Energy flux couples sulfur isotope fractionation to proteomic and metabolite profiles in Desulfovibrio vulgaris.

Microbial sulfate reduction is central to the global carbon cycle and the redox evolution of Earth's surface. Tracking the activity of sulfate reducing microorganisms over space and time relies on a nuanced understanding of stable sulfur isotope fractionation in the context of the biochemical machinery of the metabolism. Here, we link the magnitude of stable sulfur isotopic fractionation to proteomic and metabolite profiles under different cellular energetic regimes. When energy availability is limited, cell-specific sulfate respiration rates and net sulfur isotope fractionation inversely covary. Beyond net S isotope fractionation values, we also quantified shifts in protein expression, abundances and isotopic composition of intracellular S metabolites, and lipid structures and lipid/water H isotope fractionation values. These coupled approaches reveal which protein abundances shift directly as a function of energy flux, those that vary minimally, and those that may vary independent of energy flux and likely do not contribute to shifts in S-isotope fractionation. By coupling the bulk S-isotope observations with quantitative proteomics, we provide novel constraints for metabolic isotope models. Together, these results lay the foundation for more predictive metabolic fractionation models, alongside interpretations of environmental sulfur and sulfate reducer lipid-H isotope data.

Unveiling potential therapeutic targets for diabetes-induced frozen shoulder through Mendelian randomization analysis of the human plasma proteome.

INTRODUCTION: This study aimed to assess the causal relationship between diabetes and frozen shoulder by investigating the target proteins associated with diabetes and frozen shoulder in the human plasma proteome through Mendelian randomization (MR) and to reveal the corresponding pathological mechanisms. RESEARCH DESIGN AND METHODS: We employed the MR approach for the purposes of establishing: (1) the causal link between diabetes and frozen shoulder; (2) the plasma causal proteins associated with frozen shoulder; (3) the plasma target proteins associated with diabetes; and (4) the causal relationship between diabetes target proteins and frozen shoulder causal proteins. The MR results were validated and consolidated through colocalization analysis and protein-protein interaction network. RESULTS: Our MR analysis demonstrated a significant causal relationship between diabetes and frozen shoulder. We found that the plasma levels of four proteins were correlated with frozen shoulder at the Bonferroni significance level (p<3.03E-5). According to colocalization analysis, parathyroid hormone-related protein (PTHLH) was moderately correlated with the genetic variance of frozen shoulder (posterior probability=0.68), while secreted frizzled-related protein 4 was highly correlated with the genetic variance of frozen shoulder (posterior probability=0.97). Additionally, nine plasma proteins were activated during diabetes-associated pathologies. Subsequent MR analysis of nine diabetic target proteins with four frozen shoulder causal proteins indicated that insulin receptor subunit alpha, interleukin-6 receptor subunit alpha, interleukin-1 receptor accessory protein, glutathione peroxidase 7, and PTHLH might contribute to the onset and progression of frozen shoulder induced by diabetes. CONCLUSIONS: Our study identified a causal relationship between diabetes and frozen shoulder, highlighting the pathological pathways through which diabetes influences frozen shoulder.

Comparative proteomic analysis of the ovarian fluid and eggs of Siberian sturgeon.

BACKGROUND: Sturgeon species are living fossils that exhibit unique reproductive characteristics, and elucidation of the molecular processes governing the formation and quality of sturgeon eggs is crucial. However, comprehensive data on the protein composition of sturgeon ovarian fluid (OF) and eggs and their functional significance are lacking. To address this knowledge gap, the aim of the present study was to conduct a comprehensive comparative proteomic analysis of Siberian sturgeon OF and eggs using liquid chromatography-mass spectrometry (LC-MS/MS). RESULTS: A total of 617 proteins were identified in OF, and 565 proteins were identified in eggs. A total of 772 proteins showed differential abundance. Among the differentially abundant proteins, 365 were more abundant in OFs, while 407 were more abundant in eggs. We identified 339 proteins unique to OFs and 287 proteins specific to eggs, and further investigated the top 10 most abundant proteins in each. The functional annotation of the OF proteins highlighted their predominant association with immune system processes, including the complement and coagulation cascade, neutrophil and leukocyte-mediated immunity, cholesterol metabolism, and regulation of the actin cytoskeleton. Analysis of egg proteins revealed enrichment in metabolic pathways, such as oxidative phosphorylation and fatty acid metabolism, and protein ubiquitination and translation. OF-specific proteins included extracellular matrix and secretory vesicles, and eggs were enriched in proteins localized to mitochondria and ribosome components. CONCLUSIONS: This study presents the first comprehensive characterization of the protein composition of sturgeon OF and eggs and elucidates their distinct functional roles. These findings advance our understanding of sturgeon reproduction, OF-egg signaling and the origin of OF proteins. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium with the dataset identifier PXD044168 to ensure accessibility for further research.

Cord Blood Proteomic Profiles, Birth Weight, and Early Life Growth Trajectories.

Importance: The cord blood proteome, a repository of proteins derived from both mother and fetus, might offer valuable insights into the physiological and pathological state of the fetus. However, its association with birth weight and growth trajectories early in life remains unexplored. Objective: To identify cord blood proteins associated with birth weight and the birth weight ratio (BWR) and to evaluate the associations of these cord blood proteins with early growth trajectories. Design, Setting, and Participants: This cohort study included 288 mother-child pairs from the ongoing prospective Environmental Influence on Early Aging birth cohort study. Newborns were recruited from East-Limburg Hospital in Genk, Belgium, between February 2010 and November 2017 and followed up until ages 4 to 6 years. Data were analyzed from February 2022 to September 2023. Main Outcomes and Measures: The outcome of interest was the associations of 368 inflammatory-related cord blood proteins with birth weight or BWR and with early life growth trajectories (ie, rapid growth at age 12 months and weight, body mass index [BMI] z score, waist circumference, and overweight at age 4-6 years) using multiple linear regression models. The BWR was calculated by dividing the birth weight by the median birth weight of the population-specific reference growth curve, considering parity, sex, and gestational age. Results are presented as estimates or odds ratios (ORs) for each doubling in proteins. Results: The sample included 288 infants (125 [43.4%] male; mean [SD] gestation age, 277.2 [11.6] days). The mean (SD) age of the child at the follow-up examination was 4.6 (0.4) years old. After multiple testing correction, there were significant associations of birth weight and BWR with 7 proteins: 2 positive associations: afamin (birth weight: coefficient, 341.16 [95% CI, 192.76 to 489.50]) and secreted frizzled-related protein 4 (SFRP4; birth weight: coefficient, 242.60 [95% CI, 142.77 to 342.43]; BWR: coefficient, 0.07 [95% CI, 0.04 to 0.10]) and 5 negative associations: cadherin EGF LAG 7-pass G-type receptor 2 (CELSR2; birth weight: coefficient, -237.52 [95% CI, -343.15 to -131.89]), ephrin type-A receptor 4 (EPHA4; birth weight: coefficient, -342.78 [95% CI, -463.10 to -222.47]; BWR: coefficient, -0.11 [95% CI, -0.14 to -0.07]), SLIT and NTRK-like protein 1 (SLITRK1; birth weight: coefficient, -366.32 [95% CI, -476.66 to -255.97]; BWR: coefficient, -0.11 [95% CI, -0.15 to -0.08]), transcobalamin-1 (TCN1; birth weight: coefficient, -208.75 [95% CI, -305.23 to -112.26]), and unc-5 netrin receptor D (UNC5D; birth weight: coefficient, -209.27 [95% CI, -295.14 to -123.40]; BWR: coefficient, -0.07 [95% CI, -0.09 to -0.04]). Further evaluation showed that 2 proteins were still associated with rapid growth at age 12 months (afamin: OR, 0.32 [95% CI, 0.11-0.88]; TCN1: OR, 2.44 [95% CI, 1.26-4.80]). At age 4 to 6 years, CELSR2, EPHA4, SLITRK1, and UNC5D were negatively associated with weight (coefficients, -1.33 to -0.68 kg) and body mass index z score (coefficients, -0.41 to -0.23), and EPHA4, SLITRK1, and UNC5D were negatively associated with waist circumference (coefficients, -1.98 to -0.87 cm). At ages 4 to 6 years, afamin (OR, 0.19 [95% CI, 0.05-0.70]) and SLITRK1 (OR, 0.32 [95% CI, 0.10-0.99]) were associated with lower odds for overweight. Conclusions and Relevance: This cohort study found 7 cord blood proteins associated with birth weight and growth trajectories early in life. Overall, these findings suggest that stressors that could affect the cord blood proteome during pregnancy might have long-lasting associations with weight and body anthropometrics.

Comparative proteomic analysis of renal tissue of normotensive and hypertensive rats.

Comparative proteomic analysis of kidney tissue from normotensive (WKY) and spontaneously hypertensive (SHR) rats revealed quantitative and qualitative changes in renal proteins. The number of renal proteins specific for WKY rats (blood pressure 110-120 mm Hg) was 13-16. There were 20-24 renal proteins specific for SHR (blood pressure 180 mm Hg and more). The total number of identified renal proteins common for both rat strains included 972-975 proteins. A pairwise comparison of all possible (SHR-WKY) variants identified 8 proteins specific only for normotensive (WKY) animals, and 7 proteins specific only for hypertensive ones (SHR). Taking into consideration their biological roles, the lack of some enzyme proteins in hypertensive rats (for example, biliverdin reductase A) reduces the production of molecules exhibiting antihypertensive properties, while the appearance of others (e.g. betaine-homocysteine S-methyltransferase 2, septin 2, etc.) can be interpreted as a compensatory reaction. Renal proteins with altered relative content (with more than 2.5-fold change) accounted for no more than 5% of all identified proteins. Among the proteins with an increased relative content in hypertensive animals, the largest group consisted of proteins involved in the processes of energy generation and carbohydrate metabolism, as well as antioxidant and protective proteins. In the context of the development of hypertension, the identified relative changes can apparently be considered compensatory. Among the proteins with the most pronounced decrease in the relative content in hypertensive rats, the dramatic reduction in acyl-CoA medium-chain synthetase-3 (ACSM3) appears to make an important contribution to the development of renal pathology in these animals.

Wheat-Based Glues in Conservation and Cultural Heritage: (Dis)solving the Proteome of Flour and Starch Pastes and Their Adhering Properties.

Plant-based adhesives, such as those made from wheat, have been prominently used for books and paper-based objects and are also used as conservation adhesives. Starch paste originates from starch granules, whereas flour paste encompasses the entire wheat endosperm proteome, offering strong adhesive properties due to gluten proteins. From a conservation perspective, understanding the precise nature of the adhesive is vital as the longevity, resilience, and reaction to environmental changes can differ substantially between starch- and flour-based pastes. We devised a proteomics method to discern the protein content of these pastes. Protocols involved extracting soluble proteins using 0.5 M NaCl and 30 mM Tris-HCl solutions and then targeting insoluble proteins, such as gliadins and glutenins, with a buffer containing 7 M urea, 2 M thiourea, 4% CHAPS, 40 mM Tris, and 75 mM DTT. Flour paste's proteome is diverse (1942 proteins across 759 groups), contrasting with starch paste's predominant starch-associated protein makeup (218 proteins in 58 groups). Transformation into pastes reduces proteomes' complexity. Testing on historical bookbindings confirmed the use of flour-based glue, which is rich in gluten and serpins. High levels of deamidation were detected, particularly for glutamine residues, which can impact the solubility and stability of the glue over time. The mass spectrometry proteomics data have been deposited to the ProteomeXchange, Consortium (http://proteomecentral.proteomexchange.org) via the MassIVE partner repository with the data set identifier MSV000093372 (ftp://MSV000093372@massive.ucsd.edu).

Comprehensive Prostate Fluid-Based Spectral Libraries for Enhanced Protein Detection in Urine.

Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.

Bone Proteomics Method Optimization for Forensic Investigations.

The application of proteomic analysis to forensic skeletal remains has gained significant interest in improving biological and chronological estimations in medico-legal investigations. To enhance the applicability of these analyses to forensic casework, it is crucial to maximize throughput and proteome recovery while minimizing interoperator variability and laboratory-induced post-translational protein modifications (PTMs). This work compared different workflows for extracting, purifying, and analyzing bone proteins using liquid chromatography with tandem mass spectrometry (LC-MS)/MS including an in-StageTip protocol previously optimized for forensic applications and two protocols using novel suspension-trap technology (S-Trap) and different lysis solutions. This study also compared data-dependent acquisition (DDA) with data-independent acquisition (DIA). By testing all of the workflows on 30 human cortical tibiae samples, S-Trap workflows resulted in increased proteome recovery with both lysis solutions tested and in decreased levels of induced deamidations, and the DIA mode resulted in greater sensitivity and window of identification for the identification of lower-abundance proteins, especially when open-source software was utilized for data processing in both modes. The newly developed S-Trap protocol is, therefore, suitable for forensic bone proteomic workflows and, particularly when paired with DIA mode, can offer improved proteomic outcomes and increased reproducibility, showcasing its potential in forensic proteomics and contributing to achieving standardization in bone proteomic analyses for forensic applications.

Sample Preparation and Phosphopeptide Enrichment for Plant Phosphoproteomics via Label-Free Mass Spectrometry.

Phosphopeptide enrichment is the main bottleneck of every phosphorylation study. Therefore, in this chapter, a general workflow tries to overbridge the hurdles of plant sample handling from sample collection to protein extraction, protein solubilization, enzymatic digestion, and enrichment step prior to mass spectrometry. The workflow provides information to perform global proteomics as well as phosphoproteomics enabling the researcher to use the protocol in both fields.

Use of data-independent acquisition mass spectrometry to identify an objective serum indicator of the need for osteoporotic therapeutic intervention.

Osteoporosis is characterized by weakened bone microstructure and loss of bone mass. Current diagnostic criteria for osteoporosis are based on the T-score, which is a measure of bone mineral density. However, osteoporotic fragility fractures can occur regardless of the T-score, underscoring the need for additional criteria for the early detection of patients at fracture risk. To identify indicators of reduced bone strength, we performed serum proteomic analysis using data-independent acquisition mass spectrometry with serum samples from two patient groups, one with osteoporosis but no fractures and the other with osteopenia and fragility fractures. Collective evaluation of the results identified six serum proteins that changed to a similar extent in both patient groups compared with controls. Of these, extracellular matrix protein 1 (ECM1), which contributes to bone formation, showed the most significant increase in serum levels in both patient groups. An ELISA-based assay suggested that ECM1 could serve as a serum indicator of the need for therapeutic intervention; however, further prospective studies with a larger sample size are necessary to confirm these results. The present findings may contribute to the provision of early and appropriate therapeutic strategies for patients at risk of osteoporotic fractures. SIGNIFICANCE: This study aimed to identify objective serum indicators of the need for therapeutic intervention in individuals at risk of osteoporotic fracture. Comprehensive proteome analyses of serum collected from patients with osteoporosis but no fractures, patients with osteopenia and fragility fractures, and controls were performed by data-independent acquisition mass spectrometry. Collective evaluation of the proteome analysis data and ELISA-based assays identified serum ECM1 as a potential objective marker of the risk of fragility fractures in patients with osteoporosis or osteopenia. The findings are an important step toward the development of appropriate bone health management methods to improve well-being and maintain quality of life.

AlphaFun: Structural-Alignment-Based Proteome Annotation Reveals why the Functionally Unknown Proteins (uPE1) Are So Understudied.

With the rapid expansion of sequencing of genomes, the functional annotation of proteins becomes a bottleneck in understanding proteomes. The Chromosome-centric Human Proteome Project (C-HPP) aims to identify all proteins encoded by the human genome and find functional annotations for them. However, until now there are still 1137 identified human proteins without functional annotation, called uPE1 proteins. Sequence alignment was insufficient to predict their functions, and the crystal structures of most proteins were unavailable. In this study, we demonstrated a new functional annotation strategy, AlphaFun, based on structural alignment using deep-learning-predicted protein structures. Using this strategy, we functionally annotated 99% of the human proteome, including the uPE1 proteins and missing proteins, which have not been identified yet. The accuracy of the functional annotations was validated using the known-function proteins. The uPE1 proteins shared similar functions to the known-function PE1 proteins and tend to express only in very limited tissues. They are evolutionally young genes and thus should conduct functions only in specific tissues and conditions, limiting their occurrence in commonly studied biological models. Such functional annotations provide hints for functional investigations on the uPE1 proteins. This proteome-wide-scale functional annotation strategy is also applicable to any other species.

Delineating molecular regulatory network of meat quality of longissimus dorsi indicated by transcriptomic, proteomic, and metabolomics analysis in rabbit.

This study aims to investigate the potential regulatory network responsible for the meat quality using multi-omics to help developing better varieties. Slaughter performance and meat quality of Shuxing No.1 rabbit outperformed IRA rabbit according to the tested rabbit parameters. Differentially expressed genes (DEGs) and differentially abundance proteins (DAPs) were involved in meat quality-related pathways, such as PI3K - Akt and MAPK signaling pathways. Only SMTNL1 and PM20D2 shared between DEGs and DAPs. Olfactory-sensitive undecanal, a differentially abundant metabolite (DAM) in volatilomics (vDAMs), correlated with all of the remaining 11 vDAMs, and most of 12 vDAMs were associated with amino acid metabolism. Integration revealed that 829 DEGs/DAPs were associated with 15 DAMs in four KEGG pathways, such as melatonin (a DAM in widely targeted metabolomics) was significantly positively correlated with ALDH and negatively correlated with RAB3D and CAT in the tryptophan metabolism pathway. This study sheds light on the potential mechanisms that contribute to the improved meat quality and flavor. SIGNIFICANCE: Shuxing No.1 rabbit is a new breed of meat rabbit in the Chinese market. In meat marketing, meat quality usually determines the purchase intention of consumers. Determining the biological and molecular mechanisms of meat quality in meat rabbit is essential for developing strategies to improve meat quality. According to the tested rabbit parameters, this study ascertained that the slaughter performance and meat quality of Shuxing No.1 rabbit surpasses that of IRA rabbit. The present study profiled the transcriptome, proteome, widely targeted metabolome, and volatilome of longissimus dorsi from Shuxing No.1 rabbit and IRA rabbit. The study found that meat quality and flavor-related tryptophan metabolism pathway is enriched with many DEGs/DAPs (including ALDH, RAB3D, and CAT), as well as a DAM, melatonin. This study sheds light on the potential mechanisms that contribute to the improved meat quality and flavor.

The effects of immortalization on the N-glycome and proteome of CDK4-transformed lung cancer cells.

Biological experiments are often conducted in vitro using immortalized cells due to their accessibility and ease of propagation compared to primary cells and live animals. However, immortalized cells may present different proteomic and glycoproteomic characteristics from the primary cell source due to the introduction of genes that enhance proliferation (e.g. CDK4) or enable telomere lengthening. To demonstrate the changes in phenotype upon CDK4-transformation, we performed LC-MS/MS glycomic and proteomic characterizations of a human lung cancer primary cell line (DTW75) and a CDK4-transformed cell line (GL01) derived from DTW75. We observed that the primary and CDK4-transformed cells expressed significantly different levels of sialylated, fucosylated, and sialofucosylated N-glycans. Specifically, the primary cells expressed higher levels of hybrid- and complex-type sialylated N-glycans, while CDK4-transformed cells expressed higher levels of complex-type fucosylated and sialofucosylated N-glycans. Further, we compared the proteomic differences between the cell lines and found that CDK4-transformed cells expressed higher levels of RNA-binding and adhesion proteins. Further, we observed that the CDK4-transformed cells changed N-glycosylation after 31 days in cell culture, with a decrease in high-mannose and increase in fucosylated, sialylated, and sialofucosylated N-glycans. Identifying these changes between primary and CDK4-transformed cells will provide useful insight when adapting cell lines that more closely resemble in vivo physiological conditions.

Arachidonic acid and docosahexaenoic acid levels correlate with the inflammation proteome in extremely preterm infants.

BACKGROUND & AIM: Clinical trials supplementing the long-chain polyunsaturated fatty acids (LCPUFAs) docosahexaenoic acid (DHA) and arachidonic acid (AA) to preterm infants have shown positive effects on inflammation-related morbidities, but the molecular mechanisms underlying these effects are not fully elucidated. This study aimed to determine associations between DHA, AA, and inflammation-related proteins during the neonatal period in extremely preterm infants. METHODS: A retrospective exploratory study of infants (n = 183) born below 28 weeks gestation from the Mega Donna Mega trial, a randomized multicenter trial designed to study the effect of DHA and AA on retinopathy of prematurity. Serial serum samples were collected after birth until postnatal day 100 (median 7 samples per infant) and analyzed for phospholipid fatty acids and proteins using targeted proteomics covering 538 proteins. Associations over time between LCPUFAs and proteins were explored using mixed effect modeling with splines, including an interaction term for time, and adjusted for gestational age, sex, and center. RESULTS: On postnatal day one, 55 proteins correlated with DHA levels and 10 proteins with AA levels. Five proteins were related to both fatty acids, all with a positive correlation. Over the first 100 days after birth, we identified 57 proteins to be associated with DHA and/or AA. Of these proteins, 41 (72%) related to inflammation. Thirty-eight proteins were associated with both fatty acids and the overall direction of association did not differ between DHA and AA, indicating that both LCPUFAs similarly contribute to up- and down-regulation of the preterm neonate inflammatory proteome. Primary examples of this were the inflammation-modulating cytokines IL-6 and CCL7, both being negatively related to levels of DHA and AA in the postnatal period. CONCLUSIONS: This study supports postnatal non-antagonistic and potentially synergistic effects of DHA and AA on the inflammation proteome in preterm infants, indicating that supplementation with both fatty acids may contribute to limiting the disease burden in this vulnerable population. CLINICAL REGISTRATION NUMBER: ClinicalTrials.gov (NCT03201588).

Unveiling Cryptosporidium parvum sporozoite-derived extracellular vesicles: profiling, origin, and protein composition.

Cryptosporidium parvum is a common cause of a zoonotic disease and a main cause of diarrhea in newborns. Effective drugs or vaccines are still lacking. Oocyst is the infective form of the parasite; after its ingestion, the oocyst excysts and releases four sporozoites into the host intestine that rapidly attack the enterocytes. The membrane protein CpRom1 is a large rhomboid protease that is expressed by sporozoites and recognized as antigen by the host immune system. In this study, we observed the release of CpRom1 with extracellular vesicles (EVs) that was not previously described. To investigate this phenomenon, we isolated and resolved EVs from the excystation medium by differential ultracentrifugation. Fluorescence flow cytometry and transmission electron microscopy (TEM) experiments identified two types of sporozoite-derived vesicles: large extracellular vesicles (LEVs) and small extracellular vesicles (SEVs). Nanoparticle tracking analysis (NTA) revealed mode diameter of 181 nm for LEVs and 105 nm for SEVs, respectively. Immunodetection experiments proved the presence of CpRom1 and the Golgi protein CpGRASP in LEVs, while immune-electron microscopy trials demonstrated the localization of CpRom1 on the LEVs surface. TEM and scanning electron microscopy (SEM) showed that LEVs were generated by means of the budding of the outer membrane of sporozoites; conversely, the origin of SEVs remained uncertain. Distinct protein compositions were observed between LEVs and SEVs as evidenced by their corresponding electrophoretic profiles. Indeed, a dedicated proteomic analysis identified 5 and 16 proteins unique for LEVs and SEVs, respectively. Overall, 60 proteins were identified in the proteome of both types of vesicles and most of these proteins (48 in number) were already identified in the molecular cargo of extracellular vesicles from other organisms. Noteworthy, we identified 12 proteins unique to Cryptosporidium spp. and this last group included the immunodominant parasite antigen glycoprotein GP60, which is one of the most abundant proteins in both LEVs and SEVs.

Global O-glycoproteome enrichment and analysis enabled by a combinatorial enzymatic workflow.

A comprehensive analysis of site-specific protein O-glycosylation is hindered by the absence of a consensus O-glycosylation motif, the diversity of O-glycan structures, and the lack of a universal enzyme that cleaves attached O-glycans. Here, we report the development of a robust O-glycoproteomic workflow for analyzing complex biological samples by combining four different strategies: removal of N-glycans, complementary digestion using O-glycoprotease (IMPa) with/without another protease, glycopeptide enrichment, and mass spectrometry with fragmentation of glycopeptides using stepped collision energy. Using this workflow, we cataloged 474 O-glycopeptides on 189 O-glycosites derived from 79 O-glycoproteins from human plasma. These data revealed O-glycosylation of several abundant proteins that have not been previously reported. Because many of the proteins that contained unannotated O-glycosylation sites have been extensively studied, we wished to confirm glycosylation at these sites in a targeted fashion. Thus, we analyzed selected purified proteins (kininogen-1, fetuin-A, fibrinogen, apolipoprotein E, and plasminogen) in independent experiments and validated the previously unknown O-glycosites.

Overcoming the detrimental O-acylation in TMTpro labeling improves the proteome depth and quantification precision.

BACKGROUND: With the advent of proline-based reporter isobaric Tandem Mass Tag (TMTpro) reagents, the sample multiplexing capacity of tandem mass tags (TMTs) has been expanded, and up to 18 samples can be quantified in a multiplexed manner. Like classic TMT reagents, TMTpro reagents contain a tertiary amine group, which markedly enhances their reactivity toward hydroxyl groups and results in O-acylation of serine, threonine and tyrosine residues. This overlabeling significantly compromises proteome analysis in terms of depth and precision. In particular, the reactivity of hydroxyl-containing residues can be dramatically enhanced when coexisting with a histidine in the same peptides, leading to a severe systematic bias against the analysis of these peptides. Although some protocols using a reduced molar excess of TMT under alkaline conditions can alleviate overlabeling of histidine-free peptides to some extent, they have a limited effect on histidyl- and hydroxyl-containing peptides. RESULTS: Here, we report a novel TMTpro labeling method that overcomes detrimental overlabeling while providing high labeling efficiency of amines. Additionally, our method is cost-effective, as it requires only half the amount of TMTpro reagents recommended by the reagent manufacturer. In a deep-scale analysis of a yeast/human two-proteome model sample, we compared our method with a typical alkaline labeling method using a reduced molar excess of TMTpro. Even at a depth of over 10,000 proteins, our method detected 23.7% more unique peptides and 8.7% more protein groups compared to the alkaline labeling method. Moreover, our method significantly improved the quantitative precision due to the reduced variability in labeling and increased protein sequence coverage. This substantially enhanced the statistical power of our method for detecting differentially abundant proteins, providing an average of 13% more yeast proteins that reached statistical significance. SIGNIFCANCE: We presented a novel TMTpro labeling method that overcomes the detrimental O-acylation and thus significantly improves the depth and quantitative precision for proteome analysis.

Proteomic insights into paediatric cancer: Unravelling molecular signatures and therapeutic opportunities.

Survival rates in some paediatric cancers have improved greatly over recent decades, in part due to the identification of diagnostic, prognostic and predictive molecular signatures, and the development of risk-directed therapies. However, other paediatric cancers have proved difficult to treat, and there is an urgent need to identify novel biomarkers that reveal therapeutic opportunities. The proteome is the total set of expressed proteins present in a cell or tissue at a point in time, and is vastly more dynamic than the genome. Proteomics holds significant promise for cancer research, as proteins are ultimately responsible for cellular phenotype and are the target of most anticancer drugs. Here, we review the discoveries, opportunities and challenges of proteomic analyses in paediatric cancer, with a focus on mass spectrometry (MS)-based approaches. Accelerating incorporation of proteomics into paediatric precision medicine has the potential to improve survival and quality of life for children with cancer.

Synthetic Knockout Protein Standard for Evaluating Interference in Tandem Mass Tag-Based Proteomics.

Isobaric labeling is widely used for unbiased, proteome-wide studies, and it provides several advantages, such as fewer missing values among samples and higher quantitative precision. However, ion interference may lead to compressed or distorted observed ratios due to the coelution and coanalysis of peptides. Here, we introduced a synthetic KnockOut standard (sKO) for evaluating interference in tandem mass tags-based proteomics. sKO is made by mixing TMTpro-labeled tryptic peptides derived from four nonhuman proteins and a whole human proteome as background at different proportions. We showcased the utility of the sKO standard by exploring ion interference at different peptide concentrations (up to a 30-fold change in abundance) and using a variety of mass spectrometer data acquisition strategies. We also demonstrated that the sKO standard could provide valuable information for the rational design of acquisition strategies to achieve optimal data quality and discussed its potential applications for high-throughput proteomics workflows development.