Abstract: Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1–4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.

Abstract: Virus inactivation is a prerequisite for safe handling of high-risk infectious samples. β-Propiolactone (BPL) is an established reagent with proven virucidal efficacy. BPL primarily reacts with DNA, RNA, and amino acids. The latter may modify antigenic protein epitopes interfering with binding properties of affinity reagents such as antibodies and aptamers used in affinity proteomic screens. We investigated (i) the impact of BPL treatment on the analysis of protein levels in plasma samples using the aptamer-based affinity proteomic platform SomaScan and (ii) effects on protein detection in conditioned medium samples using the proximity extension assay-based Olink Target platform. In the former setup, BPL-treated and native plasma samples from patients with ovarian cancer (<i>n</i> = 12) and benign diseases (<i>n</i> = 12) were analyzed using the SomaScan platform. In the latter, conditioned media samples collected from cultured T cells with (<i>n</i> = 3) or without (<i>n</i> = 3) anti-CD3 antibody stimulation were analyzed using the Olink Target platform. BPL-related changes in protein detection were evaluated comparing native and BPL-treated states, simulating virus inactivation, and impact on measurable group differences was assessed. While approximately one-third of SomaScan measurements were significantly changed by the BPL treatment, a majority of antigen/aptamer interactions remained unaffected. Interaction effects of BPL treatment and disease state, potentially altering detectability of group differences, were observable for less than one percent of targets (0.6%). BPL effects on protein detection with Olink Target were also limited, affecting 3.6% of detected proteins with no observable interaction effects. Thus, effects of BPL treatment only moderately interfere with affinity proteomic detectability of differential protein expression between different experimental groups. Overall, the results prove high-throughput affinity proteomics well suited for the analysis of high-risk samples inactivated using BPL.

Abstract: <i>Rhizoctonia solani</i> causes serious plant diseases. Neocryptolepine presented the significant antifungal activity against <i>R</i>. <i>solani</i>, however the mode of action is unclear. In this paper, we investigated the potential mode of action of neocryptolepine against <i>R</i>. <i>solani</i> integrated the proteomics and transcriptomics. Results showed that after treatment with neocryptolepine, 1012 differentially expressed proteins and 10 920 differentially expressed genes of <i>R</i>. <i>solani</i> were found, most of them were enriched in mitochondrial respiratory chain. It affected oxidative phosphorylation led to the enrichment of ROS and the decrease of MMP, and inhibited complex III activity with the inhibition rate of 63.51% at 10 μg/mL. The mitochondrial structural and function were damaged. Cytochrome <i>b</i>-c1 complex subunit Rieske (UQCRFS1) with the high binding score to neocryptolepine was found as a potential target. In addition, it inhibited the sclerotia formation and presented antifungal efficacy by decreasing the diameter of a wound in potato in a concentration-dependent manner. Above results indicated that neocryptolepine inhibited the complex III activity by binding UQCRFS1 and blocked the ion transfer to cause the death of <i>R</i>. <i>solani</i> mycelia. This study laid the foundation for the future development of neocryptolepine as an alternative biofungicide.

Abstract: Mass spectrometry (MS)-based top-down characterization of integral membrane proteins (IMPs) is crucial for understanding their functions in biological processes. However, it is technically challenging due to their low solubility in typical MS-compatible buffers. In this work, for the first time, we developed an efficient capillary zone electrophoresis (CZE)-tandem MS (MS/MS) method for the top-down proteomics (TDP) of IMPs enriched from mouse brains. Our technique employs a sample buffer containing 30% (v/v) formic acid and 60% (v/v) methanol for solubilizing IMPs and utilizes a separation buffer of 30% (v/v) acetic acid and 30% (v/v) methanol for maintaining the solubility of IMPs during CZE separation. Single-shot CZE-MS/MS identified 51 IMP proteoforms from the mouse brain sample. Coupling size exclusion chromatography (SEC) to CZE-MS/MS enabled the identification of 276 IMP proteoforms from the mouse brain sample containing 1–4 transmembrane domains. This proof-of-concept work demonstrates the high potential of CZE-MS/MS for the large-scale TDP of IMPs.

Abstract: Natural plant extracts have demonstrated significant potential in alternative antibiotic therapies. Cinnamaldehyde (CA) has garnered considerable attention as a natural antibacterial agent. In this study, Tandem mass tag (TMT) quantitative proteomics combined with Western blot and RT-qPCR methods were employed to explore the antibacterial mechanism of CA against Methicillin-Resistant Staphylococcus aureus (MRSA) at the protein level. The results showed that a total of 254 differentially expressed proteins (DEPs) were identified in the control group and CA treatment group, of which 161 were significantly upregulated and 93 were significantly downregulated. DEPs related to nucleotide synthesis, homeostasis of the internal environment, and protein biosynthesis were significantly upregulated, while DEPs involved in the cell wall, cell membrane, and virulence factors were significantly downregulated. The results of GO and KEGG enrichment analyses demonstrated that CA could exert its antibacterial effects by influencing pyruvate metabolism, the tricarboxylic acid (TCA) cycle, teichoic acid biosynthesis, and the Staphylococcus aureus (S. aureus) infection pathway in MRSA. CA significantly inhibited the expression of recombinant protein MgrA (<i>p</i> < 0.05), significantly reduced the mRNA transcription levels of <i>mgrA</i>, <i>hla</i>, and <i>sdrD</i> genes (<i>p</i> < 0.05), and thermostability migration assays demonstrated that CA can directly interact with MgrA protein, thereby inhibiting its activity. These findings suggest that CA exerts its antibacterial mechanism by regulating the expression of related proteins, providing a theoretical basis for further development of clinical applications of antimicrobial agents derived from natural plant essential oils in the treatment of dairy cow mastitis.

Abstract: Elucidating the mechanisms by which protein synthesis contributes to complex biological processes has remained a challenging endeavor. This is particularly true in the field of neuroscience, where multiple, tightly regulated periods of new protein synthesis in different cell-types are thought to facilitate intricate neurological functions, such as memory formation. Current methods for labeling the <i>de novo</i> proteome have lacked the spatial and temporal resolution to accurately discriminate these overlapping and often competing windows of mRNA translation. To address this technological limitation, here we describe a novel, light-inducible specific method for labeling newly synthesized proteins within a targeted cell-type.By developing Opto-ANL, a photocaged version of the nonendogenous amino acid azidonorleucine (ANL), we can selectively label newly synthesized proteins in specific cell-types through the targeted expression of a mutant methionyl-tRNA synthetase (L274G-MetRS). We demonstrate that Opto-ANL can be rapidly uncaged by UV light treatment in both cell culture and mouse brain slices, with Opto-ANL labeled proteins being able to be visualized via fluorescent noncanonical amino acid tagging. We also reveal that pretreatment with Opto-ANL not only allows for the period of <i>de novo</i> proteomic labeling to be tightly controlled, but also improves labeling efficiency compared to regular ANL. To demonstrate the potential applications of this novel technique, we use Opto-ANL to detect insulin-induced increases in protein synthesis and to label the excitatory neuronal <i>de novo</i> proteome in mouse brain slices. We believe that this application of photopharmacology will allow researchers to generate novel insights into how the translational landscape is altered across cell-types during complex neurological phenomena such as memory formation.

Abstract: Precise spatiotemporal regulation of protein complex assembly is essential for cells to achieve a meaningful rely of information flow via intracellular signaling networks in response to extracellular cues, whose disruption would lead to disease. Although various attempts have been made for spatial and/or temporal analysis of protein complexes, it is still a challenge to track cell-wide dynamics of a particular protein complex under physiological conditions. Here we describe a workflow that combines endogenous expression of tagged proteins, organelle marker distribution-directed subcellular fractionation, scaffold protein-mediated receptor complex purification, and targeted proteomics for spatiotemporal quantification of protein complexes in whole cell scale. We applied our method to investigate the assembly kinetics of EGF-dependent ErbB receptor complexes. After fractionation using the density gradient centrifugation and organelle assignment based on organelle markers, endogenous ErbB complex in different subcellular fractionation was efficiently enriched. By using targeted mass spectrometry, ErbB complex components that expressed medium to low level was precisely quantified with in-depth coverage, simultaneously in time and subcellular spaces. Our results revealed a sophisticated scheme of complex behaviors characterized by multiple subcomplexes with distinct molecular composition formed across subcellular fractions enriched with cytosol, plasma membrane, endosome, or mitochondria, implying organelle-specific ErbB functions. Remarkably, our results demonstrated for the first time that activated ErbB receptors might increase their signaling range through promoting a cytosolic, receptor-free subcomplex, consisting of Shc1, Grb2, Arhgef5, Garem1, and Lrrk1. These findings emphasize the potential of our strategy as a powerful tool to study spatiotemporal dynamics of protein complexes.

Abstract: Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus-infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, <i>k</i>-means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host–pathogen interactions.

Abstract: Deciphering the endogenous interactors of histone post-translational modifications (hPTMs, also called histone marks) is essential to understand the mechanisms of epigenetic regulation. However, most of the analytical methods to determine hPTM interactomes are in vitro settings, lacking interrogating native chromatin. Although lysine crotonylation (Kcr) has recently been considered an important hPTM for the regulation of gene transcription, the interactors of Kcr still remain to be explored. Herein, we present a general approach relying upon a genetic code expansion system, APEX2 (engineered peroxidase)-mediated proximity labeling, and quantitative proteomics to profile interactomes of the selected hPTMs in living cells. We genetically fused APEX2 to the recombinant histone H3 with a crotonyl lysine inserted site specifically to generate APEX2–H3K9cr that incorporated into native chromatin. Upon activation, APEX2 triggered in vivo biotin labeling of H3K9cr interactors that can then be enriched with streptavidin beads and identified by mass spectrometry. Proteomic analysis further revealed the endogenous interactomes of H3K9cr and confirmed the reliability of the method. Moreover, DPF2 was identified as a candidate interactor, and the binding interaction of DPF2 to H3K9c was further characterized and verified. This study provides a novel strategy for the identification of hPTM interactomes in living cells, and we envision that this is key to elucidating epigenetic regulatory pathways.

Abstract: Cyanobacteria, the evolutionary ancestors of plant chloroplasts, contribute substantially to the Earth’s biogeochemical cycles and are of great interest for a sustainable economy. Knowledge of protein expression is the key to understanding cyanobacterial metabolism; however, proteome studies in cyanobacteria are limited and cover only a fraction of the theoretical proteome. Here, we performed a comprehensive proteogenomic analysis of the model cyanobacterium <i>Synechocystis</i> sp. PCC 6803 to characterize the expressed (phospho)­proteome, re-annotate known and discover novel open reading frames (ORFs). By mapping extensive shotgun mass spectrometry proteomics data onto a six-frame translation of the <i>Synechocystis</i> genome, we refined the genomic annotation of 64 ORFs, including eight completely novel ORFs. Our study presents the largest reported (phospho)­proteome dataset for a unicellular cyanobacterium, covering the expression of about 80% of the theoretical proteome under various cultivation conditions, such as nitrogen or carbon limitation. We report 568 phosphorylated S/T/Y sites that are present on numerous regulatory proteins, including the transcriptional regulators cyAbrB1 and cyAbrB2. We also catalogue the proteins that have never been detected under laboratory conditions and found that a large portion of them is plasmid-encoded. This dataset will serve as a resource, providing dedicated information on growth condition-dependent protein expression and phosphorylation.

Abstract: Proteomics research has been transformed due to high-throughput liquid chromatography (LC-MS/MS) tandem mass spectrometry instruments combined with highly sophisticated automated sample preparation and multiplexing workflows. However, scaling proteomics experiments to large sample cohorts (hundreds to thousands) requires thoughtful quality control (QC) protocols. Robust QC protocols can help with reproducibility, quantitative accuracy, and provide opportunities for more decisive troubleshooting. Our laboratory conducted a plasma proteomics study of a cohort of <i>N</i> = 335 patient samples using tandem mass tag (TMT_pro) 16-plex batches. Over the course of a 10-month data acquisition period for this cohort we collected 271 pooled QC LC-MS/MS result files obtained from MS/MS analysis of a patient-derived pooled plasma sample, representative of the entire cohort population. This sample was tagged with TMT_zero or TMT_pro reagents and used to inform the daily performance of the LC-MS/MS instruments and to allow within and across sample batch normalization. Analytical variability of a number of instrumental and data analysis metrics including protein and peptide identifications, peptide spectral matches (PSMs), number of obtained MS/MS spectra, average peptide abundance, percent of peptides with a Δ <i>m</i>/<i>z</i> between ±0.003 Da, percent of MS/MS spectra obtained at the maximum injection time, and the retention time of selected tracking peptides were evaluated to help inform the design of a robust LC-MS/MS QC workflow for use in future cohort studies. This study also led to general tips for using selected metrics to inform real-time troubleshooting of LC-MS/MS performance issues with daily QC checks.

Abstract: Large scale proteomic profiling of cell lines can reveal molecular signatures attributed to variable genotypes or induced perturbations, enabling proteogenomic associations and elucidation of pharmacological mechanisms of action. Although isobaric labeling has increased the throughput of proteomic analysis, the commonly used sample preparation workflows often require time-consuming steps and costly consumables, limiting their suitability for large scale studies. Here, we present a simplified and cost-effective one-pot reaction workflow in a 96-well plate format (SimPLIT) that minimizes processing steps and demonstrates improved reproducibility compared to alternative approaches. The workflow is based on a sodium deoxycholate lysis buffer and a single detergent cleanup step after peptide labeling, followed by quick off-line fractionation and MS2 analysis. We showcase the applicability of the workflow in a panel of colorectal cancer cell lines and by performing target discovery for a set of molecular glue degraders in different cell lines, in a 96-sample assay. Using this workflow, we report frequently dysregulated proteins in colorectal cancer cells and uncover cell-dependent protein degradation profiles of seven cereblon E3 ligase modulators (CRL4^CRBN). Overall, SimPLIT is a robust method that can be easily implemented in any proteomics laboratory for medium-to-large scale TMT-based studies for deep profiling of cell lines.

Abstract: Butenyl-spinosyn is a highly effective and broad-spectrum biopesticide produced by Saccharopolyspora pogona. However, the yield of this compound is difficult to increase because the regulatory mechanism of secondary metabolism is still unknown. Here, the transcriptional regulator Sp13016 was discovered to be highly associated with butenyl-spinosyn synthesis and bacterial growth. Overexpression of <i>sp13016</i> improved butenyl-spinosyn production to a level that was 2.84-fold that of the original strain, while deletion of <i>sp13016</i> resulted in a significant decrease in yield and growth inhibition. Comparative proteomics revealed that these phenotypic changes were attributed to the influence of Sp13016 on the central carbon metabolism pathway to regulate the supply of precursors. Our research helps to reveal the regulatory mechanism of butenyl-spinosyn biosynthesis and provides a reference for increasing the yield of natural products of <i>Actinomycetes</i>.

Abstract: The PRIDE database is the largest public data repository of mass spectrometry-based proteomics data and currently stores more than 40,000 data sets covering a wide range of organisms, experimental techniques, and biological conditions. During the past few years, PRIDE has seen a significant increase in the amount of submitted data-independent acquisition (DIA) proteomics data sets. This provides an excellent opportunity for large-scale data reanalysis and reuse. We have reanalyzed 15 public label-free DIA data sets across various healthy human tissues to provide a state-of-the-art view of the human proteome in baseline conditions (without any perturbations). We computed baseline protein abundances and compared them across various tissues, samples, and data sets. Our second aim was to compare protein abundances obtained here from the results of previous analyses using human baseline data-dependent acquisition (DDA) data sets. We observed a good correlation across some tissues, especially in the liver and colon, but weak correlations were found in others, such as the lung and pancreas. The reanalyzed results including protein abundance values and curated metadata are made available to view and download from the resource Expression Atlas.

Abstract: Protein <i>O</i>-GlcNAcylation plays extremely important roles in mammalian cells, regulating signal transduction and gene expression. This modification can happen during protein translation, and systematic and site-specific analysis of protein co-translational <i>O</i>-GlcNAcylation can advance our understanding of this important modification. However, it is extraordinarily challenging because normally <i>O</i>-GlcNAcylated proteins are very low abundant and the abundances of co-translational ones are even much lower. Here, we developed a method integrating selective enrichment, a boosting approach, and multiplexed proteomics to globally and site-specifically characterize protein co-translational <i>O</i>-GlcNAcylation. The boosting approach using the TMT labeling dramatically enhances the detection of co-translational glycopeptides with low abundance when enriched <i>O</i>-GlcNAcylated peptides from cells with a much longer labeling time was used as a boosting sample. More than 180 co-translational <i>O</i>-GlcNAcylated proteins were site-specifically identified. Further analyses revealed that among co-translational glycoproteins, those related to DNA binding and transcription are highly overrepresented using the total identified <i>O</i>-GlcNAcylated proteins in the same cells as the background. Compared with the glycosylation sites on all glycoproteins, co-translational sites have different local structures and adjacent amino acid residues. Overall, an integrative method was developed to identify protein co-translational <i>O</i>-GlcNAcylation, which is very useful to advance our understanding of this important modification.

Abstract: Sarcopenia has been recognized as an emerging complication of type 2 diabetes mellitus (T2DM). Currently, the pathogenesis of T2DM-related sarcopenia remains unclear. The aim of this study was to investigate the molecular mechanisms and potential therapeutic targets for T2DM-related sarcopenia. In this study, a T2DM-related sarcopenia mouse model was established using db/db mice. Proteins extracted from the gastrocnemius muscles of db/db mice and littermate control db/m mice were analyzed by a 4D label-free quantitative proteomics approach. A total of 131 upregulated and 68 downregulated proteins were identified as differentially expressed proteins (DEPs). Bioinformatics analysis revealed that DEPs were significantly enriched in lipid metabolism. Protein–protein interaction network analysis revealed that six hub proteins, including ACOX1, CPT2, ECI2, ACADVL, ACADL, and ECH1, were involved in the fatty acid oxidation. The hub protein-transcription factor-miRNA network was also constructed using the NetworkAnalyst tool. Finally, the hub proteins were validated by Western blotting and immunohistochemistry and further confirmed to be significantly negatively correlated with muscle mass and grip strength. Our study suggested that lipid metabolism, especially excessive fatty acid oxidation, may be a crucial contributor to the progression of T2DM-related sarcopenia and a common cause of the inter-relationship between T2DM and sarcopenia. Targeting lipid metabolism may be a promising therapeutic strategy for T2DM-related sarcopenia.

Abstract: In spite of its central role in biology and disease, protein turnover is a largely understudied aspect of most proteomic studies due to the complexity of computational workflows that analyze in vivo turnover rates. To address this need, we developed a new computational tool, TurnoveR, to accurately calculate protein turnover rates from mass spectrometric analysis of metabolic labeling experiments in Skyline, a free and open-source proteomics software platform. TurnoveR is a straightforward graphical interface that enables seamless integration of protein turnover analysis into a traditional proteomics workflow in Skyline, allowing users to take advantage of the advanced and flexible data visualization and curation features built into the software. The computational pipeline of TurnoveR performs critical steps to determine protein turnover rates, including isotopologue demultiplexing, precursor-pool correction, statistical analysis, and generation of data reports and visualizations. This workflow is compatible with many mass spectrometric platforms and recapitulates turnover rates and differential changes in turnover rates between treatment groups calculated in previous studies. We expect that the addition of TurnoveR to the widely used Skyline proteomics software will facilitate wider utilization of protein turnover analysis in highly relevant biological models, including aging, neurodegeneration, and skeletal muscle atrophy.

Abstract: Chemical proteomics utilizes small-molecule probes to covalently engage with their interacting proteins. Since chemical probes are tagged to the active or binding sites of functional proteins, chemical proteomics can be used to profile protein targets, reveal precise binding sites/mechanisms, and screen inhibitors competing with probes in a biological context. These capabilities of chemical proteomics have great potential to enable discoveries of both drug targets and lead compounds. However, chemical proteomics is limited by the time-consuming bottleneck of sample preparations, which are processed manually. With the advancement of robotics and artificial intelligence, it is now possible to automate workflows to make chemical proteomics sample preparation a high-throughput process. An automated robotic system represents a major technological opportunity to speed up advances in proteomics, open new frontiers in drug target discovery, and broaden the future of chemical biology.

Abstract: A progressive loss of functional nephrons defines chronic kidney disease (CKD). Complications related to cardiovascular disease (CVD) are the principal causes of mortality in CKD; however, the acceleration of CVD in CKD remains unresolved. Our study used a complementary proteomic approach to assess mild and advanced CKD patients with different atherosclerosis stages and two groups of patients with different classical CVD progression but without renal dysfunction. We utilized a label-free approach based on LC-MS/MS and functional bioinformatic analyses to profile CKD and CVD leukocyte proteins. We revealed dysregulation of proteins involved in different phases of leukocytes’ diapedesis process that is very pronounced in CKD’s advanced stage. We also showed an upregulation of apoptosis-related proteins in CKD as compared to CVD. The differential abundance of selected proteins was validated by multiple reaction monitoring, ELISA, Western blotting, and at the mRNA level by ddPCR. An increased rate of apoptosis was then functionally confirmed on the cellular level. Hence, we suggest that the disturbances in leukocyte extravasation proteins may alter cell integrity and trigger cell death, as demonstrated by flow cytometry and microscopy analyses. Our proteomics data set has been deposited to the ProteomeXchange Consortium via the PRIDE repository with the data set identifier PXD018596.

Abstract: The PRIDE database is the largest public data repository of mass spectrometry-based proteomics data and currently stores more than 40,000 data sets covering a wide range of organisms, experimental techniques, and biological conditions. During the past few years, PRIDE has seen a significant increase in the amount of submitted data-independent acquisition (DIA) proteomics data sets. This provides an excellent opportunity for large-scale data reanalysis and reuse. We have reanalyzed 15 public label-free DIA data sets across various healthy human tissues to provide a state-of-the-art view of the human proteome in baseline conditions (without any perturbations). We computed baseline protein abundances and compared them across various tissues, samples, and data sets. Our second aim was to compare protein abundances obtained here from the results of previous analyses using human baseline data-dependent acquisition (DDA) data sets. We observed a good correlation across some tissues, especially in the liver and colon, but weak correlations were found in others, such as the lung and pancreas. The reanalyzed results including protein abundance values and curated metadata are made available to view and download from the resource Expression Atlas.

Abstract: Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus-infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, <i>k</i>-means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host–pathogen interactions.

Abstract: The interaction between copper ions and amyloid peptide Aβ has been reported to be involved in Alzheimer’s disease (AD) pathology. Based on copper coordination biochemistry, we designed specific copper chelators [tetradentate monoquinolines (TDMQs)] in order to regulate copper homeostasis in the AD brain and inhibit the deleterious oxidative stress catalyzed by copper-Aβ complexes. We previously reported that TDMQ20, a highly selective copper chelator selected as a drug candidate, was able to extract copper from the Cu-Aβ_1–16 complex and restore cognitive and behavioral deficits in AD mouse models. For a better understanding of the mechanism of action of TDMQ20, we decided to investigate the change of profile of proteins expressed in 5xFAD mice after an oral treatment of TDMQ20 (dose = 10 mg/kg, once every two days for 3 months, in total 45 times). Clioquinol (CQ), a non-specific chelator, has been used as a comparator. Here, we report the proteomic alterations in the cortex of 5xFAD mice using iTRAQ (isobaric tags for relative and absolute quantification) proteomics technology. The results indicated that 178 differentially expressed proteins (DEPs) have been identified in the AD mouse group with respect to wild type (WT) animals (AD/WT). After treatment by TDMQ20, 35 DEPs were found common in AD/WT and TDMQ20/AD groups in an opposite change manner (up- or down-regulated, respectively). In addition, among the 35 DEPs mentioned above, 10 common target proteins have been identified in AD/WT, TDMQ20/AD, and CQ/AD groups, among which 3 target proteins were successfully validated by western blot analysis. In particular, the expression levels of ChAT and CHRM4 are significantly increased upon TDMQ20 treatment with respect to 5xFAD mice, while CQ did not significantly change the expression of these proteins. Our study suggests the involvement of the copper chelator TDMQ20 on the cholinergic system, a feature that may explain the improved cognitive and behavioral performance in AD mice upon oral treatment of TDMQ20.

Abstract: Arsenic contamination in food and groundwater constitutes a public health concern for more than 200 million people worldwide. Individuals chronically exposed to arsenic through drinking and ingestion exhibit a higher risk of developing cancers and cardiovascular diseases. Nevertheless, the underlying mechanisms of arsenic toxicity are not fully understood. Arsenite is known to bind to and deactivate RING finger E3 ubiquitin ligases; thus, we reason that a systematic interrogation about how arsenite exposure modulates global protein ubiquitination may reveal novel molecular targets for arsenic toxicity. By employing liquid chromatography-tandem mass spectrometry, in combination with stable isotope labeling by amino acids in cell culture (SILAC) and immunoprecipitation of di-glycine-conjugated lysine-containing tryptic peptides, we assessed the alterations in protein ubiquitination in GM00637 human skin fibroblast cells upon arsenite exposure at the entire proteome level. We observed that arsenite exposure led to altered ubiquitination of many proteins, where the alterations in a large majority of ubiquitination events are negatively correlated with changes in expression of the corresponding proteins, suggesting their modulation by the ubiquitin-proteasomal pathway. Moreover, we observed that arsenite exposure confers diminished ubiquitination of a rate-limiting enzyme in cholesterol biosynthesis, HMGCR, at Lys²⁴⁸. We also revealed that TRC8 is the major E3 ubiquitin ligase for HMGCR ubiquitination in HEK293T cells, and the arsenite-induced diminution of HMGCR ubiquitination is abrogated upon genetic depletion of TRC8. In summary, we systematically characterized arsenite-induced perturbations in a ubiquitinated proteome in human cells and found that the arsenite-elicited attenuation of HMGCR ubiquitination in HEK293T cells involves TRC8.

Abstract: A major challenge in proteoform characterization is to obtain information on coexisting post-translational modifications (PTMs), which is lost in traditional bottom-up analysis. Middle-down approaches of antibodies provide a good balance of resolution, site-specificity, and proteoform heterogeneity to characterize individual proteoforms at subunit level. Currently, most middle-down studies focus on terminal fragment ions, which may not cover or resolve PTMs in the center of the sequence or with minor mass shifts such as deamidation, often a critical quality attribute for antibody drugs. Antibody glycosylation at Asn 297 and deamidation at Asn 325 are two important PTMs impacting the interaction with Fc gamma receptors and hence effector functions such as antibody-dependent cellular cytotoxicity. Here, we established a new middle-down workflow that uses internal fragment ions for the qualitative and quantitative assessment of a functional relevant deamidation site, Asn 325, through higher energy collision dissociation fragmentation of individual antibody glycoforms upon quadrupole isolation. We identified a signature internal fragment ion to resolve and estimate the relative abundances of deamidation of individual glycoforms in complex mixtures. Our proof-of-concept work demonstrates the feasibility to identify and quantify Asn 325 deamidation at the glycoform-resolved subunit level using internal fragment ions, which greatly advances the capabilities to study PTM dynamics by middle-down analysis.

Abstract: Glycoproteins play important roles in numerous physiological processes and are often implicated in disease. Analysis of site-specific protein glycobiology through glycoproteomics has evolved rapidly in recent years thanks to hardware and software innovations. Particularly, the introduction of parallel accumulation serial fragmentation (PASEF) on hybrid trapped ion mobility time-of-flight mass spectrometry instruments combined deep proteome sequencing with separation of (near-)­isobaric precursor ions or converging isotope envelopes through ion mobility separation. However, the reported use of PASEF in integrated glycoproteomics workflows to comprehensively capture the glycoproteome is still limited. To this end, we developed an integrated methodology using timsTOF Pro 2 to enhance N-glycopeptide identifications in complex mixtures. We systematically optimized the ion optics tuning, collision energies, mobility isolation width, and the use of dopant-enriched nitrogen gas (DEN). Thus, we obtained a marked increase in unique glycopeptide identification rates compared to standard proteomics settings, showcasing our results on a large set of glycopeptides. With short liquid chromatography gradients of 30 min, we increased the number of unique N-glycopeptide identifications in human plasma samples from around 100 identifications under standard proteomics conditions to up to 1500 with our optimized glycoproteomics approach, highlighting the need for tailored optimizations to obtain comprehensive data.

Abstract: Protein synthesis and degradation responding to environmental cues is critical for understanding the mechanisms involved. Chemical proteomics introducing bioorthogonal tagging into proteins and isolation by biotin affinity purification is applicable for enrichment of newly synthesized proteins (NSPs). Current enrichment methods based on biotin–streptavidin interaction lack efficiency to release enriched NSPs under mild conditions. Here we designed a novel method for enriching newly synthesized peptides by click chemistry followed by release of enriched peptides via tryptic digestion based on cleavable bioorthogonal tagging (CBOT). CBOT-modified peptides can further enhance identification in mass spectrometry analysis and provide a confirmation by small mass shift. Our method achieved an improvement in specificity (97.1%) and sensitivity for NSPs in cell lysate, corresponding to profiling at a depth of 4335 NSPs from 2 mg of starting materials in a single LC-MS/MS run. In addition, the CBOT strategy can quantify NSPs when coupling a pair of isotope-labeled azidohomoalanine (AHA/hAHA) with decent reproducibility. Furthermore, we applied it to analyze newly synthesized proteomes in the autophagy process after 6 h rapamycin stimulation in cells, 2910 NSPs were quantified, and 337 NSPs among them were significantly up- and down-regulated. We envision CBOT as an effective and alternative approach for bioorthogonal chemical proteomics to study stimuli-sensitive subsets.

Abstract: This study was conducted to optimize a targeted plant proteomics approach from signature peptide selection and liquid chromatography with tandem mass spectrometry (LC-MS/MS) analytical method development and optimization to sample preparation method optimization. Three typical protein extraction and precipitation methods, including trichloroacetic acid (TCA)/acetone method, phenol method, and TCA/acetone/phenol method, and two digestion methods, including trypsin digestion and LysC/trypsin digestion, were evaluated for selected proteins related to the impact of engineered nanomaterials (ENMs) on wheat (Triticum aestivum) plant growth. In addition, we compared two plant tissue homogenization methods: grinding freeze-dried tissue and fresh tissue into a fine powder using a mortar and pestle aided with liquid nitrogen. Wheat plants were grown under a 16 h photoperiod (light intensity 150 μmol·m^–2·s^–1) for 4 weeks at 22 °C with a relative humidity of 60% and were watered daily to maintain a 70–90% water content in the soil. Processed samples were analyzed with an optimized LC-MS/MS method. The concentration of selected signature peptides for the wheat proteins of interest indicated that the phenol extraction method using fresh plant tissue, coupled with trypsin digestion, was the best sample preparation method for the targeted proteomics study. Overall, the optimized approach yielded the highest total peptide concentration (68,831 ng/g, 2.4 times the lowest concentration) as well as higher signature peptide concentrations for most peptides (19 out of 28). In addition, three of the signature peptides could only be detected using the optimized approach. This study provides a workflow for optimizing targeted proteomics studies.