Proteomes

42 pages, 11117 KB

Open AccessArticle

A Propeller with a Flexible Twist: A Computational Analysis of Intrinsically Disordered Regions in PIEZO Gating and PIEZO-Associated Channelopathies

by Shivam Shukla, Mason Elzy, Abiral Shrestha and Vladimir N. Uversky

Proteomes 2026, 14(3), 41; https://doi.org/10.3390/proteomes14030041 - 11 Aug 2026

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Abstract

Background: Mechanosensitive ion channels PIEZO1 and PIEZO2 are key mediators of mechanotransduction, which converts physical forces into cellular signals involved in proprioception, touch, vascular function, and other physiological processes. Mutations in human PIEZO proteins are linked to various diseases, such as hereditary xerocytosis, [...] Read more.

Background: Mechanosensitive ion channels PIEZO1 and PIEZO2 are key mediators of mechanotransduction, which converts physical forces into cellular signals involved in proprioception, touch, vascular function, and other physiological processes. Mutations in human PIEZO proteins are linked to various diseases, such as hereditary xerocytosis, lymphatic dysplasia, and proprioceptive dysfunction. However, the role of intrinsic disorder in the regulation of these proteins and their susceptibility for disease-associated mutations remains unclear. Methods: We analyzed canonical human PIEZO1 and PIEZO2 protein sequences using machine learning, neural network, and energy-based disorder predictors, together with the prediction of disorder-mediated binding regions, phase separation propensity, interaction networks, evolutionary conservation, clinically annotated human variants, and peptide structural modeling. Results: Both proteins showed moderate intrinsic disorder, with PIEZO2 having slightly greater disorder propensity and higher predicted phase separation potential. Intrinsically disordered regions frequently overlapped binding-prone segments and post-translational modification sites, supporting regulatory functions. Evolutionary comparisons showed strong conservation of PIEZO proteins, while selected disordered regions retained disorder propensity despite greater sequence variability. Disease-causing variants mainly affected the ordered regions of both proteins, whereas disordered regions contained proportionally more benign variants and relatively few pathogenic mutations. The modeling of mutations within disordered hotspots showed altered local conformational tendencies, indicating that some disease variants may disrupt dynamic interaction interfaces rather than global structure. Interaction network analysis linked both proteins to enriched mechanotransduction, ion transport, and cytoskeletal pathways. Conclusions: Overall, our findings identify intrinsic disorder as an underappreciated feature of PIEZO channel biology and provide a framework for interpreting PIEZO-associated channelopathies. PIEZO proteins also perfectly illustrate the proteoform concept, where one gene yields a highly diverse kit of mechanosensitive molecular tools. While humans only have two primary PIEZO genes (PIEZO1 and PIEZO2), the body generates a vast array of functional variations. Full article

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19 pages, 931 KB

Open AccessArticle

Comparative Analysis of Progesterone Secretion and Plasma Proteome Across the Pregnant and Non-Pregnant Luteal Phase of the Koala (Phascolarctos cinereus)

by Brooke E. Hartley, Stephen D. Johnston, Yolande Campbell, Kerry Fanson, Vere Nicolson, Ashleigh Neal and Taylor Pini

Proteomes 2026, 14(3), 40; https://doi.org/10.3390/proteomes14030040 - 6 Aug 2026

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Abstract

Background: Koalas are a vulnerable marsupial species with unique reproductive traits. Efforts to develop assisted breeding technologies have been hindered by a limited understanding of maternal recognition of pregnancy and physiological changes induced by the foeto-placental unit. Differences in the reproductive physiology of [...] Read more.

Background: Koalas are a vulnerable marsupial species with unique reproductive traits. Efforts to develop assisted breeding technologies have been hindered by a limited understanding of maternal recognition of pregnancy and physiological changes induced by the foeto-placental unit. Differences in the reproductive physiology of pregnant and non-pregnant koalas were examined to investigate the possibility of maternal recognition and identify potential pregnancy and/or embryonic loss biomarkers. Methods: Koalas were separated into three groups: pregnant (n = 4 cycles from three females), mated but non-parturient (n = 4 cycles from three females), and gonadotropin-releasing hormone (GnRH) agonist-treated females (n = 7). Plasma was collected on day of mating/GnRH injection (D0) and on multiple subsequent days. Progesterone concentrations were measured by enzyme immunoassay, and plasma proteomes were analysed using filter-aided sample preparation followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), employing sequential window acquisition of all theoretical fragment ion spectra. Results: Ovulation induction mechanisms influenced peri-ovulatory progesterone secretion (pregnant 40.7 ± 3.3 ng/mL vs. GnRH-treated 15.7 ± 1.8 ng/mL), with no significant differences in progesterone that occurred later in the luteal phase. LC-MS/MS identified 158 proteins, representing the first koala plasma proteome. Leucine-rich alpha-2-glycoprotein (LRG1) was significantly elevated at D2 in pregnant females compared to GnRH-treated females, and pregnant D9 and D19. In pregnant females, fibronectin (FN1) was significantly more abundant at D19 compared to D9 but not significantly different between treatments. Conclusions: These preliminary findings provide foundational data for further investigation into maternal recognition and pregnancy/embryonic loss in koalas. Full article

(This article belongs to the Section Animal Proteomics)

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22 pages, 6583 KB

Open AccessArticle

Proteomic Analysis of Paraffin-Embedded Intestines from Schistosoma mansoni Infection in Mice: Highlighting Molecular Players During Acute Schistosomiasis

by Lara Geralda Magela dos Santos Vieira, Ana Flávia Pinho Souza, Camilo Elber Vital, Dávila Regina Pacheco Silva, Flávia de Souza Marques, Gustavo Gonçalves Silva, Paula Melo de Abreu Vieira, R Alan Wilson and William Castro-Borges

Proteomes 2026, 14(3), 39; https://doi.org/10.3390/proteomes14030039 - 29 Jul 2026

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Abstract

Background: Adult Schistosoma mansoni parasites inhabit the hepatic portal system of the vertebrate host, their deposited eggs causing granulomatous pathology in both the intestines and liver. In the intestines, egg secretions drive inflammatory processes involved in extravasation to the gut lumen. Methods: Here, [...] Read more.

Background: Adult Schistosoma mansoni parasites inhabit the hepatic portal system of the vertebrate host, their deposited eggs causing granulomatous pathology in both the intestines and liver. In the intestines, egg secretions drive inflammatory processes involved in extravasation to the gut lumen. Methods: Here, we investigate parasite-host interactions in a mouse model during the acute phase of a patent infection at 5 and 7 weeks, using parallel histological and proteomic analysis of paraffin-embedded ileal tissues. Results: Histology at week 7 showed infected animals had more inflammation and longer villi than at week 5, as well as more Goblet cells reflecting enhanced mucus production. LC-MS/MS analysis of deparaffinized ileal sections, subjected to in-solution tryptic digestion, revealed a total of 1615 protein groups. Differentially abundant proteins were found early at week 5, coinciding with the onset of egg deposition. A contrasting scenario, dominated by upregulation of protein components from the innate and adaptive immune systems, was seen at week 7; at this point, egg migration and excretion are underway. Among the proteins were mast cell proteases, fibrinogens, arginase-1, and molecules associated with extracellular matrix remodeling. Conclusions: Our findings reflect intestinal proteome changes likely participating in S. mansoni egg passage from the vascular bed to the intestinal lumen. Full article

(This article belongs to the Section Animal Proteomics)

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27 pages, 1926 KB

Open AccessArticle

Proteomic Mediators Linking Autoimmune Diseases to Major Adverse Cardiovascular Events: Insights from the UK Biobank

by Jingwen Huang, Chang Liu, Laurence S. Sperling, Arshed A. Quyyumi and Yan V. Sun

Proteomes 2026, 14(3), 38; https://doi.org/10.3390/proteomes14030038 - 24 Jul 2026

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Abstract

Background: Autoimmune diseases (AIDs) are associated with increased cardiovascular risk. However, specific protein mediators linking AIDs to major adverse cardiovascular events (MACE) and cardiovascular death (CV death) remain unexplored. This study identifies proteomic mediators linking AIDs to MACE via high-dimensional mediation analysis in [...] Read more.

Background: Autoimmune diseases (AIDs) are associated with increased cardiovascular risk. However, specific protein mediators linking AIDs to major adverse cardiovascular events (MACE) and cardiovascular death (CV death) remain unexplored. This study identifies proteomic mediators linking AIDs to MACE via high-dimensional mediation analysis in the UK Biobank. Methods: We used UK Biobank data with proteomic profiling by Olink platform. Participants with prevalent myocardial infarction (MI), stroke, and heart failure at baseline were excluded. AIDs were categorized into musculoskeletal (MSK), vasculitis, gastrointestinal (GI), neurologic, and rheumatic fever subsets. Fine–Gray models assessed associations between AIDs and MACE and CV death. Proteome-wide association studies identified proteins associated with both AIDs and cardiovascular outcomes. High-dimensional mediation analysis (HIMA) explored protein-mediated pathways. All models adjusted for age, sex, lipids, BMI, smoking, hypertension, diabetes, chronic kidney disease, atrial fibrillation, and coronary artery disease. Results: Among 400,633 participants (median follow-up 14.5 years, 44.8% male), AIDs were present in 28,754 (7.2%). All AID categories were associated with increased MACE (sHR: MSK 1.34, vasculitis 1.67, GI 1.20, neurologic 1.33, rheumatic fever 1.38; all p < 0.001). For CV death, MSK, vasculitis, and rheumatic fever showed increased risk (sHR 1.34, 1.78, 1.51; all p ≤ 0.004), but not GI or neurologic AIDs. In 43,599 participants with proteomic data, HIMA identified 66 and 32 unique potential mediators linking AIDs to MACE and CV death, respectively. Four proteins (Growth Differentiation Factor 15, Interleukin-15, urokinase plasminogen activator receptor, and Tenascin C) mediated the AID-MACE relationship across multiple AID categories. Growth Differentiation Factor 15 and Interleukin-15 were shared mediators for CV death. Conclusions: This proteomic analysis identifies specific proteins that may mediate the association between AIDs and adverse cardiovascular outcomes, offering mechanistic insights into immune-related cardiovascular risk. These findings are hypothesis-generating and require replication and validation before the identified proteins can be considered causal mediators or adopted for clinical risk stratification. Full article

(This article belongs to the Section Proteomics of Human Diseases and Their Treatments)

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27 pages, 10788 KB

Open AccessArticle

Proteomic Profiling Reveals Region-Specific Brain Responses During Acclimation to Elevated Water Temperature in Atlantic Salmon (Salmo salar L.)

by Manojkumar Chandraprakasham, Gianluca Amoroso, Chris G. Carter, Chloe J. English, Lambertus Koster, Richard Wilson, Richard S. Taylor and Omar Mendoza-Porras

Proteomes 2026, 14(3), 37; https://doi.org/10.3390/proteomes14030037 - 23 Jul 2026

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Abstract

Background: Increasing summer seawater temperatures pose challenges for Atlantic salmon aquaculture, while brain region-specific responses to elevated temperature remain poorly understood. Methods: Atlantic salmon in the warm treatment (WT) underwent thermal ramping from 15 °C to 19 °C, with mortality observed at the [...] Read more.

Background: Increasing summer seawater temperatures pose challenges for Atlantic salmon aquaculture, while brain region-specific responses to elevated temperature remain poorly understood. Methods: Atlantic salmon in the warm treatment (WT) underwent thermal ramping from 15 °C to 19 °C, with mortality observed at the end of week 4 (15.78%). The WT temperature was subsequently reduced to 18 °C in week 5, while the control treatment (CT) was adjusted from 15 °C to 14 °C, and the WT (18 °C) and CT (14 °C) conditions were maintained thereafter. At the end of the trial (week 10), six brain regions, including the cerebellum (CBE), hypothalamus (HYP), medulla oblongata (MED), optic tectum (OPT), pituitary gland (PIT), and telencephalon (TEL), were analysed using data-independent acquisition mass spectrometry-based proteomics. Results: Over 9000 protein groups were identified per brain region, and exploratory differential abundance analysis revealed predominantly region-specific protein abundance changes. Increased SERPINH1 (HSP47) abundance was observed in HYP, PIT, and TEL, suggesting roles in protein-folding and stress regulation. Functional enrichment analyses indicated differential regulation of translation, transcription, energy metabolism, and metabolic pathways across brain regions in the WT group. Conclusions: This study provides a brain region-specific proteomic resource for Atlantic salmon and advances understanding of molecular responses associated with recovery from a temperature reduction (19 °C to 18 °C) and subsequent thermal adjustment at 18 °C. Full article

(This article belongs to the Section Animal Proteomics)

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18 pages, 7604 KB

Open AccessArticle

Protein Language Model Embeddings Reveal Proteome-Scale Ortholog Divergence Relevant to Cross-Species Pharmacology

by Taichi Endoh, Gerry Amor Camer, Kotetsu Kayama, Daiji Endoh and Hiroki Teraoka

Proteomes 2026, 14(3), 36; https://doi.org/10.3390/proteomes14030036 - 23 Jul 2026

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Abstract

Background: Comparative proteome analysis can reveal functional conservation and divergence among orthologous proteins, with important implications for pharmacology and toxicology. Protein language models (PLMs) may capture sequence-derived functional relationships beyond what conventional alignment metrics capture. Methods: Orthologous proteins from Danio rerio and Danio [...] Read more.

Background: Comparative proteome analysis can reveal functional conservation and divergence among orthologous proteins, with important implications for pharmacology and toxicology. Protein language models (PLMs) may capture sequence-derived functional relationships beyond what conventional alignment metrics capture. Methods: Orthologous proteins from Danio rerio and Danio aesculapii were compared using embeddings generated by the Evolutionary Scale Modeling 2 (ESM-2) protein language model. Reciprocal best-hit inference identified 68,971 high-confidence ortholog pairs, of which 51,086 were available for embedding-based analysis. PLM divergence was quantified using cosine distance and evaluated using length-matched and bitscore-matched random controls, Gene Ontology graph-distance analysis, and localized domain-level comparisons. Results: Ortholog pairs showed strong global conservation, with a median PLM distance of 0.000487, whereas randomized controls exhibited substantially greater divergence. Increasing Gene Ontology graph distance broadened PLM-distance distributions, and leaf–parent comparisons demonstrated significant functional ordering (Wilcoxon p = 2.44 × 10⁻⁴). Local analyses revealed increased divergence in pathophysiologically relevant regions of aryl hydrocarbon receptor (AHR) and potassium channel proteins. Conclusions: PLM embeddings provide a scalable framework for comparative proteome characterization, complement conventional sequence-based analyses, and prioritize orthologs or protein regions with elevated functional divergence for experimental validation in cross-species pharmacology, toxicology, and systems biology. Full article

(This article belongs to the Section Proteome Bioinformatics)

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18 pages, 1943 KB

Open AccessArticle

Lyophilization Prior to Homogenisation and Extraction Increases Membrane Protein Detection in Gram-Negative Bacterial Proteomic Analyses

by Breyer Woodland, Luke A. Farrell, Matthew B. O’Rourke and Matthew P. Padula

Proteomes 2026, 14(3), 35; https://doi.org/10.3390/proteomes14030035 - 15 Jul 2026

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Abstract

Background: Multi-drug resistant Gram-negative bacteria (GNB) are major contributors to the antimicrobial resistance (AMR) burden. AMR mechanisms are primarily mediated by proteoforms; therefore, proteomic analyses of GNB offers a significant advantage in understanding the mechanisms of AMR. A large portion of these mechanisms [...] Read more.

Background: Multi-drug resistant Gram-negative bacteria (GNB) are major contributors to the antimicrobial resistance (AMR) burden. AMR mechanisms are primarily mediated by proteoforms; therefore, proteomic analyses of GNB offers a significant advantage in understanding the mechanisms of AMR. A large portion of these mechanisms are mediated by membrane proteins; however, they are often difficult to extract due to their hydrophobic nature and complex interactions with other components of the cell membrane. To extract the greatest number of proteoforms, an efficient homogenisation protocol is required to effectively disrupt the rigid cell wall and membrane. Methods: Using Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii and Pseudomonas aeruginosa, we systematically compared the extraction efficiency of bead-beating with flash frozen and lyophilized cell pellets. Results: We demonstrate that lyophilization improves bead-beating extraction methods by increasing the detection of membrane proteins. We detected numerous unique membrane proteins in each bacterial isolate, including ABC transporters and proteins involved in lipopolysaccharide synthesis, when lyophilizing prior to bead-beating, compared to only flash-freezing. Conclusions: As membrane proteins play a central role in AMR mechanisms, this improvement in their isolation and identification will aid in understanding the resistance and molecular mechanisms associated with multi-drug resistant GNB. Full article

(This article belongs to the Section Proteomics Technology and Methodology Development)

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8 pages, 520 KB

Open AccessTechnical Note

An Ultrafast GPU-Enabled MGVB

by Metodi V. Metodiev

Proteomes 2026, 14(3), 34; https://doi.org/10.3390/proteomes14030034 - 7 Jul 2026

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Abstract

Background: cMGVB is a graphical processing unit (GPU)-enabled implementation of the computational proteomics data analysis toolset MGVB. MGVB was released in 2025 as a Linux program designed to run on multi-node servers. It utilizes a novel algorithm for finding combinations of post-translational [...] Read more.

Background: cMGVB is a graphical processing unit (GPU)-enabled implementation of the computational proteomics data analysis toolset MGVB. MGVB was released in 2025 as a Linux program designed to run on multi-node servers. It utilizes a novel algorithm for finding combinations of post-translational modification in peptide MS/MS data. The original combinatorial algorithm required a significant amount of resources to be practical. Hence, the aim of the research reported here was to port the algorithm to GPU and thus increase its speed and efficiency. Methods: To accomplish this it was recoded in CUDA C; recursive functions and data structures were re-implemented as non-recursive, and the algorithm was incorporated in a new version of MGVB, now termed cMGVB. Results: The re-implemented algorithm is much faster and, unlike the original program, can run on single CPU workstations equipped with inexpensive GPUs and still be much faster than the original algorithm running on HPC clusters. A typical focused search is completed in about a minute by cMGVB compared to 10–15 min by the original implementation. Illustrative case studies are presented and discussed in this report. Conclusions: cMGVB enables workflows that were not practical or even possible with the original MGVB. Full article

(This article belongs to the Section Proteome Bioinformatics)

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13 pages, 3418 KB

Open AccessArticle

A Dual-Background Statistical Framework for Phosphoproteomics Highlights Intrinsic, High-Confidence Phosphorylation Signature by Mitigating Orthogonal Sources of Bias

by Bin Deng

Proteomes 2026, 14(3), 33; https://doi.org/10.3390/proteomes14030033 - 7 Jul 2026

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Abstract

Background: Distinguishing genuine kinase–substrate motifs from background noise is a growing challenge, as mass spectrometry (MS)-based global phosphoproteomics identifies a rapidly expanding set of phosphorylation sites. One of the major limitations is selecting an appropriate background model that systematically controls both technical and [...] Read more.

Background: Distinguishing genuine kinase–substrate motifs from background noise is a growing challenge, as mass spectrometry (MS)-based global phosphoproteomics identifies a rapidly expanding set of phosphorylation sites. One of the major limitations is selecting an appropriate background model that systematically controls both technical and biological sources of bias. Although using the entire proteome as a background in a FASTA format considers the overall amino acid composition, it is still prone to biases from protein abundance and the uneven distribution of sequence space (particularly around low-abundance proteins). By contrast, internal background methods can control experiment-specific detection biases, but they may not fully capture residue-specific compositions or general trends in phosphorylation. Methods: I develop a Dual-Background Enrichment (DBE) framework with a position-specific enrichment (PSE) strategy, which involves analyzing motif enrichment against two distinct background models: (1) A residue-heterogeneous internal background composed of phospho-motifs centered on the residue; e.g., phosphoserine (pS) motifs are tested relative to the pool of all detected phosphothreonine (pT) and phosphotyrosine (pY) motifs from the same experiment. (2) A FASTA background that includes all S, T, and Y residues in the UniProtKB proteome sequences. Results: Motifs are classified as high confidence if they meet statistical significance (q ≤ 0.05, fold enrichment > 1.5) against both background models. Conclusion: By applying the DBE strategy to a large-scale phosphoproteomics dataset, we distinguish motifs driven by amino acid composition (enriched in FASTA background only) from those reflecting kinase substrate specificity (enriched in both backgrounds). This dual-reference approach reduces false positives arising from sequence composition bias and enriches high-confidence candidate kinase recognition motifs. Full article

(This article belongs to the Section Proteome Bioinformatics)

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24 pages, 1650 KB

Open AccessReview

A One Health Framework for Proteomics Across the Tree of Life to Advance Food Security, Animal Health, and Ecosystem Resilience

by Tarun Mishra, Ritudhwaj Tiwari, Tuyelee Das and Maneesh Lingwan

Proteomes 2026, 14(3), 32; https://doi.org/10.3390/proteomes14030032 - 24 Jun 2026

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Abstract

As global ecosystems and food systems face unprecedented anthropogenic and climatic challenges, there is a demand for an integrated understanding of biological systems. Proteomics has emerged as a definitive approach offering a direct view of the molecular phenotype, yet it is traditionally separated [...] Read more.

As global ecosystems and food systems face unprecedented anthropogenic and climatic challenges, there is a demand for an integrated understanding of biological systems. Proteomics has emerged as a definitive approach offering a direct view of the molecular phenotype, yet it is traditionally separated into plant and animal disciplines. With recent advances in mass spectrometry (MS) and bioinformatics tools, this prospective review proposes that combining a One Health proteomics approach with deep-learning data analysis can revolutionize global food security, animal productivity, and ecosystem health by uncovering proteoform signatures that drive resilience across life. The potential of a unified One Health proteomic framework, highlighting major developments, including 4D proteomics, Data-Independent Acquisition (DIA), and single-cell resolution, and emphasizes their capacity to resolve the complex proteoform landscape across kingdoms. Review emphasizes the applications of proteogenomics as a cross-disciplinary tool to improve genome annotations, explain evolutionary differences, discover biomarkers in animals and resolve complex signaling networks in plants under stress. Nevertheless, contemporary proteogenomics methods still show limitations in their ability to comprehensively resolve proteoforms due to the fact that the use of peptide-based approaches makes it difficult to fully appreciate the post-translational modifications specific to each protein isoform. We show that One Health proteomics will provide a transformative roadmap for deciphering the functional proteoform signatures that underpin resilience across the tree of life. Full article

(This article belongs to the Special Issue Plant Genomics and Proteomics)

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