The throughput of mass spectrometry (MS) proteomics can be increased substantially by multiplexing that enables parallelization of data acquisition. Such parallelization in the mass domain (plexDIA) and the time domain (timePlex) increases the density of mass spectra and the overlap between ions originating from different precursors, potentially complicating their analysis. To enhance sequence identification and quantification from such spectra, we developed an open source software for Joint Modeling of mass spectra: JMod. It uses the intrinsic structure in the spectra and explicitly models overlapping peaks as linear superpositions of their components. This modeling enabled performing 9-plexDIA using 2 Da offset PSMtags by deconvolving the resulting overlapping isotopic envelopes in both MS1 and MS2 space. The results demonstrate 9-fold higher throughput with preserved quantitative accuracy and coverage depth. This support for smaller mass offsets increases multiplexing capacity and thus proteomic throughput for a given plexDIA tag, and we demonstrate this generalizability with diethyl labeling. By supporting enhanced decoding of DIA spectra multiplexed in the mass and time domains, JMod provides an open and flexible software that enables increasing the throughput of sensitive proteomics. ### Competing Interest Statement K.M.D., J.D., H.S. and N.S. are listed as inventors on a patent application for timePlex which uses JMod. H.S., S.S., M.Y. and N.S. are listed as inventors on a patent application for PSMtag.

Mass spectrometry-based proteomics enables comprehensive characterization of protein abundance, function, and interactions. Label-free approaches are simple to implement but challenging to scale to thousands of samples per day. Multiplexed techniques, such as plexDIA, can address these limitations but remain restricted by the lack of mass tags optimized for data-independent acquisition (DIA) workflows. Here, we present a systematic approach screening a library of 576 compounds that identifies several small molecules that, when conjugated to peptides, improve their detection and sequence identification by mass spectrometry. The lead molecule, PSMtag, substantially increases the detection of fragment b-ions, which increases the confidence of sequence identification and enhances de novo sequencing. PSMtags allow 9-plexDIA, using only stable isotopes of carbon, oxygen and nitrogen. As a result, it allows simultaneously increasing proteome coverage and sample throughput for plexDIA workflows without compromising quantitative accuracy. We demonstrate 240 samples-per-day with 9-plexDIA, while acquiring 28,359 protein data points in the same time label-free methods acquire 4,340. Our approach constitutes an expandable framework for designing mass tags to overcome existing limitations in multiplexed proteomics and provides plexDIA reagents capable of analyzing over 1,000 samples per day when using 10 minute runs. By facilitating higher throughput and improved identification, this innovation holds significant potential for accelerating proteomic studies across diverse biological and clinical applications. ### Competing Interest Statement H.S., M.Y., S.S., D.B.S., M.A., W.V., A.Y., M.A.L., B.P. and N.S. are listed as inventors on a patent application for the tags described in this paper.

While non-mammalian embryos often rely on spatial pre-patterning, mammalian development has long been thought to begin with equivalent blastomeres. However, emerging evidence challenges this. Here, using multiplexed and label-free single-cell proteomics, we identify over 300 asymmetrically abundant proteins-many involved in protein degradation and transport-dividing mouse 2-cell-stage blastomeres into two distinct clusters, which we term alpha and beta. These proteomic asymmetries are detectable as early as the zygote stage, intensify by the 4-cell stage, and correlate with the sperm entry site, implicating fertilization as a symmetry-breaking event. Splitting 2-cell-stage embryos into halves reveals that beta blastomeres possess greater developmental potential than alpha blastomeres. Similar clustering and protein enrichment patterns found in human 2-cell embryos suggest this early asymmetry might be conserved. These findings uncover a previously unrecognized proteomic pre-patterning triggered by fertilization in mammalian embryos, with important implications for understanding totipotency and early lineage bias.

Liquid chromatography-mass spectrometry (LC-MS) can enable precise and accurate quantification of analytes at high-sensitivity, but the rate at which samples can be analyzed remains limiting. Throughput can be increased by multiplexing samples in the mass domain with plexDIA, yet multiplexing along one dimension will only linearly scale throughput with plex. To enable combinatorial-scaling of proteomics throughput, we developed a complementary multiplexing strategy in the time domain, termed 'timePlex'. timePlex staggers and overlaps the separation periods of individual samples. This strategy is orthogonal to isotopic multiplexing, which enables combinatorial multiplexing in mass and time domains when paired together, and thus multiplicatively increased throughput. We demonstrate this with 3-timePlex and 3-plexDIA, enabling the multiplexing of 9 samples per LC-MS run, and 3-timePlex and 9-plexDIA exceeding 500 samples / day with a combinatorial 27-plex. Crucially, timePlex supports sensitive analyses, including of single cells. These results establish timePlex as a methodology for label-free multiplexing and combinatorial scaling of the throughput of LC-MS proteomics. We project this combined approach will eventually enable an increase in throughput exceeding 1,000 samples / day.

Pre-patterning of the embryo, driven by spatially localized factors, is a common feature across several non-mammalian species 1-4 . However, mammals display regulative development and thus it was thought that blastomeres of the embryo do not show such pre-patterning, contributing randomly to the three lineages of the blastocyst: the epiblast, primitive endoderm and trophectoderm that will generate the new organism, the yolk sac and placenta respectively 4-6 . Unexpectedly, early blastomeres of mouse and human embryos have been reported to have distinct developmental fates, potential and heterogeneous abundance of certain transcripts 7-12 . Nevertheless, the extent of the earliest intra-embryo differences remains unclear and controversial. Here, by utilizing multiplexed and label-free single-cell proteomics by mass-spectrometry 13 , we show that 2-cell mouse and human embryos contain an alpha and a beta blastomere as defined by differential abundance of hundreds of proteins exhibiting strong functional enrichment for protein synthesis, transport, and degradation. Such asymmetrically distributed proteins include Gps1 and Nedd8, depletion or overexpression of which in one blastomere of the 2-cell embryo impacts lineage segregation. These protein asymmetries increase at 4-cell stage. Intriguingly, halved mouse zygotes display asymmetric protein abundance that resembles alpha and beta blastomeres, suggesting differential proteome localization already within zygotes. We find that beta blastomeres give rise to a blastocyst with a higher proportion of epiblast cells than alpha blastomeres and that vegetal blastomeres, which are known to have a reduced developmental potential, are more likely to be alpha. Human 2-cell blastomeres also partition into two clusters sharing strong concordance with clusters found in mouse, in terms of differentially abundant proteins and functional enrichment. To our knowledge, this is the first demonstration of intra-zygotic and inter-blastomere proteomic asymmetry in mammals that has a role in lineage segregation.

Mycobacterium bovis Bacillus Calmette-Guérin (BCG) protects against childhood tuberculosis; and unlike most vaccines, BCG broadly impacts immunity to other pathogens and even some cancers. Early in the COVID-19 pandemic, epidemiological studies identified a protective association between BCG vaccination and outcomes of SARS-CoV-2, but the associations in later studies were inconsistent. We sought possible reasons and noticed the study populations often lived in the same country. Since individuals from the same regions can share common ancestors, we hypothesized that genetic background could influence associations between BCG and SARS-CoV-2. To explore this hypothesis in a controlled environment, we performed a pilot study using Diversity Outbred mice. First, we identified amino acid sequences shared by BCG and SARS-CoV-2 spike protein. Next, we tested for IgG reactive to spike protein from BCG-vaccinated mice. Sera from some, but not all, BCG-vaccinated Diversity Outbred mice contained higher levels of IgG cross-reactive to SARS-CoV-2 spike protein than sera from BCG-vaccinated C57BL/6J inbred mice and unvaccinated mice. Although larger experimental studies are needed to obtain mechanistic insight, these findings suggest that genetic background may be an important variable contributing to different associations observed in human randomized clinical trials evaluating BCG vaccination on SARS-CoV-2 and COVID-19.

Huntington’s disease (HD) is a neurodegenerative disorder caused by an inherited unstable HTT CAG repeat that expands further, thereby eliciting a disease process that may be initiated by polyglutamine-expanded huntingtin or a short polyglutamine-product. Phosphorylation of selected candidate residues is reported to mediate polyglutamine-fragment degradation and toxicity. Here to support the discovery of phosphosites involved in the life-cycle of (full-length) huntingtin, we employed mass spectrometry-based phosphoproteomics to systematically identify sites in purified huntingtin and in the endogenous protein by proteomic and phosphoproteomic analyses of members of an HD neuronal progenitor cell panel. Our results bring total huntingtin phosphosites to 95, with more located in the N-HEAT domain relative to numbers in the Bridge and C-HEAT domains. Moreover, phosphorylation of C-HEAT Ser2550 by cAMP-dependent protein kinase (PKA), the top hit in kinase activity screens, was found to hasten huntingtin degradation, such that levels of the catalytic subunit (PRKACA) were inversely related to huntingtin levels. Taken together, these findings highlight categories of phosphosites that merit further study and provide a phosphosite kinase pair (pSer2550-PKA) with which to investigate the biological processes that regulate huntingtin degradation and thereby influence the steady state levels of huntingtin in HD cells.

The Bacillus Calmette-Guérin (BCG) vaccine, the only vaccine against tuberculosis, induces cross-protection against pathogens unrelated to Mycobacterium, including viruses. Epidemiological studies have identified potential benefits of BCG vaccination against SARS-CoV-2 infection. While BCG’s heterologous effects have been widely attributable to trained immunity, we hypothesized BCG vaccination could induce cross-reactive antibodies against the spike protein of SARS-CoV-2 Wuhan-Hu-1. The concentration of IgG reactive to SARS-CoV-2 spike protein from the sera of BCG-vaccinated, Diversity Outbred (DO) mice and C57BL/6J inbred mice was measured using ELISA. Sera from 10/15 BCG-vaccinated DO mice possessed more IgG reactive to recombinant spike protein than sera from BCG-vaccinated C57BL/6J mice and unvaccinated DO mice. Amino acid sequences common to BCG cell wall/membrane proteins and SARS-CoV-2 spike protein were identified as potential antigen candidates for future study. These results imply a humoral mechanism, influenced by genotype, by which BCG vaccination could confer immunity to SARS-CoV-2. Graphic Abstract

Major aims of single-cell proteomics include increasing the consistency, sensitivity and depth of protein quantification, especially for proteins and modifications of biological interest. Here, to simultaneously advance all these aims, we developed prioritized Single-Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while maximizing instrument time spent analyzing identifiable peptides, thus increasing proteome depth. These strategies increased the sensitivity, data completeness and proteome coverage over twofold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport, similarly across both treatment conditions. This covariation is coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at http://scp.slavovlab.net/pSCoPE .

Loss-of-function mutations in the secreted enzyme ADAMTS7 (a disintegrin and metalloproteinase with thrombospondin motifs 7) are associated with protection for coronary artery disease (CAD). ADAMTS7 catalytic inhibition has been proposed as a therapeutic strategy for treating CAD; however, the lack of an endogenous substrate has hindered the development of activity-based biomarkers. To identify ADAMTS7 extracellular substrates and their cleavage sites relevant to vascular disease, we used TAILS (terminal amine isotopic labeling of substrates), a method for identifying protease-generated neo-N termini. We compared the secreted proteome of vascular smooth muscle and endothelial cells expressing either full-length mouse ADAMTS7 WT, catalytic mutant ADAMTS7 E373Q or a control luciferase adenovirus. Significantly enriched N-terminal cleavage sites in ADAMTS7 WT samples were compared to the negative control conditions and filtered for stringency, resulting in catalogs of high confidence candidate ADAMTS7 cleavage sites from our three independent TAILS experiments. Within the overlap of these discovery sets, we identified 24 unique cleavage sites from 16 protein substrates, including cleavage sites in EFEMP1 (EGF-containing fibulin-like extracellular matrix protein 1/Fibulin-3). The ADAMTS7 TAILS preference for EMEMP1 cleavage at the amino acids 123.124 over the adjacent 124.125 site was validated using both endogenous EFEMP1 and purified EFEMP1 in a binary in vitro cleavage assay. Collectively our TAILS discovery experiments have uncovered hundreds of potential substrates and cleavage sites to explore disease related biological substrates and facilitate activity-based ADAMTS7 biomarker development.

Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using three-plex non-isobaric mass tags, plexDIA enables quantification of threefold more protein ratios among nanogram-level samples. Using 1-hour active gradients, plexDIA quantified ~8,000 proteins in each sample of labeled three-plex sets and increased data completeness, reducing missing data more than twofold across samples. Applied to single human cells, plexDIA quantified ~1,000 proteins per cell and achieved 98% data completeness within a plexDIA set while using ~5 minutes of active chromatography per cell. These results establish a general framework for increasing the throughput of sensitive and quantitative protein analysis. Proteomics of small sample sizes using data-independent acquisition methods achieves higher throughput with multiplexing.

Single-cell proteomics analysis requires sensitive, quantitatively accurate, widely accessible, and robust methods. To meet these requirements, the Single-Cell ProtEomics (SCoPE2) protocol was developed as a second-generation method for quantifying hundreds to thousands of proteins from limited samples, down to the level of a single cell. Experiments using this method have achieved quantifying over 3,000 proteins across 1,500 single mammalian cells (500-1,000 proteins per cell) in 10 days of mass spectrometer instrument time. SCoPE2 leverages a freeze-heat cycle for cell lysis, obviating the need for clean-up of single cells and consequently reducing sample losses, while expediting sample preparation and simplifying its automation. Additionally, the method uses an isobaric carrier, which aids protein identification and reduces sample losses. This video protocol provides detailed guidance to enable the adoption of automated single-cell protein analysis using only equipment and reagents that are widely accessible. We demonstrate critical steps in the procedure of preparing single cells for proteomic analysis, from harvesting up to injection to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Additionally, viewers are guided through the principles of experimental design with the isobaric carrier, quality control for both isobaric carrier and single-cell preparations, and representative results with a discussion of limitations of the approach.

Major aims of single-cell proteomics include increasing the consistency, sensitivity, and depth of protein quantification, especially for proteins and modifications of biological interest. To simultaneously advance all these aims, we developed prioritized Single Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while analyzing identifiable peptides at full duty-cycle, thus increasing proteome depth. These strategies increased the sensitivity, data completeness, and proteome coverage over 2-fold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport. This protein covariation within a treatment condition was similar across the treatment conditions and coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at: scp.slavovlab.net/pSCoPE Abstract Figure

ADVERTISEMENT RETURN TO ISSUEHighlightsNEXTBeyond Protein Sequence: Protein Isomerization in Alzheimer’s DiseaseHarrison SpechtHarrison SpechtDepartment of Bioengineering, Northeastern University, Boston, Massachusetts 02115, United StatesBarnett Institute, Northeastern University, Boston, Massachusetts 02115, United StatesMore by Harrison Spechthttps://orcid.org/0000-0003-3151-6803 and Nikolai Slavov*Nikolai SlavovDepartment of Bioengineering, Northeastern University, Boston, Massachusetts 02115, United StatesBarnett Institute, Northeastern University, Boston, Massachusetts 02115, United States*Email: [email protected], [email protected]More by Nikolai Slavovhttps://orcid.org/0000-0003-2035-1820Cite this: J. Proteome Res. 2022, 21, 2, 299–300Publication Date (Web):February 4, 2022Publication History Published online4 February 2022Published inissue 4 February 2022https://doi.org/10.1021/acs.jproteome.2c00016Copyright © Published 2022 by American Chemical SocietyRIGHTS & PERMISSIONSArticle Views268Altmetric-Citations1LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit Read OnlinePDF (426 KB) Get e-AlertscloseSUBJECTS:Chromatography,Isomerization,Molecular structure,Nervous system diseases,Peptides and proteins Get e-Alerts

Major aims of single-cell proteomics include increasing the consistency, sensitivity, and depth of protein quantification, especially for proteins and modifications of biological interest. To simultaneously advance all these aims, we developed prioritized Single Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while analyzing identifiable peptides at full duty-cycle, thus increasing proteome depth. These strategies increased the sensitivity, data completeness, and proteome coverage over 2-fold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport. This protein covariation within a treatment condition was similar across the treatment conditions and coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at: scp.slavovlab.net/pSCoPE The files contained in this .zip directory are necessary for replicating the analysis and figures associated with the pSCoPE manuscript.

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug-treatment in cells and tissues but are presently lacking. Here we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response and resistance to therapy.

Protocol for preparing single cells for mass-spec analysis by SCoPE2 as described by Specht et al., doi: 10.1101/665307 (2019) and Specht et al., Genome Biology, doi: 10.1186/s13059-021-02267-5 (2021). For a detailed protocol paper, see Petelski A, Emmott E, Leduc A, Huffman RG, Specht H, Perlman D, Slavov N (2021) Multiplexed single-cell proteomics using SCoPE2 Nature Protocols (in press)

Many biological systems are composed of diverse single cells. This diversity necessitates functional and molecular single-cell analysis. Single-cell protein analysis has long relied on affinity reagents, but emerging mass-spectrometry methods (either label-free or multiplexed) have enabled quantifying >1,000 proteins per cell while simultaneously increasing the specificity of protein quantification. Here we describe the Single Cell ProtEomics (SCoPE2) protocol, which uses an isobaric carrier to enhance peptide sequence identification. Single cells are isolated by FACS or CellenONE into multiwell plates and lysed by Minimal ProteOmic sample Preparation (mPOP), and their peptides labeled by isobaric mass tags (TMT or TMTpro) for multiplexed analysis. SCoPE2 affords a cost-effective single-cell protein quantification that can be fully automated using widely available equipment and scaled to thousands of single cells. SCoPE2 uses inexpensive reagents and is applicable to any sample that can be processed to a single-cell suspension. The SCoPE2 workflow allows analyzing ~200 single cells per 24 h using only standard commercial equipment. We emphasize experimental steps and benchmarks required for achieving quantitative protein analysis.