Cerebrospinal Fluid Protein Markers Indicate Neuro-Damage in SARS-CoV-2-Infected Nonhuman Primates.

Neurologic manifestations are among the most frequently reported complications of COVID-19. However, given the paucity of tissue samples and the highly infectious nature of the etiologic agent of COVID-19, we have limited information to understand the neuropathogenesis of COVID-19. Therefore, to better understand the impact of COVID-19 on the brain, we used mass-spectrometry-based proteomics with a data-independent acquisition mode to investigate cerebrospinal fluid (CSF) proteins collected from two different nonhuman primates, Rhesus Macaque and African Green Monkeys, for the neurologic effects of the infection. These monkeys exhibited minimal to mild pulmonary pathology but moderate to severe central nervous system (CNS) pathology. Our results indicated that CSF proteome changes after infection resolution corresponded with bronchial virus abundance during early infection and revealed substantial differences between the infected nonhuman primates and their age-matched uninfected controls, suggesting these differences could reflect altered secretion of CNS factors in response to SARS-CoV-2-induced neuropathology. We also observed the infected animals exhibited highly scattered data distributions compared to their corresponding controls indicating the heterogeneity of the CSF proteome change and the host response to the viral infection. Dysregulated CSF proteins were preferentially enriched in functional pathways associated with progressive neurodegenerative disorders, hemostasis, and innate immune responses that could influence neuroinflammatory responses following COVID-19. Mapping these dysregulated proteins to the Human Brain Protein Atlas found that they tended to be enriched in brain regions that exhibit more frequent injury following COVID-19. It, therefore, appears reasonable to speculate that such CSF protein changes could serve as signatures for neurologic injury, identify important regulatory pathways in this process, and potentially reveal therapeutic targets to prevent or attenuate the development of neurologic injuries following COVID-19.

Species-specific quantification of circulating ebolavirus burden using VP40-derived peptide variants.

Six ebolavirus species are reported to date, including human pathogens Bundibugyo virus (BDBV), Ebola virus (EBOV), Sudan virus (SUDV), and Taï Forest virus (TAFV); non-human pathogen Reston virus (RESTV); and the plausible Bombali virus (BOMV). Since there are differences in the disease severity caused by different species, species identification and viral burden quantification are critical for treating infected patients timely and effectively. Here we developed an immunoprecipitation-coupled mass spectrometry (IP-MS) assay for VP40 antigen detection and quantification. We carefully selected two regions of VP40, designated as peptide 8 and peptide12 from the protein sequence that showed minor variations among Ebolavirus species through MS analysis of tryptic peptides and antigenicity prediction based on available bioinformatic tools, and generated high-quality capture antibodies pan-specific for these variant peptides. We applied this assay to human plasma spiked with recombinant VP40 protein from EBOV, SUDV, and BDBV and virus-like particles (VLP), as well as EBOV infected NHP plasma. Sequence substitutions between EBOV and SUDV, the two species with highest lethality, produced affinity variations of 2.6-fold for p8 and 19-fold for p12. The proposed IP-MS assay differentiates four of the six known EBV species in one assay, through a combination of p8 and p12 data. The IP-MS assay limit of detection (LOD) using multiple reaction monitoring (MRM) as signal readout was determined to be 28 ng/mL and 7 ng/mL for EBOV and SUDV respectively, equivalent to ~1.625-6.5×105 Geq/mL, and comparable to the LOD of lateral flow immunoassays currently used for Ebola surveillance. The two peptides of the IP-MS assay were also identified by their tandem MS spectra using a miniature MALDI-TOF MS instrument, greatly increasing the feasibility of high specificity assay in a decentralized laboratory.

Large-scale Identification of N-linked Intact Glycopeptides in Human Serum using HILIC Enrichment and Spectral Library Search.

Large-scale identification of N-linked intact glycopeptides by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) in human serum is challenging because of the wide dynamic range of serum protein abundances, the lack of a complete serum N-glycan database and the existence of proteoforms. In this regard, a spectral library search method was presented for the identification of N-linked intact glycopeptides from N-linked glycoproteins in human serum with target-decoy and motif-specific false discovery rate (FDR) control. Serum proteins were firstly separated into low-abundance and high-abundance proteins by acetonitrile (ACN) precipitation. After digestion, the N-linked intact glycopeptides were enriched by hydrophilic interaction liquid chromatography (HILIC) and a portion of the enriched N-linked intact glycopeptides were processed by Peptide-N-Glycosidase F (PNGase F) to generate N-linked deglycopeptides. Both N-linked intact glycopeptides and deglycopeptides were analyzed by LC-MS/MS. From N-linked deglycopeptides data sets, 764 N-linked glycoproteins, 1699 N-linked glycosites and 3328 unique N-linked deglycopeptides were identified. Four types of N-linked glycosylation motifs (NXS/T/C/V, X≠P) were used to recognize the N-linked deglycopeptides. The spectra of these N-linked deglycopeptides were utilized for N-linked deglycopeptides library construction and identification of N-linked intact glycopeptides. A database containing 739 N-glycan masses was constructed and utilized during spectral library search for the identification of N-linked intact glycopeptides. In total, 526 N-linked glycoproteins, 1036 N-linked glycosites, 22,677 N-linked intact glycopeptides and 738 N-glycan masses were identified under 1% FDR, representing the most in-depth serum N-glycoproteome identified by LC-MS/MS at N-linked intact glycopeptide level.

Alphabet Projection of Spectra.

In the metabolomics, glycomics, and mass spectrometry of structured small molecules, the combinatoric nature of the problem renders a database impossibly large, and thus de novo analysis is necessary. De novo analysis requires an alphabet of mass difference values used to link peaks in fragmentation spectra when they are different by a mass in the alphabet divided by a charge. Often, this alphabet is not known, prohibiting de novo analysis. A method is proposed that, given fragmentation mass spectra, identifies an alphabet of m/z differences that can build large connected graphs from many intense peaks in each spectrum from a collection. We then introduce a novel approach to efficiently find recurring substructures in the de novo graph results.

Antigen 85B peptidomic analysis allows species-specific mycobacterial identification.

BACKGROUND: Nontuberculous mycobacteria (NTM)-mediated infections are a growing cause of worldwide morbidity, but lack of rapid diagnostics for specific NTM species can delay the initiation of appropriate treatment regimens. We thus examined whether mass spectrometry analysis of an abundantly secreted mycobacterial antigen could identify specific NTM species. METHODS: We analyzed predicted tryptic peptides of the major mycobacterial antigen Ag85B for their capacity to distinguish Mycobacterium tuberculosis and three NTM species responsible for the majority of pulmonary infections caused by slow-growing mycobacterial species. Next, we analyzed trypsin-digested culture supernatants of these four mycobacterial species by liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect candidate species-specific Ag85B peptides, the identity of which were validated by LC-MS/MS performed in parallel reaction monitoring mode. RESULTS: Theoretical tryptic digests of the Ag85B proteins of four common mycobacterial species produced peptides with distinct sequences, including two peptides that could each identify the species origin of each Ag85B protein. LC-MS/MS analysis of trypsinized culture supernatants of these four species detected one of these species-specific signature peptides in each sample. Subsequent LC-MS/MS analyses confirmed these results by targeting these species-specific Ag85B peptides. CONCLUSIONS: LC-MS/MS analysis of Ag85B peptides from trypsin-digested mycobacterial culture supernatants can rapidly detect and identify common mycobacteria responsible for most pulmonary infections caused by slow-growing mycobacteria, and has the potential to rapidly diagnose pulmonary infections caused by these mycobacteria through direct analysis of clinical specimens.

Characterization and relative quantification of phospholipids based on methylation and stable isotopic labeling.

Phospholipids (PLs), one of the lipid categories, are not only the primary building blocks of cellular membranes, but also can be split to produce products that function as second messengers in signal transduction and play a pivotal role in numerous cellular processes, including cell growth, survival, and motility. Here, we present an integrated novel method that combines a fast and robust TMS-diazomethane-based phosphate derivatization and isotopic labeling strategy, which enables simultaneous profiling and relative quantification of PLs from biological samples. Our results showed that phosphate methylation allows fast and sensitive identification of the six major PL classes, including their lysophospholipid counterparts, under positive ionization mode. The isotopic labeling of endogenous PLs was achieved by deuterated diazomethane, which was generated through acid-catalyzed hydrogen/deuterium (H/D) exchange and methanolysis of TMS-diazomethane during the process of phosphate derivatization. The measured H/D ratios of unlabeled and labeled PLs, which were mixed in known proportions, indicated that the isotopic labeling strategy is capable of providing relative quantitation with adequate accuracy, reproducibility, and a coefficient of variation of 9.1%, on average. This novel method offers unique advantages over existing approaches and presents a powerful tool for research of PL metabolism and signaling.

Evaluation of Different N-Glycopeptide Enrichment Methods for N-Glycosylation Sites Mapping in Mouse Brain.

N-Glycosylation of proteins plays a critical role in many biological pathways. Because highly heterogeneous N-glycopeptides are present in biological sources, the enrichment procedure is a crucial step for mass spectrometry analysis. Five enrichment methods, including IP-ZIC-HILIC, hydrazide chemistry, lectin affinity, ZIC-HILIC-FA, and TiO2 affinity were evaluated and compared in the study of mapping N-glycosylation sites in mouse brain. On the basis of our results, the identified N-glycosylation sites were 1891, 1241, 891, 869, and 710 and the FDR values were 3.29, 5.62, 9.54, 9.54, and 20.02%, respectively. Therefore, IP-ZIC-HILIC enrichment method displayed the highest sensitivity and specificity. In this work, we identified a total of 3446 unique glycosylation sites conforming to the N-glycosylation consensus motif (N-X-T/S/C; X ≠ P) with (18)O labeling in 1597 N-glycoproteins. N-glycosylation site information was used to confirm or correct the transmembrane topology of the 57 novel transmembrane N-glycoproteins.

Proteomic Comparison and MRM-Based Comparative Analysis of Metabolites Reveal Metabolic Shift in Human Prostate Cancer Cell Lines.

One of the major challenges in prostate cancer therapy remains the development of effective treatments for castration-resistant prostate cancer (CRPC), as the underlying mechanisms for its progression remain elusive. Previous studies showed that androgen receptor (AR) is crucially involved in regulation of metabolism in prostate cancer (PCa) cells throughout the transition from early stage, androgen-sensitive PCa to androgen-independent CRPC. AR achieves such metabolic rewiring directively either via its transcriptional activity or via interactions with AMP-activated protein kinase (AMPK). However, due to the heterogeneous expression and activity status of AR in PCa cells, it remains a challenge to investigate the links between AR status and metabolic alterations. To this end, we compared the proteomes of three pairs of androgen-sensitive (AS) and androgen-independent (AI) PCa cell lines, namely, PC3-AR(+)/PC3, 22Rv1/Du145, and LNCaP/C42B, using an iTRAQ labeling approach. Our results revealed that most of the differentially expressed proteins between each pair function in metabolism, indicating a metabolic shift between AS and AI cells, as further validated by multiple reaction monitoring (MRM)-based quantification of nucleotides and relative comparison of fatty acids between these cell lines. Furthermore, increased adenylate kinase isoenzyme 1 (AK1) in AS relative to AI cells may result in activation of AMPK, representing a major regulatory factor involved in the observed metabolic shift in PCa cells.

Profiling and relative quantitation of phosphoinositides by multiple precursor ion scanning based on phosphate methylation and isotopic labeling.

Phosphoinositides, the phosphorylated derivatives of phosphatidylinositol (PtdIns), are key regulators of many fundamental biological processes, including cell growth, proliferation, and motility. Here, we present a novel method for rapid, sensitive, and simultaneous profiling of phosphatidylinositol trisphosphate (PtdInsP3), phosphatidylinositol bisphosphate (PtdInsP2), and phosphatidylinositol phosphate (PtdInsP) of different fatty acid compositions. This method is based on a technique called "charged diacylglycerol fragment ion-specific multiple precursor ion scanning" (DAG(+)-specific MPIS), coupled with prior phosphate methylation. Using DAG(+)-specific MPIS, we were able to identify 32 PtdIns, 28 PtdInsP, 30 PtdInsP2, and 3 PtdInsP3 molecular species from bovine brain extracts or prostatic cancer cell lines in an efficient and time-saving manner. Our analysis revealed a large range of fatty acyl compositions in phosphoinositides not obtained previously from mammalian samples. We also developed a method that involves isotopic labeling of endogenous phosphoinositides with deuterated diazomethane (CD2N2) for quantitation of phosphoinositides. CD2N2 was generated in situ through acid-catalyzed H/D exchange and methanolysis of trimethylsilyl diazomethane (TMS-diazomethane). Phosphoinositides, extracted from a PC3 prostatic cancer cell line, were labeled either with CH2N2 or CD2N2 and mixed in known proportions for DAG(+)-specific MPIS-based mass spectrometry (MS) analysis. The results indicate that isotopic labeling is capable of providing accurate quantitation of PtdInsP3, PtdInsP2, and PtdInsP with adequate linearity as well as high reproducibility with an average coefficient variation of 18.9%. More importantly, this new methods excluded the need for multiple phosphoinositide internal standards. DAG(+)-specific MPIS and isotopic labeling based MS analysis of phosphoinositides offers unique advantages over existing approaches and presents a powerful tool for research of phosphoinositide metabolism.

Assay design for unambiguous identification and quantification of circulating pathogen-derived peptide biomarkers.

Rationale: Circulating pathogen-derived proteins can serve as useful biomarkers for infections but may be detected with poor sensitivity and specificity by standard immunoassays due to masking effects and cross-reactivity. Mass spectrometry (MS)-read immunoassays for biomarker-derived peptides can resolve these issues, but lack standard workflows to select species-specific peptides with strong MS signal that are suitable for antibody generation. Methods:Using a Mycobacterium tuberculosis (Mtb) protein as an example, candidate peptides were selected by length, species-specificity, MS intensity, and antigenicity score. MS data from spiked healthy serum was employed to define MS feature thresholds, including a novel measure of internal MS data correlation, to produce a peak detection algorithm. Results: This algorithm performed better in rejecting false positive signal than each of its criteria, including those currently employed for this purpose. Analysis of an Mtb peptide biomarker (CFP-10pep) by this approach identified tuberculosis cases not detected by microbiologic assays, including extrapulmonary tuberculosis and tuberculosis cases in children infected with HIV-1. Circulating CFP-10pep levels measured in a non-human primate model of tuberculosis distinguished disease from asymptomatic infection and tended to correspond with Mtb granuloma size, suggesting that it could also serve as a surrogate marker for Mtb burden and possibly treatment response. Conclusions: These biomarker selection and analysis approach appears to have strong potential utility for infectious disease diagnosis, including cryptic infections, and possibly to monitor changes in Mtb burden that may reflect disease progression or a response to treatment, which are critical needs for more effective disease control.

Nanopore-based disease diagnosis using pathogen-derived tryptic peptides from serum.

Nanopore sensors have shown great utility in nucleic acid detection and sequencing approaches. Recent studies also indicate that current signatures produced by peptide-nanopore interactions can distinguish high purity peptide mixtures, but the utility of nanopore sensors in clinical applications still needs to be explored due to the inherent complexity of clinical specimens. To fill this gap between research and clinical nanopore applications, we describe a methodology to select peptide biomarkers suitable for use in an immunoprecipitation-coupled nanopore (IP-NP) assay, based on their pathogen specificity, antigenicity, charge, water solubility and ability to produce a characteristic nanopore interaction signature. Using tuberculosis as a proof-of-principle example in a disease that can be challenging to diagnose, we demonstrate that a peptide identified by this approach produced high-affinity antibodies and yielded a characteristic peptide signature that was detectable over a broad linear range, to detect and quantify a pathogen-derived peptide from digested human serum samples with high sensitivity and specificity. This nanopore signal distinguished serum from a TB case, non-disease controls, and from a TB-case after extended anti-TB treatment. We believe this assay approach should be readily adaptable to other infectious and chronic diseases that can be diagnosed by peptide biomarkers.

N-Linked Glycopeptide Identification Based on Open Mass Spectral Library Search.

Confident characterization of intact glycopeptides is a challenging task in mass spectrometry-based glycoproteomics due to microheterogeneity of glycosylation, complexity of glycans, and insufficient fragmentation of peptide bones. Open mass spectral library search is a promising computational approach to peptide identification, but its potential in the identification of glycopeptides has not been fully explored. Here we present pMatchGlyco, a new spectral library search tool for intact N-linked glycopeptide identification using high-energy collisional dissociation (HCD) tandem mass spectrometry (MS/MS) data. In pMatchGlyco, (1) MS/MS spectra of deglycopeptides are used to create spectral library, (2) MS/MS spectra of glycopeptides are matched to the spectra in library in an open (precursor tolerant) manner and the glycans are inferred, and (3) a false discovery rate is estimated for top-scored matches above a threshold. The efficiency and reliability of pMatchGlyco were demonstrated on a data set of mixture sample of six standard glycoproteins and a complex glycoprotein data set generated from human cancer cell line OVCAR3.

Comparative proteomics reveals abnormal binding of ATGL and dysferlin on lipid droplets from pressure overload-induced dysfunctional rat hearts.

Excessive retention of neutral lipids in cardiac lipid droplets (LDs) is a common observation in cardiomyopathy. Thus, the systematic investigation of the cardiac LD proteome will help to dissect the underlying mechanisms linking cardiac steatosis and myocardial dysfunction. Here, after isolation of LDs from normal and dysfunctional Sprague-Dawley rat hearts, we identified 752 heart-associated LD proteins using iTRAQ quantitative proteomic method, including 451 proteins previously unreported on LDs. The most noteworthy finding was the identification of the membrane resealing protein, dysferlin. An analysis of dysferlin truncation mutants indicated that its C2 domain was responsible for its LD localization. Quantitative proteomic results further determined that 27 proteins were increased and 16 proteins were decreased in LDs from post pressure overload-induced dysfunctional hearts, compared with normal hearts. Notably, adipose triacylglycerol lipase (ATGL) was dramatically decreased and dysferlin was substantially increased on dysfunctional cardiac LDs. This study for the first time reveals the dataset of the heart LD proteome in healthy tissue and the variation of it under cardiac dysfunction. These findings highlight an association between the altered LD protein localization of dysferlin and ATGL and myocardial dysfunction.