Using SWATH-MS to identify new molecular biomarkers in gingival crevicular fluid for detecting periodontitis and its response to treatment.

AIM: To identify new biomarkers to detect untreated and treated periodontitis in gingival crevicular fluid (GCF) using sequential window acquisition of all theoretical mass spectra (SWATH-MS). MATERIALS AND METHODS: GCF samples were collected from 44 periodontally healthy subjects and 40 with periodontitis (Stages III-IV). In the latter, 25 improved clinically 2 months after treatment. Samples were analysed using SWATH-MS, and proteins were identified by the UniProt human-specific database. The diagnostic capability of the proteins was determined with generalized additive models to distinguish the three clinical conditions. RESULTS: In the untreated periodontitis vs. periodontal health modelling, five proteins showed excellent or good bias-corrected (bc)-sensitivity/bc-specificity values of >80%. These were GAPDH, ZG16B, carbonic anhydrase 1, plasma protease inhibitor C1 and haemoglobin subunit beta. GAPDH with MMP-9, MMP-8, zinc-α-2-glycoprotein and neutrophil gelatinase-associated lipocalin and ZG16B with cornulin provided increased bc-sensitivity/bc-specificity of >95%. For distinguishing treated periodontitis vs. periodontal health, most of these proteins and their combinations revealed a predictive ability similar to previous modelling. No model obtained relevant results to differentiate between periodontitis conditions. CONCLUSIONS: New single and dual GCF protein biomarkers showed outstanding results in discriminating untreated and treated periodontitis from periodontal health. Periodontitis conditions were indistinguishable. Future research must validate these findings.

Temporal insights into molecular and cellular responses during rAAV production in HEK293T cells.

The gene therapy field seeks cost-effective, large-scale production of recombinant adeno-associated virus (rAAV) vectors for high-dosage therapeutic applications. Although strategies like suspension cell culture and transfection optimization have shown moderate success, challenges persist for large-scale applications. To unravel molecular and cellular mechanisms influencing rAAV production, we conducted an SWATH-MS proteomic analysis of HEK293T cells transfected using standard, sub-optimal, and optimal conditions. Gene Ontology and pathway analysis revealed significant protein expression variations, particularly in processes related to cellular homeostasis, metabolic regulation, vesicular transport, ribosomal biogenesis, and cellular proliferation under optimal transfection conditions. This resulted in a 50% increase in rAAV titer compared with the standard protocol. Additionally, we identified modifications in host cell proteins crucial for AAV mRNA stability and gene translation, particularly regarding AAV capsid transcripts under optimal transfection conditions. Our study identified 124 host proteins associated with AAV replication and assembly, each exhibiting distinct expression pattern throughout rAAV production stages in optimal transfection condition. This investigation sheds light on the cellular mechanisms involved in rAAV production in HEK293T cells and proposes promising avenues for further enhancing rAAV titer during production.

Data-independent acquisition-based SWATH-MS proteomics profiling to decipher the impact of farming system and chicken strain and discovery of biomarkers of authenticity in organic versus antibiotic-free chicken meat.

In the literature, there is a paucity of methods and tools that allow the identification of biomarkers of authenticity to discriminate organic and non-organic chicken meat products. Shotgun proteomics is a powerful tool that allows the investigation of the entire proteome of a muscle and/or meat sample. In this study, a shotgun proteomics approach using Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) has been applied for the first time to characterize and identify candidate protein biomarkers of authenticity in post-mortem chicken Pectoralis major muscles produced under organic and non-organic farming systems (antibiotic-free). The proteomics characterization was further performed within two chicken strains, these being Ross 308 and Ranger Classic, which differ in their growth rate. From the candidate protein biomarkers, the bioinformatics enrichment analyses revealed significant differences in the muscle proteome between the two chicken strains, which may be related to their genetic background and rearing conditions. The results further provided novel insights on the potential interconnected pathways at interplay that are associated with the differences as a consequence of farming system of chicken strain, such as muscle contraction and energy metabolism. This study could pave the way to more in-depth investigations in proteomics applications to assess chicken meat authenticity and better understand the impact of farming systems on the chicken muscle and meat quality.

Evaluation of a proteomic signature coupled with the kidney failure risk equation in predicting end stage kidney disease in a chronic kidney disease cohort.

BACKGROUND: The early identification of patients at high-risk for end-stage renal disease (ESRD) is essential for providing optimal care and implementing targeted prevention strategies. While the Kidney Failure Risk Equation (KFRE) offers a more accurate prediction of ESRD risk compared to static eGFR-based thresholds, it does not provide insights into the patient-specific biological mechanisms that drive ESRD. This study focused on evaluating the effectiveness of KFRE in a UK-based advanced chronic kidney disease (CKD) cohort and investigating whether the integration of a proteomic signature could enhance 5-year ESRD prediction. METHODS: Using the Salford Kidney Study biobank, a UK-based prospective cohort of over 3000 non-dialysis CKD patients, 433 patients met our inclusion criteria: a minimum of four eGFR measurements over a two-year period and a linear eGFR trajectory. Plasma samples were obtained and analysed for novel proteomic signals using SWATH-Mass-Spectrometry. The 4-variable UK-calibrated KFRE was calculated for each patient based on their baseline clinical characteristics. Boruta machine learning algorithm was used for the selection of proteins most contributing to differentiation between patient groups. Logistic regression was employed for estimation of ESRD prediction by (1) proteomic features; (2) KFRE; and (3) proteomic features alongside KFRE. RESULTS: SWATH maps with 943 quantified proteins were generated and investigated in tandem with available clinical data to identify potential progression biomarkers. We identified a set of proteins (SPTA1, MYL6 and C6) that, when used alongside the 4-variable UK-KFRE, improved the prediction of 5-year risk of ESRD (AUC = 0.75 vs AUC = 0.70). Functional enrichment analysis revealed Rho GTPases and regulation of the actin cytoskeleton pathways to be statistically significant, inferring their role in kidney function and the pathogenesis of renal disease. CONCLUSIONS: Proteins SPTA1, MYL6 and C6, when used alongside the 4-variable UK-KFRE achieve an improved performance when predicting a 5-year risk of ESRD. Specific pathways implicated in the pathogenesis of podocyte dysfunction were also identified, which could serve as potential therapeutic targets. The findings of our study carry implications for comprehending the involvement of the Rho family GTPases in the pathophysiology of kidney disease, advancing our understanding of the proteomic factors influencing susceptibility to renal damage.

Peeking into the Stingers: A Comprehensive SWATH-MS Study of the European Hornet Vespa crabro (Linnaeus, 1758) (Hymenoptera: Vespidae) Venom Sac Extracts.

This study aimed to investigate the venom sac extracts (VSEs) of the European hornet (EH) Vespa crabro (Linnaeus, 1758) (Hymenoptera: Vespidae), focusing on the differences between stinging females, gynes (G), and workers (W), at the protein level. Using a quantitative "Sequential Window Acquisition of all Theoretical Fragment Ion Mass Spectra" (SWATH-MS) analysis, we identified and quantified a total of 240 proteins. Notably, within the group, 45.8% (n = 110) showed significant differential expression between VSE-G and VSE-W. In this set, 57.3% (n = 63) were upregulated and 42.7% (n = 47) downregulated in the G. Additionally, the two-hundred quantified proteins from the class Insecta belong to sixteen different species, six of them to the Hymenoptera/Apidae lineage, comprising seven proteins with known potential allergenicity. Thus, phospholipase A1 (Vesp v 1), phospholipase A1 verutoxin 2b (VT-2b), hyaluronidase A (Vesp v 2A), hyaluronidase B (Vesp v 2B), and venom allergen 5 (Vesp v 5) were significantly downregulated in the G, and vitellogenin (Vesp v 6) was upregulated. Overall, 46% of the VSE proteins showed differential expression, with a majority being upregulated in G. Data are available via ProteomeXchange with identifier PXD047955. These findings shed light on the proteomic differences in VSE between EH castes, potentially contributing to our understanding of their behavior and offering insights for allergy research.

Computational inhibition of S100A8 (calgranulin A) as a potential non-invasive biomarker for rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic joint pain and inflammation, loss of mobility, which affects the quality of life. The etiology of RA is unknown, and there is no isolated cause for the development of this illness. Synovial inflammation, autoantibody generation and bone degradation leading to deformity are classic characteristics of RA. The search for a non-invasive biomarker is crucial for helping patients receive standard therapies leading to faster treatments, as diagnosis depends on invasive biopsies. Therefore, in the present investigation, using transcriptomics and proteomic approaches, potential genes involved in crucial networks in RA were identified. Gene expression datasets of two tissue types i.e. whole blood and synovial tissue were retrieved from the GEO database and used for transcriptomic analyses. Using SWATH-MS analysis, differentially expressed proteins were identified from collected saliva of RA patients. Through bioinformatics analysis, S100A8, also known as Calprotectin (a complex of S100A8/A9) or Calgranulin A, was found to be common among all tissue types. S100A8 was then further quantified in saliva of healthy volunteers and RA patients, where it was found that the protein's level in healthy controls was lowered when compared to RA patients. Through in-silico characterization, potential plant-based inhibitors of S100A8 were also identified, to reduce its pro-inflammatory effects. Thus, it may be important in the pathophysiology of RA and, in the future, might help guide targeted treatment. as well as act as a non-invasive diagnostic biomarker platform.

Quantification of Adaptive Immune Responses Against Protein-Binding Interfaces in the Streptococcal M1 Protein.

Bacterial or viral antigens can contain subdominant protein regions that elicit weak antibody responses upon vaccination or infection although there is accumulating evidence that antibody responses against subdominant regions can enhance the protective immune response. One proposed mechanism for subdominant protein regions is the binding of host proteins that prevent antibody production against epitopes hidden within the protein binding interfaces. Here, we used affinity purification combined with quantitative mass spectrometry (AP-MS) to examine the level of competition between antigen-specific antibodies and host-pathogen protein interaction networks using the M1 protein from Streptococcus pyogenes as a model system. As most humans have circulating antibodies against the M1 protein, we first used AP-MS to show that the M1 protein interspecies protein network formed with human plasma proteins is largely conserved in naïve mice. Immunizing mice with the M1 protein generated a time-dependent increase of anti-M1 antibodies. AP-MS analysis comparing the composition of the M1-plasma protein network from naïve and immunized mice showed significant enrichment of 292 IgG peptides associated with 56 IgG chains in the immune mice. Despite the significant increase of bound IgGs, the levels of interacting plasma proteins were not significantly reduced in the immune mice. The results indicate that the antigen-specific polyclonal IgG against the M1 protein primarily targets epitopes outside the other plasma protein binding interfaces. In conclusion, this study demonstrates that AP-MS is a promising strategy to determine the relationship between antigen-specific antibodies and host-pathogen interaction networks that could be used to define subdominant protein regions of relevance for vaccine development.

SWATH-MS as a strategy for CHO host cell protein identification and quantification supporting the characterization of mAb purification platforms.

Host cell proteins (HCPs) are process-related impurities expressed by the host cells during biotherapeutics' manufacturing, such as monoclonal antibodies (mAbs). Some challenging HCPs evade clearance during the downstream processing and can be co-purified with the molecule of interest, which may impact product stability, efficacy, and safety. Therefore, HCP content is a critical quality attribute to monitor and quantify across the bioprocess. Here we explored a mass spectrometry (MS)-based proteomics tool, the sequential window acquisition of all theoretical fragment-ion spectra (SWATH) strategy, as an orthogonal method to traditional ELISA. The SWATH workflow was applied for high-throughput individual HCP identification and quantification, supporting characterization of a mAb purification platform. The design space of HCP clearance of two polishing resins was evaluated through a design of experiment study. Absolute quantification of high-risk HCPs was achieved (reaching 1.8 and 4.2 ppm limits of quantification, for HCP A and B respectively) using HCP-specific synthetic heavy labeled peptide calibration curves. Profiling of other HCPs was also possible using an average calibration curve (using labeled peptides from different HCPs). The SWATH approach is a powerful tool for HCP assessment during bioprocess development enabling simultaneous monitoring and quantification of different individual HCPs and improving process understanding of their clearance.

Proteomic Profiling Identifies Candidate Diagnostic Biomarkers of Hydrosalpinx in Endometrial Fluid: A Pilot Study.

Hydrosalpinx is a fluid occlusion and distension of the fallopian tubes, often resulting from pelvic inflammatory disease, which reduces the success of artificial reproductive technologies (ARTs) by 50%. Tubal factors account for approximately 25% of infertility cases, but their underlying molecular mechanisms and functional impact on other reproductive tissues remain poorly understood. This proteomic profiling study applied sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) to study hydrosalpinx cyst fluid and pre- and post-salpingectomy endometrial fluid. Among the 967 proteins identified, we found 19 and 17 candidate biomarkers for hydrosalpinx in pre- and post-salpingectomy endometrial fluid, respectively. Salpingectomy significantly affected 76 endometrial proteins, providing insights into the enhanced immune response and inflammation present prior to intervention, and enhanced coagulation cascades and wound healing processes occurring one month after intervention. These findings confirmed that salpingectomy reverses the hydrosalpinx-related functional impairments in the endometrium and set a foundation for further biomarker validation and the development of less-invasive diagnostic strategies for hydrosalpinx.

Cerebrospinal fluid proteins in idiopathic intracranial hypertension: An exploratory SWATH proteomics analysis.

PURPOSE: The pathogenesis of idiopathic intracranial hypertension (IIH) is currently poorly understood. This exploratory study aimed to identify potential cerebrospinal fluid (CSF) biomarkers in IIH cases compared to controls using SWATH-MS proteomics approach. EXPERIMENTAL DESIGN: CSF samples were collected prospectively from IIH cases and control subjects which were subjected to SWATH-MS based untargeted proteomics. Proteins with fold change > 1.5 or < 0.67 and p-value < 0.05 were considered significantly differentially expressed. Data are available via ProteomeXchange with identifier PXD027751. Statistical analysis was conducted in R version 3.6.2. RESULTS: We included CSF samples from 33 subjects, consisting of 13 IIH cases and 20 controls. A total of 262 proteins were identified in Proteinpilot search. Through SWATH analysis, we quantified 232 proteins. We observed 37 differentially expressed proteins between the two groups with 24 upregulated and 13 downregulated proteins. There were two differential proteins among overweight versus non-overweight IIH cases. Network for 23 proteins was highly connected in the interaction analysis. CONCLUSIONS AND CLINICAL RELEVANCE: Neurosecretory, neuroendocrine, and inflammatory proteins were predominantly involved in causing IIH. This exploratory study served as a platform to identify 37 differentially expressed proteins in IIH and also showed significant differences between overweight and non-overweight IIH patients.

Temporal Profiling of Host Proteome against Different M. tuberculosis Strains Reveals Delayed Epigenetic Orchestration.

Apart from being preventable and treatable, tuberculosis is the deadliest bacterial disease afflicting humankind owing to its ability to evade host defence responses, many of which are controlled by epigenetic mechanisms. Here, we report the temporal dynamics of the proteome of macrophage-like host cells after infecting them for 6, 18, 30, and 42 h with two laboratory strains (H37Ra and H37Rv) and two clinical strains (BND433 and JAL2287) of Mycobacterium tuberculosis (MTB). Using SWATH-MS, the proteins characterized at the onset of infection broadly represented oxidative stress and cell cytoskeleton processes. Intermediary and later stages of infection are accompanied by a reshaping of the combination of proteins implicated in histone stability, gene expression, and protein trafficking. This study provides strain-specific and time-specific variations in the proteome of the host, which might further the development of host-directed therapeutics and diagnostic tools against the pathogen. Also, our findings accentuate the importance of proteomic tools in delineating the complex recalibration of the host defence enabled as an effect of MTB infection. To the best of our knowledge, this is the first comprehensive proteomic account of the host response to avirulent and virulent strains of MTB at different time periods of the life span of macrophage-like cells. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE repository with the dataset identifier PXD022352.

Urine-HILIC: Automated Sample Preparation for Bottom-Up Urinary Proteome Profiling in Clinical Proteomics.

Urine provides a diverse source of information related to a patient's health status and is ideal for clinical proteomics due to its ease of collection. To date, most methods for the preparation of urine samples lack the throughput required to analyze large clinical cohorts. To this end, we developed a novel workflow, urine-HILIC (uHLC), based on an on-bead protein capture, clean-up, and digestion without the need for bottleneck processing steps such as protein precipitation or centrifugation. The workflow was applied to an acute kidney injury (AKI) pilot study. Urine from clinical samples and a pooled sample was subjected to automated sample preparation in a KingFisher™ Flex magnetic handling station using the novel approach based on MagReSyn® HILIC microspheres. For benchmarking, the pooled sample was also prepared using a published protocol based on an on-membrane (OM) protein capture and digestion workflow. Peptides were analyzed by LCMS in data-independent acquisition (DIA) mode using a Dionex Ultimate 3000 UPLC coupled to a Sciex 5600 mass spectrometer. The data were searched in Spectronaut™ 17. Both workflows showed similar peptide and protein identifications in the pooled sample. The uHLC workflow was easier to set up and complete, having less hands-on time than the OM method, with fewer manual processing steps. Lower peptide and protein coefficient of variation was observed in the uHLC technical replicates. Following statistical analysis, candidate protein markers were filtered, at ≥8.35-fold change in abundance, ≥2 unique peptides and ≤1% false discovery rate, and revealed 121 significant, differentially abundant proteins, some of which have known associations with kidney injury. The pilot data derived using this novel workflow provide information on the urinary proteome of patients with AKI. Further exploration in a larger cohort using this novel high-throughput method is warranted.

SWATH-MS analysis of plasma proteins among Indian HIV-1 infected patients.

The identification and characterization of plasma proteins in drug resistant and drug sensitive in HIV-1 infected/AIDS patients were carried out using the SWATH-MS protocol. In total, 204 proteins were identified and quantified, 57 proteins were differentially expressed, out of which 25 proteins were down regulated and 32 proteins were up regulated in drug resistant patients. Six proteins such as complement C4-A, immunoglobulin heavy variable 1-2, carboxylic ester hydrolase, fibulin-1, immunoglobulin lambda constant7, secreted phosphoprotein 24 were differentially expressed in individuals with drug resistant HIV as compared to individuals with drug sensitive HIV. Gene ontology of 57 differentially expressed proteins was analysed and documented.

Revealing the chemical differences and their application in the storage year prediction of Qingzhuan tea by SWATH-MS based metabolomics analysis.

It's generally believed that the longer the storage, the better the quality of dark tea, but the chemical differences of Qingzhuan tea (QZT) with different storage years is still unclear. Herein, in this work, an untargeted metabolomic approach based on SWATH-MS was established to investigate the differential compounds of QZT with 0-9 years' storage time. These QZT samples were roughly divided into two categories by principal component analysis (PCA). After orthogonal projections to latent structures discriminant analysis (OPLS-DA), 18 differential compounds were putatively identified as chemical markers for the storage year variation of QZT. Heatmap visualization showed that the contents of catechins, fatty acids, and some phenolic acids significantly reduced, flavonoid glycosides, triterpenoids, and 8-C N-ethyl-2-pyrrolidinone-substituted flavan-3-ols (EPSFs) increased with the increase of storage time. Furthermore, these chemical markers were verified by the peak areas corresponding to MS2 ions from SWATH-MS. Based on the extraction chromatographic peak areas of MS and MS2 ions, a duration time prediction model was built for QZT with correlation coefficient R2 of 0.9080 and 0.9701, and RMSEP value of 0.85 and 1.24, respectively. This study reveals the chemical differences of QZT with different storage years and provides a theoretical basis for the quality evaluation of stored dark tea.

Proteome Changes Resulting from Malting in Hordein-Reduced Barley Lines.

Hordeum vulgare L., commonly known as barley, is primarily used for animal feed and malting. The major storage proteins in barley are hordeins, known triggers of celiac disease (CD). Here, sequential window acquisition of all theoretical mass spectra (SWATH)-MS proteomics was employed to investigate the proteome profile of grain and malt samples from the malting barley cultivar Sloop and single-, double-, and triple hordein-reduced lines bred in a Sloop background. Using a discovery proteomics approach, 2688 and 3034 proteins were detected from the grain and malt samples, respectively. By utilizing label-free relative quantitation through SWATH-MS, a total of 2654 proteins have been quantified from grain and malt. The comparative analyses between the barley grain and malt samples revealed that the C-hordein-reduced lines have a more significant impact on proteome level changes due to malting than B- and D-hordein-reduced lines. Upregulated proteins in C-hordein-reduced lines were primarily involved in the tricarboxylic acid cycle and fatty acid peroxidation processes to provide more energy for seed germination during malting. By applying proteomics approaches after malting in hordein-reduced barley lines, we uncovered additional changes in the proteome driven by the genetic background that were not apparent in the sound grain. Our findings offer valuable insights for barley breeders and maltsters seeking to understand and optimize the performance of gluten-free grains in malt products.

Impact of sampling location and aging on the Longissimus thoracis et lumborum muscle proteome of dry-aged beef.

This study aimed to explore the differences in the proteome and molecular pathways between two sampling locations (external, internal) of bovine Longissimus thoracis et lumborum (LTL) muscles at 0, 21, and 28 days of dry-aging (i.e. 3, 24, and 31 days post-mortem). It further assessed the impact of post-mortem aging on the meat proteome changes and the biological processes at interplay. Proteins related to defence response to bacterium and regulation of viral entry into host cell were identified to be more abundant on the external location before dry-aging, which may be associated to the oxidative conditions and microbial activity to which post-mortem muscle is exposed during dressing, chilling, and/or quartering of the carcasses. This highlights the relevance of sampling from interior tissues when searching for meat quality biomarkers. As dry-aging progressed, the meat proteome and related biological processes changed differently between sampling locations; proteins related to cell-cell adhesion and ATP metabolic processes pathways were revealed in the external location at 21 and 28 days, respectively. On the other hand, the impact of aging on the proteome of the interior meat samples, evidenced that muscle contraction and structure together with energy metabolism were the major pathways driving dry-aging. Additionally, aging impacted other pathways in the interior tissues, such as regulation of calcium import, neutrophil activation, and regeneration. Overall, the differences in the proteome allowed discriminating the three dry-aging times, regardless of the sampling location. Several proteins were proposed for validation as robust biomarkers to monitor the aging process (tenderization) of dry-aged beef: TTN, GRM4, EEF1A1, LDB3, CILP2, TNNT3, GAPDH, SERPINI1, and OMD.

Nutrition, allergenicity and physicochemical qualities of food-grade protein extracts from Nannochloropsis oculata.

Microalgae offer an opportunity to act as a sustainable source of dietary protein. This study aimed to evaluate the impact of different protein extraction methods on the nutritional and physicochemical properties of Nannochloropsis oculata. Food-grade protein extracts were obtained by hypotonic osmotic shock using milli-Q water. Food grade (FG) and non-food grade (NFG) extraction buffers were compared along with three cell disruption methods including bead beating, probe sonication and a combination of both methods for protein extraction. Mass spectrometry was used for protein and putative allergen identification in FG extracts. Bead beating led to a slightly higher number of identifiable proteins in FG extracts compared to control condition. Putative allergenic proteins were identified in FG extracts of N. oculata using different in-silico methods. These findings support the need to further evaluate the potential allergenic proteins in microalgae including N. oculata such as immunoglobulin E (IgE) binding tests.

Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.

BACKGROUND: Halting progression of chronic kidney disease (CKD) to established end stage kidney disease is a major goal of global health research. The mechanism of CKD progression involves pro-inflammatory, pro-fibrotic, and vascular pathways, but pathophysiological differentiation is currently lacking. METHODS: Plasma samples of 414 non-dialysis CKD patients, 170 fast progressors (with ∂ eGFR-3 ml/min/1.73 m2/year or worse) and 244 stable patients (∂ eGFR of - 0.5 to + 1 ml/min/1.73 m2/year) with a broad range of kidney disease aetiologies, were obtained and interrogated for proteomic signals with SWATH-MS. We applied a machine learning approach to feature selection of proteins quantifiable in at least 20% of the samples, using the Boruta algorithm. Biological pathways enriched by these proteins were identified using ClueGo pathway analyses. RESULTS: The resulting digitised proteomic maps inclusive of 626 proteins were investigated in tandem with available clinical data to identify biomarkers of progression. The machine learning model using Boruta Feature Selection identified 25 biomarkers as being important to progression type classification (Area Under the Curve = 0.81, Accuracy = 0.72). Our functional enrichment analysis revealed associations with the complement cascade pathway, which is relevant to CKD as the kidney is particularly vulnerable to complement overactivation. This provides further evidence to target complement inhibition as a potential approach to modulating the progression of diabetic nephropathy. Proteins involved in the ubiquitin-proteasome pathway, a crucial protein degradation system, were also found to be significantly enriched. CONCLUSIONS: The in-depth proteomic characterisation of this large-scale CKD cohort is a step toward generating mechanism-based hypotheses that might lend themselves to future drug targeting. Candidate biomarkers will be validated in samples from selected patients in other large non-dialysis CKD cohorts using a targeted mass spectrometric analysis.

Comparison of SPEED, S-Trap, and In-Solution-Based Sample Preparation Methods for Mass Spectrometry in Kidney Tissue and Plasma.

Mass spectrometry is a powerful technique for investigating renal pathologies and identifying biomarkers, and efficient protein extraction from kidney tissue is essential for bottom-up proteomic analyses. Detergent-based strategies aid cell lysis and protein solubilization but are poorly compatible with downstream protein digestion and liquid chromatography-coupled mass spectrometry, requiring additional purification and buffer-exchange steps. This study compares two well-established detergent-based methods for protein extraction (in-solution sodium deoxycholate (SDC); suspension trapping (S-Trap)) with the recently developed sample preparation by easy extraction and digestion (SPEED) method, which uses strong acid for denaturation. We compared the quantitative performance of each method using label-free mass spectrometry in both sheep kidney cortical tissue and plasma. In kidney tissue, SPEED quantified the most unique proteins (SPEED 1250; S-Trap 1202; SDC 1197). In plasma, S-Trap produced the most unique protein quantifications (S-Trap 150; SDC 148; SPEED 137). Protein quantifications were reproducible across biological replicates in both tissue (R2 = 0.85-0.90) and plasma (SPEED R2 = 0.84; SDC R2 = 0.76, S-Trap R2 = 0.65). Our data suggest SPEED as the optimal method for proteomic preparation in kidney tissue and S-Trap or SPEED as the optimal method for plasma, depending on whether a higher number of protein quantifications or greater reproducibility is desired.

Proteomics of Vespa velutina nigrithorax Venom Sac Queens and Workers: A Quantitative SWATH-MS Analysis.

Health risks caused by stings from Vespa velutina nigrithorax (VV), also known as the yellow-legged Asian hornet, have become a public concern, but little is known about its venom composition. This study presents the proteome profile of the VV's venom sac (VS) based on Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH-MS). The study also performed proteomic quantitative analysis and examined the biological pathways and molecular functions of the proteins in the VS of VV gynes (i.e., future queens [SQ]) and workers [SW]. The total protein content per VS was significantly higher in the SW than in the SQ (274 ± 54 µg/sac vs. 175 ± 22 µg/sac; p = 0.02). We quantified a total of 228 proteins in the VS, belonging to 7 different classes: Insecta (n = 191); Amphibia and Reptilia (n = 20); Bacilli, γ-Proteobacteria and Pisoniviricetes (n = 12); and Arachnida (n = 5). Among the 228 identified proteins, 66 showed significant differential expression between SQ and SW. The potential allergens hyaluronidase A, venom antigen 5 and phospholipase A1 were significantly downregulated in the SQ venom.