replicates. In mouse brain tissue, we detected more than 10,000 proteins in only 100 min, and sensitivity extended into the low-attomolar range.

EASI-tag enables accurate multiplexed and interference-free MS2-based proteome quantification.

We developed EASI-tag (easily abstractable sulfoxide-based isobaric-tag), a new type of amine-derivatizing and sulfoxide-containing isobaric labeling reagents for highly accurate quantitative proteomics analysis using mass spectrometry. We observed that EASI-tag labels dissociate at low collision energy and generate peptide-coupled, interference-free reporter ions with high yield. Efficient isolation of 12C precursors and quantification at the MS2 level allowed accurate determination of quantitative differences between up to six multiplexed samples.

MaxQuant.Live Enables Global Targeting of More Than 25,000 Peptides.

Mass spectrometry (MS)-based proteomics is often performed in a shotgun format, in which as many peptide precursors as possible are selected from full or MS1 scans so that their fragment spectra can be recorded in MS2 scans. Although achieving great proteome depths, shotgun proteomics cannot guarantee that each precursor will be fragmented in each run. In contrast, targeted proteomics aims to reproducibly and sensitively record a restricted number of precursor/fragment combinations in each run, based on prescheduled mass-to-charge and retention time windows. Here we set out to unify these two concepts by a global targeting approach in which an arbitrary number of precursors of interest are detected in real-time, followed by standard fragmentation or advanced peptide-specific analyses. We made use of a fast application programming interface to a quadrupole Orbitrap instrument and real-time recalibration in mass, retention time and intensity dimensions to predict precursor identity. MaxQuant.Live is freely available (www.maxquant.live) and has a graphical user interface to specify many predefined data acquisition strategies. Acquisition speed is as fast as with the vendor software and the power of our approach is demonstrated with the acquisition of breakdown curves for hundreds of precursors of interest. We also uncover precursors that are not even visible in MS1 scans, using elution time prediction based on the auto-adjusted retention time alone. Finally, we successfully recognized and targeted more than 25,000 peptides in single LC-MS runs. Global targeting combines the advantages of two classical approaches in MS-based proteomics, whereas greatly expanding the analytical toolbox.

MaxQuant.Live Enables Global Targeting of More Than 25,000 Peptides.

Mass spectrometry (MS)-based proteomics is often performed in a shotgun format, in which as many peptide precursors as possible are selected from full or MS1 scans so that their fragment spectra can be recorded in MS2 scans. Although achieving great proteome depths, shotgun proteomics cannot guarantee that each precursor will be fragmented in each run. In contrast, targeted proteomics aims to reproducibly and sensitively record a restricted number of precursor/fragment combinations in each run, based on prescheduled mass-to-charge and retention time windows. Here we set out to unify these two concepts by a global targeting approach in which an arbitrary number of precursors of interest are detected in real-time, followed by standard fragmentation or advanced peptide-specific analyses. We made use of a fast application programming interface to a quadrupole Orbitrap instrument and real-time recalibration in mass, retention time and intensity dimensions to predict precursor identity. MaxQuant.Live is freely available (www.maxquant.live) and has a graphical user interface to specify many predefined data acquisition strategies. Acquisition speed is as fast as with the vendor software and the power of our approach is demonstrated with the acquisition of breakdown curves for hundreds of precursors of interest. We also uncover precursors that are not even visible in MS1 scans, using elution time prediction based on the auto-adjusted retention time alone. Finally, we successfully recognized and targeted more than 25,000 peptides in single LC-MS runs. Global targeting combines the advantages of two classical approaches in MS-based proteomics, whereas greatly expanding the analytical toolbox. MaxQuant.Live builds on the fast application programming interface of quadrupole Orbitrap mass analyzers to control data acquisition in real-time (freely available at www.maxquant.live). Its graphical user interface enables advanced data acquisition strategies, such as in-depth characterization of peptides of interest. Online recalibration in mass, retention time, and intensity dimensions extends this concept to more than 25,000 peptides per run. Our "global targeting" strategy combines the best of targeted and shotgun approaches.

The bacterial pigment pyocyanin inhibits the NLRP3 inflammasome through intracellular reactive oxygen and nitrogen species.

Inflammasomes are cytosolic complexes that mature and secrete the inflammatory cytokines interleukin 1ß (IL-1ß) and IL-18 and induce pyroptosis. The NLRP3 (NACHT, LRR, and PYD domains-containing protein 3) inflammasome detects many pathogen- and danger-associated molecular patterns, and reactive oxygen species (ROS)/reactive nitrogen species (RNS) have been implicated in its activation. The phenazine pyocyanin (PCN) is a virulence factor of Pseudomonas aeruginosa and generates superoxide in cells. Here we report that PCN inhibits IL-1ß and IL-18 release and pyroptosis upon NLRP3 inflammasome activation in macrophages by preventing speck formation and Caspase-1 maturation. Of note, PCN did not regulate the AIM2 (absent in melanoma 2) or NLRC4 inflammasomes or tumor necrosis factor (TNF) secretion. Imaging of the fluorescent glutathione redox potential sensor Grx1-roGFP2 indicated that PCN provokes cytosolic and nuclear but not mitochondrial redox changes. PCN-induced intracellular ROS/RNS inhibited the NLRP3 inflammasome posttranslationally, and hydrogen peroxide or peroxynitrite alone were sufficient to block its activation. We propose that cytosolic ROS/RNS inhibit the NLRP3 inflammasome and that PCN's anti-inflammatory activity may help P. aeruginosa evade immune recognition.

Human GBP1 does not localize to pathogen vacuoles but restricts Toxoplasma gondii.

Guanylate binding proteins (GBPs) are a family of large interferon-inducible GTPases that are transcriptionally upregulated upon infection with intracellular pathogens. Murine GBPs (mGBPs) including mGBP1 and 2 localize to and disrupt pathogen-containing vacuoles (PVs) resulting in the cell-autonomous clearing or innate immune detection of PV-resident pathogens. Human GBPs (hGBPs) are known to exert antiviral host defense and activate the NLRP3 inflammasome, but it is unclear whether hGBPs can directly recognize and control intravacuolar pathogens. Here, we report that endogenous or ectopically expressed hGBP1 fails to associate with PVs formed in human cells by the bacterial pathogens Chlamydia trachomatis or Salmonella typhimurium or the protozoan pathogen Toxoplasma gondii. While we find that hGBP1 expression has no discernible effect on intracellular replication of C. trachomatis and S. typhimurium, we observed enhanced early Toxoplasma replication in CRISPR hGBP1-deleted human epithelial cells. We thus identified a novel role for hGBP1 in cell-autonomous immunity that is independent of PV translocation, as observed for mGBPs. This study highlights fundamental differences between human and murine GBPs and underlines the need to study the functions of GBPs at cellular locations away from PVs.

Rapid hierarchical assembly of medium-size DNA cassettes.

Synthetic biology applications call for efficient methods to generate large gene cassettes that encode complex gene circuits in order to avoid simultaneous delivery of multiple plasmids encoding individual genes. Multiple methods have been proposed to achieve this goal. Here, we describe a novel protocol that allows one-step cloning of up to four gene-size DNA fragments, followed by a second assembly of these concatenated sequences into large circular DNA. The protocols described here comprise a simple, cheap and fast solution for routine construction of cassettes with up to 10 gene-size components.

Proteome profiling of cerebrospinal fluid reveals biomarker candidates for Parkinson's disease.

Parkinson's disease (PD) is a growing burden worldwide, and there is no reliable biomarker used in clinical routines to date. Cerebrospinal fluid (CSF) is routinely collected in patients with neurological symptoms and should closely reflect alterations in PD patients' brains. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomics workflow for CSF proteome profiling. From two independent cohorts with over 200 individuals, our workflow reproducibly quantifies over 1,700 proteins from minimal CSF amounts. Machine learning determines OMD, CD44, VGF, PRL, and MAN2B1 to be altered in PD patients or to significantly correlate with clinical scores. We also uncover signatures of enhanced neuroinflammation in LRRK2 G2019S carriers, as indicated by increased levels of CTSS, PLD4, and HLA proteins. A comparison with our previously acquired urinary proteomes reveals a large overlap in PD-associated changes, including lysosomal proteins, opening up new avenues to improve our understanding of PD pathogenesis.

Urinary proteome profiling for stratifying patients with familial Parkinson's disease.

The prevalence of Parkinson's 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 were 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.

High-resolution serum proteome trajectories in COVID-19 reveal patient-specific seroconversion.

A deeper understanding of COVID-19 on human molecular pathophysiology is urgently needed as a foundation for the discovery of new biomarkers and therapeutic targets. Here we applied mass spectrometry (MS)-based proteomics to measure serum proteomes of COVID-19 patients and symptomatic, but PCR-negative controls, in a time-resolved manner. In 262 controls and 458 longitudinal samples of 31 patients, hospitalized for COVID-19, a remarkable 26% of proteins changed significantly. Bioinformatics analyses revealed co-regulated groups and shared biological functions. Proteins of the innate immune system such as CRP, SAA1, CD14, LBP, and LGALS3BP decreased early in the time course. Regulators of coagulation (APOH, FN1, HRG, KNG1, PLG) and lipid homeostasis (APOA1, APOC1, APOC2, APOC3, PON1) increased over the course of the disease. A global correlation map provides a system-wide functional association between proteins, biological processes, and clinical chemistry parameters. Importantly, five SARS-CoV-2 immunoassays against antibodies revealed excellent correlations with an extensive range of immunoglobulin regions, which were quantified by MS-based proteomics. The high-resolution profile of all immunoglobulin regions showed individual-specific differences and commonalities of potential pathophysiological relevance.

Genome-wide CRISPR screen reveals novel host factors required for Staphylococcus aureus α-hemolysin-mediated toxicity.

Staphylococcus aureus causes a wide variety of infections and antibiotic resistant strains are a major problem in hospitals. One of the best studied virulence factors of S. aureus is the pore-forming toxin alpha hemolysin (αHL) whose mechanism of action is incompletely understood. We performed a genome-wide loss-of-function screen using CRISPR/Cas9 technology to identify host targets required for αHL susceptibility in human myeloid cells. We found gRNAs for ten genes enriched after intoxication with αHL and focused on the top five hits. Besides a disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), the host receptor for αHL, we identified three proteins, Sys1 golgi trafficking protein (SYS1), ADP-ribosylation factor 1 (ARFRP1), and tetraspanin-14 (TSPAN14) which regulate the presentation of ADAM10 on the plasma membrane post-translationally. Interestingly, we also showed that cells lacking sphingomyelin synthase 1 (SGMS1) resist αHL intoxication, but have only a slightly reduced ADAM10 surface expression. SGMS1 regulates lipid raft formation, suggesting that αHL requires these membrane microdomains for attachment and cytotoxicity.

Determinants of GBP recruitment to Toxoplasma gondii vacuoles and the parasitic factors that control it.

IFN-γ is a major cytokine that mediates resistance against the intracellular parasite Toxoplasma gondii. The p65 guanylate-binding proteins (GBPs) are strongly induced by IFN-γ. We studied the behavior of murine GBP1 (mGBP1) upon infection with T. gondii in vitro and confirmed that IFN-γ-dependent re-localization of mGBP1 to the parasitophorous vacuole (PV) correlates with the virulence type of the parasite. We identified three parasitic factors, ROP16, ROP18, and GRA15 that determine strain-specific accumulation of mGBP1 on the PV. These highly polymorphic proteins are held responsible for a large part of the strain-specific differences in virulence. Therefore, our data suggest that virulence of T. gondii in animals may rely in part on recognition by GBPs. However, phagosomes or vacuoles containing Trypanosoma cruzi did not recruit mGBP1. Co-immunoprecipitation revealed mGBP2, mGBP4, and mGBP5 as binding partners of mGBP1. Indeed, mGBP2 and mGBP5 co-localize with mGBP1 in T. gondii-infected cells. T. gondii thus elicits a cell-autonomous immune response in mice with GBPs involved. Three parasitic virulence factors and unknown IFN-γ-dependent host factors regulate this complex process. Depending on the virulence of the strains involved, numerous GBPs are brought to the PV as part of a large, multimeric structure to combat T. gondii.