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MassIVE.quant is a repository infrastructure and data resource for reproducible quantitative mass spectrometry–based proteomics, which is compatible with all mass spectrometry data acquisition types and computational analysis tools. A branch structure enables MassIVE.quant to systematically store raw experimental data, metadata of the experimental design, scripts of the quantitative analysis workflow, intermediate input and output files, as well as alternative reanalyses of the same dataset. MassIVE.quant is a data repository and data resource for reproducible quantitative mass spectrometry–based proteomics.

Ongoing social, political and ecological changes in the 21st century have placed more people at risk of life-threatening acute and chronic infections than ever before. The development of new diagnostic, prophylactic, therapeutic and curative strategies is critical to address this burden but is predicated on a detailed understanding of the immensely complex relationship between pathogens and their hosts. Traditional, reductionist approaches to investigate this dynamic often lack the scale and/or scope to faithfully model the dual and co-dependent nature of this relationship, limiting the success of translational efforts. With recent advances in large-scale, quantitative omics methods as well as in integrative analytical strategies, systems biology approaches for the study of infectious disease are quickly forming a new paradigm for how we understand and model host–pathogen relationships for translational applications. Here, we delineate a framework for a systems biology approach to infectious disease in three parts: discovery — the design, collection and analysis of omics data; representation — the iterative modelling, integration and visualization of complex data sets; and application — the interpretation and hypothesis-based inquiry towards translational outcomes.This Review outlines a broad, universal framework for systems biology applied to infectious disease research. From study design and omics data collection, analysis, visualization and interpretation to translational outcomes, the authors illustrate how systems biology can provide insights into host–pathogen relationships for the betterment of human health.

Among the wide range of proteomic technologies, targeted mass spectrometry (MS) has shown great potential for biomarker studies. To extend the degree of multiplexing achieved by selected reaction monitoring (SRM), we recently developed SWATH MS. SWATH MS is a variant of the emerging class of data-independent acquisition (DIA) methods and essentially converts the molecules in a physical sample into perpetually re-usable digital maps. The thus generated SWATH maps are then mined using a targeted data extraction strategy, allowing us to profile disease-related proteomes at a high degree of reproducibility. The successful application of both SRM and SWATH MS requires the a priori generation of reference spectral maps that provide coordinates for quantification. Herein, we demonstrate that the application of the mass spectrometric reference maps and the acquisition of personalized SWATH maps hold a particular promise for accelerating the current process of biomarker discovery.

Targeted proteomics based on selected reaction monitoring (SRM) mass spectrometry is commonly used for accurate and reproducible quantification of protein analytes in complex biological mixtures. Strictly hypothesis-driven, SRM assays quantify each targeted protein by collecting measurements on its peptide fragment ions, called transitions. To achieve sensitive and accurate quantitative results, experimental design and data analysis must consistently account for the variability of the quantified transitions. This consistency is especially important in large experiments, which increasingly require profiling up to hundreds of proteins over hundreds of samples. Here we describe a robust and automated workflow for the analysis of large quantitative SRM data sets that integrates data processing, statistical protein identification and quantification, and dissemination of the results. The integrated workflow combines three software tools: mProphet for peptide identification via probabilistic scoring; SRMstats for protein significance analysis with linear mixed-effect models; and PASSEL, a public repository for storage, retrieval and query of SRM data. The input requirements for the protocol are files with SRM traces in mzXML format, and a file with a list of transitions in a text tab-separated format. The protocol is especially suited for data with heavy isotope–labeled peptide internal standards. We demonstrate the protocol on a clinical data set in which the abundances of 35 biomarker candidates were profiled in 83 blood plasma samples of subjects with ovarian cancer or benign ovarian tumors. The time frame to realize the protocol is 1–2 weeks, depending on the number of replicates used in the experiment.

The μ-opioid receptor (μOR) represents an important target of therapeutic and abused drugs. So far, most understanding of μOR activity has focused on a subset of known signal transducers and regulatory molecules. Yet μOR signaling is coordinated by additional proteins in the interaction network of the activated receptor, which have largely remained invisible given the lack of technologies to interrogate these networks systematically. Here we describe a proteomics and computational approach to map the proximal proteome of the activated μOR and to extract subcellular location, trafficking and functional partners of G-protein-coupled receptor (GPCR) activity. We demonstrate that distinct opioid agonists exert differences in the μOR proximal proteome mediated by endocytosis and endosomal sorting. Moreover, we identify two new μOR network components, EYA4 and KCTD12, which are recruited on the basis of receptor-triggered G-protein activation and might form a previously unrecognized buffering system for G-protein activity broadly modulating cellular GPCR signaling. A proteomics and computational approach was developed to map the proximal proteome of the activated μ-opioid receptor and to extract subcellular location, trafficking and functional partners of G-protein-coupled receptor activity.

Enteroviruses cause a number of medically relevant and widespread human diseases with no approved antiviral therapies currently available. Host-directed therapies present an enticing option for this diverse genus of viruses. We have previously identified the actin histidine methyltransferase SETD3 as a critical host factor physically interacting with the viral protease 2A. Here, we report the 3.5 Å cryo-EM structure of SETD3 interacting with coxsackievirus B3 2A at two distinct interfaces, including the substrate-binding surface within the SET domain. Structure-function analysis revealed that mutations of key residues in the SET domain resulted in severely reduced binding to 2A and complete protection from enteroviral infection. Our findings provide insight into the molecular basis of the SETD3-2A interaction and a framework for the rational design of host-directed therapeutics against enteroviruses. Actin histidine methyltransferase SETD3 is a host factor critical for the replication of enteroviruses. Here, the authors report the 3.5 Å cryoEM structure of SETD3 interacting with enterovirus CV-B3 2A protease, defining the actin-binding SET domain as essential for virus replication.

Differentiation proceeds along a continuum of increasingly fate-restricted intermediates, referred to as canalization 1 , 2 . Canalization is essential for stabilizing cell fate, but the mechanisms that underlie robust canalization are unclear. Here we show that the BRG1/BRM-associated factor (BAF) chromatin-remodelling complex ATPase gene Brm safeguards cell identity during directed cardiogenesis of mouse embryonic stem cells. Despite the establishment of a well-differentiated precardiac mesoderm, Brm −/− cells predominantly became neural precursors, violating germ layer assignment. Trajectory inference showed a sudden acquisition of a non-mesodermal identity in Brm −/− cells. Mechanistically, the loss of Brm prevented de novo accessibility of primed cardiac enhancers while increasing the expression of neurogenic factor POU3F1, preventing the binding of the neural suppressor REST and shifting the composition of BRG1 complexes. The identity switch caused by the Brm mutation was overcome by increasing BMP4 levels during mesoderm induction. Mathematical modelling supports these observations and demonstrates that Brm deletion affects cell fate trajectory by modifying saddle–node bifurcations 2 . In the mouse embryo, Brm deletion exacerbated mesoderm-deleted Brg1 -mutant phenotypes, severely compromising cardiogenesis, and reveals an in vivo role for Brm . Our results show that Brm is a compensable safeguard of the fidelity of mesoderm chromatin states, and support a model in which developmental canalization is not a rigid irreversible path, but a highly plastic trajectory. The BAF chromatin-remodelling complex ATPase gene Brm safeguards cell identity during directed cardiogenesis of mouse embryonic stem cells.

Non‐invasive detection of colorectal cancer with blood‐based markers is a critical clinical need. Here we describe a phased mass spectrometry‐based approach for the discovery, screening, and validation of circulating protein biomarkers with diagnostic value. Initially, we profiled human primary tumor tissue epithelia and characterized about 300 secreted and cell surface candidate glycoproteins. These candidates were then screened in patient systemic circulation to identify detectable candidates in blood plasma. An 88‐plex targeting method was established to systematically monitor these proteins in two large and independent cohorts of plasma samples, which generated quantitative clinical datasets at an unprecedented scale. The data were deployed to develop and evaluate a five‐protein biomarker signature for colorectal cancer detection. Synopsis A five‐protein biomarker signature discovered and validated by mass spectrometry can accurately predict colorectal cancer (CRC) diagnosis non‐invasively from a blood sample. Secreted protein biomarker candidates discovered in tumor tissue were detected in the circulation of healthy and CRC subjects. A five‐protein predictive diagnostic signature was developed in a cohort of 100 healthy and 100 CRC subjects, and independently validated in an external cohort of 67 healthy and 202 CRC subjects. The protein biomarker signature was found to be more effective for CRC subjects with larger tumors. Graphical Abstract A five‐protein biomarker signature discovered and validated by mass spectrometry can accurately predict colorectal cancer (CRC) diagnosis non‐invasively from a blood sample.

mProphet, a computational tool for statistically validating selected reaction monitoring (SRM) mass spectrometry data, is described. Selected reaction monitoring (SRM) is a targeted mass spectrometric method that is increasingly used in proteomics for the detection and quantification of sets of preselected proteins at high sensitivity, reproducibility and accuracy. Currently, data from SRM measurements are mostly evaluated subjectively by manual inspection on the basis of ad hoc criteria, precluding the consistent analysis of different data sets and an objective assessment of their error rates. Here we present mProphet, a fully automated system that computes accurate error rates for the identification of targeted peptides in SRM data sets and maximizes specificity and sensitivity by combining relevant features in the data into a statistical model.

Enteroviruses (EVs) comprise a large genus of positive-sense, single-stranded RNA viruses whose members cause a number of important and widespread human diseases, including poliomyelitis, myocarditis, acute flaccid myelitis and the common cold. How EVs co-opt cellular functions to promote replication and spread is incompletely understood. Here, using genome-scale CRISPR screens, we identify the actin histidine methyltransferase SET domain containing 3 (SETD3) as critically important for viral infection by a broad panel of EVs, including rhinoviruses and non-polio EVs increasingly linked to severe neurological disease such as acute flaccid myelitis (EV-D68) and viral encephalitis (EV-A71). We show that cytosolic SETD3, independent of its methylation activity, is required for the RNA replication step in the viral life cycle. Using quantitative affinity purification–mass spectrometry, we show that SETD3 specifically interacts with the viral 2A protease of multiple enteroviral species, and we map the residues in 2A that mediate this interaction. 2A mutants that retain protease activity but are unable to interact with SETD3 are severely compromised in RNA replication. These data suggest a role of the viral 2A protein in RNA replication beyond facilitating proteolytic cleavage. Finally, we show that SETD3 is essential for in vivo replication and pathogenesis in multiple mouse models for EV infection, including CV-A10, EV-A71 and EV-D68. Our results reveal a crucial role of a host protein in viral pathogenesis, and suggest targeting SETD3 as a potential mechanism for controlling viral infections. The actin methyltransferase SETD3, by virtue of its ability to interact with the viral 2A protein and independently of its enzymatic activity, is necessary for RNA replication of several enteroviruses in cell culture and in vivo.