Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible coronavirus responsible for the pandemic coronavirus disease 2019 (COVID-19), which has had a devastating impact on society. Here, we summarize proteomic research that has helped elucidate hallmark proteins associated with the disease with respect to both short- and long-term diagnosis and prognosis. Additionally, we review the highly variable humoral response associated with COVID-19 and the increased risk of autoimmunity.

Protein phosphorylation in prokaryotes has gained more attention in recent years as several studies linked it to regulatory and signaling functions, indicating importance similar to protein phosphorylation in eukaryotes. Studies on bacterial phosphorylation have so far been conducted using manual or HPLC-supported phosphopeptide enrichment, whereas automation of phosphopeptide enrichment has been established in eukaryotes, allowing for high-throughput sampling. To facilitate the prospect of studying bacterial phosphorylation on a systems level, we here established an automated Ser/Thr/Tyr phosphopeptide enrichment workflow on the Agilent AssayMap platform. We present optimized buffer conditions for TiO2 and Fe(III)-NTA-IMAC cartridge-based enrichment and the most advantageous, species-specific loading amounts for Streptococcus pyogenes, Listeria monocytogenes, and Bacillus subtilis. For higher sample amounts (≥250 μg), we observed superior performance of the Fe(III)-NTA cartridges, whereas for lower sample amounts (≤100 μg), TiO2-based enrichment is equally efficient. Both cartridges largely enriched the same set of phosphopeptides, suggesting no improvement of peptide yield by the complementary use of the two cartridges. Our data represent, to the best of our knowledge, the largest phosphoproteome identified in a single study for each of these bacteria.

The prolyl-alanyl-specific endoprotease (EndoPro) is an industrial enzyme produced in Aspergillus niger. EndoPro is mainly used for food applications but also as a protease in proteomics. In-depth characterization of this enzyme is essential to understand its structural features and functionality. However, there is a lack of analytical methods capable of maintaining both the structural and functional integrity of separated proteoforms. In this study, we developed an anion exchange (AEX) method coupled to native mass spectrometry (MS) for profiling EndoPro proteoforms. Moreover, we investigated purified EndoPro proteoforms with complementary MS-based approaches, including released N-glycan and glycopeptide analysis, to obtain a comprehensive overview of the structural heterogeneity. We showed that EndoPro has at least three sequence variants and seven N-glycosylation sites occupied by high-mannose glycans that can be phosphorylated. Each glycosylation site showed high microheterogeneity with ∼20 glycans per site. The functional characterization of fractionated proteoforms revealed that EndoPro proteoforms remained active after AEX-separation and the specificity of these proteoforms did not depend on N-glycan phosphorylation. Nevertheless, our data confirmed a strong pH dependence of EndoPro cleavage activity. Altogether, our study demonstrates that AEX-MS is an excellent tool to characterize complex industrial enzymes under native conditions.

Successful proteome analysis requires reliable sample preparation beginning with protein solubilization and ending with a sample free of contaminants, ready for downstream analysis. Most proteome sample preparation technologies utilize precipitation or filter-based separation, both of which have significant disadvantages. None of the current technologies are able to prepare both intact proteins or digested peptides. Here, we introduce a reversible protein tag, ProMTag, that enables whole proteome capture, cleanup, and release of intact proteins for top-down analysis. Alternatively, the addition of a novel Trypsin derivative to the workflow generates peptides for bottom-up analysis. We show that the ProMTag workflow yields >90% for intact proteins and >85% for proteome digests. For top-down analysis, ProMTag cleanup improves resolution on 2D gels; for bottom-up exploration, this methodology produced reproducible mass spectrometry results, demonstrating that the ProMTag method is a truly universal approach that produces high-quality proteome samples compatible with multiple downstream analytical techniques. Data are available via ProteomeXchange with identifier PXD027799.

Serum-derived extracellular vesicles (EVs) are a promising source of biomarkers; however, major challenges in EV separation and proteomic profiling remain for isolating EVs from a small amount, that is, on the microliter scale, of human serum while minimizing the contamination of blood proteins and lipoprotein particles coeluting in EV preparations. Herein we have developed a column-based CD9-antibody-immobilized high-performance liquid chromatography immunoaffinity chromatography(CD9-HPLC-IAC) technology for EV isolation from a microliter scale of serum for downstream proteomic analysis. The CD9-HPLC-IAC method achieved EV isolation from 40 μL of serum in 30 min with a yield of 8.0 × 109 EVs, where EVs were further processed with a postcolumn cleaning step using the 50 kDa molecular weight cut-off filter for the buffer exchange, concentration, and reduction of potentially coeluting serum proteins. In total, 482 proteins were identified in EVs by using liquid chromatography tandem mass spectrometry, including the common exosomal markers such as CD63, CD81, CD82, Alix, and TSG101. The statistical analysis of EV protein content showed that the top 10 serum proteins in EVs were significantly decreased by using the CD9-HPLC-IAC method compared with the use of ultracentrifugation (p = 0.001) and size exclusion chromatography (p = 0.009), and apolipoproteins were significantly reduced 4.8-fold compared with the SEC method (p < 0.001). The result demonstrates the potential of the CD9-HPLC-IAC method for the efficient isolation and proteomic characterization of EVs from a microscale volume of serum.

Cell signaling involves a network of protein-protein interactions and post-translational modifications that govern cellular responses to environmental cues. To understand and ultimately modulate these signaling pathways to confront disease, the complex web of proteins that becomes phosphorylated after extracellular stimulation has been studied using mass spectrometry-based proteomics methods. To complement prior work and fully characterize all phosphorylated proteins after the stimulation of cell signaling, we developed K-BMAPS (kinase-catalyzed biotinylation to map signaling), which utilizes ATP-biotin as a kinase cosubstrate to biotin label substrates. As a first application of the K-BMAPS method, the well-characterized epidermal growth factor receptor (EGFR) kinase signaling pathway was monitored by treating epidermal growth factor (EGF)-stimulated HeLa lysates with ATP-biotin, followed by streptavidin enrichment and quantitative mass spectrometry analysis. On the basis of the dynamic phosphoproteins identified, a pathway map was developed considering functional categories and known interactors of EGFR. Remarkably, 94% of the K-BMAPS hit proteins were included in the EGFR pathway map. With many proteins involved in transcription, translation, cell adhesion, and GTPase signaling, K-BMAPS identified phosphoproteins were associated with late and continuous signaling events. In summary, the K-BMAPS method is a powerful tool to map the dynamic phosphorylation governing cell signaling pathways.

Science is full of overlooked and undervalued research waiting to be rediscovered. Proteomics is no exception. In this perspective, we follow the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing tryptic peptides across animal species. This pioneering work directly led to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics. In the decades following, proteins continued to provide essential clues on evolutionary history. While technology has continued to improve, contemporary proteomics has strayed from this larger biological context, rarely comparing species or asking how protein structure, function, and interactions have evolved. Here we recombine proteomics with molecular phylogenetics, highlighting the value of framing proteomic results in a larger biological context and how almost forgotten research, though technologically surpassed, can still generate new ideas and illuminate our work from a different perspective. Though it is infeasible to read all research published on a large topic, looking up older papers can be surprisingly rewarding when rediscovering a "gem" at the end of a long citation chain, aided by digital collections and perpetually helpful librarians. Proper literature study reduces unnecessary repetition and allows research to be more insightful and impactful by truly standing on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/) as dataset MSV000087993.

Here, we present an integrated multivariate, univariate, network reconstruction and differential analysis of metabolite-metabolite and metabolite-lipid association networks built from an array of 18 serum metabolites and 110 lipids identified and quantified through nuclear magnetic resonance spectroscopy in a cohort of 248 patients, of which 22 died and 82 developed a poor functional outcome within 3 months from acute ischemic stroke (AIS) treated with intravenous recombinant tissue plasminogen activator. We explored differences in metabolite and lipid connectivity of patients who did not develop a poor outcome and who survived the ischemic stroke from the related opposite conditions. We report statistically significant differences in the connectivity patterns of both low- and high-molecular-weight metabolites, implying underlying variations in the metabolic pathway involving leucine, glycine, glutamine, tyrosine, phenylalanine, citric, lactic, and acetic acids, ketone bodies, and different lipids, thus characterizing patients' outcomes. Our results evidence the promising and powerful role of the metabolite-metabolite and metabolite-lipid association networks in investigating molecular mechanisms underlying AIS patient's outcome.

Chronic low-dose exposure to organophosphorus pesticides is associated with the risk of neurodegenerative disease. The mechanism of neurotoxicity is independent of acetylcholinesterase inhibition. Adducts on tyrosine, lysine, threonine, and serine can occur after exposure to organophosphorus pesticides, the most stable being adducts on tyrosine. Rabbit monoclonal 1C6 to diethoxyphosphate-modified tyrosine (depY) was created by single B cell cloning. The amino acid sequence and binding constant (Kd 3.2 × 10-8 M) were determined. Cultured human neuroblastoma SH-SY5Y and mouse neuroblastoma N2a cells incubated with a subcytotoxic dose of 10 μM chlorpyrifos oxon contained depY-modified proteins detected by monoclonal 1C6 on Western blots. depY-labeled peptides from tryptic digests of cell lysates were immunopurified by binding to immobilized 1C6. Peptides released with 50% acetonitrile and 1% formic acid were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) on an Orbitrap Fusion Lumos mass spectrometer. Protein Prospector database searches identified 51 peptides modified on tyrosine by diethoxyphosphate in SH-SY5Y cell lysate and 73 diethoxyphosphate-modified peptides in N2a cell lysate. Adducts appeared most frequently on the cytoskeleton proteins tubulin, actin, and vimentin. It was concluded that rabbit monoclonal 1C6 can be useful for studies that aim to understand the mechanism of neurotoxicity resulting from low-dose exposure to organophosphorus pesticides.

Severe coronavirus disease 2019 (COVID-19) infection may lead to lung injury, multi-organ failure, and eventually death. Cytokine storm due to excess cytokine production has been associated with fatality in severe infections. However, the specific molecular signatures associated with the elevated immune response are yet to be elucidated. We performed a mass-spectrometry-based proteomic and metabolomic analysis of COVID-19 plasma samples collected at two time points. Using Orbitrap Fusion LC-MS/MS-based label-free proteomic analysis, we identified around 10 significant proteins, 32 significant peptides, and 5 metabolites that were dysregulated at the severe time points. Few of these proteins identified by quantitative proteomics were validated using the multiple reaction monitoring (MRM) assay. Integrated pathway analysis using distinct proteomic and metabolomic signatures revealed alterations in complement and coagulation cascade, platelet aggregation, myeloid leukocyte activation pathway, and arginine metabolism. Further, we highlight the role of leukocyte activation and arginine metabolism in COVID-19 pathogenesis and targeting these pathways for COVID-19 therapeutics.