The resistance properties of the bacterial spores are partially due to spore surface proteins, ∼30% of which are said to form an insoluble protein fraction. Previous research has also identified a group of spore coat proteins affected by spore maturation, which exhibit an increased level of interprotein cross-linking. However, the proteins and the types of cross-links involved, previously proposed based on indirect evidence, have yet to be confirmed experimentally. To obtain more insight into the structural basis of the proteinaceous component of the spore coat, we attempted to identify coat cross-links and the proteins involved using new peptide fractionation and bioinformatic methods. Young (day 1) and matured (day 5) Bacillus subtilis spores of wild-type and transglutaminase mutant strains were digested with formic acid and trypsin, and cross-linked peptides were enriched using strong cation exchange chromatography. The enriched cross-linked peptide fractions were subjected to Fourier-transform ion cyclotron resonance tandem mass spectrometry, and the high-quality fragmentation data obtained were analyzed using two specialized software tools, pLink2 and XiSearch, to identify cross-links. This analysis identified specific disulfide bonds between coat proteins CotE-CotE and CotJA-CotJC, obtained evidence of disulfide bonds in the spore crust proteins CotX, CotY, and CotZ, and identified dityrosine and ε-(γ)-glutamyl-lysine cross-linked coat proteins. The findings in this Letter are the first direct biochemical data on protein cross-linking in the spore coat and the first direct evidence of the cross-linked building blocks of the highly ordered and resistant structure called the spore coat.

A novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19) and continues to be a global health challenge. To understand viral disease biology, we have carried out proteo-genomic analysis using next-generation sequencing (NGS) and mass spectrometry on nasopharyngeal swabs of COVID-19 patients to examine the clinical genome and proteome. Our study confirms the mutability of SARS-CoV-2 showing multiple single-nucleotide polymorphisms. NGS analysis detected 27 mutations, of which 14 are synonymous, 11 are missense, and 2 are extragenic in nature. Phylogenetic analysis of SARS-CoV-2 isolates indicated their close relation to a Bangladesh isolate and multiple origins of isolates within the country. Our proteomic analysis, for the first time, identified 13 different SARS-CoV-2 proteins from the clinical swabs. Of the total 41 peptides captured by high-resolution mass spectrometry, 8 matched to nucleocapsid protein, 2 to ORF9b, and 1 to spike glycoprotein and ORF3a, with remaining peptides mapping to ORF1ab polyprotein. Additionally, host proteome analysis revealed several key host proteins to be uniquely expressed in COVID-19 patients. Pathway analysis of these proteins points toward modulation in immune response, especially involving neutrophil and IL-12-mediated signaling. Besides revealing the aspects of host-virus pathogenesis, our study opens new avenues to develop better diagnostic markers and therapeutic approaches.

Isotope analyses are some of the most common analytical methods applied to ancient bone, aiding the interpretation of past diets and chronology. For this, the evaluation of "collagen yield" (as defined in radiocarbon dating and stable isotope research) is a routine step that allows for the selection of specimens that are deemed adequate for subsequent analyses, with samples containing less than ∼1% "collagen yield" normally being used for isotopic analysis but discounted for radiocarbon dating. The aims of this study were to use proteomic methods of MALDI-TOF (matrix assisted laser desorption ionization time-of-fligh mass spectrometry) and LC-ESI-MS/MS (liquid chromatography electrospray ionization tandem mass spectrometry) to investigate the endogeneity of the dominant proteinaceous biomolecules within samples that are typically considered to contain poorly preserved protein. Taking 29 archaeological samples, we evaluated the proteome variability between different acid-soluble fractions removed prior to protein gelatinization and considered waste as part of the radiocarbon dating process. We then correlated these proteomes against the commonly used "collagen yield" proxy for preservation. We found that these waste fractions contained a significant amount of both collagenous and noncollagenous proteins (NCPs) but that the abundance of these was not correlated with the acquired "collagen yield". Rather than a depleted protein load as would be expected from a low "collagen yield", the variety of the extracted NCPs was comparable with that commonly obtained from ancient samples and included informative proteins useful for species identification, phylogenetic studies, and potentially even for isotopic analyses, given further method developments. Additionally, we did not observe any correlation between "collagen yield" and peptide mass fingerprint success or between the different fractions taken from the same sample but at different radiocarbon pretreatment stages. Overall, these findings highlight the value in retaining and analyzing sample fractions that are otherwise discarded as waste during the radiocarbon dating process but more importantly, that low "collagen yield" specimens that are often misinterpreted by archaeologists as being devoid of protein can still yield useful molecular sequence-based information.

This work presents methods for identifying and then creating a mass spectral library for disulfide-linked peptides originating from the NISTmAb, a reference material of the humanized IgG1k monoclonal antibody (RM 8671). Analyses involved both partially reduced and non-reduced samples under neutral and weakly basic conditions followed by nanoflow liquid chromatography tandem mass spectrometry (LC-MS/MS). Spectra of peptides containing disulfide bonds are identified by both MS1 ion and MS2 fragment ion data in order to completely map all the disulfide linkages in the NISTmAb. This led to the detection of 383 distinct disulfide-linked peptide ions, arising from fully tryptic cleavage, missed cleavage, irregular cleavage, complex Met/Trp oxidation mixtures, and metal adducts. Fragmentation features of disulfide bonds under low-energy collision dissociation were examined. These include (1) peptide bond cleavage leaving disulfide bonds intact; (2) disulfide bond cleavage, often leading to extensive fragmentation; and (3) double cleavage products resulting from breakages of two peptide bonds or both peptide and disulfide bonds. Automated annotation of various complex MS/MS fragments enabled the identification of disulfide-linked peptides with high confidence. Peptides containing each of the nine native disulfide bonds were identified along with 86 additional disulfide linkages arising from disulfide bond shuffling. The presence of shuffled disulfides was nearly completely abrogated by refining digest conditions. A curated spectral library of 702 disulfide-linked peptide spectra was created from this analysis and is publicly available for free download. Since all IgG1 antibodies have the same constant regions, the resulting library can be used as a tool for facile identification of "hard-to-find" disulfide-bonded peptides. Moreover, we show that one may identify such peptides originating from IgG1 proteins in human serum, thereby serving as a means of monitoring the completeness of protein reduction in proteomics studies. Data are available via ProteomeXchange with identifier PXD023358.

In-depth LC-MS-based proteomic profiling of limited biological and clinical samples, such as rare cells or tissue sections from laser capture microdissection or microneedle biopsies, has been problematic due, in large, to the inefficiency of sample preparation and attendant sample losses. To address this issue, we developed on-microsolid-phase extraction tip (OmSET)-based sample preparation for limited biological samples. OmSET is simple, efficient, reproducible, and scalable and is a widely accessible method for processing ∼200 to 10,000 cells. The developed method benefits from minimal sample processing volumes (1-3 μL) and conducting all sample processing steps on-membrane within a single microreactor. We first assessed the feasibility of using micro-SPE tips for nanogram-level amounts of tryptic peptides, minimized the number of required sample handling steps, and reduced the hands-on time. We then evaluated the capability of OmSET for quantitative analysis of low numbers of human monocytes. Reliable and reproducible label-free quantitation results were obtained with excellent correlations between protein abundances and the amounts of starting material (R2 = 0.93) and pairwise correlations between sample processing replicates (R2 = 0.95) along with the identification of approximately 300, 1800, and 2000 protein groups from injected ∼10, 100, and 500 cell equivalents, resulting from processing approximately 200, 2000, and 10,000 cells, respectively.

Secondary structure predictions of proteins were compared to experimental results by wide-line 1H NMR. IUPred2A was used to generate predictions of disordered protein or binding regions. Thymosin-β4 and the stabilin-2 cytoplasmic domain were found to be mainly disordered, in agreement with the experimental results. α-Synuclein variants were predicted to be disordered, as in the experiments, but the A53T mutant showed less predicted disorder, in contrast with the wide-line 1H NMR result. A disordered binding site was found for thymosin-β4, whereas the stabilin-2 cytoplasmic domain was indicated as such in its entire length. The last third of the α-synuclein variant's sequence was a disordered binding site. Thymosin-β4 and the stabilin-2 cytoplasmic domain contained only coils and helices according to five secondary structure prediction methods (SPIDER3-SPOT-1D, PSRSM, MUFold-SSW, Porter 5, and RaptorX). β-Sheets are present in α-synucleins, and they extend to more amino acid residues in the A53T mutant according to the predictions. The latter is verified by experiments. The comparison of the predictions with the experiments suggests that helical parts are buried.

With 28 potential N-glycosylation sites, human carcinoembryonic antigen (CEA) bears an extreme amount of N-linked glycosylation, and approximately 60% of its molecular mass can be attributed to its carbohydrates. CEA is often overexpressed and released by many solid tumors, including colorectal carcinomas. CEA displays an impressive heterogeneity and variability in sugar content; however, site-specific distribution of carbohydrate structures has not been reported so far. The present study investigated CEA samples purified from human colon carcinoma and human liver metastases and enabled the characterization of 21 out of 28 potential N-glycosylation sites with respect to their occupancy. The coverage was achieved by a multienzymatic digestion approach with specific enzymes, such as trypsin, endoproteinase Glu-C, and the nonspecific enzyme, Pronase, followed by analysis using sheathless CE-MS/MS. In total, 893 different N-glycopeptides and 128 unique N-glycan compositions were identified. Overall, a great heterogeneity was found both within (micro) and in between (macro) individual N-glycosylation sites. Moreover, notable differences were found on certain N-glycosylation sites between primary adenocarcinoma and metastatic tumor in regard to branching, bisection, sialylation, and fucosylation. Those features, if further investigated in a targeted manner, may pave the way toward improved diagnostics and monitoring of colorectal cancer progression and recurrence. Raw mass spectrometric data and Skyline processed data files that support the findings of this study are available in the MassIVE repository with the identifier MSV000086774 [DOI: 10.25345/C5Z50X].

Erratum in J Proteome Res. 2021 Mar 24;:

Extracellular vesicles (EVs) are secreted by any neural cells in the central nervous system for molecular clearance, cellular communications, and disease spread in multiple neurodegenerative diseases, including Alzheimer's disease (AD), although their exact molecular mechanism is poorly understood. We hypothesize that high-resolution proteomic profiling of EVs separated from animal models of AD would determine the composition of EV contents and their cellular origin. Here, we examined recently developed transgenic mice (CAST.APP/PS1), which express familial AD-linked mutations of amyloid precursor protein (APP) and presenilin-1 (PS1) in the CAST/EiJ mouse strain and develop hippocampal neurodegeneration. Quantitative proteomics analysis of EVs separated from CAST.APP/PS1 and age-matched control mice by tandem mass tag-mass spectrometry identified a total of 3444 unique proteins, which are enriched in neuron-, astrocyte-, oligodendrocyte-, and microglia-specific molecules. CAST.APP/PS1-derived EVs show significant enrichment of Psen1, APP, and Itgax and reduction of Wdr61, Pmpca, Aldh1a2, Calu, Anp32b, Actn4, and Ndufv2 compared to WT-derived EVs, suggesting the involvement of Aβ-processing complex and disease-associated/neurodegenerative microglia (DAM/MGnD) in EV secretion. In addition, Itgax and Apoe, DAM/MGnD markers, in EVs show a positive correlation with Itgax and Apoe mRNA expression from brain tissue in CAST.APP/PS1 mice. These datasets indicate the significant contribution of Aβ plaque and neurodegeneration-induced DAM/MGnD microglia for EV secretion in CAST.APP/PS1 mice and shed light on understanding AD pathogenesis.

Psoriasis is an inflammatory disease of the epidermis based on an immunological mechanism involving Langerhans cells and T lymphocytes that produce pro-inflammatory cytokines. Genetic factors, environmental factors, and improper nutrition are considered triggers of the disease. Numerous studies have reported that in a high number of patients, psoriasis is associated with obesity. Excess adipose tissue, typical of obesity, causes a systemic inflammatory status coming from the inflammatory active adipose tissue; therefore, weight reduction is a strategy to fight this pro-inflammatory state. This study aimed to evaluate how a nutritional regimen based on a ketogenic diet influenced the clinical parameters, metabolic profile, and inflammatory state of psoriasis patients. To this end, 30 psoriasis patients were subjected to a ketogenic nutritional regimen and monitored for 4 weeks by evaluating the clinical data, biochemical and clinical parameters, NMR metabolomic profile, and IL-2, IL-1β, TNF-α, IFN-γ, and IL-4 concentrations before and after the nutritional regimen. Our data show that a low-calorie ketogenic diet can be considered a successful strategy and therapeutic option to gain an improvement in psoriasis-related dysmetabolism, with significant correction of the full metabolic and inflammatory status.

Erratum in J Proteome Res. 2021 Apr 16;:

Since the outset of COVID-19, the pandemic has prompted immediate global efforts to sequence SARS-CoV-2, and over 450 000 complete genomes have been publicly deposited over the course of 12 months. Despite this, comparative nucleotide and amino acid sequence analyses often fall short in answering key questions in vaccine design. For example, the binding affinity between different ACE2 receptors and SARS-COV-2 spike protein cannot be fully explained by amino acid similarity at ACE2 contact sites because protein structure similarities are not fully reflected by amino acid sequence similarities. To comprehensively compare protein homology, secondary structure (SS) analysis is required. While protein structure is slow and difficult to obtain, SS predictions can be made rapidly, and a well-predicted SS structure may serve as a viable proxy to gain biological insight. Here we review algorithms and information used in predicting protein SS to highlight its potential application in pandemics research. We also showed examples of how SS predictions can be used to compare ACE2 proteins and to evaluate the zoonotic origins of viruses. As computational tools are much faster than wet-lab experiments, these applications can be important for research especially in times when quickly obtained biological insights can help in speeding up response to pandemics.