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Summary: Background: Synaptic proteins are increasingly studied as biomarkers for synaptic dysfunction and loss, which are early and central events in Alzheimer's disease (AD) and strongly correlate with the degree of cognitive decline. In this study, we specifically investigated the synaptic binding partners neurexin (NRXN) and neuroligin (Nlgn) proteins, to assess their biomarker's potential. Methods: we developed a parallel reaction monitoring mass spectrometric method for the simultaneous quantification of NRXNs and Nlgns in cerebrospinal fluid (CSF) of neurodegenerative diseases, focusing on AD. Specifically, NRXN-1α, NRXN-1β, NRXN-2α, NRXN-3α and Nlgn1, Nlgn2, Nlgn3 and Nlgn4 proteins were targeted. Findings: The proteins were investigated in a clinical cohort including CSF from controls (n=22), mild cognitive impairment (MCI) due to AD (n=44), MCI due to other conditions (n=46), AD (n=77) and a group of non-AD dementia (n=28). No difference in levels of NRXNs and Nlgns was found between AD (both at dementia and MCI stages) or controls or the non-AD dementia group for any of the targeted proteins. NRXN and Nlgn proteins correlated strongly with each other, but only a weak correlation with the AD core biomarkers and the synaptic biomarkers neurogranin and growth-associated protein 43, was found, possibly reflecting different pathogenic processing at the synapse. Interpretation: we conclude that NRXN and Nlgn proteins do not represent suitable biomarkers for synaptic pathology in AD. The panel developed here could aid in future investigations of the potential involvement of NRXNs and Nlgns in synaptic dysfunction in other disorders of the central nervous system. Funding: a full list of funding can be found under the acknowledgments section.

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field., Graphical abstract, Highlights • Advanced acquisition methods improve focus of mass spectrometers on target peptides. • This review discusses existing methods based on two strategies. • Retention time adjustment-based methods enable intelligent scheduling of peptide RTs. • In spike-in triggered acquisition methods targeted scans are initiated by spike-ins., In Brief The analytical power of targeted proteomics depends on how efficiently the mass spectrometer detects target peptides. A number of “smart” acquisition approaches have been developed that enable more targets per run and improve analytical performance such as sensitivity, specificity, and quantitative accuracy. This review provides an introduction to these methods and highlights their inherent strengths and weaknesses.

Patients with chronic kidney disease (CKD) are at high risk for CVD. However, traditional lipid risk factors, including low HDL levels, cannot completely explain the increased risk. Altered HDL proteome is linked with both CVD and CKD, but the role of HDL proteins in incident CVD events in patients with CKD is unknown. In this prospective case-control study, we used targeted proteomics to quantify 31 HDL proteins in 92 subjects (46 incident new CVD and 46 one-to-one matched controls) at various stages of CKD. We tested associations of HDL proteins with incident CVD using matched logistic regression analysis. In the model fully adjusted for clinical confounders, lipid levels, C-reactive protein, and proteinuria, no significant associations were found for HDL-C, but we observed inverse associations between levels of HDL proteins paraoxonase/arylesterase 1 (PON1), paraoxonase/arylesterase 3 (PON3), and LCAT and incident CVD. Odds ratios (per 1 SD) were 0.38 (0.18–0.97, P = 0.042), 0.42 (0.20–0.92, P = 0.031), and 0.30 (0.11–0.83, P = 0.020) for PON1, PON3, and LCAT, respectively. Apolipoprotein A-IV remained associated with incident CVD in CKD patients in models adjusted for clinical confounders and lipid levels but lost significance with the addition of C-reactive protein and proteinuria to the model. In conclusion, levels of four HDL proteins, PON1, PON3, LCAT, and apolipoprotein A-IV, were found to be inversely associated with incident CVD events in CKD patients. Our observations indicate that HDLs' protein cargo, but not HDL-C levels, can serve as a marker—and perhaps mediator—for elevated CVD risk in CKD patients.

One of the most fascinating features of the brain is its ability to adapt to its surroundings. Synaptic plasticity, the dynamic mechanism of functional and structural alterations in synaptic strength, is essential for brain functioning and underlies a variety of processes such as learning and memory. Although the molecular mechanisms underlying such rapid plasticity are not fully understood, a consensus exists on the important role of proteins. The study of these neuronal proteins using neuroproteomics has increased rapidly in the last decades, and advancements in MS-based proteomics have broadened our understanding of neuroplasticity exponentially. In this review, we discuss the trends in MS-based neuroproteomics for the study of synaptic protein–protein interactions and protein signaling dynamics, with a focus on sample types, different labeling and enrichment approaches, and data analysis and interpretation. We highlight studies from the last 5 years, with a focus on synapse structure, composition, functioning, or signaling and finally discuss some recent developments that could further advance the field of neuroproteomics., Graphical Abstract, Highlights • The study of neuronal proteins using proteomics has developed rapidly. • Focus on synapse structure, composition, functioning, or signaling. • Isolation of single-cell types and organoids for ideal sample material. • Increase in the use of bio-orthogonal and proximity labeling strategies., In Brief Advancements in MS-based proteomics have increased the study of synaptic proteins using neuroproteomics. The development of proximity, genetic labeling and bio-orthogonal amino acid labeling approaches now allow for the study of synaptic protein–protein interactions and protein signaling dynamics. In this review, we highlight studies from the last 5 years, with a focus on synapse structure, composition, functioning, or signaling and finally discuss some recent developments that could further advance the field of neuroproteomics.

The dynamic modification of specific serine and threonine residues of intracellular proteins by O-linked N-acetyl-β-D-glucosamine (O-GlcNAc) mitigates injury and promotes cytoprotection in a variety of stress models. The O-GlcNAc transferase (OGT) and the O-GlcNAcase are the sole enzymes that add and remove O-GlcNAc, respectively, from thousands of substrates. It remains unclear how just two enzymes can be specifically controlled to affect glycosylation of target proteins and signaling pathways both basally and in response to stress. Several lines of evidence suggest that protein interactors regulate these responses by affecting OGT and O-GlcNAcase activity, localization, and substrate specificity. To provide insight into the mechanisms by which OGT function is controlled, we have used quantitative proteomics to define OGT’s basal and stress-induced interactomes. OGT and its interaction partners were immunoprecipitated from OGT WT, null, and hydrogen peroxide–treated cell lysates that had been isotopically labeled with light, medium, and heavy lysine and arginine (stable isotopic labeling of amino acids in cell culture). In total, more than 130 proteins were found to interact with OGT, many of which change their association upon hydrogen peroxide stress. These proteins include the major OGT cleavage and glycosylation substrate, host cell factor 1, which demonstrated a time-dependent dissociation after stress. To validate less well-characterized interactors, such as glyceraldehyde 3-phosphate dehydrogenase and histone deacetylase 1, we turned to parallel reaction monitoring, which recapitulated our discovery-based stable isotopic labeling of amino acids in cell culture approach. Although the majority of proteins identified are novel OGT interactors, 64% of them are previously characterized glycosylation targets that contain varied domain architecture and function. Together these data demonstrate that OGT interacts with unique and specific interactors in a stress-responsive manner., Graphical Abstract, Highlights • O-GlcNAc levels change dynamically in response to injury. • Injury does not induce changes in activity of the enzymes that cycle O-GlcNAc. • Quantitative proteomics identified and validated interactors of OGT. • The interactome of OGT changes significantly in response to oxidative stress., In Brief The goal of these studies was to provide insight into the regulation of the O-GlcNAc transferase (OGT) basally and in response to oxidative stress, as well as the role that O-GlcNAc plays in promoting cytoprotection. Using quantitative proteomics, the basal and injury-induced interactome of OGT has been defined and validated. Protein interactors are anticipated to regulate either the activity or substrate targeting of OGT, or to be substrates of OGT, thus affecting cytoprotection.

Glycogen Storage Disease type 1b (GSDIb) is a genetic disorder with long term severe complications. Accumulation of the glucose analog 1,5-anhydroglucitol-6-phosphate (1,5AG6P) in neutrophils inhibits the phosphorylation of glucose in these cells, causing neutropenia and neutrophil dysfunctions. This condition leads to serious infections and inflammatory bowel disease (IBD) in GSDIb patients. We show here that dapagliflozin, an inhibitor of the renal sodium-glucose co-transporter-2 (SGLT2), improves neutrophil function in an inducible mouse model of GSDIb by reducing 1,5AG6P accumulation in myeloid cells.

Mass spectrometry (MS) is the state-of-the-art methodology for capturing the breadth and depth of the immunopeptidome across human leukocyte antigen (HLA) allotypes and cell types. The majority of studies in the immunopeptidomics field are discovery driven. Hence, data-dependent tandem MS (MS/MS) acquisition (DDA) is widely used, as it generates high-quality references of peptide fingerprints. However, DDA suffers from the stochastic selection of abundant ions that impairs sensitivity and reproducibility. In contrast, in data-independent acquisition (DIA), the systematic fragmentation and acquisition of all fragment ions within given isolation m/z windows yield a comprehensive map for a given sample. However, many DIA approaches commonly require generating comprehensive DDA-based spectrum libraries, which can become impractical for studying noncanonical and personalized neoantigens. Because the amount of HLA peptides eluted from biological samples such as small tissue biopsies is typically not sufficient for acquiring both meaningful DDA data necessary for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy by matching DIA data against libraries with growing complexity—from sample-specific libraries to libraries combining 2 to 40 different immunopeptidomics samples. Analyzing DIA immunopeptidomics data against a complex multi-HLA spectral library resulted in a two-fold increase in peptide identification compared with sample-specific library and in a three-fold increase compared with DDA measurements, yet with no detrimental effect on the specificity. Furthermore, we demonstrated the implementation of DIA for sensitive personalized neoantigen discovery through the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands. We conclude that a comprehensive multi-HLA library for DIA approach in combination with MS/MS prediction is highly advantageous for clinical immunopeptidomics, especially when low amounts of biological samples are available., Graphical Abstract, Highlights • So far, DIA in the immunopeptidomics translational research has been limited. • DIA immunopeptidomics data were analyzed against a complex multi-HLA spectral library. • This resulted in improved sensitivity with no detrimental effect on the specificity. • We implemented DIA for clinical antigen discovery combined with predicted MS/MS spectra., In Brief The implementation of DIA in the immunopeptidomics translational research domain has remained limited because the amount of HLA peptides eluted from clinical samples is typically not sufficient for acquiring both meaningful DDA data for generating comprehensive spectral libraries and DIA MS measurements. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy with libraries of growing complexity and multi-HLA libraries. In addition, we demonstrated the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands.

Histone post-translational modifications (hPTMs) are epigenetic marks that strongly affect numerous processes, including cell cycling and protein interactions. They have been studied by both antibody- and MS-based methods for years, but the analyses are still challenging, mainly because of the diversity of histones and their modifications arising from high contents of reactive amine groups in their amino acid sequences. Here, we introduce use of trimethylacetic anhydride (TMA) as a new reagent for efficient histone derivatization, which is a requirement for bottom–up proteomic hPTM analysis. TMA can derivatize unmodified amine groups of lysine residues and amine groups generated at peptide N-termini by trypsin digestion. The derivatization is facilitated by microwave irradiation, which also reduces incubation times to minutes. We demonstrate that histone derivatization with TMA reliably provides high yields of fully derivatized peptides and thus is an effective alternative to conventional methods. TMA afforded more than 98% and 99% labeling efficiencies for histones H4 and H3, respectively, thereby enabling accurate quantification of peptide forms. Trimethylacetylation substantially improves chromatographic separation of peptide forms, which is essential for direct quantification based on signals extracted from MS1 data. For this purpose, software widely applied by the proteomics community can be used without additional computational development. Thorough comparison with widely applied propionylation highlights the advantages of TMA-based histone derivatization for monitoring hPTMs in biological samples., Graphical abstract, Highlights • Microwave-assisted labeling of histones using TMA for bottom–up proteomics. • TMA enables discrimination of isobaric peptides by improved chromatographic behavior. • TMA facilitates histone quantification from MS1-level spectral information. • TMA provides excellent performance for monitoring hPTM pattern in the tissues., In Brief The discrimination of isobaric peptides represents a common challenge in histone characterization. This study reports TMA as a novel derivatization reagent for bottom–up proteomics of histone proteoforms. TMA substantially improves separation of positional isomers, which is a prerequisite for identification and quantification of post-translationally modified histone forms.

Growing implications of glycosylation in physiological occurrences and human disease have prompted intensive focus on revealing glycomic perturbations through absolute and relative quantification. Empowered by seminal methodologies and increasing capacity for detection, identification, and characterization, the past decade has provided a significant increase in the number of suitable strategies for glycan and glycopeptide quantification. Mass-spectrometry-based strategies for glycomic quantitation have grown to include metabolic incorporation of stable isotopes, deposition of mass difference and mass defect isotopic labels, and isobaric chemical labeling, providing researchers with ample tools for accurate and robust quantitation. Beyond this, workflows have been designed to harness instrument capability for label-free quantification, and numerous software packages have been developed to facilitate reliable spectrum scoring. In this review, we present and highlight the most recent advances in chemical labeling and associated techniques for glycan and glycopeptide quantification., Graphical Abstract, Highlights • Novel glycomic applications of label-free, metabolic, isotopic, and isobaric labeling quantitation • Informatic tools for investigative quantitative glycomics • Critical considerations for entry or expansion of quantitative glycomics • Introduction of synthetically facile, cost-effective labeling technology, In Brief Recent years have seen an explosion in novel strategies for quantitative glycomics and glycoproteomics. Whether through metabolic incorporation of stable isotopes, deposition of custom isotopic labels, or high-throughput isobaric chemical tags, these numerous novel strategies provide ease of access to glycomic and glycoproteomic investigation. This review highlights the recent innovations in labeling methods, label-free strategies, acquisition modes, and bioinformatic tools for glycan and glycopeptide quantitation, while providing critical evaluations and technical considerations to enable effective analysis.

Complex protein glycosylation occurs through biosynthetic steps in the secretory pathway that create macro- and microheterogeneity of structure and function. Required for all life forms, glycosylation diversifies and adapts protein interactions with binding partners that underpin interactions at cell surfaces and pericellular and extracellular environments. Because these biological effects arise from heterogeneity of structure and function, it is necessary to measure their changes as part of the quest to understand nature. Quite often, however, the assumption behind proteomics that posttranslational modifications are discrete additions that can be modeled using the genome as a template does not apply to protein glycosylation. Rather, it is necessary to quantify the glycosylation distribution at each glycosite and to aggregate this information into a population of mature glycoproteins that exist in a given biological system. To date, mass spectrometric methods for assigning singly glycosylated peptides are well-established. But it is necessary to quantify glycosylation heterogeneity accurately in order to gauge the alterations that occur during biological processes. The task is to quantify the glycosylated peptide forms as accurately as possible and then apply appropriate bioinformatics algorithms to the calculation of micro- and macro-similarities. In this review, we summarize current approaches for protein quantification as they apply to this glycoprotein similarity problem., Graphical Abstract, Highlights • Singly glycosylated peptides can be identified unambiguously using HCD LC-MS. • For calculation of glycoprotein similarity, quantify all glycopeptide glycoforms. • Glycoprotein similarities can be calculated using the Tanimoto coefficient. • Similarity calculations require high reproducibility of glycoproteomics LC-MS data., In Brief To understand the roles of glycoproteins in biological processes, it is necessary to quantify the changes that occur to glycosylation at individual sites and to the whole molecule. That glycoprotein glycosylation is inherently heterogeneous means that the distribution of glycoforms at each glycosite must be quantified in order to inform calculation of molecular similarities. We review analytical and statistical methods for determining glycoprotein molecular similarities from glycoproteomics data.

Glaucoma is the leading cause of irreversible blindness worldwide. The proteome characterization of glaucoma is not clearly understood. A total of 175 subjects, including 57 primary acute angle-closure glaucoma (PAACG), 50 primary chronic angle-closure glaucoma (PCACG), 35 neovascular glaucoma (NVG), and 33 cataract patients, were enrolled and comparison proteomic analysis was provided. The samples were randomly divided into discovery group or validation group, whose aqueous humor proteome was analyzed by data-independent acquisition or by parallel reaction monitoring. The common proteome features of three types of glaucoma were immune response, lipid metabolism, and cell death. Three proteins, VTN, SERPIND1, and CD14, showed significant upregulation in glaucoma and could discriminate glaucoma from cataract. Mutual differential proteomic analysis of PAACG, PCACG, and NVG showed different proteome characterization of the three types of glaucoma. NVG was characterized with activated angiogenesis. PAACG was characterized with activation of inflammation response. SERPIND1 was discovered to play vital role in glaucoma occurrences, which is associated with eye transparency decrease and glucose metabolism. This study would provide insights in understanding proteome characterization of glaucoma and benefit the clinical application of AH proteome., Graphical Abstract, Highlights • Aqueous humor proteome of different glaucoma (PACG, NVG) was profiled. • Potential protein biomarkers for glaucoma were proposed. • Potential mechanism of glaucoma was described. • SERPIND1 was discovered to have potential value for glaucoma diagnosis., In Brief Liu et al. characterized the proteome of aqueous humor from three types of glaucoma. Fifty-seven primary acute angle-closure glaucoma (PAACG), 50 primary chronic angle-closure glaucoma (PCACG), 35 neovascular glaucoma (NVG), and 33 cataract patient samples were analyzed using data-independent analysis and parallel reaction monitoring. Lipid metabolism, immune response, and cell death pathways showed different degrees of activation among the three types of glaucoma but were all higher relative to cataract. SERPIND1 was discovered as a vital protein in glaucoma.

Histones are highly posttranslationally modified proteins that regulate gene expression by modulating chromatin structure and function. Acetylation and methylation are the most abundant histone modifications, with methylation occurring on lysine (mono-, di-, and trimethylation) and arginine (mono- and dimethylation) predominately on histones H3 and H4. In addition, arginine dimethylation can occur either symmetrically (SDMA) or asymmetrically (ADMA) conferring different biological functions. Despite the importance of histone methylation on gene regulation, characterization and quantitation of this modification have proven to be quite challenging. Great advances have been made in the analysis of histone modification using both bottom-up and top-down mass spectrometry (MS). However, MS-based analysis of histone posttranslational modifications (PTMs) is still problematic, due both to the basic nature of the histone N-terminal tails and to the combinatorial complexity of the histone PTMs. In this report, we describe a simplified MS-based platform for histone methylation analysis. The strategy uses chemical acetylation with d0-acetic anhydride to collapse all the differently acetylated histone forms into one form, greatly reducing the complexity of the peptide mixture and improving sensitivity for the detection of methylation via summation of all the differently acetylated forms. We have used this strategy for the robust identification and relative quantitation of H4R3 methylation, for which stoichiometry and symmetry status were determined, providing an antibody-independent evidence that H4R3 is a substrate for both Type I and Type II PRMTs. Additionally, this approach permitted the robust detection of H4K5 monomethylation, a very low stoichiometry methylation event (0.02% methylation). In an independent example, we developed an in vitro assay to profile H3K27 methylation and applied it to an EZH2 mutant xenograft model following small-molecule inhibition of the EZH2 methyltransferase. These specific examples highlight the utility of this simplified MS-based approach to quantify histone methylation profiles., Graphical Abstract, Highlights • Simplification of histone complexity for analysis of lysine and arginine methylation. • Improved sensitivity for the analysis of dimethylarginine symmetry. • Accurate ratio of symmetric and asymmetric H4R3 dimethylarginine in cancer cells. • Catalog of accessible histone methyl marks to facilitate assay development., In Brief A simple derivatization strategy that uses chemical acetylation with d0-acetic anhydride to collapse all the differently acetylated histone forms into one, greatly reduces complexity, and improves sensitivity for the detection of methyl marks. A major advantage of this approach is demonstrated by the ability to reproducibly determine the ratio of symmetric and asymmetric dimethylarginine in cancer cells. This work also demonstrates that the approach can facilitate the site-specific location and relative ratio of closely spaced methyl marks.

Today it is the norm that all relevant proteomics data that support the conclusions in scientific publications are made available in public proteomics data repositories. However, given the increase in the number of clinical proteomics studies, an important emerging topic is the management and dissemination of clinical, and thus potentially sensitive, human proteomics data. Both in the United States and in the European Union, there are legal frameworks protecting the privacy of individuals. Implementing privacy standards for publicly released research data in genomics and transcriptomics has led to processes to control who may access the data, so-called “controlled access” data. In parallel with the technological developments in the field, it is clear that the privacy risks of sharing proteomics data need to be properly assessed and managed. In our view, the proteomics community must be proactive in addressing these issues. Yet a careful balance must be kept. On the one hand, neglecting to address the potential of identifiability in human proteomics data could lead to reputational damage of the field, while on the other hand, erecting barriers to open access to clinical proteomics data will inevitably reduce reuse of proteomics data and could substantially delay critical discoveries in biomedical research. In order to balance these apparently conflicting requirements for data privacy and efficient use and reuse of research efforts through the sharing of clinical proteomics data, development efforts will be needed at different levels including bioinformatics infrastructure, policymaking, and mechanisms of oversight., Graphical Abstract, Highlights • Availability of proteomics data in public repositories (ProteomeXchange) has become the norm. • There are growing ethical issues and legal requirements related to human clinical proteomics data. • We review the current state of the art and provide our thoughts about some proteomics data types. • We make concrete recommendations to address these issues, summarized in four different points., In Brief Availability of proteomics data in the public domain has become the norm, as it has been the case in genomics and transcriptomics for many years. Analogously to sequencing data, there are increasing ethical issues and legal requirements related to sensitive human clinical proteomics data. We review the current state of the art and make concrete recommendations to address these issues in the proteomics field, which are summarized in four different areas.

Knowledge about the peptide repertoire presented by human leukocyte antigens (HLA) holds the key to unlock target-specific cancer immunotherapies such as adoptive cell therapies or bispecific T cell engaging receptors. Therefore, comprehensive and accurate characterization of HLA peptidomes by mass spectrometry (immunopeptidomics) across tissues and disease states is essential. With growing numbers of immunopeptidomics datasets and the scope of peptide identification strategies reaching beyond the canonical proteome, the likelihood for erroneous peptide identification as well as false annotation of HLA-independent peptides as HLA ligands is increasing. Such “fake ligands” can lead to selection of nonexistent targets for immunotherapeutic development and need to be recognized as such as early as possible in the preclinical pipeline. Here we present computational and experimental methods that enable the identification of “fake ligands” that might be introduced at different steps of the immunopeptidomics workflow. The statistics presented herein allow discrimination of true HLA ligands from coisolated HLA-independent proteolytic fragments. In addition, we describe necessary steps to ensure system suitability of the chromatographic system. Furthermore, we illustrate an algorithm for detection of source fragmentation events that are introduced by electrospray ionization during mass spectrometry. For confirmation of peptide sequences, we present an experimental pipeline that enables high-throughput sequence verification through similarity of fragmentation pattern and coelution of synthetic isotope-labeled internal standards. Based on these methods, we show the overall high quality of existing datasets but point out limitations and pitfalls critical for individual peptides and how they can be uncovered in order to identify true ligands., Graphical Abstract, Highlights • Best practices to identify true HLA ligands as targets for cancer immunotherapies. • Quality control in mass spectrometry to improve neoantigen/crypto-target discovery. • Computational methods to assess fragment contamination in immunopeptidomics. • Experimental methods for LC system suitability testing and HT sequence verification., In Brief Accurate characterization of the HLA ligandome by mass spectrometry holds the key to unlock target-specific cancer immunotherapies such as adoptive cell therapies or bispecific T cell engaging receptors. Quality control at each step of the immunopeptidomics pipeline is relevant to differentiate between false and true HLA ligands. Here, we present computational and experimental methods as part of our XPRESIDENT technology platform that allow identification of true HLA ligands—an essential prerequisite for successful therapeutic development.

Plague is a zoonotic disease that primarily infects rodents via fleabite. Transmission from flea to host niches requires rapid adaption of Yersinia pestis to the outer environments to establish infection. Here, quantitative proteome and secretome analyses of Y. pestis grown under conditions mimicking the two typical niches, i.e., the mammalian host (Mh) and the flea vector (Fv), were performed to understand the adaption strategies of this deadly pathogen. A secretome of Y. pestis containing 308 proteins has been identified using TMT-labeling mass spectrometry analysis. Although some proteins are known to be secreted, such as the type III secretion substrates, PsaA and F1 antigen, most of them were found to be secretory proteins for the first time. Comparative proteomic analysis showed that membrane proteins, chaperonins and stress response proteins are significantly upregulated under the Mh condition, among which the previously uncharacterized proteins YP_3416∼YP_3418 are remarkable because they cannot only be secreted but also translocated into HeLa cells by Y. pestis. We further demonstrated that the purified YP_3416 and YP_3418 exhibited E3 ubiquitin ligase activity in in vitro ubiquitination assay and yp_3416∼3418 deletion mutant of Y. pestis showed significant virulence attenuation in mice. Taken together, our results represent the first Y. pestis secretome, which will promote the better understanding of Y. pestis pathogenesis, as well as the development of new strategies for treatment and prevention of plague., Graphical Abstract, Highlights • Quantitative proteome analysis of Y. pestis was performed to understand its adaption strategies. • A secretome of Y. pestis containing 308 proteins has been identified. • YP_3416 and YP_3418 exhibited strong E3 ubiquitin ligase activity. • yp_3416∼3418 deletion mutant of Y. pestis showed significant virulence attenuation in mice., In Brief Rapid adaption to the environments is critical for microbes to establish infection. Quantitative proteome and secretome analyses of Y. pestis grown under conditions mimicking its two typical natural niches were performed to understand the adaption strategies of this deadly pathogen. We identified three secreted proteins that can be translocated into host cells and further demonstrated that two of them show strong E3 ubiquitin ligase activity and contribute significantly to the virulence of Y. pestis.

Calcific aortic valve disease (CAVD) occurs when subpopulations of valve cells undergo specific differentiation pathways, promoting tissue fibrosis and calcification. Lipoprotein particles carry oxidized lipids that promote valvular disease, but low-density lipoprotein-lowering therapies have failed in clinical trials, and there are currently no pharmacological interventions available for this disease. Apolipoproteins are known promoters of atherosclerosis, but whether they possess pathogenic properties in CAVD is less clear. To search for a possible link, we assessed 12 apolipoproteins in nonfibrotic/noncalcific and fibrotic/calcific aortic valve tissues by proteomics and immunohistochemistry to understand if they were enriched in calcified areas. Eight apolipoproteins (apoA-I, apoA-II, apoA-IV, apoB, apoC-III, apoD, apoL-I, and apoM) were enriched in the calcific versus nonfibrotic/noncalcific tissues. Apo(a), apoB, apoC-III, apoE, and apoJ localized within the disease-prone fibrosa and colocalized with calcific regions as detected by immunohistochemistry. Circulating apoC-III on lipoprotein(a) is a potential biomarker of aortic stenosis incidence and progression, but whether apoC-III also induces aortic valve calcification is unknown. We found that apoC-III was increased in fibrotic and calcific tissues and observed within the calcification-prone fibrosa layer as well as around calcification. In addition, we showed that apoC-III induced calcification in primary human valvular cell cultures via a mitochondrial dysfunction/inflammation-mediated pathway. This study provides a first assessment of a broad array of apolipoproteins in CAVD tissues, demonstrates that specific apolipoproteins associate with valvular calcification, and implicates apoC-III as an active and modifiable driver of CAVD beyond its potential role as a biomarker.

Many small ORFs embedded in long noncoding RNA (lncRNA) transcripts have been shown to encode biologically functional polypeptides (small ORF-encoded polypeptides [SEPs]) in different organisms. Despite some novel SEPs have been found, the identification is still hampered by their poor predictability, diminutive size, and low relative abundance. Here, we take advantage of NONCODE, a repository containing the most complete collection and annotation of lncRNA transcripts from different species, to build a novel database that attempts to maximize a collection of SEPs from human and mouse lncRNA transcripts. In order to further improve SEP discovery, we implemented two effective and complementary polypeptide enrichment strategies using 30-kDa molecular weight cutoff filter and C8 solid-phase extraction column. These combined strategies enabled us to discover 353 SEPs from eight human cell lines and 409 SEPs from three mouse cell lines and eight mouse tissues. Importantly, 19 of them were then verified through in vitro expression, immunoblotting, parallel reaction monitoring, and synthetic peptides. Subsequent bioinformatics analysis revealed that some of the physical and chemical properties of these novel SEPs, including amino acid composition and codon usage, are different from those commonly found in canonical proteins. Intriguingly, nearly 65% of the identified SEPs were found to be initiated with non-AUG start codons. The 762 novel SEPs probably represent the largest number of SEPs detected by MS reported to date. These novel SEPs might not only provide new clues for the annotation of noncoding elements in the genome but also serve as a valuable resource for functional study., Graphical abstract, Highlights • Complementary enrichment strategies combined with membrane filtration and C8 SPE. • A combined database with the comprehensive putative SEPs and canonical proteins used. • Seven hundred sixty-two novel SEPs identified from human cell lines, mouse cell lines, and mouse tissues. • Nineteen SEPs have been validated by fusion expression or synthetic peptides., In Brief This study proposed a new and effective strategy for the improved discovery and identification of novel SEPs, including the construction of databases maximally collecting all putative small ORFs from human and mouse lncRNA transcripts in NONCODE and the effective enrichment of polypeptides based on 30-kDa molecular weight cutoff (MWCO) membrane and C8 solid-phase extraction column. This effort led to the discovery of 762 novel lncRNA-encoded SEPs from multiple cell lines and tissues.

Hirschsprung disease (HSCR) is a heterogeneous group of neurocristopathy characterized by the absence of the enteric ganglia along a variable length of the intestine. Genetic defects play a major role in the pathogenesis of HSCR, whereas family studies of pathogenic variants in all the known genes (loci) only demonstrate incomplete penetrance and variable expressivity for unknown reasons. Here, we applied large-scale, quantitative proteomics of human colon tissues from 21 patients using isobaric tags for relative and absolute quantification. method followed by bioinformatics analysis. Selected findings were confirmed by parallel reaction monitoring verification. At last, the interesting differentially expressed proteins were confirmed by Western blot. A total of 5341 proteins in human colon tissues were identified. Among them, 664 proteins with >1.2-fold difference were identified in six groups: groups A1 and A2 pooled protein from the ganglionic and aganglionic colon of male, long-segment HSCR patients (n = 7); groups B1 and B2 pooled protein from the ganglionic and aganglionic colon of male, short-segment HSCR patients (n = 7); and groups C1 and C2 pooled protein from the ganglionic and aganglionic colon of female, short-segment HSCR patients (n = 7). Based on these analyses, 49 proteins from five pathways were selected for parallel reaction monitoring verification, including ribosome, endocytosis, spliceosome, oxidative phosphorylation, and cell adhesion. The downregulation of three neuron projection development genes ARF4, KIF5B, and RAB8A in the aganglionic part of the colon was verified in 15 paired colon samples using Western blot. The findings of this study will shed new light on the pathogenesis of HSCR and facilitate the development of therapeutic targets., Graphical Abstract, Highlights • Large-scale, quantitative proteomics of human colon tissues from Hirschsprung disease patients. • Parallel reaction monitoring, Western blotting, and immunohistochemical staining for validation. • Four pathways related to differentially expressed proteins: ribosome, endocytosis, spliceosome, and axon guidance. • Downregulation of ARF4, KIF5B, and RAB8A in the aganglionic (stenotic) colon segment., In Brief Quantitative proteomics revealed differentially expressed proteins in paired colon tissues from 21 patients diagnosed with Hirschsprung disease (HSCR). Hierarchical clustering suggests that the protein abundancy and expression pattern in normal intestinal tissues are closely related to gender. Gene ontology enrichment analysis revealed spliceosome, axon guidance, and extracellular exosome as the most related biological processes/molecular functions. Three neuron projection development molecules, ARF4, KIF5B, and RAB8A, were downregulated in the aganglionic segment which may be involved in the pathogenesis of HSCR.