Ischemia reperfusion injury contributes to adverse cardiovascular diseases in part by producing a burst of reactive oxygen species that induce oxidations of many muscular proteins. Glutathionylation is one of the major protein cysteine oxidations that often serve as molecular mechanisms behind the pathophysiology associated with ischemic stress. Despite the biological significance of glutathionylation in ischemia reperfusion, identification of specific glutathionylated cysteines under ischemic stress has been limited. In this report, we have analyzed glutathionylation under oxygen-glucose deprivation (OGD) or repletion of nutrients after OGD (OGD/R) by using a clickable glutathione approach that specifically detects glutathionylated proteins. Our data find that palmitate availability induces a global level of glutathionylation and decreases cell viability during OGD/R. We have then applied a clickable glutathione-based proteomic quantification strategy, which enabled the identification and quantification of 249 glutathionylated cysteines in response to palmitate during OGD/R in the HL-1 cardiomyocyte cell line. The subsequent bioinformatic analysis found 18 glutathionylated cysteines whose genetic variants are associated with muscular disorders. Overall, our data report glutathionylated cysteines under ischemic stress that may contribute to adverse outcomes or muscular disorders.

Mass spectrometry-based proteomics is applied in SARS-CoV-2 research and is, moreover, being discussed as a novel method for SARS-CoV-2 diagnostics. However, the safe inactivation of coronaviruses by proteomics lysis buffers has not been systematically analyzed yet. Hence, for safety reasons a heating step prior to sample preparation is often performed. This step could be omitted once the safe inactivation with the typical buffers is proven. Here we test five different proteomics lysis buffers-4% SDS, 1% SDC, TFA, 6 M GdmCl, and 8 M urea-for their inactivation capacity of coronaviruses. Two representative human coronaviruses, namely HCoV-229E and HCoV-OC43, were used as surrogate for SARS-CoV-2. Lysis was performed at room temperature and at 95 °C for 5 min. Inactivation was confirmed by the absence of a cytopathic effect in MRC-5 cells, and equivocal results were further confirmed by serial passaging and quantitative real-time PCR. While at room temperature SDS, SDC, and TFA inactivated both coronaviruses, and GdmCl and urea resulted in partially incomplete inactivation. This demonstrates that care should be taken when choosing lysis buffers for proteomics analysis of coronaviruses, because some buffers do not ensure inactivation and, hence, biosafety during the further sample preparation.

A method for representing and comparing distributions of N-linked glycans located at specific sites on proteins is presented. The representation takes the form of a simple mass spectrum for a given peptide sequence, with each peak corresponding to a different glycopeptide. The mass (in place of m/z) of each peak is that of the glycan mass, and its abundance corresponds to its relative abundance in the electrospray MS1 spectrum. This provides a facile means of representing all identifiable glycopeptides arising from a single protein "sequon" on a specific sequence, thereby enabling the comparison and searching of these distributions as routinely done for mass spectra. Likewise, these reference glycopeptide abundance distribution spectra (GADS) can be stored in searchable libraries. A set of such libraries created from available data is provided along with an adapted version of the widely used NIST-MS library-search software. Since GADS contain only MS1 abundances and identifications, they are equally suitable for expressing collision-induced fragmentation and electron-transfer dissociation determinations of glycopeptide identity. Comparisons of GADS for N-glycosylated sites on several proteins, especially the SARS-CoV-2 spike protein, demonstrate the potential reproducibility of GADS and their utility for comparing site-specific distributions.

Tissue microenvironment properties like blood flow, extracellular matrix, or proximity to immune-infiltrate are important regulators of cell biology. However, methods to study regional protein expression in the native tissue environment are limited. To address this need, we developed a novel approach to visualize, purify, and measure proteins in situ using automated spatially targeted optical microproteomics (AutoSTOMP). Here, we report custom codes to specify regions of heterogeneity in a tissue section and UV-biotinylate proteins within those regions. We have developed liquid chromatography-mass spectrometry (LC-MS)/MS-compatible biochemistry to purify those proteins and label-free quantification methodology to determine protein enrichment in target cell types or structures relative to nontarget regions in the same sample. These tools were applied to (a) identify inflammatory proteins expressed by CD68+ macrophages in rat cardiac infarcts and (b) characterize inflammatory proteins enriched in IgG4+ lesions in human esophageal tissues. These data indicate that AutoSTOMP is a flexible approach to determine regional protein expression in situ on a range of primary tissues and clinical biopsies where current tools and sample availability are limited.

Acquired resistance to MAPK inhibitors limits the clinical efficacy in melanoma treatment. We and others have recently shown that BRAF inhibitor (BRAFi)-resistant melanoma cells can develop a dependency on the therapeutic drugs to which they have acquired resistance, creating a vulnerability for these cells that can potentially be exploited in cancer treatment. In drug-addicted melanoma cells, it was shown that this induction of cell death was preceded by a specific ERK2-dependent phenotype switch; however, the underlying molecular mechanisms are largely lacking. To increase the molecular understanding of this drug dependency, we applied a mass spectrometry-based proteomic approach on BRAFi-resistant BRAFMUT 451Lu cells, in which ERK1, ERK2, and JUNB were silenced separately using CRISPR-Cas9. Inactivation of ERK2 and, to a lesser extent, JUNB prevents drug addiction in these melanoma cells, while, conversely, knockout of ERK1 fails to reverse this phenotype, showing a response similar to that of control cells. Our analysis reveals that ERK2 and JUNB share comparable proteome responses dominated by reactivation of cell division. Importantly, we find that EMT activation in drug-addicted melanoma cells upon drug withdrawal is affected by silencing ERK2 but not ERK1. Moreover, transcription factor (regulator) enrichment shows that PIR acts as an effector of ERK2 and phosphoproteome analysis reveals that silencing of ERK2 but not ERK1 leads to amplification of GSK3 kinase activity. Our results depict possible mechanisms of drug addiction in melanoma, which may provide a guide for therapeutic strategies in drug-resistant melanoma.

Presentation of antigens by human leukocyte antigen (HLA) complexes at the cell surface is a key process in the immune response. The α-chain, containing the peptide-binding groove, is one of the most polymorphic proteins in the proteome. All HLA class I α-chains carry a conserved N-glycosylation site, but little is known about its nature and function. Here, we report an in-depth characterization of N-glycosylation features of HLA class I molecules. We observe that different HLA-A α-chains carry similar glycosylation, distinctly different from the HLA-B, HLA-C, and HLA-F α-chains. Although HLA-A displays the broadest variety of glycan characteristics, HLA-B α-chains carry mostly mature glycans, and HLA-C and HLA-F α-chains carry predominantly high-mannose glycans. We expected these glycosylation features to be directly linked to cellular localization of the HLA complexes. Indeed, analyzing HLA class I complexes from crude plasma and inner membrane-enriched fractions confirmed that most HLA-B complexes can be found at the plasma membrane, while most HLA-C and HLA-F molecules reside in the endoplasmic reticulum and Golgi membrane, and HLA-A molecules are more equally distributed over these cellular compartments. This allotype-specific cellular distribution of HLA molecules should be taken into account when analyzing peptide antigen presentation by immunopeptidomics.

Recent advances in sample preparation enable label-free mass spectrometry (MS)-based proteome profiling of small numbers of mammalian cells. However, specific devices are often required to downscale sample processing volume from the standard 50-200 μL to sub-μL for effective nanoproteomics, which greatly impedes the implementation of current nanoproteomics methods by the proteomics research community. Herein, we report a facile one-pot nanoproteomics method termed SOPs-MS (surfactant-assisted one-pot sample processing at the standard volume coupled with MS) for convenient robust proteome profiling of 50-1000 mammalian cells. Building upon our recent development of SOPs-MS for label-free single-cell proteomics at a low μL volume, we have systematically evaluated its processing volume at 10-200 μL using 100 human cells. The processing volume of 50 μL that is in the range of volume for standard proteomics sample preparation has been selected for easy sample handling with a benchtop micropipette. SOPs-MS allows for reliable label-free quantification of ∼1200-2700 protein groups from 50 to 1000 MCF10A cells. When applied to small subpopulations of mouse colon crypt cells, SOPs-MS has revealed protein signatures between distinct subpopulation cells with identification of ∼1500-2500 protein groups for each subpopulation. SOPs-MS may pave the way for routine deep proteome profiling of small numbers of cells and low-input samples.

Nonreceptor tyrosine kinases (NRTKs) represent an important class of signaling molecules driving diverse cellular pathways. Aberrant expression and hyperphosphorylation of TNK2, an NRTK, have been implicated in multiple cancers. However, the exact proteins and cellular events that mediate phenotypic changes downstream of TNK2 are unclear. Biological systems that employ proximity-dependent biotinylation methods, such as BioID, are being increasingly used to map protein-protein interactions, as they provide increased sensitivity in discovering interaction partners. In this study, we employed stable isotope labeling with amino acids in cell culture and BioID coupled to the biotinylation site identification technology (BioSITe) method that we recently developed to quantitatively explore the interactome of TNK2. By performing a controlled comparative analysis between full-length TNK2 and its truncated counterpart, we were able to not only identify site-level biotinylation of previously well-established TNK2 binders and substrates including NCK1, NCK2, CTTN, and STAT3, but also discover several novel TNK2 interacting partners. We also performed co-immunoprecipitation and immunofluorescence analysis to validate the interaction between TNK2 and CLINT1, a novel TNK2 interacting protein. Overall, this work reveals the power of the BioSITe method coupled to BioID and highlights several molecules that warrant further exploration to assess their functional significance in TNK2-mediated signaling.

Previous work employing five SARS-CoV-2 spike protein receptor-binding domain (RBD) constructs, comprising versions originally developed by Mt. Sinai or the Ragon Institute and later optimized in-house, revealed potential heterogeneity which led to questions regarding variable seropositivity assay performance. Each construct was subjected to N-deglycosylation and subsequent intact mass analysis, revealing significant deviations from predicted theoretical mass for all five proteins. Complementary tandem MS/MS analysis revealed the presence of an additional pyroGlu residue on the N-termini of the two Mt. Sinai RBD constructs, as well as on the N-terminus of the full-length spike protein from which they were derived, thus explaining the observed mass shift and definitively establishing the spike protein N-terminal sequence. Moreover, the observed mass additions for the three Ragon Institute RBD constructs were identified as variable N-terminal cleavage points within the signal peptide sequence employed for recombinant expression. To resolve this issue and minimize heterogeneity for further seropositivity assay development, the best-performing RBD construct was further optimized to exhibit complete homogeneity, as determined by both intact mass and tandem MS/MS analysis. This new RBD construct has been validated for seropositivity assay performance, is available to the greater scientific community, and is recommended for use in future assay development.

Nowadays, massive genomics and transcriptomics data can be generated at the single-cell level. However, proteomics in this setting is still a big challenge. Despite the great improvements in sensitivity and performance of mass spectrometry instruments and the better knowledge on sample preparation processing, it is widely acknowledged that multistep proteomics workflows may lead to substantial sample loss, especially when working with paucicellular samples. Still, in clinical fields, frequently limited sample amounts are available for downstream analysis, thereby hampering comprehensive characterization at protein level. To aim at better protein and peptide recoveries, we compare existing and novel approaches in the multistep sample preparation protocols for mass spectrometry studies, from sample collection, cell lysis, protein quantification, and electrophoresis/staining to protein digestion, peptide recovery, and LC-MS/MS instruments. From this critical evaluation, we conclude that the recent innovations and technologies, together with high quality management of samples, make proteomics on paucicellular samples possible, which will have immediate impact for the proteomics community.

The emergence of COVID-19 pandemic has engaged the scientific community around the globe in the rapid development of effective therapeutics and vaccines. Owing to its crucial role in the invasion of the host cell, spike (S) glycoprotein is one of the major targets in these studies. The S1 subunit of the S protein (S1 protein) accommodates the receptor-binding domain, which enables the initial binding of the virus to the host cell. Being a heavily glycosylated protein, numerous studies have investigated its glycan composition. However, none of the studies have explored the isomeric glycan distribution of this protein. Furthermore, this isomeric glycan distribution has never been compared to that in S1 proteins of other coronaviruses, severe acute respiratory syndrome coronavirus 1 and Middle East respiratory syndrome coronavirus, which were responsible for past epidemics. This study explores the uncharted territory of the isomeric glycan distribution in the coronaviruses' S1 protein using liquid chromatography coupled to tandem mass spectrometry. We believe that our data would facilitate future investigations to study the role of isomeric glycans in coronavirus viral pathogenesis.

To characterize the impact of metabolic disease on the peptidome of human and mouse pancreatic islets, LC-MS was used to analyze extracts of human and mouse islets, purified mouse alpha, beta, and delta cells, supernatants from mouse islet incubations, and plasma from patients with type 2 diabetes. Islets were obtained from healthy and type 2 diabetic human donors, and mice on chow or high fat diet. All major islet hormones were detected in lysed islets as well as numerous peptides from vesicular proteins including granins and processing enzymes. Glucose-dependent insulinotropic peptide (GIP) was not detectable. High fat diet modestly increased islet content of proinsulin-derived peptides in mice. Human diabetic islets contained increased content of proglucagon-derived peptides at the expense of insulin, but no evident prohormone processing defects. Diabetic plasma, however, contained increased ratios of proinsulin and des-31,32-proinsulin to insulin. Active GLP-1 was detectable in human and mouse islets but 100-1000-fold less abundant than glucagon. LC-MS offers advantages over antibody-based approaches for identifying exact peptide sequences, and revealed a shift toward islet insulin production in high fat fed mice, and toward proglucagon production in type 2 diabetes, with no evidence of systematic defective prohormone processing.

Metaproteomics is a powerful analytical approach that can assess the functional capabilities deployed by microbial communities in both environmental and biomedical microbiome settings. Yet, the mass spectra resulting from these mixed biological communities are challenging to obtain due to the high number of low intensity peak features. The use of multiple dimensions of chromatographic separation prior to mass spectrometry analyses has been applied to proteomics previously but can require increased sampling handling and instrument time. Here, we demonstrate an automated online comprehensive active modulation two-dimensional liquid chromatography method for metaproteome sample analysis. A high pH PLRP-S column was used in the first dimension followed by low pH separation in the second dimension using dual modulating C18 traps and a C18 column. This method increased the number of unique peptides found in ocean metaproteome samples by more than 50% when compared to a one-dimension separation while using the same amount of sample and instrument time.

High abundant protein depletion is a common strategy applied to increase analytical depth in global plasma proteomics experiment setups. The standard strategies for depletion of the highest abundant proteins currently rely on multiple-use HPLC columns or multiple-use spin columns. Here we evaluate the performance of single-use spin columns for plasma depletion and show that the single-use spin reduces handling time by allowing parallelization and is easily adapted to a nonspecialized lab environment without reducing the high plasma proteome coverage and reproducibility. In addition, we evaluate the effect of viral heat inactivation on the plasma proteome, an additional step in the plasma preparation workflow that allows the sample preparation of SARS-Cov2-infected samples to be performed in a BSL3 laboratory, and report the advantage of performing the heat inactivation postdepletion. We further show the possibility of expanding the use of the depletion column cross-species to macaque plasma samples. In conclusion, we report that single-use spin columns for high abundant protein depletion meet the requirements for reproducibly in in-depth plasma proteomics and can be applied on a common animal model while also reducing the sample handling time.