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PubMed2025

Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics.

Data-independent acquisition (DIA)-based mass spectrometry is becoming an increasingly popular mass spectrometry acquisition strategy for carrying out quantitative proteomics experiments. Most of the popular DIA search engines make use of in silico generated spectral libraries. However, the generation of high-quality spectral libraries for DIA data analysis remains a challenge, particularly because most such libraries are generated directly from data-dependent acquisition (DDA) data or are from in silico prediction using models trained on DDA data. In this study, we developed Carafe, a tool that generates high-quality experiment-specific in silico spectral libraries by training deep learning models directly on DIA data. We demonstrate the performance of Carafe on a wide range of DIA datasets, where we observe improved fragment ion intensity prediction and peptide detection relative to existing pretrained DDA models. To make Carafe more accessible to the community, we have integrated Carafe into the widely used Skyline tool.

Journal Article↗
PubMed2025

Benchmark for Quantitative Global and Redox Proteomics Analysis by Combining Protein-Aggregation Capture and Data Independent Acquisition.

Oxidative damage plays a critical role in various diseases including cardiovascular and neurological disorders. Thiol redox reactions, acting as oxidative stress sensors, influence protein structure and function. Redox proteomics, based on the differential alkylation of cysteine sites followed by mass spectrometry, enables the comprehensive analysis of thiol redox status in cells and tissues. However, these approaches require extensive sample manipulation and are not compatible with data-independent acquisition techniques. Here, we introduce PACREDOX, an innovative strategy based on protein aggregation capture (PAC), and demonstrate its compatibility with library-free DIA. Compared with traditional methods such as FASILOX, PACREDOX reduces preparation time and costs while maintaining thiol and proteome coverage. To enable library-free DIA, we corrected in silico spectral libraries in DIA-NN using experimental retention time data from methylthiolated-Cys peptides. PACREDOX with DIA was benchmarked against FASILOX in a myocardial infarction model, yielding the same biological insights, while enhancing peptide and protein coverage. Our results underscore the potential and efficiency of this methodology for studying oxidative damage. Overall, PACREDOX offers an automatable, high-throughput, and cost-effective strategy for redox proteomics.

Proteomics↗
PubMed2025

Proteomic signatures and predictive modeling of cadmium-associated anxiety in middle-aged and elderly populations: an environmental exposure association study.

BACKGROUND: Emerging evidence implicates environmental contaminants such as cadmium (Cd) as modifiable risk factors for anxiety. Despite growing recognition of heavy metal toxicity in neuropsychiatric disorders, the molecular mechanisms linking environmental exposure to anxiety pathogenesis remain poorly understood. METHODS: Based on the established cohort of individuals with cognitive impairment in cadmium-contaminated areas, this cross-sectional association study enrolled 50 middle-aged and elderly hospitalized patients from these regions, adhering to the STROBE guidelines. Blood concentrations of cadmium (Cd), lead (Pb), and mercury (Hg) were analyzed in relation to anxiety severity assessed via the Hamilton Anxiety Rating Scale (HAMA). Plasma proteomic profiling was performed using data-independent acquisition (DIA) quantitative technology with an LC-MS/MS platform (timsTOF Pro, Bruker Daltonics), systematically characterizing 2,531 proteins across all samples. Machine learning techniques, specifically XGBoost and LASSO, were employed to identify biomarkers that were subsequently validated through mediation analysis and animal experiments, allowing for the screening of key protein signatures. Finally, clinical variables were integrated to construct a comprehensive model, which was then thoroughly evaluated. RESULTS: Anxious individuals exhibited significantly higher blood Cd levels than controls (&#x3b2;&#x2009;=&#x2009;0.50, 95% CI: 0.07-0.93, p&#x2009;<&#x2009;0.01), with anxiety positively correlating with depression (r&#x2009;=&#x2009;0.62, p&#x2009;=&#x2009;0.003) and inversely with ApoE3 genotype prevalence. Proteomics identified 120 differentially expressed proteins in anxious patients, enriched in oxidative phosphorylation and neurodegenerative pathways. CCDC126 emerged as a cadmium-associated biomarker, validated in rat models exposed to Cd. Combining CCDC126, blood Cd, Pb, and hypertension, a clinical prediction model achieved robust discrimination (AUC&#x2009;=&#x2009;0.80, validation cohort). CONCLUSIONS: This first integrative environmental-proteomic study highlights cadmium's synergistic role in anxiety pathophysiology and psychiatric comorbidity. The predictive model offers translatable potential for early risk stratification, while CCDC126 provides mechanistic insights for targeted interventions in populations exposed to environmental pollutants.

Cadmium↗
PubMed2026

Integrated analysis of gut microbiota, serum metabolomics, and proteomics reveals novel associations with clinical symptoms in patients with cerebral infarction.

BACKGROUND: Cerebral infarction (CI) is a major cause of adult disability and mortality worldwide. Mounting evidence supports the critical role of the gut-brain axis in cerebrovascular disease progression. This study aimed to characterize the alterations in gut microbiota, serum metabolome, and serum proteome in patients with CI, and to identify multi-omics signatures associated with clinical symptoms. METHODS: A total of 20 CI patients and 20 healthy controls (HC) were enrolled. Fecal microbiota was profiled using 16&#xa0;S rRNA gene high-throughput sequencing. Serum metabolomics and proteomics were analyzed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and data-independent acquisition (DIA) proteomics, respectively. Spearman correlation and multi-omics integration were applied to explore the associations among microbiota, metabolites, proteins, and clinical indicators. RESULTS: CI patients displayed significant gut microbiota dysbiosis, with a markedly lower gut microbiota health index (GMHI) and higher microbiota disorder index (MDI) compared with HC (P&#x2009;<&#x2009;0.001). The genera g_norank_o_RF39 and Oxalobacter were significantly enriched in CI patients, whereas Clostridium_sensu_stricto_1 and Agathobacter were enriched in HC. Metabolomic analysis identified 445 differential metabolites, mainly involved in glycerophospholipid metabolism, phenylalanine metabolism, and caffeine metabolism. Proteomic analysis revealed 140 differentially expressed proteins linked to inflammatory responses, calcium signaling, and NF-&#x3ba;B signaling. Multi-omics integration showed that signature gut microbiota was strongly correlated (P&#x2009;<&#x2009;0.005) with key serum metabolites and proteins implicated in CI pathogenesis. CONCLUSIONS: This integrated multi-omics study revealed distinct gut microbiota, serum metabolomic, and proteomic alterations in CI patients. The microbiota-metabolite-protein regulatory axes provide novel insights into the gut-brain axis in CI and may serve as potential diagnostic biomarkers or therapeutic targets.

Humans↗
PubMed2025

Stage-dependent proteomic alterations in aqueous humor of diabetic retinopathy patients based on data-independent acquisition and parallel reaction monitoring.

BACKGROUND: Diabetic retinopathy (DR), a microvascular complication of diabetes mellitus (DM), represents the predominant cause of preventable vision loss in working-age populations globally. While the pathophysiological mechanisms underlying DR progression remain incompletely understood, our study employs comprehensive proteomic profiling of aqueous humor (AH) to identify stage-specific biomarkers and therapeutic targets in type 2 diabetes mellitus (T2DM) patients across DR progression. METHODS: Utilizing data-independent acquisition (DIA) mass spectrometry, we quantified AH proteomes in a discovery cohort comprising 24 subjects: 18 T2DM patients stratified by DR severity [6 non-DR, 6 non-proliferative DR (NPDR), 6 proliferative DR (PDR)] and 6 cataract controls without diabetes (non-DM). Validation cohort analysis (including 10 AH samples in each group) was performed using parallel reaction monitoring (PRM) strategy for verification of target proteins. Comprehensive bioinformatics analyses included gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, protein-protein interaction (PPI) network construction, receiver operating characteristic (ROC) curve analysis, and ConnectivityMap (Cmap)-based drug prediction. RESULTS: Proteomic profiling identified 739 quantifiable AH proteins (62% extracellular) with clear separation among the four clinical stages in the discovery cohort. GSEA uncovered altered expression of proteins mainly related to complement and coagulation cascades, folate metabolism, and the selenium micronutrient network in patients with DR. WGCNA-derived protein modules yielded 83 PRM-validated targets, including 5 hub proteins differentiating NPDR from non-DR and 33 hub proteins showed significant upregulation in PDR versus NPDR comparison. Clinical correlation analysis identified F2, FGG, FGB, RBP4, AMBP, VTN, C8A, CPB2, and C2 associated with clinical traits. C6, FAM3C, SPP1, and JCHAIN levels were altered post-anti-VEGF treatment. Pharmacological prediction identified potential therapeutic compounds, including perindopril, triciribine, and XAV-939 for NPDR, and topiramate, triciribine, and vecuronium for PDR. CONCLUSION: This study established a comprehensive AH proteomic signature of DR progression, offering insights into the pathogenesis of DR and highlighting potential biomarkers and novel therapeutic targets.

Humans↗
PubMed2026

Integrated LiP-MS and quantitative proteomics reveal coordinated alterations in protein conformation and expression across tumor and peritumoral regions in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) exhibits substantial molecular heterogeneity, yet protein-level alterations beyond abundance remain insufficiently characterized. Here, we integrated limited proteolysis mass spectrometry (Lip-MS) with 4D label-free quantitative proteomics to investigate conformational accessibility and protein abundance across tumor, peritumoral-near, and peritumoral-far tissues from HCC patients. Differential LiP peptides identified by both DDA and DIA corresponded to 725, 674, and 33 differentially conformed proteins in the Tumor vs. Peritumor-far, Tumor vs. Peritumor-near, and Peritumor-near vs. Peritumor-far comparisons, respectively. Quantitative proteomics identified 405, 365, and 4 differentially expressed proteins in the corresponding comparisons. Integrated analysis identified 488 and 469 conformation-specific altered proteins (CSAPs), which showed altered conformational accessibility without significant abundance changes, and 237 and 205 conformation-expression coupled proteins (CECPs) in the two tumor-involved comparisons. LiP peptide and protein abundance changes were positively correlated, with Spearman coefficients of 0.69-0.72, and more than 99% of CECPs showed concordant directions. Among them, 169 region-conserved CECPs (rcCECPs) were predominantly associated with metabolic and redox-related pathways. Protein-protein interaction analysis identified 30 hub rcCECPs. ACLY, ALDH18A1, GMPS, and DHX9 showed increased representative LiP peptide signals and protein abundance, elevated transcript expression in HCC, and associations with poorer overall survival. Peptide mapping further localized their differential LiP signals to specific sequence regions and annotated domains. Collectively, these findings provide an integrated view of regional conformational accessibility and protein abundance alterations in HCC and identify candidate proteins for further structural and functional investigation.

Humans↗
PubMed2025

Landscape and m6A post-transcriptional regulation of soybean proteome.

The soybean is a critical source of vegetable protein, but its proteome remains undercharacterized. Here, we quantify 12,855 proteins across 14 soybean organs using 4D data-independent acquisition mass spectrometry (4D-DIA-MS), creating the most extensive soybean proteome dataset to date. Organ-specific protein expression and co-expression analyses highlight functional specificity with significant differences in protein-transcript abundance across organs. We also map N6-methyladenosine (m6A) modifications, identifying their key role in post-transcriptional protein regulation. Integrative analysis of the proteome and m6A methylome identifies a novel regulator in m6A methylation. This comprehensive proteomic and m6A landscape advances our understanding of soybean biology and provides a valuable resource for crop improvement.

Glycine max↗
PubMed2026

Relaxin-2: Shaping the Proteomic Landscape of Skeletal Muscle Physiology, Glucose Trafficking, and Mitochondrial Function in Rat.

Relaxin-2 is a hormone with robust beneficial effects on the heart and blood vessels and potential as a therapy for cardiovascular (CV) disease. Considering the interorgan communication between skeletal muscle and heart, and the relation between muscle quality/composition and CV events, we hypothesize that relaxin-2 may regulate skeletal muscle physiology and metabolism. We aim to evaluate the impact of relaxin-2 on the proteome of skeletal muscle from healthy Sprague-Dawley rats. Animals were treated with 0.4&#x2009;mg/kg/day of serelaxin (recombinant form of human relaxin-2) or vehicle (PBS) for 2&#x2009;weeks employing subcutaneous osmotic minipumps. Skeletal muscle protein identification and quantification were performed by LC-MS/MS using a Data-Independent Acquisition (DIA)-Sequential Window Acquisition of All Theoretical Fragment Ion Spectra (SWATH) method. SWATH/MS quantitative analysis identified that relaxin-2 significantly decreased 95 proteins and significantly increased 32 proteins in rat skeletal muscle when compared to control rats. From these, 34 proteins were associated with muscle function, myogenesis, muscle differentiation and/or regeneration, 20 are mitochondrial proteins (six from the complexes of the electron transport chain), and 10 proteins participate in glucose metabolism. Qualitative data-dependent workflow analysis identified 35 proteins exclusive to the skeletal muscle of the relaxin-2-treated group: eight proteins related to processes of skeletal muscle function (size, ion homeostasis or organization of caveolae structures and cytoskeleton) and myogenesis, and two proteins involved in muscle differentiation. Our work highlighted for the first time the role of relaxin-2 in crucial processes of muscle physiology and energetic metabolism, which could influence several processes involved in myopathy and CV.

Animals↗
PubMed2026

narrowPASEF: A Sample-Aware diaPASEF Method Optimization Strategy Improving Differential Proteomics Performance on Low-Abundance Proteins.

Recent instrumental and computational innovations in mass-spectrometry-based proteomics offer new promise in biomarker discovery, thanks to unprecedented proteome coverage and depth. Data-independent acquisition (DIA) methods are very promising in this context as they allow improved proteome coverage, reduced missing value rates, and enhanced quantification precision. However, DIA methods also suffer from their own challenges, such as increased data complexity, cycle times, and background noise. In this work, we propose a sample-aware diaPASEF method optimization strategy for a timsTOF platform. Thorough method optimizations have first been conducted on standard HeLa lysates. Then, a ground-truth calibrated sample series, consisting of a range of UPS amounts spiked into a complex Arabidopsis background, was used to mimic differential analyses under controlled conditions. These benchmark experiments demonstrate clear benefits of using narrowPASEF for differential protein discovery. Finally, our strategy was applied to real use case biological samples to conduct a differential analysis of purified mouse astrocyte cells across two different conditions. narrowPASEF improved the proteome depth by 13%, considering proteins quantified with a coefficient of variation (CV) of <20%, and led to a 68% (435 vs 729) increase in differentially expressed proteins. These results provide an opportunity for a more precise and comprehensive analysis of the biological functions of biomarkers, offering a more profound understanding of the disease mechanisms. The benefits of our sample-aware narrowPASEF strategy demonstrated the most substantial impact on low-abundance proteins. Overall, these results show promise for more valuable and robust biomarker discoveries in the future.

Proteomics↗
PubMed2026

Intraspecific variation in Bothrops neuwiedi snake venom: Influence of age and sex.

Snake venom is a complex mixture of molecules and is subject to intraspecific variations due to the influence of abiotic and/or biotic factors, one of which is the animal's ontogeny. Some studies have already shown the influence of age on the composition and properties of snake venom, but these variations are not uniform, and each species may exhibit a specific pattern of variation. Therefore, this study aimed to analyze the influence of age on the venom of Bothrops neuwiedi, using 5 age groups, differentiating between males and females. To this end, we analyzed the protein profile of these venoms (using SDS-PAGE, HPLC, and proteomic analyses); enzymatic activities (PLA2, LAAO, and proteolytic activities); coagulant activity, in vivo assays (MDH; LD50 and ED50), and immunorecognition tests (Western blotting and ELISA). Protein profile analysis showed that males exhibited a gradual increase in SVMP and PLA2 concentrations. Both sexes showed a decrease in CTL concentration and a loss of PLA2 activity, which occurred more gradually in males. Proteolytic activity did not show clear ontogenetic differences, but both sexes showed activity peaks in the 2-year-old and senile groups, with females exhibiting higher proteolytic activity than males. Regarding LAAO activity, it increased in males and decreased in females. Although the LD50 did not show age-dependent differences, the venom from the 1-year-old group took longer to cause death in mice but showed a higher hemorrhagic activity than seniles. Furthermore, more antivenom was needed to neutralize the venom from the 1-year-old group than the venom from the senile group; despite this, immunorecognition tests did not show significant ontogenetic variations. In conclusion, the venom of the snake B. neuwiedi undergoes ontogenetic variations with certain sexual differences, showing some peculiarities that have not been found in ontogenetic analyses of other species of the same genus.

Animals↗
PubMed2006

A novel histology-directed strategy for MALDI-MS tissue profiling that improves throughput and cellular specificity in human breast cancer.

We describe a novel tissue profiling strategy that improves the cellular specificity and analysis throughput of protein profiles obtained by direct MALDI analysis. The new approach integrates the cellular specificity of histology, the accuracy and reproducibility of robotic liquid dispensing, and the speed and objectivity of automated spectra acquisition. Traditional methodologies for preparing and analyzing tissue samples rely heavily on manual procedures, which for various reasons discussed, restrict cellular specificity and sample throughput. Here, a robotic spotter deposits micron-sized droplets of matrix precisely onto foci of normal mammary epithelium, ductal carcinoma in situ, invasive mammary cancer, and peritumoral stroma selected by a pathologist from high resolution histological images of sectioned human breast cancer samples. The location of each matrix spot was then determined and uploaded into the instrument to facilitate automated profile acquisition by MALDI-TOF. In the example shown, the different lesions were clearly differentiated using mass profiling. Further, the workflow permits a visual projection of any information produced from the profile analyses directly on the histological image for a unique combination of proteomic and histological assessment of sample regions. The higher performance characteristics offered by the new workflow promises to be a significant advancement toward the next generation of tissue profiling studies.

Adult↗
PubMed2026

Saliva and salivary pellicle composition and proteomic profile in smokers vs. non-smokers and its effect on dental erosion.

OBJECTIVE: To analyse the salivary composition and proteomic profile of saliva and the salivary pellicle in smokers compared to non-smokers, and to examine potential differences in the erosion-protective capacity of the salivary pellicle. METHODS: Twenty-five smokers and 25 non-smokers were included. Unstimulated and stimulated saliva samples were analysed regarding flow rate, pH, buffer capacity, calcium, phosphate, fluoride, and protein content. Saliva and salivary pellicle samples were analysed by data-independent acquisition mass spectrometry (DIA-MS) for proteome profiling. In an in situ experiment, intraoral splints were loaded with bovine enamel and dentine specimens for 120 min. Pellicle-covered specimens were extraorally eroded (HCl, pH 2.3, 60 s). Calcium release was determined photometrically and compared to pellicle-free controls. RESULTS: Except for phosphate in stimulated saliva (padj.=0.003), salivary parameters were not significantly different between smokers and non-smokers. Proteome profiling detected 1759&#xb1;154 proteins (cumulative 1963) in saliva, and 4262&#xb1;362 proteins (cumulative 4625) in the salivary pellicle. The relative abundances of 282 (unstimulated saliva), 338 (stimulated saliva), and 4 (salivary pellicle) protein groups differed significantly between smokers and non-smokers. Functional enrichment analysis of differentially abundant human proteins revealed biological processes such as coagulation, immune response, and carcinogenic reactive oxygen species processes to be impacted by smoking. The salivary pellicle had a significant erosion-protective effect in enamel compared to the control (41.4 &#xb1; 6.3 nmol/mm2), but no differences between smokers (33.2 &#xb1; 10.6 nmol/mm2, padj.=0.001) and non-smokers (32.7 &#xb1; 8.6 nmol/mm2, padj.=0.001) were found. CONCLUSION: The proteomic profiles of both unstimulated and stimulated saliva and the salivary pellicle differ between smokers and non-smokers. CLINICAL SIGNIFICANCE: Despite the different proteomic profiles indicating a significant impact of smoking on the oral cavity, the erosion-protective capacity of the salivary pellicle of smokers and non-smokers does not differ.

Dental Pellicle↗
PubMed2025

A Study on Differential Proteomics in Differentiated Gastric Adenocarcinoma With Low-grade Atypia Based on Paraffin-embedded Tissues.

In this study, we analyzed and characterized differentially expressed proteins in differentiated gastric adenocarcinoma with low-grade atypia for screening potential protein markers. We collected gastric tissue specimens from 90 patients treated at the Pathology Department of the First People's Hospital of Yunnan Province, China, between January 2019 and December 2022. These specimens had been fixed in 10% neutral-buffered formalin and embedded in paraffin. We classified these samples into 3 groups: the control group (normal gastric mucosa), the low-grade atypia group (differentiated gastric adenocarcinoma with low-grade atypia), and the high-grade atypia group (differentiated gastric adenocarcinoma with high-grade atypia), consisting of 30 cases in each group. We analyzed differential proteomes with the data-independent acquisition-mass spectrometry (DIA-MS) methodology and selected 4 differentially expressed proteins that were subjected to immunohistochemistry (IHC) staining for validation. A total of 4406 proteins were identified, among which 598 and 357 proteins were statistically different in the low-grade atypia group as compared with the control group and the high-grade atypia group, respectively. IHC staining showed that the expression of FHL3, CSRP2, and FCGR3A was significantly higher in the low-grade atypia group than in the control group ( P <0.05) and significantly higher in the high-grade atypia group than in the low-grade atypia group ( P <0.05). FHL2 expression was negative to weakly positive in the control and low-grade atypia groups and not significantly different between the 2 groups, whereas FHL2 expression in the high-grade atypia group was significantly higher than in the control and low-grade atypia groups ( P <0.05). Proteomic analysis is helpful for discovering new protein markers. Using a combination of FHL3, CSRP2, and FCGR3A can increase the accuracy of the pathologic diagnosis of differentiated gastric adenocarcinoma with low-grade atypia.

Humans↗
PubMed2026

Physicochemical characterization of nanoparticles in highly diluted preparations and exploratory plasma proteomic correlates in an N-of-1 study.

The physicochemical properties of highly diluted homeopathic preparations remain insufficiently characterized. This study investigated particulate features of Kali carbonicum (K2CO3) at 50-millesimal potencies (LM4-LM7, &#x223c;1:50,000 dilutions per step) and explored plasma proteomic changes in a placebo-controlled N-of-1 trial. Scanning electron microscopy showed larger particle size in Kali carbonicum (67.3&#xa0;nm) than in the lactose control (47.5&#xa0;nm) at LM4 in a descriptive comparison. Dynamic light scattering showed no significant differences in size, polydispersity, or zeta potential among Kali carbonicum, lactose control, and solvent blank, accounting for vial-level clustering. Atomic force microscopy showed more compact dendritic assemblies in Kali than in lactose controls, suggesting trituration influences self-organization. Raman spectroscopy of LM7 detected carbonate-associated bands absent in controls. Plasma proteomics identified six FDR-significant proteins during Kali exposure, including increased S100A9, with exploratory enrichment for inflammation, cytoskeletal, and motility terms. These findings are exploratory and do not imply causality.

Proteomics↗
PubMed2026

Transcriptomic and proteomic signatures underlying nymphal adaptation and foam production in the forage pest Mahanarva spectabilis.

The spittlebug Mahanarva spectabilis (Distant, 1909) (Hemiptera: Cercopidae) is an important pest of forage grasses in South America, where its nymphs cause pasture damage by feeding on xylem sap and producing a characteristic foam that protects them against environmental stressors. To investigate the molecular basis of this adaptation, we integrated RNA-seq analysis of nymphs with LC-MS/MS proteomics of the Batelli gland, the primary source of foam secretion. De novo assembly of 100,666 unigenes revealed broad functional diversity, with strong representation of detoxification enzymes (CYP450s, GSTs, UGTs, carboxylesterases), transporters and ion pumps, cuticle proteins, and stress- and immunity-related genes. Nearly 16% of loci exhibited alternative splicing, particularly within detoxification, chemosensory and osmoregulatory gene families, highlighting evidence of transcriptomic variability. Signal peptide and secreted protein predictions identified 168 high-confidence candidate secreted proteins, including detoxification enzymes, proteases, structural proteins and immune-related factors, several of which are consistent with antimicrobial and surfactant-related functions. Proteomic profiling of the Batelli gland confirmed 500 proteins, enriched in chaperones, metabolic enzymes, detoxification pathways and osmoregulatory components, with the most abundant proteins corresponding to Hsp70 chaperones, ATP synthases, cuticle proteins and carbonic anhydrases. Together, these results provide an integrative transcriptomic and proteomic overview for M. spectabilis nymphs, highlighting genes and proteins associated with xylem feeding, foam production and responses potentially related to environmental stress tolerance. This comprehensive dataset not only advances the understanding of spittlebug biology but also identifies candidate molecular targets that may inform innovative strategies for controlling nymphal stages and mitigating spittlebug damage in forage systems.

Animals↗
PubMed2024

metaExpertPro: A Computational Workflow for Metaproteomics Spectral Library Construction and Data-Independent Acquisition Mass Spectrometry Data Analysis.

Analysis of large-scale data-independent acquisition mass spectrometry metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS, protein identification and quantification using data-independent acquisition mass spectrometry, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-min diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score&#xa0;=&#xa0;0.67-0.90) in genus diversity and showed a high correlation (rSpearman&#xa0;=&#xa0;0.73-0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.

Proteomics↗
PubMed2026

Plasma Proteomic Profiling of Comorbid and Noncomorbid COVID-19 Patients in ICU.

Type 2 Diabetes (T2D) and hypertension (HTN) are common comorbidities in severe COVID-19, yet their specific impact on proteomic recovery remains unclear. This study analyzed plasma protein signatures of critical COVID-19 patients with and without these comorbidities (COVID-only group [COG] and COVID comorbid group [CTHG]) on the first and last days of ICU stay. Proteomic analysis revealed a systemic shift characterized by upregulated immune responses and downregulated metabolic processes at admission across all patients. Survival was fundamentally defined by the restoration of homeostasis; liver-derived proteins&#x2500;including LPA, TTR, and AHSG&#x2500;were initially suppressed but rebounded significantly in survivors. This homeostatic recovery was impaired in CTHG compared to COG, with CTHG survivors showing attenuated recovery of metabolic markers. Distinct mortality-associated signatures also emerged between groups. COG nonsurvivors exhibited liver failure and severe hemolysis marked by persistent suppression of haptoglobin (HP). In contrast, CTHG mortality was driven by lipid metabolism dysregulation, with CD5L and APOA2 levels dropping specifically in comorbid nonsurvivors, often accompanied by a paradoxical elevation in APOA4&#x2500;likely reflecting impaired renal clearance rather than restored lipid homeostasis. These findings indicate that preexisting T2D and HTN hinder physiological resolution of metabolic and lipid dysregulation, providing proteomic evidence for distinct mortality risks associated with failure to restore metabolic homeostasis in comorbid COVID-19 patients.

Humans↗