Proteomes doi: 10.3390/proteomes14020025

Authors: Georgina H. Charlton Cleidiane Zampronio Andrew R. Bottrill John Sinclair Peter M. Kilby Alexandra M. E. Jones

Background: Maize is a vital crop, supporting 19.5% of global calorie intake. However, maize is vulnerable to even brief periods of drought which substantially reduces seed set and therefore yield. Methods: To identify proteins involved in responses of maize to drought, soluble proteins were extracted from leaf and silk tissues of Zea mays and protein abundance and phosphorylation status were quantified relative to well-watered controls. Label-free quantification and phosphopeptide enrichment were applied to the same biological samples and over 300 proteins were identified with significantly different changes. Results: Proteins known to be involved in drought responses were identified, such as the abscisic acid pathway and transcription factors. Of particular interest is a group of dehydrins quantified at both total protein and phosphopeptide levels, permitting insight into stoichiometry. The biological function of dehydrins in the model plant Arabidopsis thaliana is known to be regulated by phosphorylation. Conclusions: Translation of protein function from model plant to crops remains highly challenging because genome duplication has created complex sets of orthologous and homologous proteins. By focusing on proteomic changes during crop stress responses, this work enables the identification of known and novel proteins, substantially aiding the transfer of knowledge from model plants to crops.

Proteomes doi: 10.3390/proteomes14020024

Authors: Hope K. Hutson Guoting Qin Chengzhi Cai Gergana G. Nestorova

Background: Extracellular vesicles (EVs) mediate intercellular communication in the central nervous system and are a major source of biomarkers. This study characterizes the EV-derived proteome secreted by human endothelial brain cells (HEBCs), astrocytes, and neurons to identify cell-specific roles in intercellular communication in the brain. Methods: Mass spectrometry analyses of EVs and corresponding parent cells were performed to identify differentially enriched proteins. Gene Ontology (GO) analysis of statistically significant, abundantly expressed proteins between EVs and parent cells (log2 fold-change ≥ 2.0, p < 0.05) was performed to assess cell-specific functions. Results: Proteome analysis identified on average 932 proteins in astrocyte EVs (versus 1725 in parent cells), 1040 in HEBC EVs (versus 5451 in parent cells), and 470 in neuronal EVs (versus 578 in parent cells). The analysis indicated that astrocytes had the highest number of significantly abundant proteins (118), followed by HEBCs (24) and neurons (25). Astrocyte EVs were enriched in lipoproteins, complement factors, and protease inhibitors; HEBCs EVs in tight junction proteins, adhesion molecules, and protease regulators; and neuronal EVs in chromatin-associated histones, tubulin isoforms, and RNA-binding proteins. Conclusions: The proteomic signatures of EVs from different neurovascular unit cells suggest specialized roles in blood–brain barrier homeostasis, immune regulation, and synaptic and epigenetic signaling under healthy conditions. These baseline signatures provide a framework for future studies to investigate how brain cell-derived EVs may contribute to neurodegenerative disorders.

Proteomes doi: 10.3390/proteomes14020023

Authors: Ruixiang Liu Xiaohang Li Zixin Zha Meijing Zhang Lingjie Kong Yakun Cui Wenming Zhao Qingchang Meng Youhua Wang Yanping Chen

Background: During maize anthesis, heat stress severely limits productivity—particularly under humid conditions where high humidity suppresses transpirational cooling, forcing tissues to endure direct thermal load. Methods: Using field enclosures to impose enclosure-imposed humid heat shock (EHS), we screened 135 maize inbred lines for flowering-stage yield resilience, using grain weight per ear at maturity under EHS relative to the corresponding control (CK) condition as the primary selection criterion. Based on this screen, we selected two tolerant (R025, R100) and two sensitive (R133, R135) genotypes for data-independent acquisition mass spectrometry (DIA-MS) profiling of the tassel-subtending leaf. Results: At baseline, the selected tolerant lines exhibited a constitutively distinct proteomic state, including lower abundance of light-harvesting complex components and higher abundance or detection frequency of several regulatory proteins, including SRK2E/OST1 and HSF-B2a. Under sustained EHS, the selected sensitive lines showed extensive proteomic disruption, including reduced abundance of photosynthesis-related proteins and oxidative phosphorylation, together with increased abundance of proteins associated with endoplasmic reticulum stress responses and protein turnover. In contrast, the selected tolerant lines displayed a more constrained acclimation response, characterized by relative maintenance of photosynthesis-related proteins together with selective increases in chaperone systems (HSP90/sHSPs) and benzoxazinoid biosynthesis-related proteins. Several proteins showed switch-like detection patterns between the selected tolerant and sensitive lines, including TMEM97-like and a peptidyl-prolyl isomerase, indicating potentially distinct regulatory states. Conclusions: These findings suggest that tolerant performance under enclosure-imposed heat stress is associated with a pre-conditioned proteomic state and enhanced protein homeostasis (proteostasis) buffering capacity that may help preserve photosynthetic function during flowering-stage stress. The identified proteins should be regarded as candidate markers requiring further functional validation before any application in breeding programs aimed at improving adaptation to increasingly frequent heat-stress events.

Proteomes doi: 10.3390/proteomes14020022

Authors: Jens R. Coorssen Matthew P. Padula

We begin by expressing our sincere thanks to all Editorial Board Members, Guest Editors, Reviewers, Authors, and the staff in the Editorial Office for their dedicated service in support of Proteomes [...]

Proteomes doi: 10.3390/proteomes14020021

Authors: Somar Khalil Jean-François Dierick Pascal Bourguignon Michel Plisnier

Background: Untargeted proteomics enables quantitative host cell protein (HCP) determination in biotherapeutics, yet no workflow has been validated under ICH Q2(R2) for regulated quality control. Methods: A prospective total-error (TE) validation of label-free ddaPASEF proteomics was performed. A stable isotope-labeled whole-proteome standard was spiked into NISTmAb at seven levels (20–80 ng) and analyzed in four independent assays (198 injections), supporting one-way random-effects ANOVA with Welch–Satterthwaite adjustment. Peptide-level identification error was evaluated by dual entrapment. Results: Empirical false-discovery proportions were below 1% at q = 0.01. Weighted least-squares regression (R2 = 0.993) confirmed stable proportional compression with 81–85% recovery. Repeatability dominated the variance structure (median CV 2.7%); intermediate precision SD ranged from 0.69% to 3.81%. Both 95% β-expectation and 95/95 content tolerance intervals were contained within ±30% at all levels, defining a validated range of 20–80 ng. Abundance-stratified TE profiling revealed concentration-dependent calibration heterogeneity, with stratum-specific intervals within ±35% defining an abundance-aware LLOQ of 3.6 ppm (P95 = 3.87 ppm). Robustness under independent search software (FragPipe v24.0, CCC = 0.998) and cross-platform acquisition (Astral, CCC = 0.980) remained within ±30% limits. Conclusions: This constitutes the first prospective ICH Q2(R2)-aligned validation of untargeted proteomics for HCP quantification, with a transferable statistical framework for high-dimensional analytical methods.

Proteomes doi: 10.3390/proteomes14020020

Authors: Rui Vitorino

Recent advances in mass spectrometry, data-independent acquisition, proteoform-resolving workflows, and multi-omics integration have significantly expanded the scale and scope of proteomics. However, the reuse and translational application of these datasets are limited by inconsistent standards, insufficient metadata, and inadequate computational interoperability. Proteoform-centric approaches provide higher molecular resolution by capturing intact protein variants and patterns of post-translational modification. Computational methods, including selected applications of machine learning and large language models (LLMs), are increasingly used for tasks such as spectral prediction and pattern discovery in clinical proteomics datasets. Despite these advancements, FAIR (Findable, Accessible, Interoperable, and Reusable) data practices, proteoform biology, and AI analytics are often pursued independently. This work presents an integrated framework for next-generation proteomics in which standardization and FAIR (Findable, Accessible, Interoperable, and Reusable) principles establish machine-actionable foundations for proteoform-resolved analysis and computational inference. It examines community efforts to promote data sharing and interoperability, as well as strategies for characterizing proteoforms using bottom-up, middle-down, and top-down approaches. It also highlights emerging AI and ML applications within the proteomics workflow. The framework emphasizes the importance of treating proteoforms as primary computational entities and adopting FAIR practices during data collection to enable reproducible and interpretable modeling. Finally, it introduces an architectural model that integrates FAIR infrastructures and proteoform resolution. In addition, practical recommendations for making AI-ready proteomics, including a minimal community checklist to support reproducibility, benchmarking, and translational scalability, are provided.

Proteomes doi: 10.3390/proteomes14020019

Authors: Alberto Fucarino Yousef Mohamadi Francesco Cappello Federica Scalia Giulia Russo Giuseppe Gullo Leila Noori

Proteostasis, defined as the coordinated regulation of protein synthesis, folding, trafficking, and degradation, is essential for maintaining cellular integrity and supporting normal development. During reproduction and early life stages, efficient proteostasis is crucial for gamete quality, successful fertilization, embryonic development, and neurodevelopmental outcomes. Increasing evidence suggests that impaired proteostasis contributes to infertility and may be intertwined with biological vulnerabilities associated with assisted reproductive technologies [ARTs]. This review provides an integrative perspective on the role of disrupted proteostasis in infertility, ART procedures, and neurodevelopmental differences [NDD]. We review epidemiological and molecular findings indicating proteostasis failure in both male and female infertility, with particular emphasis on molecular chaperones. Among these, heat shock protein 60 [Hsp60] is discussed as a central mediator linking mitochondrial function, protein quality control, and reproductive competence. We further highlight that ART procedures coincide with sensitive periods of epigenetic reprogramming and proteostasis regulation during early embryogenesis, indicating that disturbances in proteostasis may affect epigenetic stability and subsequent neurodevelopmental outcomes. In addition, this review emphasizes the importance of proteoforms and proteome complexity as critical determinants of reproductive success and neurodevelopmental robustness in the context of ART. Finally, we discuss the potential of proteomic and chaperone-based biomarkers as emerging tools to optimize ART strategies, improve gamete and embryo selection, and enhance risk assessment and clinical outcomes. The current review underscores proteostasis as a fundamental yet underrecognized mechanism linking reproductive biology, ART outcomes, and long-term neurodevelopment while highlighting future directions for translational investigations.

Proteomes doi: 10.3390/proteomes14020018

Authors: Sarena Banu P. V. Anusha Pedro Beltran-Alvarez Mohammed M. Idris Katharina C. Wollenberg Valero Francisco Rivero

In the original publication [...]

Proteomes doi: 10.3390/proteomes14020017

Authors: Afreen Khanum Leona Dcunha Suhail Subair Athira Perunelly Gopalakrishnan Akhina Palollathil Rajesh Raju

Background: YES1 is an Src family non-receptor tyrosine-protein kinase that regulates cell growth, migration, survival, and oncogenic signaling. Although YES1 activation mechanisms and substrates have been extensively studied, its phosphosite-specific regulation across diverse biological contexts remains poorly understood. Methods: We performed a large-scale integrative analysis of 3825 publicly available human mass spectrometry-based phosphoproteomic datasets to map YES1 phosphorylation events. Co-modulation, co-occurrence, evolutionary conservation, and disease-association analyses were conducted to characterize the functional and clinical relevance of site-specific YES1 phosphorylation. Results: Y426 emerged as the predominant YES1 phosphosite across diverse biological conditions, localized within the activation loop of the kinase domain and conserved across Src family kinases. Co-modulation analysis identified 421 positively and 102 negatively associated phosphosites enriched in biological processes related to cell cycle regulation, transcription, cytoskeletal remodeling, apoptosis, and carcinogenesis. Among these high-confidence protein phosphosites, we identified 24 binary interactors, 5 upstream regulators, and 8 candidate downstream substrates. Comparison with DisGeNet cancer biomarkers showed overlap between YES1-associated phosphoproteomic signatures and site-specific oncogenic markers across multiple cancers, such as breast cancer, colorectal cancer, leukemia, and lung adenocarcinoma. Conclusions: This study provides a systems-level, phosphosite-focused view of YES1 signaling and supports a central regulatory role for Y426 within global phosphoregulatory and cancer-associated networks.

Proteomes doi: 10.3390/proteomes14020016

Authors: Federica Franzetti Nicole Giugni Manuel Airoldi Heather Bondi Tiziana Alberio Mauro Fasano

Proteomics represents a fundamental layer for understanding the molecular complexity of solid tumors by quantifying protein abundance and capturing proteoforms and post-translational modifications undetected in genomics or transcriptomics analyses. As mass spectrometry-based technologies and public proteomics repositories have expanded, opportunities for large-scale data reuse have grown accordingly. Nevertheless, data availability has not been translated into straightforward reuse: differences in experimental design, acquisition strategies, quantification workflows and metadata quality still limit the reproducibility and cross-study comparability. In this review, proteomics data reuse is defined as the systematic reanalysis and integration of publicly available datasets to support precision oncology applications such as biomarker assessment and antibody–drug conjugate target prioritization. We discuss reuse as an end-to-end analytical process, focusing on data analysis workflows, harmonization strategies, and the impact of heterogeneous experimental and analytical choices on interoperability. The increased application of artificial intelligence in proteomics data integration and reuse is also addressed, highlighting its analytical potential while underscoring the risks of overinterpretation when biological context and data structure are not adequately considered. Using colorectal and prostate cancer as representative examples, we illustrate how proteomics data reuse can support biological discovery and translational research, while critically examining the factors that limit robustness and clinical relevance.

Proteomes doi: 10.3390/proteomes14010015

Authors: Varsha V. Balu Dean R. Jerry Andreas L. Lopata

Background: Fish skin mucus contains proteins involved in diverse biological pathways, representing a valuable non-invasive diagnostic of fish health. Methods: Skin mucus from three male and three female barramundi was analysed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) following protein extraction and S-Trap digestion. Results and Discussion: A total of 1801 protein groups were matched to the L. calcarifer reference proteome and functionally annotated using Gene Ontology (GO) terms via UniProt ID mapping, with representation across Biological Process, Cellular Component, and Molecular Function categories. Functional classification using eggNOG-mapper further associated leading protein group sequences with Clusters of Orthologous Groups (COGs) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways. GO-based screening prioritised 352 putatively immune-relevant protein groups and 24 protein groups associated with sex- and reproduction-related processes, highlighting the functional complexity of the skin mucus proteome. Comparative analysis revealed sex-associated patterns in protein group detection and relative abundance, with differential abundance analysis identifying 244 protein groups exhibiting statistically significant differences between male and female samples. Conclusions: This study provides the first comprehensive discovery-based characterisation of the barramundi skin mucus proteome and establishes a baseline reference dataset for this aquaculture-relevant species. The findings support the utility of skin mucus proteomics for exploring immune and sex-associated molecular patterns and provide a baseline dataset for future validation studies investigating non-invasive health and reproductive monitoring.

Proteomes doi: 10.3390/proteomes14010014

Authors: Ayadathil Sujina Amal Fahma Suhail Subair Rajesh Raju Poornima Ramesh

Vaccinia-Related Kinase 3 (VRK3) is increasingly recognized as a crucial signaling modulator in both normal and pathological processes. This kinase was long thought of as a catalytically inactive pseudokinase, until recently it was established to phosphorylate Barrier to Autointegration Factor (BAF) proteins through its extracatalytic domain. VRK3 regulates diverse cellular pathways through scaffold interactions and context-dependent phosphorylation. This review is centered around the phosphoregulatory network that modulates VRK3 phosphorylation with implications in its abundance and function. A large-scale phosphoproteomic data integration was performed by combining phosphoproteomics profiling and differential phosphorylation from 115 mass spectrometry studies, identifying 32 high-confidence phosphorylation sites on VRK3. Notably, VRK3 (S59), (S82), and (S83) were predominantly observed highlighting plausible functional significance. These phosphorylation sites share 33 potential upstream kinases, and multiple interactor proteins, which in combination are known to regulate ERK, Hippo, and GPCR pathways. These insights advance the understanding of phosphorylation control by kinases and highlight opportunities to target VRK3-associated networks for therapeutic intervention in diseases such as glioma and liver cancer.

Proteomes doi: 10.3390/proteomes14010013

Authors: Terry C. C. Lim Kam Sian Yue Ding Scott A. Blundell Ralf B. Schittenhelm Pouya Faridi

Background: Mass spectrometry (MS)-based immunopeptidomics has emerged as the gold standard for profiling HLA-bound peptides, yet detection remains challenging due to their non-tryptic nature, variable lengths, and lack of basic residues, which limit ionisation and fragmentation efficiency. Methods: To address these limitations, we investigated the impact of incorporating 5% dimethyl sulfoxide (DMSO) into LC-MS/MS mobile-phase buffers on immunopeptidomic workflows. Using B-lymphoblastoid cell lines expressing HLA class I and II alleles and elastase-digested HeLa lysates as a surrogate for non-tryptic peptides, we assessed peptide identification, ionisation efficiency, charge state distribution, and fragmentation quality. Results: DMSO significantly increased peptide identifications across all sample types, with gains of ~1.33 folds for HLA class I, ~1.55 folds for HLA class II, and ~1.24 folds for elastase digests. Improvements were systematic and reproducible, driven by enhanced electrospray ionisation, higher charge states, and superior MS2 spectral quality, evidenced by ~2-fold increase in b- and y-ion intensities. Importantly, DMSO did not introduce major sequence bias, preserving motif integrity and predicted binding characteristics. Conclusions: Overall, these findings establish DMSO as a robust additive for improving sensitivity and reliability in immunopeptidomics, particularly for low-input or clinically derived samples.

Proteomes doi: 10.3390/proteomes14010012

Authors: Anastasia Boura-Theodorou Konstantina Psatha Stefania Maniatsi Areti Kourti Georgia Kaiafa Michalis Aivaliotis Kali Makedou

Immune thrombocytopenia (ITP) is a hematological disorder commonly found in individuals of any gender, race, or age. Patients with ITP will present with thrombocytopenia either in a primary form or because of an infection or a dysfunction in the immune system. The severity of ITP is linked to diminished production of platelets due to the blockage of production in the bone marrow niche and increased destruction of platelets, which confirms the diagnosis of the disorder. The investigation of the pathogenesis of ITP is of critical importance as it can give an important indication of the state of the patient, guiding us through risk assessment and treatment. Proteomics can provide tools to explore the protein profile of ITP. In this review, we aimed to uncover different biomarkers, both diagnostic and prognostic, that have been investigated with proteomic methodologies and that might help in understanding the pathogenesis of ITP and providing personalized treatment to patients. Several differentially abundant proteins were identified, including haptoglobin isoforms, heat shock proteins (HSPA6, HSPA8), integrin β3 (ITGB3), 14-3-3 protein eta (YWHAH), vitamin D-binding protein, fibrinogen chains, MYH9, and FETUB, which are involved in key signaling pathways, such as PI3K/akt, TNF-a, and mTOR, and they demonstrate potential as diagnostic and prognostic biomarkers. Collectively, current data support the value of proteomics for uncovering the molecular landscape of ITP and guiding the development of precision diagnostics and personalized therapeutic strategies.

Proteomes doi: 10.3390/proteomes14010011

Authors: Sabine Lüthje Ayse Gül Yilmaz Kalaivani Ramanathan Waldemar Gräfenstein Jenny M. Tabbert Stefanie Wienkoop Katrin Heino François Clement Perrineau Sönke Harder

Background: Crop plants have to deal with long-term cadmium exposure to farmlands contaminated by intensive use of fertilizers and pesticides. For uptake and sequestration, Cd2+ has to pass the plasma membrane and tonoplast. Class III peroxidases, plasma membrane, and tonoplast sub-proteomes were studied. Methods: Control and Cd2+-treated maize (Zea mays L.) were grown in hydroponics for 18 days. Soluble peroxidases were partially purified by chromatofocusing and characterized by substrate specificity. Membrane-bound peroxidases were analyzed spectrophotometrically and by non-reducing SDS-PAGE. Soluble and plasma membrane-bound peroxidases were identified by mass spectrometry. Shotgun proteomics was used to identify membrane proteins of differential abundance. Results: Guaiacol peroxidase activities increased in soluble fractions of Cd2+ samples. A Cd2+-specific soluble peroxidase (ZmPrx101) was identified, and ZmPrx85 abundance increased significantly in the plasma membrane. Substrate specificity of peroxidases revealed a preference for ferulic acid and esculetin, which was confirmed by docking analyses. Primary active transporters increased auxin efflux (brachytic2, ABCB9, and ABCB21), Cd2+ exclusion (ABCG34), and sequestration into the vacuole (HMA2, ABCB27). Evaluation of sub-proteome fractions demonstrated significant changes for proteins involved in disease resistance responses and cell wall modification. Conclusions: Molecular adjustments of maize root proteome to long-term Cd2+ exposure revealed relevance of low-abundant proteins for Cd2+ tolerance and putative stress markers.

Proteomes doi: 10.3390/proteomes14010010

Authors: Jadranka Miletić Vukajlović Bojana Ilić Bella Bruszel Tanja Panić-Janković Goran Mitulović

Background: Low-volume trapping columns are essential for sample enrichment, desalting, and injection profile focusing on nano-LC–MS-based proteomics. They enable higher sample loading, improve chromatographic performance, and protect the analytical column by removing salts and contaminants. Recently, monolithic trap columns with micropillar architecture have emerged as alternatives to conventionally packed traps. This study compares the performance of a packed and a micropillar monolithic trap column for the analysis of tryptic peptides. Methods: A tryptic digest of HeLa cell lysate was analyzed under identical LC–MS conditions using both trap types. Peptides were detected at 214 nm and analyzed by nano-ESI on a Q Exactive Plus Orbitrap. Data were searched against the human UniProt database (February 2023) using FragPipe v20.0, and statistical evaluation of MaxLFQ intensities was performed in Perseus using Welch’s t-test and clustering analysis. Results: Over 2500 proteins were identified with both setups. The packed trap column yielded more total peptides, particularly those with post-translational modifications and higher hydrophilicity, whereas the monolithic column favored peptides of intermediate hydrophobicity. Chromatographic profiles confirmed a slight reduction in the trapping efficiency of hydrophilic peptides by the monolithic trap. Conclusions: Trap column design significantly influences peptide recovery and proteome coverage.

Proteomes doi: 10.3390/proteomes14010009

Authors: Julie Flecheux Chloé Bardet Laura Herment Tanguy Fortin Jérôme Lemoine

Background: Host cell proteins (HCPs) are process-related impurities that must be monitored in biopharmaceutical products due to their potential impact on product quality and patient safety. Targeted LC–MS/MS approaches such as multiple reaction monitoring (MRM) enable protein-specific HCP quantification but are difficult to apply in highly multiplexed assays because of retention time (RT) variability across complex bioprocess matrices. Methods: Here, we show that conventional RT-scheduled MRM workflows lack transferability when applied to heterogeneous drug substances and process intermediates. Using a targeted assay comprising 240 peptides corresponding to 97 CHO-derived HCPs, RT shifts of several minutes resulted in truncated chromatographic peaks and peptide signal loss, even when wide scheduling windows were used. To overcome this limitation, a scout-triggered MRM (st-MRM) acquisition strategy based on event-driven monitoring was implemented. Results: This approach enabled robust peptide detection across diverse matrices within a single injection, without method re-optimization. Absolute quantification using stable isotope-labeled peptides spanned six orders of magnitude, with HCPs quantified down to 2.9 ppm in purified drug substances. Conclusion: Overall, st-MRM improves the robustness and transferability of highly multiplexed targeted proteomics workflows for HCP analysis.

Proteomes doi: 10.3390/proteomes14010008

Authors: Akhina Palollathil Althaf Mahin Athira Perunelly Gopalakrishnan Tejaswini R Poojari Alimath Sambreena Prathik Basthikoppa Shivamurthy Rajesh Raju

Background: Fibroblast growth factor receptors (FGFRs) play a crucial role in tissue homeostasis and organ development by regulating cellular processes, including proliferation, differentiation, and survival. Dysregulation of FGFRs contributes to developmental disorders and carcinogenesis. As membrane-bound receptors, they represent promising targets for therapeutic intervention and drug development. Methods: This study employed a systematic in silico analysis of publicly available phosphoproteomics datasets to provide a comprehensive overview of the phosphorylation regulatory network of the FGFR family. Results: We identified predominant phosphosites in FGFR1-4 that exhibited differential abundance across diverse experimental conditions, specifically, Y653 in FGFR1; S453, Y586, Y656, and Y657 in FGFR2; S444 and S445 in FGFR3; and S573 in FGFR4. Our analysis identified 32 and 89 significantly co-modulated phosphosites on other proteins with FGFR3 and FGFR4, respectively. Beyond the upstream kinases from the FGFR family, we also identified MAPK1 as a potential upstream kinase of FGFR4. Furthermore, disease enrichment analysis revealed that proteins co-modulated with FGFR3 were primarily involved in skeletal developmental disorders, such as brachydactyly, short toe, and syndactyly of fingers, whereas those associated with FGFR4 were linked to various cancers. Conclusions: Our findings highlight key disease-associated phosphosites within the FGFRs and offer a foundation for advancing phosphosite-focused therapeutic research.

Proteomes doi: 10.3390/proteomes14010007

Authors: Yury Yu. Strogov Sergey A. Spirin Mark V. Ivanov Maria A. Kulebyakina Anastasia Yu. Efimenko Oleg I. Klychnikov

Background: Currently, post-translational modification (PTM) search in MS/MS data is performed using either open modification search (OMS) or closed search (CS) algorithms. The OMS method allows for the determination of many PTMs and unknown mass-shifts in one run. In contrast, closed search algorithms are more sensitive but limited in the number of PTMs that can be specified in one search. Methods: In this manuscript, we propose an optimized Python algorithm based on the IdentiPy search engine that performs an automated sequential search for each PTM based on previous annotations from public databases and customized protein lists. We also determined the sufficient size of the search space to increase the significance of false discovery rate (FDR) estimation. We modified the FDR calculation algorithm by implementing a spline approximation of the ratio of the modified decoys, and by calculating error propagation to filter out unstable data and determine the cutoff value. Results: The results of this pipeline for a test dataset were comparable to previously published data in terms of the number of unmodified peptides and proteins. Additionally, we identified 13 different types of peptide PTMs and achieved an increase in relative protein coverage. Our filtration method based on spline transferred FDR showed a superior number of identified peptides compared to separate FDR. Conclusions: Our developed pipeline can be used as a standalone application or as a module of multiple PTM search in data analysis platforms.

Proteomes doi: 10.3390/proteomes14010006

Authors: Mohadeseh Montazeri Shatouri Igor Pirozzi Pinar Demir Soker Zeshan Ali Ardeshir Amirkhani Paul A. Haynes

Background: Commercial feed formulations are increasingly being evaluated for their nutritional impacts on aquaculture species, yet the molecular consequences of commonly used commercial diets remain underexplored. Methods: This study investigated the effects of two commercial diets, diet A (higher land animal protein) and diet B (higher fish meal content), on the protein profile in the brain, liver, and intestine of barramundi (Lates calcarifer). A 12-week feeding trial was conducted with controlled water quality, and proteomic profiling was performed using data-independent acquisition. Results: Differential analysis revealed consistent changes between diets across all tissues, with a higher percentage of differentially abundant proteins observed in between-diet comparisons (12.99% in brain, 12.73% in liver, and 16.59% in intestine) than within-diet controls (<8%), confirming a measurable dietary effect size. In total, 3901 proteins in the brain, 3660 in the liver, and 5025 in the intestine were quantified. Functional enrichment highlighted upregulation of ferroptosis pathways, downregulation of apelin signaling in the brain, and increased digestive proteases in the liver. ICP-MS confirmed elevated iron concentrations in the brain, liver, and intestine of fish fed on diet B. Conclusions: These findings demonstrate that molecular pathways linked to iron metabolism, digestion, and growth regulation are very sensitive to dietary composition, highlighting how proteomics can help identify subtle impacts of compositional differences in aquaculture feeding. Although physiological parameters did not differ significantly, the proteomic alterations observed across tissues likely indicate organ-specific metabolic adaptations to the differing nutrient availability between diets.

Proteomes doi: 10.3390/proteomes14010005

Authors: Xia Peng Jing Chen Xiaoyu Zheng Xige Zhao Yijia Wang Xiaotong Wang Juan Du

Background: Cleft palate (CP) is a prevalent craniofacial malformation, with the TGFβ pathway playing a critical role. Recent evidence links autophagy to regulating mouse embryonic palatal mesenchyme (MEPM) cells, but its interaction with TGFβ-activated phosphorylation cascades remains largely unknown. Here, we investigated the interplay between these pathways during palatogenesis. Methods: H&E and IHC analyses revealed increased expression of Beclin 1 and LC3 during the critical period of palatal shelf elevation and fusion (E13.5–E15.5). Bulk RNA sequencing (Bulk RNA-seq) further revealed enrichment of autophagy-related pathways and their interaction with TGFβ signaling. TMT-based phosphoproteomics was performed on TGFβ2-treated MEPM cells. Results: We identified 23,471 peptides and 3952 proteins, including 6339 phosphopeptides corresponding to 2195 phosphoproteins. Differential analysis found 477 phosphopeptides with increased abundance and 53 with decreased abundance, revealing the enrichment of seven serine (p-Ser) motifs (RxxS, SDxD, SDxE, SP, SxDE, SxEE, SxxxxD) and one threonine (p-Thr) motif (TP). Notably, kinase-substrate enrichment analysis identified CSNK2A as a previously unrecognized phosphorylation regulator, together with MAPKs and CDKs. Functional enrichment showed significant involvement of mTOR, MAPK, and autophagy/mitophagy pathways. Conclusions: Our findings revealed that TGFβ2 reshapes the MEPM phosphoproteome through Smad-independent pathway, expanding the palate-specific phospho-signaling atlas beyond the canonical Smad cascade.

Proteomes doi: 10.3390/proteomes14010004

Authors: Hinano Takase Sotaro Katagiri Takuma Ide Aina Nagano Haruki Sakurai Hana Kokubo Taiki Yanagisawa Masanori Okamoto Taishi Umezawa

Background: Abscisic acid (ABA) is a key phytohormone that regulates plant growth and stress responses through protein phosphorylation. While ABA-induced phosphosignaling has been extensively studied in Arabidopsis thaliana, its conservation and divergence across plant species remain unclear. Methods: Here, we performed phosphoproteomic analysis using LC-MS/MS in Arabidopsis, rice (Oryza sativa), and soybean (Glycine max) to compare ABA-responsive phosphorylation profiles among monocots, dicots, and legumes. Results: ABA treatments on Arabidopsis, rice, and soybean seedlings yielded approximately 24,604, 18,865, and 24,930 phosphopeptides, respectively. Comparative analyses revealed both conserved and species-specific ABA-responsive phosphoproteins. Conclusions: This work provides insights into the evolutionary diversification of ABA signaling and its potential applications in improving crop stress tolerance.

Proteomes doi: 10.3390/proteomes14010003

Authors: Sarena Banu P. Anusha Pedro Beltran-Alvarez Mohammed Idris Katharina Wollenberg Valero Francisco Rivero

Background: Dictyostelium discoideum is widely used in developmental and evolutionary biology due to its ability to transition from a single cell to a multicellular organism in response to starvation. While transcriptome information across its life cycle is widely available, only early-stage data exist at the proteome level. This study characterizes and compares the proteomes of D. discoideum cells at the vegetative, aggregation, mound, culmination and fruiting body stages. Methods: Samples were collected from cells developing synchronously on nitrocellulose filters. Proteins were extracted and digested with trypsin, and peptides were analyzed by liquid chromatography–tandem mass spectrometry. Data were processed using Proteome Discoverer™ for protein identification and label-free quantification. Results: A total of 4502 proteins were identified, of which 1848 (41%) were present across all stages. Pairwise comparisons between adjacent stages revealed clear transitions, the largest ones occurring between the culmination and fruiting body and between the fruiting body and vegetative stage, involving 29% and 52% of proteins, respectively. Hierarchical clustering assigned proteins to one of nine clusters, each displaying a distinct pattern of abundances across the life cycle. Conclusions: This study presents the first complete developmental proteomic time series for D. discoideum, revealing changes that contribute to multicellularity, cellular differentiation and morphogenesis.

Proteomes doi: 10.3390/proteomes14010002

Authors: Rachel L. Watkin Avedis A. Kazanjian Jennifer R. Damicis Elizabeth Yohannes

Background: Despite existing proteomics studies of other cell types, a comprehensive proteome of mesothelial cells has not been characterized. This study establishes a crucial baseline proteome for mesothelial cells to better understand their fundamental bioprocesses in healthy and injured states. Methods: Using mass spectrometry-based shotgun proteomics, we characterized the cellular fraction (CF) and conditioned medium (CM) proteomes of mesothelial cell line MeT-5A. The datasets were analyzed for Gene Ontology (GO) terms and canonical pathway enrichments to identify biological themes. Results: Our analysis identified 5087 protein groups, including 1532 shared proteins, 3122 unique to the CF and 433 exclusive to the CM. GO annotation revealed distinct functional enrichment profiles, reflecting the differing roles of intracellular and secreted proteins. While intracellular proteins were linked to core cellular functions, the extracellular proteome was enriched for signaling and cell-to-cell interaction pathways. The proteins shared by both compartments provided an integrated view of the molecular coordination between the cellular and extracellular environments. Conclusions: This study provides the first comprehensive baseline proteome for mesothelial cells and their secreted medium, offering a vital resource for future investigations into the mesothelium, particularly in the context of disease or injury.

Proteomes doi: 10.3390/proteomes14010001

Authors: Brett Sather James Larson Kian Hutt Vater Jade Westrum Timothy R. McDermott Brian Bothner

Background: The arsenic-responsive repressor, ArsR, has long been understood as a canonical regulator of the arsRBC operon, which confers resistance to arsenic stress. However, recent studies suggest a broader regulatory scope for ArsR. Here, we investigated the proteomic landscape of Escherichia coli strains with and without ArsR to elucidate ArsR as an activator in both non-stressing and arsenic-stressing conditions. Methods: Using mass-spectrometry-based shotgun proteomics and statistical analyses, we characterized the differential abundance of proteins across AW3110 (ΔarsRBC), AW3110 complemented with arsR, and wild-type K-12 strains under control and arsenite-stressed conditions. Results: Our study shows that ArsR influences proteomic networks beyond the ars operon, integrating metabolic and redox responses crucial for cellular adaptation and survival. This suggests that ArsR has a significant role in gut microbiome metabolomic profiles in response to arsenite. Proteins involved in alanine, lactaldehyde, arginine, thioredoxin, and proline pathways were significantly elevated in strains where ArsR was detected, both with and without arsenite. We identified proteins exhibiting an “ArsR-dependent” activation pattern, highlighting ArsR’s potential role in redox balance and energy metabolism. Conclusions: These findings challenge the classical view of ArsR as a repressor and position it as a pleiotropic regulator, including broad activation.

Proteomes doi: 10.3390/proteomes13040068

Authors: Andrew Hesketh Juned Kadiwala Vaishnavi Ravikumar Ana Rita Garizo Patrícia Beldade Marjorie Fournier Rameen Shakur

Background: Insect metamorphosis is one of the most fascinating developmental processes in the natural world. Complete metamorphosis requires the breakdown and reorganisation of larval tissues and the coordinated construction and development of adult structures. The molecular events that achieve this transformation are, however, incompletely understood, and there is a particular shortage of data describing changes in protein abundance that occur during the process. Methods: Here, using a label-free quantitative bottom-up approach, we perform a novel whole-organism proteomic analysis of consecutive developmental stages of male Bicyclus anynana butterflies as they develop from caterpillars into adults via pupation. Results: Our analysis generated a dynamic reference dataset representing 2749 detected proteins. Statistical analysis identified 90 proteins changing significantly in abundance during metamorphosis, and functional interpretation highlights cuticle formation, apoptosis and autophagy during the pupal stages, and the up-regulation of respiration and energy metabolism upon completion of the fully formed adult. A preliminary search for potential peptide phosphorylation modifications identified 15 candidates, including three proteins with roles in muscle function. Conclusions: The study provides a basis for future protein-level analysis of butterfly metamorphosis and suggests the importance of dissecting the post-translational regulation associated with this fascinating developmental transformation.

Proteomes doi: 10.3390/proteomes13040067

Authors: Petra Magdolna Bertalan Erdenetsetseg Nokhoijav Ádám Pap George C. Neagu Miklós Káplár Zsuzsanna Darula Gergő Kalló Laszlo Prokai Éva Csősz

Background: Obesity is a major risk factor for type 2 diabetes (T2D); however, the molecular links between these conditions are not fully understood. Methods: We performed an integrative serum proteomics study on samples from 134 individuals (healthy controls, patients with obesity and/or T2D) using both data-independent (DIA) and data-dependent (DDA) liquid chromatography-mass spectrometry approaches, complemented by phosphopeptide enrichment, kinase activity prediction, network and pathway analyses to get more information on the different proteoforms involved in the pathophysiology of the diseases. Results: We identified 235 serum proteins, including 13 differentially abundant proteins (DAPs) between groups. Both obesity and T2D were characterized by activation of complement and coagulation cascades, as well as alterations in lipid metabolism. Ingenuity Pathway Analysis® (IPA) revealed shared canonical pathways, while phosphorylation-based regulation differentiated the two conditions. Elevated hemopexin (HPX), vitronectin (VTN), kininogen-1 (KNG1) and pigment epithelium-derived factor (SERPINF1), along with decreased adiponectin (ADIPOQ) and apolipoprotein D (APOD), indicated a pro-inflammatory, pro-coagulant serum profile. Network analyses of antimicrobial and immunomodulatory peptides (AMPs) revealed strong overlaps between immune regulation and lipid metabolism. Phosphoproteomics and kinase prediction highlighted altered CK2 and AGC kinase activities in obesity, suggesting signaling-level modulation. Conclusions: Our comprehensive proteomic and phosphoproteomic profiling reveals overlapping yet distinct molecular signatures in obesity and T2D, emphasizing inflammation, complement activation and phosphorylation-driven signaling as central mechanisms that potentially contribute to disease progression and therapeutic targeting.

Proteomes doi: 10.3390/proteomes13040066

Authors: Ukamaka U. Eze Rethabile Mokoena Kenneth I. Ogbu Sinegugu Dubazana Ernest C. Ngoepe Mparamoto Munangatire Romanus C. Ezeokonkwo Boniface M. Anene Sindisiwe G. Buthelezi Claude T. Sabeta

Background: Rabies is among the oldest known zoonotic viral diseases and is caused by members of the Lyssavirus genus. The prototype species, Lyssavirus rabies, effectively evades the host immune response, allowing the infection to progress unnoticed until the onset of clinical signs. At this stage, the disease is irreversible and invariably fatal, with definitive diagnosis possible only post-mortem. Given the advances in modern proteomics, this study aimed to identify potential protein biomarkers for antemortem diagnosis of rabies in dogs, which are the principal reservoir hosts of the rabies virus. Methods: Two hundred and thirty-one samples (brain tissues (BT), cerebrospinal fluids (CSF), and serum (SR) samples) were collected from apparently healthy dogs brought for slaughter for human consumption in South-East and North-Central Nigeria. All the BT were subjected to a direct fluorescent antibody test to confirm the presence of lyssavirus antigen, and 8.7% (n = 20) were positive. Protein extraction, quantification, reduction, and alkylation were followed by on-bead (HILIC) cleanup and tryptic digestion. The resulting peptides from each sample were injected into the Evosep One LC system, coupled to the timsTOF HT MS, using the standard dia-PASEF short gradient data acquisition method. Data was processed using SpectronautTM (v19). An unpaired t-test was performed to compare identified protein groups (proteins and their isoforms) between the rabies-infected and uninfected BT, CSF, and SR samples. Results: The study yielded 54 significantly differentially abundant proteins for the BT group, 299 for the CSF group, and 280 for the SR group. Forty-five overlapping differentially abundant proteins were identified between CSF and SR, one between BT and CSF, and two between BT and SR; none were found that overlapped all three groups. Within the BT group, 33 proteins showed increased abundance, while 21 showed decreased abundance in the rabies-positive samples. In the CSF group, 159 proteins had increased abundance and 140 had decreased abundance in the rabies-positive samples. For the SR group, 215 proteins showed increased abundance, and 65 showed decreased abundance in the rabies-positive samples. Functional enrichment analysis revealed that pathways associated with CSF, spinocerebellar ataxia, and neurodegeneration were among the significant findings. Conclusion: This study identified canonical proteins in CSF and SR that serve as candidate biomarkers for rabies infection, offering insights into neuronal dysfunction and potential tools for early diagnosis.

Proteomes doi: 10.3390/proteomes13040065

Authors: Lorenza Vantaggiato Marco Frisenda Enxhi Shaba Chiara Splendore Beatrice Sciarra Luca Bini Alessandro Sciarra Claudia Landi

Background: Non-muscle invasive bladder cancer (NMIBC) comprises high-grade (HG) and low-grade (LG) variants, classified by aggressiveness, recurrence risk, and stage—either non-invasive (pTa) or invading the lamina propria (pT1). Cystoscopy remains the diagnostic gold standard, with no less-invasive alternatives, while molecular mechanisms driving tumorigenesis and treatment response are poorly understood. Methods: To address this gap, we conducted a preliminary top-down proteomic study on fresh biopsies from pTa-LG and pT1-HG NMIBC at initial diagnosis to identify molecular differences and potential prognostic biomarkers. Results: Distinct protein profiles were observed between stages. Highly abundant proteins in pT1-HG were associated with nitric oxide biosynthesis, signal transduction, inhibition of apoptosis, protein folding, and immune response. Proteins of low abundance were related to cellular localization, cytoskeleton organization, cell adhesion, phagocytosis, and tissue development. Notably, multiple proteoforms of PDC6I/ALIX, a protein implicated in the regulation of apoptosis, proliferation, and PD-L1 surface presentation, were significantly downregulated in pT1-HG tumors. Furthermore, the abundance of proteins such as GANAB, GALE, THIC, SEPT8, and MYDGF/C19orf10 correlated with tumor size, suggesting their potential as prognostic biomarkers. Conclusions: These proteins, taken together, indicate that they may serve as valuable prognostic markers, offering a path toward more personalized management of NMIBC beyond the traditional one-size-fits-all approach.

Proteomes doi: 10.3390/proteomes13040064

Authors: Fotios P. Galanis Avgi E. Apostolakou Georgia I. Nasi Zoi I. Litou Vassiliki A. Iconomidou

Background: Amyloidogenic proteins, a heterogenous group of proteins characterized by their ability to form amyloid fibrils, lead to pathological conditions when they undergo abnormal folding and self-assembly. Missense single-nucleotide polymorphisms (msSNPs) may occur in their sequence, disrupting the normal structure and function of these proteins, pushing them towards amyloidogenesis. Methods: A comprehensive dataset of amyloidogenic proteins was created and their msSNPs were collected and mapped on their amino acid sequence. The chi squared test, logistic regression and the bootstrap method were used to ascertain the statistical significance of the results. Results: The distribution of pathogenic and benign msSNPs highlighted the predicted amyloidogenic segments as hotspots for pathogenic msSNPs. Analysis of the change in residue properties and pathogenicity status revealed that the substitution of negatively charged residues by any other type of residue tends to be pathogenic. Furthermore, certain substitutions were found to be more likely pathogenic than average. Additionally, a case study of APP, a key protein in Alzheimer’s disease, is used as an example. Conclusions: This study will hopefully showcase the importance of amyloidogenic protein msSNPs as well as spark an interest in research of the mechanisms that lead to the formation of amyloid deposits under the scope of pathogenic msSNPs.

Proteomes doi: 10.3390/proteomes13040063

Authors: Lina Alhourani Yasser Tabana Ashwin Anand Richard P. Fahlman

Background: Multiple myeloma (MM) is essentially an incurable cancer, but treatments with proteasome inhibitors are widely used clinically to extend patient survival. While the mechanisms of proteasome inhibition by Bortezomib are well known, the cellular responses to this proteotoxic stress that leads to sensitivity by MM are not fully elucidated. This study reports on the application of an emerging method to investigate proteostasis by proteomics. Methods: We utilized metabolic labeling with azidohomoalanine (AHA) in a MM cell line in combination with Bortezomib treatment. AHA labeling facilitates the selective isolation and identification of proteins for investigations of protein synthesis or protein degradation. Results: The data collected reveals significant changes in gene protein synthesis upon Bortezomib treatment, including protein neddylation. The data also reveals a global increase in protein degradation, which suggests the induction of an autophagy-related process. The resulting data collected reveals significant changes upon Bortezomib treatment in protein synthesis of genes, including protein neddylation, and protein degradation data reveals a global increase in protein degradation, suggesting an induction of an autophagy-related process. Subsequent cellular and proteomic analysis investigated the additional treatment of an autophagy inhibitor, hydroxychloroquine, in combination with Bortezomib treatment by label-free proteomics to further characterize the proteome-wide changes in these two proteotoxic stresses. Conclusions: AHA metabolic labeling proteomics to investigate protein synthesis and degradation enables novel complementary insights into complex cellular responses compared to that of traditional label-free proteomics.

Proteomes doi: 10.3390/proteomes13040062

Authors: Christina Karakosta Martina Samiotaki Anastasios Bisoukis Konstantinos I. Bougioukas George Panayotou Nantieznta Kyriakidou Konstantinos Moschou Marilita M. Moschos

Background: The aim of this study is to investigate the pathophysiology of cataract by analyzing signaling pathways in three sample types obtained from four different lens groups: age-related (ARC), diabetic (DC), post-vitrectomy cataract (PVC) and clear control lenses. Methods: Three sample types—the aqueous humor, the anterior capsule and the phaco cassette content—were collected during cataract surgery from 39 participants (ARC = 12, DC = 11, PVC = 7 and control = 9). The samples were prepared based on Sp3 protocol. The recognition and quantification of proteins were performed with liquid chromatography online with tandem mass spectrometry using the DIA-NN software. Perseus software (v1.6.15.0) was used for statistical analysis. Data are available via ProteomeXchange with identifiers PXD045547, PXD045554, PXD045557, and PXD069667. Results: In total, 1986 proteins were identified in the aqueous humor, 2804 in the anterior capsule, and 3337 in the phaco cassette samples. Proteins involved in actin and microtubule cytoskeleton organization, including ACTN4, were downregulated in all three cataract groups compared to controls. Proteins involved in glycolipid metabolic process, including GAL3ST1, GAL3ST4, and GLA, were upregulated in ARC compared to controls. Proteins involved in the non-canonical Wnt receptor signaling pathway, including FRZB, SFRP1, SFRP2, SFRP5, WNT5A, and WNT7A, were upregulated in ARC compared to DC, PVC, and controls. Conclusions: Comprehensive proteomic profiles were generated using DIA proteomics by comparing ARC, DC, and PVC versus controls. This is the first study to use phaco cassette contents to investigate cataract formation in comparison to controls. Our findings significantly enhance the current understanding of human cataract pathophysiology and provide novel insights into the mechanisms underlying cataract formation.

Proteomes doi: 10.3390/proteomes13040061

Authors: Savanna Wallin Sneha Pandithar Sarbjit Singh Siddhartha Kumar Amarnath Natarajan Gloria E. O. Borgstahl Nicholas Woods

Background: Mitoxantrone (MX) is regularly used to treat several cancers. Despite its long history in the clinic, recent studies continue to unveil novel protein targets. These targets may contribute to the cytotoxic effects of the drug, as well as potential non-canonical antitumor activity. A better understanding of MX’s cellular targets is required to fully comprehend the molecular consequences of treatment and to interpret MX sensitivity in homologous recombination (HR)-deficient cancer. Methods: Here, we evaluated MX activity in HR-deficient UWB1.289 (BRCA1−) ovarian cancer cells and surveyed the binding profile of MX using TMT-labeled quantitative proteomics and chemoproteomics. Results: Mass spectrometry (MS) analysis of cellular extracts from MX-treated BRCA1−UWB1.289 cells revealed unique downregulation of pathways instrumental in maintaining genomic stability, including single-strand annealing. Moreover, the BRCA1− cells exhibited a significant upregulation of proteins involved in ribosome biogenesis and RNA processing. Additional MS analyses following affinity-purification using a biotinylated-mitoxantrone probe corroborated these findings, which showed considerable targeting of proteins involved in genome maintenance and RNA processing. Conclusions: Our results suggest that an interplay of both canonical and non-canonical MX-antitumor activity overwhelms the BRCA1− UWB1.289 cells. Furthermore, this study characterizes the target landscape of MX, providing insights into off-target effects and MX action in HR-deficient cancer.

Proteomes doi: 10.3390/proteomes13040060

Authors: Tanushree Halder Roopali Bhoite Shahidul Islam Guijun Yan Md. Nurealam Siddiqui Md. Omar Kayess Kadambot H. M. Siddique

Polyploid crops such as wheat, Brassica, and cotton are critical in the global agricultural and economic system. However, their productivity is threatened increasingly by biotic stresses such as disease, and abiotic stresses such as heat, both exacerbated by climate change. Understanding the molecular basis of stress responses in these crops is crucial but remains challenging due to their complex genetic makeup—characterized by large sizes, multiple genomes, and limited annotation resources. Proteomics is a powerful approach to elucidate molecular mechanisms, enabling the identification of stress-responsive proteins; cellular localization; physiological, biochemical, and metabolic pathways; protein–protein interaction; and post-translational modifications. It also sheds light on the evolutionary consequences of genome duplication and hybridization. Breeders can improve stress tolerance and yield traits by characterizing the proteome of polyploid crops. Functional and subcellular proteomics, and identification and introgression of stress-responsive protein biomarkers, are promising for crop improvement. Nevertheless, several challenges remain, including inefficient protein extraction methods, limited organelle-specific data, insufficient protein annotations, low proteoform coverage, reproducibility, and a lack of target-specific antibodies. This review explores the genomic complexity of three key allopolyploid crops (wheat, oilseed Brassica, and cotton), summarizes recent proteomic insights into heat stress and pathogen response, and discusses current challenges and future directions for advancing proteomics in polyploid crop improvement through proteomics.

Proteomes doi: 10.3390/proteomes13040059

Authors: Kittinop Kittirotruji Utapin Ngaokrajang Visarut Buranasudja Ittichai Sujarittham San Yoon Nwe Pipob Suwanchaikasem Kaewta Rattanapisit Christine Joy I. Bulaon Waranyoo Phoolcharoen

Background: Human insulin-like growth factor 1 (hIGF-1) plays a key role in cell proliferation and tissue repair. While plant expression systems offer a cost-effective and scalable alternative for recombinant protein production, the molecular effects of plant-derived hIGF-1 on mammalian cells remain largely unexplored. Methods: In this study, a recombinant fusion protein of hIGF-1 with human Fc (hIGF-1-Fc) was transiently expressed in Nicotiana benthamiana using the geminiviral pBYR2e system and purified by Protein A affinity chromatography. SDS-PAGE and Western blotting confirmed the predicted molecular weight, and LC-MS identified N-glycosylation at the Fc N229 site with plant-type glycans such as GnMXF, GnGnXF, and MMXF. Bioactivity was evaluated using MCF-7 cell proliferation and NIH3T3 wound healing assays. Label-free quantitative proteomics was performed on NIH3T3 fibroblasts to assess molecular changes. Results: hIGF-1 Fc significantly promoted cancer cell migration and fibroblast proliferation. Proteomic profiling revealed an abundance of cytoskeletal proteins such as actin and tubulin and metabolic enzymes related to energy production. Gene ontology and pathway enrichment analyses indicated significant modulation of ribosome biogenesis and carbon metabolism. Conclusions: This study presents the first proteome-level investigation of plant-produced hIGF-1-Fc in mouse fibroblasts and reveals its impact on cytoskeletal organization and metabolic pathways involved in proliferation and wound healing.

Proteomes doi: 10.3390/proteomes13040058

Authors: Mansi Dutt Anuj Kumar Ali Toloue Ostadgavahi David J. Kelvin Gustavo Sganzerla Martinez

Background: Poxviruses constitute a family of large dsDNA viruses that can infect a plethora of species including humans. Historically, poxviruses have caused a health burden in multiple outbreaks. The large genome of poxviruses favors reverse vaccinology approaches that can determine potential antigens and epitopes. Here, we propose the modeling of a user-friendly database containing the predicted antigens and epitopes of a large cohort of poxvirus proteomes using the existing PoxiPred method for reverse vaccinology of poxviruses. Methods: In the present study, we obtained the whole proteomes of as many as 37 distinct poxviruses. We utilized each proteome to predict both antigenic proteins and T-cell epitopes of poxviruses with the aid of an Artificial Intelligence method, namely the PoxiPred method. Results: In total, we predicted 3966 proteins as potential antigen targets. Of note, we considered that this protein may exist in a set of proteoforms. Subsets of these proteins constituted a comprehensive repository of 54,291 linear T-cell epitopes. We combined the outcome of the predictions in the format of a web tool that delivers a database of antigens and epitopes of poxviruses. We also developed a comprehensive repository dedicated to providing access to end-users to obtain AI-based screened antigens and T-cell epitopes of poxviruses in a user-friendly manner. These antigens and epitopes can be utilized to design experiments for the development of effective vaccines against a plethora of poxviruses. Conclusions: The TCEPVDB repository, already deployed to the web under an open-source coding philosophy, is free to use, does not require any login, does not store any information from its users.

Proteomes doi: 10.3390/proteomes13040057

Authors: Mikhail S. Arbatskiy Dmitriy E. Balandin Alexey V. Churov

Background: The search for reliable aging biomarkers using proteomic databases and large-scale proteomic studies presents a significant challenge in biogerontology. Existing proteomic databases and studies contain valuable information; however, there is inconsistency in approaches to biomarker selection and data integration. This creates barriers to translating existing knowledge into clinical practice and use in biomedical research. This work analyzed experimental proteomic studies, the content of proteomic databases, and proposed recommendations for optimization and improvement of proteomic database formation and enrichment. Methods: The study utilized publications devoted to proteomic data acquisition methods, proteomic databases, and experimental studies. Results: Methods for obtaining proteomic data were analyzed (Protein Pathway Array (PPA), Tissue Microarray (TMA), Luminex (Bead Array), MSD (Meso Scale Discovery), Simoa (Quanterix), SOMAscan (SomaLogic), Olink (PEA), Alamar NULISA (PEA+), and Oxford Nanopore. A total of 16 proteomic databases were investigated (HAGR, KEGG, STRING, Aging Atlas, HALL, Human Protein Atlas, UniProt, AgeAnnoMO, AgeFactDB, AgingBank, iProX, jMorp, jPOSTrepo, MassIVE, MetaboAge DB, PRIDE Archive). Additionally, 22 proteomic studies devoted to aging and age-associated diseases were analyzed. Conclusions: Proteomic databases and experimental studies individually contain valuable information about aging biomarkers. Using data from different sources within biomedical research poses challenges for improving and optimizing methodological solutions for publication selection, database formation, and marker development.

Proteomes doi: 10.3390/proteomes13040056

Authors: Andrea Arévalo-Cortés Daniel Rodriguez-Pinto

Background: Molecular mimicry contributes to the development of unwanted responses to self-antigens. Autoimmune phenomena have been observed in diseases caused by Aedes aegypti-transmitted arboviruses, but the occurrence of mimicry between salivary and human proteins has been unexplored. Methods: We used bioinformatic tools to determine if peptides from Aedes aegypti salivary proteins were present in the human proteome. We further characterized the potential of shared sequences to induce immunity by analyzing their predicted binding to MHC molecules and their occurrence in peptides from the Immune Epitope Database (IEDB). Results: We analyzed 9513 octapeptides from 29 Aedes aegypti salivary proteins against the human proteome and found 47 peptides identical to sequences from 52 human proteins, ranging in length from 8 to 18 amino acids. We found 302 matches of peptides predicted to bind with high affinity to MHC-I and MHC-II alleles associated with autoimmune diseases, and 14 human peptides containing shared sequences with Aedes aegypti salivary proteins validated as immunogenic in the IEDB. Conclusions: These results support the existence of molecular mimicry between Aedes aegypti salivary proteins and human antigens and provide a framework for studies to determine its contribution to responses directed to self-antigens in the context of arboviral infections.

Proteomes doi: 10.3390/proteomes13040055

Authors: Chunyang Ren Gan Qiao Jianping Wu Yongxiang Lu Minghua Liu Chunxiang Zhang

Background: Chronic ischemic heart disease (CIHD) is characterized by persistent myocardial ischemic due to long-term reduced coronary blood flow. In the past, we mainly relied on surgical intervention or drug therapy to alleviate symptoms, but effective targeted treatments were scarce. Proteomics serves as a key tool to identify novel therapeutic targets. Methods: This study performed a bidirectional Mendelian randomization (MR) analysis by integrating genome-wide association study (GWAS) data on CIHD (10,894,596 single-nucleotide polymorphisms) with plasma proteomic data encompassing 4907 proteins. We conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify pathways linked to candidate protein biomarkers, searched the National Genomics Data Center (NGDC) database for existing evidence of their association with CIHD, and evaluated druggability through multi-dimensional analysis integrating the DSIGDB, ChEMBL, and clinical trial databases. Results: After eliminating the reverse effect, ultimately identifying 28 protein markers, including 16 risk-associated and 12 protective proteins. We also investigated their roles in the pathways related to CIHD. Meanwhile, the search confirmed that five of them were newly discovered protein markers. Ultimately, through evaluation, three priority therapeutic targets (CXCL12, PLAU, CD14) were identified for development. Conclusions: This study identified some biomarkers related to CIHD and analyzed the possible pathways involved. It also provided some new insights into the identification of the target and druggability.

Proteomes doi: 10.3390/proteomes13040054

Authors: Sarah Bernard Merumba Habiba Omar Ahmed Dong Fu Pingfang Yang

Protein–protein interactions (PPIs) are significant in understanding the complex molecular processes of plant growth, disease resistance, and stress responses. Machine learning (ML) has recently emerged as a powerful tool that can predict and analyze PPIs, offering complementary insights into traditional experimental approaches. It also accounts for proteoforms, distinct molecular variants of proteins arising from alternative splicing, or genetic variations and modifications, which can significantly influence PPI dynamics and specificity in rice. This review presents a comprehensive summary of ML-based methods for PPI predictions in rice (Oryza sativa) based on recent developments in algorithmic innovation, feature extraction processes, and computational resources. We present applications of these models in the discovery of candidate genes, unknown protein annotations, identification of plant–pathogen interactions, and precision breeding. Case studies demonstrate the utility of ML-based methods in improving rice resistance to abiotic and biotic stresses. Additionally, this review highlights key challenges like data limits, model generalizability, and future directions like multi-omics, deep learning and artificial intelligence (AI). This review provides a roadmap for researchers aiming to use ML to generate predictive and mechanistic insights on rice PPI networks, hence helping to achieve enhanced crop improvement programs.

Proteomes doi: 10.3390/proteomes13040053

Authors: D. M. N. M. Gunasekara H. D. T. U. Wijerathne Lei Wang Hyun-Soo Kim K. K. A. Sanjeewa

Marine-derived bioactive peptides (MBPs) are emerging as promising natural agents for regulating inflammatory responses. MBPs, typically obtained through enzymatic hydrolysis of proteins from various marine organisms such as fish, mollusks, and algae, exhibit diverse biological activities, including antioxidant, immunomodulatory, and anti-inflammatory effects. The ability of MBPs to modulate key inflammatory mediators such as TNF-α, IL-6, and COX-2, primarily through pathways like NF-κB and MAPK, highlights the therapeutic potential of MBPs in managing chronic inflammatory diseases. However, most existing studies are confined to in vitro assays or animal models, with limited translation to human clinical applications. This review explores the stability, bioavailability, and metabolic rate of MBPs under physiological conditions, which remain poorly understood. In addition, a lack of standardized protocols for peptide extraction, purification, and efficacy evaluation hinders comparative analysis across studies and also different proteomics approaches for separation, purification, identification, and quantification of marine-derived peptides with therapeutic properties. The structure–function relationship of MBPs is also underexplored, limiting rational design and targeted applications in functional foods or therapeutic products. These limitations are largely due to a lack of consolidated information and integrated research efforts. To address these challenges, this review summarizes recent progress in identifying MBPs with anti-inflammatory potentials, outlines key mechanisms, and highlights current limitations. Additionally, this review also emphasizes the need to enhance mechanistic understanding, optimize delivery strategies, and advance clinical validation to fully realize the therapeutic potential of MBPs.

Proteomes doi: 10.3390/proteomes13040052

Authors: Ricardo Monteiro Ingrid Chafsey Charlotte Cordonnier Valentin Ageorges Didier Viala Michel Hébraud Valérie Livrelli Alfredo Pezzicoli Mariagrazia Pizza Mickaël Desvaux

Background: EHEC O157:H7 causes severe gastrointestinal illness by first colonizing the large intestine. It intimately attaches to the epithelial lining, orchestrating distinctive “attaching and effacing” lesions that disrupt the host’s cellular landscape. While much is known about the well-established virulence factors, there are much to learn about the surface proteins’ roles in a living host. Methods: This study presents the first in vivo characterisation of the surface proteome, i.e., proteosurfaceome, of Escherichia coli O157:H7 EDL933 during intestinal infection, revealing spatial and temporal adaptations critical for colonisation and survival. Using a murine ileal loop model, surface proteomic profiles were analysed at early (3 h) and late (10 h) infection stages across the ileum and colon. Results: In total, 272 proteins were identified, with only 13 shared across all conditions, reflecting substantial niche-specific adaptations. Gene ontology enrichment analyses highlighted dominant roles in metabolic, cellular, and binding functions, while subcellular localisation prediction uncovered cytoplasmic moonlighting proteins with surface activity. Comparative analyses revealed dynamic changes in protein abundance. Conclusions: These findings indicate a coordinated shift from stress adaptation and virulence to nutrient acquisition and persistence and provide a comprehensive view of EHEC O157:H7 surface proteome dynamics during infection, highlighting key adaptive proteins that may serve as targets for future therapeutic and vaccine strategies.

Proteomes doi: 10.3390/proteomes13040051

Authors: Chang Liu Bojung Seo Qin Hui Peter W. F. Wilson Arshed A. Quyyumi Yan V. Sun

Background: Proteomic profiling may improve the understanding of obesity and cardiovascular risk prediction. This study explores the use of protein-predicted scores for body mass index (PPSBMI), body fat percentage (PPSBFP), and waist–hip ratio (PPSWHR) to estimate risk for major adverse cardiovascular events (MACEs). Methods: We used data from the UK Biobank with proteome profiling. PPSBMI, PPSBFP, and PPSWHR were derived using the LASSO algorithm. The association between these protein scores and incident MACEs was evaluated using a competing risk model. Results: Strong to moderate correlations were observed between protein-predicted obesity phenotypes and their measured counterparts (R2: BMI = 0.78, BFP = 0.85, WHR = 0.63). Each standard deviation increment of PPSBFP and PPSWHR, but not PPSBMI, was associated with greater risk of MACEs (hazard ratio [HR] 1.25, 95% CI 1.14–1.38, p < 0.0001; HR 1.15, 95% CI 1.06–1.24, p = 0.001, respectively). For predicting MACEs, compared with the PREVENT equation (C statistic 0.694), the models adjusted for only age, sex, current smoking, and protein scores showed comparable performance (C statistics 0.684–0.688). Conclusion: Protein-predicted scores of obesity showed strong independent associations and predictive performance for MACEs, suggesting they may capture additional biological risk beyond anthropometry. These scores may complement existing risk models by providing a biologically informed approach to assessing obesity-related cardiovascular risk and improving risk stratification.

Proteomes doi: 10.3390/proteomes13040050

Authors: Greeshma Sreejesh Surendranath P. Suman Gretchen G. Mafi Morgan M. Pfeiffer Ranjith Ramanathan

Background: This study aimed to investigate rapid oxidation in poultry and fish myoglobin compared to livestock myoglobin using protein structural differences and bioinformatics tools. Methods: Myoglobins from beef (Bos taurus), bison (Bos bison), sheep (Ovis aries), goat (Capra hircus), red deer (Cervus elaphus), pork (Sus scrofa), chicken (Gallus gallus), turkey (Meleagris gallopavo), yellowfin tuna (Thunnus albacares), and tilapia (Oreochromis niloticus) were analyzed to understand differences in structure and function that may influence oxidative behavior. Results: Fish and poultry had shorter or absent D-helix in their myoglobin structure than other species. Tilapia showed the largest heme cavity surface area, indicating significant internal void space, while yellowfin tuna had the largest heme cavity volume, which could affect ligand binding dynamics compared with poultry and other livestock species. However, the heme solvent-accessible area was greater in chicken and turkey than in fish and other livestock species. Tuna myoglobin contains a cysteine and fish myoglobins have fewer amino acids compared to other species. Limited knowledge is currently available on the effects of proteoform, especially post-translational modifications, on the oxidation of myoglobin from different species. Conclusions: The bioinformatics approach used in this study suggests that, in addition to physiological reasons, shorter D-helix, larger heme cavity in tilapia and yellowfin tuna, and greater solvent-accessible area in poultry contribute to increased oxidation in myoglobin from poultry and fish compared with myoglobin from livestock species.

Proteomes doi: 10.3390/proteomes13040049

Authors: Zohreh Arabpour Hanieh Niktinat Firouze Hatami Amal Yaghmour Zarife Jale Yucel Seyyedehfatemeh Ghalibafan Hamed Massoumi Zahra Bibak Bejandi Majid Salehi Elmira Jalilian Mahmood Ghassemi Victor H. Guaiquil Mark Rosenblatt Ali R. Djalilian

Corneal regeneration has gained growing interest in recent years, largely due to the limitations of conventional treatments and the persistent shortage of donor tissue. Among the emerging strategies, extracellular vehicles (EVs), especially those derived from mesenchymal stromal cells (MSCs), have shown great promise as a cell-free therapeutic approach. These nanoscale vesicles contribute to corneal healing by modulating inflammation, supporting epithelial and stromal regeneration, and promoting nerve repair. Their therapeutic potential is largely attributed to the diverse and bioactive proteomic cargo they carry, including growth factors, cytokines, and proteins involved in extracellular matrix remodeling. This review presents a comprehensive examination of the proteomic landscape of EVs in the context of corneal regenerative medicine. We explore the biological functions of EVs in corneal epithelial repair, stromal remodeling, and neurodegeneration. In addition, we discuss advanced proteomic profiling techniques such as mass spectrometry (MS) and liquid chromatography–mass spectrometry (LC-MS/MS), which have been used to identify and characterize the protein contents of EVs. This review also compares the proteomic profiles of EVs derived from various MSC sources, including adipose tissue, bone marrow, and umbilical cord, and considers how environmental cues, such as hypoxia and inflammation, influence their protein composition. By consolidating current findings, this article aims to provide valuable insights for advancing the next generation of cell-free therapies for corneal repair and regeneration.

Proteomes doi: 10.3390/proteomes13040048

Authors: Manoj Amrutkar Yuchuan Li Anette Vefferstad Finstadsveen Caroline S. Verbeke Ivar P. Gladhaug

Background: Gemcitabine (GEM) remains a cornerstone in the treatment of pancreatic cancer. Upon exposure to GEM, pancreatic cancer cells (PCCs) tend to adapt quickly to outcompete drug-induced cytotoxicity, thereby contributing to treatment failure. Thus, understanding GEM-induced molecular changes in PCCs is important. Methods: Three primary PCC lines (PCC-1, PCC-2, PCC-7) and Mia PaCa-2 cultured for 40 passages (p) in the absence (control) or presence of GEM (GemR) were assessed for phenotypic changes. Proteome profiles for all PCCs at p10, p20, p25, p30, p35, and p40 were obtained using mass spectrometry (MS). Protein expression was determined using immunoblotting. Differentially abundant proteins (DAPs) were evaluated for enrichment of functional and biological attributes and protein–protein interactions. Results: GEM sensitivity and growth were both reduced in GemR versus paired controls for all four PCC lines. MS mapped > 7000 proteins in each PCC line, and the abundance of 70–83% of these was found to be significantly altered when comparing all sample groups. Proteomic changes in GemR versus paired controls differed remarkably among the PCCs and were affected by passaging and treatment duration. DAPs at p40 were mostly related to metabolic pathways, including nucleotide metabolism and diverse cell growth processes. Several closely related DAPs and multiple hub proteins in each PCC line were identified. Conclusions: Overall, this study revealed cell-line-specific, heterogeneous changes in proteome profiles of PCCs following their long-term exposure to GEM, and these were likely affected by treatment duration, dosage, and passaging.

Proteomes doi: 10.3390/proteomes13040047

Authors: Anca-Narcisa Neagu Pathea S. Bruno Claudiu-Laurentiu Josan Natalie Waterman Hailey Morrissiey Victor T. Njoku Costel C. Darie

Cancer detection has made significant progress, moving from conventional methods to innovative, non-invasive or minimally invasive approaches aimed at improving early diagnosis, precision, and treatment outcomes. This review examines current and emerging diagnostic technologies, including liquid biopsy (LB), molecular biomarkers, and artificial intelligence (AI). LB analyzes biomarkers in bodily fluids, showing promise in detecting tumors at molecular levels, monitoring cancer progression, and predicting treatment responses. The assignment of specific proteoforms, often linked to tumor subtype, stage, and therapy resistance, adds another layer of diagnostic precision, offering valuable insights for personalized oncology. However, the clinical application of LB faces challenges related to sensitivity, specificity, tumor heterogeneity, and a lack of standardized protocols. Relatively high costs, complex result interpretation, and privacy concerns also hinder its widespread adoption in clinical practice. Despite these challenges, advancements in AI, nanotechnology, and multi-omics strategies offer opportunities to enhance cancer diagnostic accuracy. Future developments, including wearable biosensors and lab-on-a-chip technologies, could lead to personalized, real-time cancer detection with improved patient outcomes, potentially redefining cancer care and fostering a more proactive, patient-centered healthcare approach.

Proteomes doi: 10.3390/proteomes13030046

Authors: Ioannis Mavroudis Foivos Petridis Eleni Karantali Dimitrios Kazis

Neurogranin (NRGN), a synaptic protein essential for plasticity and memory function, is gaining recognition as a promising biomarker for mild traumatic brain injury (mTBI). This systematic review brings together findings from six studies that measured neurogranin levels in biofluids—including serum, cerebrospinal fluid (CSF), plasma, and exosomes—during both the acute and chronic phases following injury. In the acute phase of mTBI, elevated levels of neurogranin were consistently observed in serum samples, suggesting its potential as a diagnostic marker. These increases appear to reflect immediate synaptic disturbances caused by injury. In contrast, studies focusing on the chronic phase reported a decrease in exosomal neurogranin levels, pointing to ongoing synaptic dysfunction well after the initial trauma. This temporal shift in neurogranin expression highlights its dual utility—both as an early indicator of injury and as a longer-term marker of synaptic integrity. However, interpreting these findings is not straightforward. The studies varied considerably in terms of sample type, timing of measurements, and control for potential confounding factors such as physical activity. Such variability makes direct comparisons difficult and may influence the outcomes observed. Additionally, none of the studies included proteoform-specific analyses of neurogranin, an omission that limits our understanding of the molecular changes underlying mTBI-related synaptic alterations. Due to heterogeneity across study designs and outcome measures, a meta-analysis could not be performed. Instead, a narrative synthesis was conducted, revealing consistent patterns in neurogranin dynamics over time and underscoring the influence of biofluid selection on measured outcomes. Overall, the current evidence supports neurogranin’s potential as both a diagnostic and mechanistic biomarker for mTBI. Yet, to fully realize its clinical utility, future research must prioritize standardized protocols, the inclusion of proteoform profiling, and rigorous longitudinal validation studies.

Proteomes doi: 10.3390/proteomes13030045

Authors: Alexandra T. Star Melissa Hewitt Amanpreet Badhwar Wen Ding Tammy-Lynn Tremblay Jennifer J. Hill William G. Willmore Jagdeep K. Sandhu Arsalan S. Haqqani

Background: Extracellular vesicles (EVs) are an important source of blood biomarkers and are emerging as next-generation therapeutics. Demonstrating the purity of isolated EVs is essential for applications ranging from proteomics-based biomarker discovery to biomanufacturing. In this study, we systematically evaluated multiple EV isolation methods for plasma and developed a scoring method to identify the approach best suited for proteomics. Methods: Commonly used enrichment techniques, including size-exclusion chromatography (SEC) and precipitation-based methods, were compared against the starting plasma in terms of particle yield and size, proteomic overlap, depletion of abundant plasma proteins, and enrichment of EV markers and unique proteins. To enable rigorous purity assessment, we established a targeted parallel reaction monitoring (PRM) mass spectrometry assay that quantified key EV markers and contaminant proteins across preparations. Results: Among the methods tested, SEC showed the greatest enrichment of EV markers and unique proteins, with the lowest level of contaminants, resulting in the highest overall purity scores. SEC also allowed for the detection of EV-free proteins. Other methods, by contrast, performed sub-optimally and were less reliable for proteomics-driven biomarker discovery. Conclusions: SEC provides the most EV-enriched plasma isolates for proteomics information, with minimal contamination from plasma proteins. The PRM-based purity scoring offers an objective means of benchmarking EV preparations and may help standardize EV isolation quality for both biomarker discovery and therapeutic manufacturing.

Proteomes doi: 10.3390/proteomes13030044

Authors: Francisco Antonio Reyes-Soria Eliel Ruiz-May Enrique Castaño Miguel Ángel Herrera-Alamillo José Miguel Elizalde-Contreras Samuel David Gamboa-Tuz Lidia F. E. Huerta-Nuñez Jesús Alejandro Zamora-Briseño Luis Carlos Rodríguez-Zapata

Background: Mechanical damage to fruit during harvesting is nearly inevitable, with certain species, such as papaya, being particularly prone to spoilage. Postharvest handling can induce mechanical injuries that impair ripening and reduce shelf life, leading to significant economic losses. Although several studies have shed light on the molecular bases of mechanical damage, other aspects remain to be described (plant hormone inter-talk, physiological changes, and regulatory networks). Methods: In this study, we investigated proteomic changes in papaya fruit at two distinct ripening stages following mechanical damage. A total of 3230 proteins were identified, representing the most comprehensive proteomic analysis of papaya to date and the first assessment of proteins regulated by mechanical stress. Results: Proteins involved in ethylene biosynthesis were up-regulated on Day 2 but down-regulated on Day 12, with a similar trend observed for proteins in the abscisic acid synthesis pathway. Enzymes associated with photosynthesis, carbon fixation, primary metabolism, and carotenoid synthesis were down-regulated at both stages. In contrast, those related to plasmodesmata, calcium signaling, kinases, pathogenesis, cell wall remodeling, and proteases were up-regulated. Conclusions: These findings are thoroughly discussed, and a general model of the events triggered by mechanical impact in papaya is proposed. Our results provide a comprehensive framework for understanding papaya’s response to mechanical damage.

Proteomes doi: 10.3390/proteomes13030043

Authors: Endrei Marcantonio Amy M. Woron A. Christian Whelen Sladjana Prisic

Background: Patients with pulmonary tuberculosis (TB) typically produce sputa, which are used to identify the pathogen. Sputum also contains host proteins that may aid in diagnosis. We hypothesized that sputa from TB patients will have unique proteomes when compared to other lung diseases. Methods: Sputa were collected from 219 patients with suspected TB. Neutrophil-derived protein calprotectin (CP), which was used as a marker for lung damage, was quantified and compared between TB and non-TB groups. Three sputa with high or low CP from each group were selected and analyzed using label-free proteomics. Results: There was no difference in CP amounts between TB and non-TB groups. However, TB samples had other differentially abundant neutrophil-associated proteins. Compared to low CP, samples with high CP had much smaller number of proteins that could differentiate between TB and non-TB groups. Only two proteins, MUC5AC and MMP8, were more abundant in TB samples, regardless of CP levels. Conclusions: Our findings suggest that TB sputa may have unique proteomes that depend on CP levels, which should be further validated due to the small sample size. Therefore, controlled and more advanced TB may need a different set of biomarkers to reliably distinguish TB from other lung diseases.

Proteomes doi: 10.3390/proteomes13030042

Authors: Camila Chierici Marcantonio Maria Eduarda Scordamaia Lopes Lélio Fernando Ferreira Soares Cristiane Ribeiro Salmon Francisco Humberto Nociti Junior James Deschner Andressa Vilas Boas Nogueira Joni Augusto Cirelli

The periodontal ligament (PDL) is a dynamic connective tissue that absorbs and transmits mechanical forces, playing a critical role during orthodontic tooth movement (OTM). This study aimed to characterize the proteomic profile of rat PDLs subjected to OTM. Ten Holtzman rats were allocated into Control and OTM groups. After 15 days of force application, hemimaxillae were harvested, and PDL tissues from the first maxillary molars were isolated via laser capture microdissection. Protein extracts were analyzed using liquid chromatography–tandem mass spectrometry (LC-MS/MS), followed by quantitative and enrichment analyses. Immunohistochemistry was performed to validate selected proteins. The full proteomic datasets supporting these findings are available in the PRIDE repository under the identifiers PXD055817 and PXD033647. A total of 1121 proteins were identified; 101 were exclusive to the OTM group, 324 to the control, and 696 shared. Among the 335 proteins with differential abundance, 334 were downregulated and one (Prelp) was upregulated in the OTM group. Enrichment analysis revealed that differentially abundant proteins were associated with molecular functions such as protein binding, and cellular components including extracellular exosomes, focal adhesions, and the extracellular matrix. Immunohistochemical analysis confirmed the presence of Prelp, Rbm3, and Cirbp in PDL tissues. These findings demonstrate that OTM significantly alters the proteomic landscape of the PDL and identify key proteins potentially involved in periodontal remodeling.

Proteomes doi: 10.3390/proteomes13030041

Authors: Lidice Méndez-Pérez Yat Sen Wong Belén O. Ibáñez Ioanna Martinez-Hormaza Lleretny Rodríguez-Álvarez Fidel Ovidio Castro

Background: Endometrosis is a prevalent fibrotic condition in mares that impairs reproductive efficiency by inducing transdifferentiation of endometrial stromal cells into myofibroblasts, leading to excessive ECM deposition. Methods: To elucidate the molecular mechanisms underlying fibrosis resolution, this study employed comprehensive proteomic techniques, including LC-MS/MS and SILAC, to analyze the interaction between myofibroblasts and mesenchymal stem cells derived from the endometrium (ET-eMSCs) preconditioned with PGE2. An in vitro co-culture system was used, with samples collected at baseline and after 48 h. Results: Proteomic analysis identified significant alterations in proteins associated with ECM remodeling, immune regulation, and cellular stress response. Notably, proteins involved in collagen degradation, antioxidant defense, and growth factor signaling pathways were differentially abundant. Network analyses demonstrated robust interactions among these proteins, suggesting coordinated modulatory effects. The data indicate that PGE2-primed ET-eMSCs induce a shift in myofibroblast secretory profiles, promoting a reduction in ECM stiffness, tissue reorganization, and activation of resolution pathways. Data are available via ProteomeXchange with identifier PXD067551. Conclusions: These findings reinforce the therapeutic potential of mesenchymal stem cell-based interventions for fibrotic diseases of the endometrium, opening avenues for regenerative strategies to restore reproductive function in mares.

Proteomes doi: 10.3390/proteomes13030040

Authors: Malte Bayer Michael Snyder Simone König

Background: Bradykinin (BK) is an inflammatory mediator. The degradation of labeled synthetic BK in biofluids can be used to report on the activity of angiotensin-converting enzyme (ACE) and basic carboxypeptidases N and CBP2, for which the neuropeptide is a substrate. Clinical studies have shown significant changes in the serum activity of these enzymes in patients with inflammatory diseases. Methods: Here, we investigated variation in the cleavage of dabsylated synthetic BK (DBK) in serum and the formation of the major enzymatic fragments using a thin-layer chromatography-based neuropeptide reporter assay (NRA) in a large cohort of healthy volunteers from the international human Personal Omics Profiling consortium based at Stanford University. Results: Four major outcomes were reported. First, a set of NRA reference data for the healthy population was delivered, which is important for future investigations of patient sera. Second, it was shown that the measured serum degradation capacity for DBK was significantly higher in males than in females. There was no significant correlation of the NRA results with ethnicity, body mass index or overnight fasting. Third, a batch effect was noted among sampling sites (HUPO conferences). Thus, we used subcohorts rather than the entire collection for data mining. Fourth, as the low-cost and robust NRA is sensitive to enzyme activity, it provides such a necessary quick test to eliminate degraded and/or otherwise questionable samples. Conclusions: The results reiterate the critical importance of a high level of standardization in pre-analytical sample collection and processing—most notably, sample quality should be evaluated before conducting any large and expensive omics analyses.

Proteomes doi: 10.3390/proteomes13030039

Authors: Mohamed Saad Rakab Monica C. Asada Imaduddin Mirza Mohammed H. Morsy Amro Mostafa Francesco M. Bianco Mohamed M. Ali Chandra Hassan Mario A. Masrur Brian T. Layden Abeer M. Mahmoud

Background: Adipose-derived extracellular vesicles (adiposomes) are emerging as key mediators of inter-organ communication, yet their molecular composition and role in obesity-related pathophysiology remain underexplored. This study integrates clinical phenotyping with proteomic analysis of visceral adipose-derived adiposomes to identify obesity-linked molecular disruptions. Methods: Seventy-five obese and forty-seven lean adults were extensively profiled for metabolic, inflammatory, hepatic, and vascular parameters. Adiposomes isolated from visceral fat underwent mass spectrometry-based proteomic analysis, followed by differential abundance, pathway enrichment, regulatory network modeling, and clinical association testing. Results: Obese individuals exhibited widespread cardiometabolic dysfunction. Proteomics revealed 64 adiposomal proteins with differential abundance. Upregulated proteins (e.g., CRP, C9, APOC1) correlated with visceral adiposity, systemic inflammation, and endothelial dysfunction. In contrast, downregulated proteins (e.g., ADIPOQ, APOD, TTR, FGB, FGG) were associated with enhanced nitric oxide bioavailability and vascular protection, suggesting loss of homeostatic signaling. Network analyses identified TNF and IL1 as key upstream regulators driving inflammatory and oxidative stress pathways. Decision tree and random forest models accurately classified obesity, hypertension, diabetes, dyslipidemia, and hepatic steatosis (AUC = 0.908–0.994), identifying predictive protein signatures related to complement activation, inflammation, and lipid transport. Conclusion: Obesity alters adiposome proteomic cargo, reflecting and potentially mediating systemic inflammation, metabolic dysregulation, and vascular impairment.

Proteomes doi: 10.3390/proteomes13030038

Authors: Naoyuki Toyota Ryo Konno Shuhei Iwata Shin Fujita Yoshio Kodera Rei Noguchi Tadashi Kondo Yusuke Kawashima Yuki Yoshimatsu

Background: Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, with a multifactorial etiology involving genetic and environmental factors. Advanced proteomics offers valuable insights into the molecular mechanisms of cancer, identifying proteins that function as mediators in tumor biology. Methods: In this study, we used mass spectrometry-based data-independent acquisition (DIA) to analyze the proteomic landscape of CRC. We compared protein abundance in normal and tumor tissues from 16 patients with CRC to identify cancer-associated proteins and examine their roles in disease progression. Results: The analysis identified 10,329 proteins, including 531 cancer-associated proteins from the Catalogue Of Somatic Mutations In Cancer (COSMIC) database, and 48 proteins specifically linked to CRC. Notably, clusters of proteins showed consistent increases or decreases in abundance across disease stages, suggesting their roles in tumorigenesis and progression. Conclusions: Our findings suggest that proteome abundance trends may contribute to the identification of biomarker candidates and therapeutic targets in colorectal cancer. However, given the limited sample size and lack of subtype stratification, further studies using larger, statistically powered cohorts are warranted to establish clinical relevance. These proteins may provide insights into drug resistance and tumor heterogeneity. Limitations of the study include the inability to detect low-abundance proteins and reliance on protein abundance rather than functional activity. Future complementary approaches, such as affinity proteomics, are suggested to address these limitations.

Proteomes doi: 10.3390/proteomes13030037

Authors: Nashira H. Ridgeway Kyle K. Biggar

Post-translational modifications (PTMs) govern a multitude of protein functions within the cell, surpassing the basic function(s) encoded directly within the amino acid sequence. Despite the historical discovery of PTMs dating back over a century, recent technological advancements have facilitated the rapid expansion of the known PTM landscape. However, the elucidation of enzyme–substrate relationships responsible for PTMs, particularly for those less studied, remains a challenging endeavor. This review provides an extensive overview of methods employed in the discovery of enzyme-specific substrates for PTM catalysis. Beginning with traditional experimental approaches rooted in chemistry, biochemistry and cell biology, this review progresses to recently developed computational strategies tailored for identifying enzyme–substrate interactions. The analysis reflects on the remarkable progress achieved in PTM research to date, underscoring the increasing role of computational and high-throughput techniques in expediting enzyme–substrate discovery. Furthermore, it highlights the potential of artificial intelligence to revolutionize PTM research and emphasizes the importance of unbiased high-throughput analysis in advancing our understanding of PTM networks. Ultimately, the review advocates for the integration of sophisticated computational strategies with experimental techniques to unravel the complex enzyme–substrate networks governing PTM-mediated cellular processes.

Proteomes doi: 10.3390/proteomes13030036

Authors: Faris Alanazi Ammar Sharif Melissa Kidd Emma-Jayne Keevill Vanesa Biolatti Richard D. Unwin Peter Hoskin Ananya Choudhury Tim A. D. Smith Conrado G. Quiles

Background Plasma membrane proteins (PMPs) play key roles in cell signalling, adhesion, and trafficking, and are attractive therapeutic targets in cancer due to their surface accessibility. However, their typically low abundance limits detection by conventional proteomic approaches. Methods: To improve PMP detection, we employed a surface proteomics workflow combining cell surface biotinylation and affinity purification prior to LC-MS/MS analysis in cervical (SiHa) and bladder (UMUC3) cancer cell lines cultured under normoxic (21% O2) or hypoxic (0.1% O2) conditions. Results: In SiHa cells, 43 hypoxia-upregulated proteins were identified exclusively in the biotin-enriched fraction, including ITGB2, ITGA7, AXL, MET, JAG2, and CAV1/CAV2. In UMUC3 cells, 32 unique upregulated PMPs were detected, including CD55, ADGRB1, SLC9A1, NECTIN3, and ACTG1. These proteins were not observed in corresponding whole-cell lysates and are associated with extracellular matrix remodelling, immune modulation, and ion transport. Biotinylation enhanced the detection of membrane-associated pathways such as ECM organisation, integrin signalling, and PI3K–Akt activation. Protein–protein interaction analysis revealed links between membrane receptors and intracellular stress regulators, including mitochondrial proteins. Conclusions: These findings demonstrate that surface biotinylation improves the sensitivity and selectivity of plasma membrane proteomics under hypoxia, revealing hypoxia-responsive proteins and pathways not captured by standard whole-cell analysis.

Proteomes doi: 10.3390/proteomes13030035

Authors: Rúben Araújo Cristiana P. Von Rekowski Tiago A. H. Fonseca Cecília R. C. Calado Luís Ramalhete Luís Bento

Background: Accurate and timely prediction of mortality in intensive care unit (ICU) patients, particularly those with COVID-19, remains clinically challenging due to complex immune responses. Proteomic cytokine profiling holds promise for refining mortality risk assessment. Methods: Serum samples from 89 ICU patients (55 discharged, 34 deceased) were analyzed using a multiplex 21-cytokine panel. Samples were stratified into three groups based on time from collection to outcome: ≤48 h (Group 1: Early), >48 h to ≤7 days (Group 2: Intermediate), and >7 days to ≤14 days (Group 3: Late). Cytokine levels, simple cytokine ratios, and previously unexplored complex ratios between pro- and anti-inflammatory cytokines were evaluated. Machine learning-based feature selection identified the most predictive ratios, with performance evaluated by area under the curve (AUC), sensitivity, and specificity. Results: Complex cytokine ratios demonstrated superior predictive accuracy compared to traditional severity markers (APACHE II, SAPS II, SOFA), individual cytokines, and simple ratios, effectively distinguishing discharged from deceased patients across all groups (AUC: 0.918–1.000; sensitivity: 0.826–1.000; specificity: 0.775–0.900). Conclusions: Multiplex cytokine profiling enhanced by computationally derived complex ratios may offer robust predictive capabilities for ICU mortality risk stratification, serving as a valuable tool for personalized prognosis in critical care.

Proteomes doi: 10.3390/proteomes13030034

Authors: Domenico Milardi Edoardo Vergani Francesca Mancini Fiorella Di Nicuolo Emanuela Teveroni Emanuele Pierpaolo Vodola Alessandro Oliva Giuseppe Grande Alessandro Cina Roberto Iezzi Michela Cicchinelli Federica Iavarone Silvia Baroni Alberto Ferlin Andrea Urbani Alfredo Pontecorvi

Background: Varicocele is a common condition involving the dilation of veins in the scrotum, often linked to male infertility and testicular dysfunction. This study aimed to elucidate the molecular effects of successful varicocele treatment on sperm proteomes following percutaneous sclero-embolization. Methods: High-resolution tandem mass spectrometry was performed for proteomic profiling of pooled sperm lysates from five patients exhibiting improved semen parameters before and after (3 and 6 months) varicocele sclero-embolization. Data were validated by Western blot analysis. Results: Seven proteins were found exclusively in varicocele patients before surgery—such as stathmin, IFT20, selenide, and ADAM21—linked to inflammation and oxidative stress. After sclero-embolization, 55 new proteins emerged, including antioxidant enzymes like selenoprotein P and GPX3. Thioredoxin (TXN) and peroxiredoxin (PRDX3) were upregulated, indicating restoration of key antioxidant pathways. Additionally, the downregulation of some histones and the autophagy-related protein ATG9A suggests a shift toward an improved chromatin organization and a healthier cellular environment post-treatment. Conclusions: Varicocele treatment that improves sperm quality and fertility parameters leads to significant proteome modulation. These changes include reduced oxidative stress and broadly restored sperm maturation. Despite the limited patient cohort analyzed, these preliminary findings provide valuable insights into how varicocele treatment might enhance male fertility and suggest potential biomarkers for improved male infertility treatment strategies.

Proteomes doi: 10.3390/proteomes13030033

Authors: Xin Wen Gerelchimeg Bou Qianqian He Qi Liu Minna Yi Hong Ren

Background: The reproductive ability of equine species is a critical component of equine breeding programs, with sperm quality serving as a primary determinant of reproductive success. In this study, we perform an integrative analysis of proteomics and metabolomics in seminal plasma to identify proteins and metabolites associated with sperm quality and reproductive ability in equine species. Methods: We utilized the CEROS instrument to assess the morphology and motility of sperm samples from three horses and three donkeys. Additionally, we statistically analyzed the mating frequency and pregnancy rates in both species. Meanwhile, the 4D-DIA high-throughput proteomic and metabolomic profiling of seminal plasma samples from horses and donkeys revealed a complex landscape of proteins and metabolites. Results: Our findings reveal a certain degree of correlation between seminal plasma proteins and metabolites and sperm quality, as well as overall fertility. Notably, we found that the proteins B3GAT3, XYLT2, CHST14, HS2ST1, GLCE, and HSPG2 in the glycosaminoglycan biosynthesis signaling pathway; the metabolites D-glucose, 4-phosphopantetheine, and 4-hydroxyphenylpyruvic acid in the tyrosine metabolism, starch, and source metabolisms; and pantothenate CoA biosynthesis metabolism present unique characteristics in the seminal plasma of equine species. Conclusions: This comprehensive approach provides new insights into the molecular mechanisms underlying sperm quality and has identified potential proteins and metabolites that could be used to indicate reproduction ability. The findings from this study could be instrumental in developing novel strategies to enhance equine breeding practices and reproductive management. Future research will focus on exploring their potential for clinical application in the equine industry.

Proteomes doi: 10.3390/proteomes13030032

Authors: Afshan Masood Hicham Benabdelkamel Assim A. Alfadda Abdurhman S. Alarfaj Amina Fallata Salini Scaria Joy Maha Al Mogren Anas M. Abdel Rahman Mohamed Siaj

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disorder that predominantly affects synovial joints, leading to inflammation, pain, and progressive joint damage. Despite therapeutic advancements, the molecular basis of established RA remains poorly defined. Methods: In this study, we conducted an untargeted plasma proteomic analysis using two-dimensional differential gel electrophoresis (2D-DIGE) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in samples from RA patients and healthy controls in the discovery phase. Results: Significantly (ANOVA, p ≤ 0.05, fold change > 1.5) differentially abundant proteins (DAPs) were identified. Notably, upregulated proteins included mitochondrial dicarboxylate carrier, hemopexin, and 28S ribosomal protein S18c, while CCDC124, osteocalcin, apolipoproteins A-I and A-IV, and haptoglobin were downregulated. Receiver operating characteristic (ROC) analysis identified CCDC124, osteocalcin, and metallothionein-2 with high diagnostic potential (AUC = 0.98). Proteins with the highest selected frequency were quantitatively verified by multiple reaction monitoring (MRM) analysis in the validation cohort. Bioinformatic analysis using Ingenuity Pathway Analysis (IPA) revealed the underlying molecular pathways and key interaction networks involved STAT1, TNF, and CD40. These central nodes were associated with immune regulation, cell-to-cell signaling, and hematological system development. Conclusions: Our combined proteomic and bioinformatic approaches underscore the involvement of dysregulated immune pathways in RA pathogenesis and highlight potential diagnostic biomarkers. The utility of these markers needs to be evaluated in further studies and in a larger cohort of patients.

Proteomes doi: 10.3390/proteomes13030031

Authors: Abdulbaki Alfa-Ibrahim Adio Samuel Odo Uko Jiddah Muhammad Lawal Ibrahim Malami Nafiu Lawal Amina Jega Yusuf Jega Bilyaminu Abubakar Muhammad Bashir Bello Kasimu Ghandi Ibrahim Murtala Bello Abubakar Abdussamad Muhammad Abdussamad Mujtaba Sulaiman Abubakar Mustapha Umar Imam

Background: Snake envenomation is a major public health issue in Nigeria, primarily due to bites from Echis ocellatus, Naja nigricollis, and Bitis arietans. Understanding their venom composition is essential for effective antivenom development. This study characterizes and compares the venom proteomes of these snakes using iTRAQ-based proteomics, focusing on key toxin families and their relative abundances. Methods: Venom samples were ethically collected from adult snakes, pooled by species, lyophilized, and stored for proteomic analysis. Proteins were extracted, digested with trypsin, and labeled with iTRAQ. Peptides were analyzed via mass spectrometry, and data were processed using Mascot and IQuant for protein identification and quantification. Results: E. ocellatus and B. arietans venoms had similar profiles, rich in C-type lectins, serine proteases, and phospholipase A2s. These comprised 17%, 11%, and 5% in E. ocellatus and 47%, 10%, and 7% in B. arietans, with metalloproteinases dominating both (53% and 47%). In N. nigricollis, three-finger toxins (9%) were most abundant, followed by metalloproteinases (3%). All species shared four core protein families, with N. nigricollis also containing four uncharacterized proteins. Conclusions: This study highlights venom compositional differences, advancing snake venom biology and informing targeted antivenom development.

Proteomes doi: 10.3390/proteomes13030030

Authors: Tania Iranpour Mapenzi Mirimba Chloe Shenouda Adam Lynch Alan A. Doucette

Background: Membrane proteins are preferentially solubilized with sodium dodecyl sulfate (SDS), which necessitates a purification protocol to deplete the surfactant prior to mass spectrometry analysis. However, maintaining solubility of intact membrane proteins is challenged in an SDS-free environment. SDS precipitation with potassium salts (KCl) offers a potentially viable workflow to deplete SDS and permit proteoform analysis. The purpose of this study is to devise a robust detergent-based protocol applicable for processing and analysis of intact membrane-associated proteoforms. Methods: The precipitation conditions impacting SDS removal from spinach chloroplasts and liver membrane proteome preparations were evaluated, capitalizing on optimization of pH (highly basic), addition of MS-compatible solubilizing additives (urea) and adjustment of the KCl to SDS ratio to maximize recovery and purity. Results: Characterization of the SDS-solubilized, KCl-precipitated spinach membrane preparation revealed multiple charge envelope MS spectra displaying high signal to noise, free of SDS adducts. Precipitation at pH 12 or with urea improved protein recovery and purity. Bottom-up analysis identified 1826 distinct liver protein groups from four independent SDS precipitation conditions. While precipitation at pH 8 without urea revealed a greater number of protein identifications by mass spectrometry, precipitation under highly basic conditions (pH 12) with urea provided higher membrane protein recovery and achieved the greatest number (732 of 1056) and largest percentage (69.3%) of membrane proteins identified in the SDS removal workflow. Conclusion: This workflow provides new opportunities for MS-based proteoform analysis by capitalizing on the benefits of SDS for protein extraction while maintaining high solubility and purity of intact proteins though KCl precipitation of the surfactant.

Proteomes doi: 10.3390/proteomes13030029

Authors: Guoting Qin Cecilia Chao Shara Duong Jennyffer Smith Hong Lin Wendy W. Harrison Chengzhi Cai

Background: Type 2 diabetes mellitus (T2DM) is an epidemic chronic disease that affects millions of people worldwide. This study aims to explore the impact of T2DM on the tear proteome, specifically investigating whether alterations occur before the development of diabetic retinopathy. Methods: Flush tear samples were collected from healthy subjects and subjects with preDM and T2DM. Tear proteins were processed and analyzed by mass spectrometry-based shotgun proteomics using a data-independent acquisition parallel acquisition serial fragmentation (diaPASEF) approach. Machine learning algorithms, including random forest, lasso regression, and support vector machine, and statistical tools were used to identify potential biomarkers. Results: Machine learning models identified 17 proteins with high importance in classification. Among these, five proteins (cystatin-S, S100-A11, submaxillary gland androgen-regulated protein 3B, immunoglobulin lambda variable 3–25, and lambda constant 3) exhibited differential abundance across these three groups. No correlations were identified between proteins and clinical assessments of the ocular surface. Notably, the 17 important proteins showed superior prediction accuracy in distinguishing all three groups (healthy, preDM, and T2DM) compared to the five proteins that were statistically significant. Conclusions: Alterations in the tear proteome profile were observed in adults with preDM and T2DM before the clinical diagnosis of ocular abnormality, including retinopathy.

Proteomes doi: 10.3390/proteomes13030028

Authors: Valentina Rossio Joao A. Paulo

Background: Alterations in protein abundance profiles in yeast deletion strains are frequently utilized to gain insights into cellular functions and regulatory networks, most of which are conserved in higher eukaryotes. Methods: This study investigates the impact of protein extraction methodologies on the whole proteome analysis of S. cerevisiae, comparing detergent-based lysis versus mechanical lysis with silica beads. We evaluated the proteomic profiles of wild-type and two yeast deletion strains, siz1Δ and nfi1Δ (siz2Δ), which are SUMO E3 ligases. Combining isobaric TMTpro-labeling with mass spectrometry using real-time search MS3, we profiled over 4700 proteins, covering approximately 80% of the yeast proteome. Results: Hierarchical clustering and principal component analyses revealed that the choice of protein extraction method significantly influenced the proteomic data, overshadowing the genetic variances among these strains. Notably, the detergent-based lysis showed superior performance in extracting proteins compared to mechanical lysis. Despite minimal proteomic alterations among strains, we observed consistent changes regardless of the lysis strategy in proteins such as Ino1, Rep1, Rep2, Snz1, and Fdh1 in both SUMO E3 ligase deletion strains, implying potential redundant mechanisms of control for these proteins. Conclusion: These findings underscore the importance of method selection at each step of sample preparation in proteomic studies and enhance our comprehension of cellular adaptations to genetic perturbations.

Proteomes doi: 10.3390/proteomes13030027

Authors: Elena Zorina Natalia Ronzhina Olga Legina Nikolai Klopov Victor Zgoda Stanislav Naryzhny

Background: Human proteins exist in numerous modifications—proteoforms—which are promising targets for biomarker studies. In this study, we aimed to generate comparative proteomics data, including proteoform patterns, from hepatocellular carcinoma (HCC) and nonmalignant liver tissues. Methods: To investigate protein profiles and proteoform patterns, we employed a panoramic, integrative top-down proteomics approach: two-dimensional gel electrophoresis (2DE) coupled with liquid chromatography–electrospray ionization–tandem mass spectrometry (LC-ESI-MS/MS). Results: We visualized over 2500 proteoform patterns per sample type, enabling the identification of distinct protein signatures and common patterns differentiating nonmalignant and malignant liver cells. Among these, 1270 protein patterns were uniformly observed across all samples. Additionally, 38 proteins—including pyruvate kinase PKM (KPYM), annexin A2 (ANXA2), and others—exhibited pronounced differences in proteoform patterns between nonmalignant and malignant tissues. Conclusions: Most proteoform patterns of the same protein were highly similar, with the dominant peak corresponding to theoretical (unmodified) protein parameters. However, certain proteins displayed altered proteoform patterns and additional proteoforms in cancer compared to controls. These proteins were prioritized for further characterization.

Proteomes doi: 10.3390/proteomes13030026

Authors: José Miguel Quintero-Ferrer Lucas Silva de Oliveira Paula Marian Vieira Goulart Thiago Albuquerque Souza Campos Coralie Martin Philippe Grellier Izabela Marques Dourado Bastos Sébastien Charneau

Peroxidases are essential enzymes that catalyze redox reactions, with wide-ranging biological implications. Among these, an enhanced ascorbate peroxidase (APEX) has emerged as a valuable tool for studying intricate intracellular events with spatiotemporal precision, particularly in protein–protein, protein–RNA, and protein–DNA interaction networks in living cells. This review discusses APEX’s structural and functional attributes, its evolution through genetic engineering, and its transformative applications in high-resolution mapping used for proteomic and transcriptomic studies. Furthermore, it highlights recent advancements in substrate innovation and addresses current challenges and future directions in leveraging APEX for cutting-edge biological research.

Proteomes doi: 10.3390/proteomes13020025

Authors: Davide Perico Pierluigi Mauri

Radiotherapy resistance represents a critical aspect of cancer treatment, and molecular characterization is needed to explore the pathways and mechanisms involved. DNA repair, hypoxia, metabolic reprogramming, apoptosis, tumor microenvironment modulation, and activation of cancer stem cells are the primary mechanisms that regulate radioresistance, and understanding their complex interactions is essential for planning the correct therapeutic strategy. Proteomics has emerged as a key approach in precision medicine to study tumor heterogeneity and treatment response in cancer patients. The integration of mass spectrometry-based techniques with bioinformatics has enabled high-throughput, quantitative analyses to identify biomarkers, pathways, and new potential therapeutic targets. This review highlights recent advances in proteomic technologies and their application in identifying biomarkers predictive of radiosensitivity and radioresistance in different tumors, including head and neck, breast, lung, and prostate cancers. Sample variability, data interpretation, and the translation of findings into clinical practice remain challenging elements of proteomics. However, technological advancements support its application in a wide range of topics, allowing a comprehensive approach to radiobiology, which helps overcome radiation resistance. Ultimately, incorporating proteomics into the radiotherapy workflow offers significant potential for enhancing treatment efficacy, minimizing toxicity, and guiding precision oncology strategies.

Proteomes doi: 10.3390/proteomes13020024

Authors: Sunil S. Adav

Protein deamidation, a nonenzymatic post-translational modification that converts asparagine and glutamine residues into their acidic forms, such as aspartic acid, iso-aspartic acid, or glutamic acid, has emerged as a pivotal process affecting protein stability and function. Once considered a minor biochemical occurrence, deamidation is now recognized for its significant role in aging, age-associated diseases, disease progression, cancer, and therapeutic efficacy. This review explores the recent advances in understanding protein deamidation, its impact on cellular homeostasis, protein misfolding, and age-related and chronic diseases including neurodegeneration and cancer. The study also highlights the challenges posed by deamidation in biopharmaceuticals, where it compromises therapeutic stability and efficacy. Advancements in state-of-the-art analytical techniques and computational approaches for identifying deamidation sites and predicting deamidation-prone regions are discussed, along with deeper insights into how deamidation affects protein structure and function. Based on the current insights, this review underscores the dual role of deamidation as both a natural regulatory process and a contributor to pathological states, providing a roadmap for future research in aging biology, disease mechanisms, and therapeutics.

Proteomes doi: 10.3390/proteomes13020023

Authors: Jordana Sheahan Iris Wang Peter Galettis David I. Watson Virendra Joshi Michelle M. Hill Richard Lipscombe Kirsten Peters Scott Bringans

Background: Esophageal adenocarcinoma (EAC) diagnosis involves invasive and expensive endoscopy with biopsy, but rising EAC incidence has not been reduced by increased surveillance. This study aimed to develop and clinically validate a novel glycoprotein biomarker blood test for EAC, named PromarkerEso. Methods: Serum glycoprotein relative concentrations were measured using a lectin-based magnetic bead array pulldown method, with multiple reaction monitoring mass spectrometry in 259 samples across three independent cohorts. A panel of glycoproteins: alpha-1-antitrypsin, alpha-1-antichymotrypsin, complement C9 and plasma kallikrein, were combined with clinical factors (age, sex and BMI) in an algorithm to categorize the samples by the risk of EAC. Results: PromarkerEso demonstrated a strong discrimination of EAC from the controls (area under the curve (AUC) of 0.91 in the development cohort and 0.82 and 0.98 in the validation cohorts). The test exhibited a high sensitivity for EAC (98% in the development cohort, and 99.9% and 91% in the validation cohorts) and a high specificity (88% in the development cohort, and 86% and 99% in the validation cohorts). PromarkerEso identified individuals with and without EAC (96% and 95% positive and negative predictive values). Conclusions: This less invasive approach for EAC detection with the novel combination of these glycoprotein biomarkers and clinical factors coalesces in a potential step toward improved diagnosis.

Proteomes doi: 10.3390/proteomes13020022

Authors: Rui Yan Heng-Wee Tan Na-Li Cai Le Yu Yan Gao Yan-Ming Xu Andy T. Y. Lau

Background: Previously, we found that an uncharacterized protein CXorf38 is significantly downregulated in human ZIP8-knockout (KO) cells. Given that ZIP8 regulates essential micronutrients linked to diseases including cancer, this study aims to characterize CXorf38 and evaluate its role in lung adenocarcinoma. Methods: iTRAQ-based proteomics was previously used to identify the abundance of proteins in ZIP8-KO cells. Cell proliferation and colony formation assays were used to examine the function of CXorf38 by overexpressing the gene in lung adenocarcinoma cell lines. Kaplan–Meier survival analysis was used to assess the prognostic value of CXorf38, while TCGA clinical database analysis was used to evaluate its expression in lung cancer tissues, particularly in smokers. Bioinformatics analyses (GO, KEGG, PPI, and ICI) were performed on CXorf38-coexpressed genes derived from patients with lung cancer. Results: CXorf38 overexpression suppressed lung cancer cell proliferation and colony formation, suggesting a tumor-suppressive role. Higher CXorf38 expression correlated with improved survival in patients with lung adenocarcinoma, but not in lung squamous cell carcinoma. Clinical data showed CXorf38 downregulation with lung cancer tissues of smokers, indicating a potential role in smoking-induced cancer progression and treatment. Functional analysis using bioinformatics linked CXorf38 to immune response regulation, suggesting involvement in the tumor immune microenvironment. Conclusions: Our study reveals for the first time that CXorf38 is a potential tumor suppressor, prognostic biomarker, and/or tumor immune regulator in lung adenocarcinoma—further research is warranted to explore its role in tumor immunity and its therapeutic potential.

Proteomes doi: 10.3390/proteomes13020021

Authors: Anastasia Boura-Theodorou Konstantina Psatha Stefania Maniatsi Areti Kourti Georgia Kaiafa Michalis Aivaliotis Kali Makedou

Myelodysplastic syndromes (MDS) belong to a category of malignant stem-cell and myeloid disorders that deteriorate the function of the hematopoietic system exacerbated by the omnipresent anemia that characterizes myelodysplasia. The pathogenesis of MDS is driven by cytogenetic abnormalities along with the excessive production of pro-inflammatory cytokines and disruptions in inflammatory signaling pathway, particularly through the influence of carbonylated proteins, which are linked to MDS progression. An additional and major contributor to the pathogenesis of MDS is oxidative stress marked by uncontrolled levels of reactive oxygen species (ROS), which have been suggested as potential biomarkers for assessing disease severity and stratifying MDS cases throughout a variety of methods. Excessive and non-accumulative levels of free iron can also lead to iron overload (IOL)—related promotion of a high oxidative state, whether we refer to treatment-related IOL or natural IOL mechanisms. Proteomic analysis has emerged as a powerful tool for profiling protein samples, and, consequently, understanding the molecular changes underlying MDS. In this review, we evaluated studies and their methodologies aiming in investigating distinctive proteomics signatures associated with MDS pathogenesis, focusing on the role of oxidative stress at the protein level.

Proteomes doi: 10.3390/proteomes13020020

Authors: Mathilde Resell Elisabeth Pimpisa Graarud Hanne-Line Rabben Animesh Sharma Lars Hagen Linh Hoang Nan T. Skogaker Anne Aarvik Magnus K. Svensson Manoj Amrutkar Caroline S. Verbeke Surinder K. Batra Gunnar Qvigstad Timothy C. Wang Anil Rustgi Duan Chen Chun-Mei Zhao

Background: Knowledge discovery in databases (KDD) can contribute to translational research, also known as translational medicine, by bridging the gap between in vitro and in vivo studies, and clinical applications. Here, we propose a ‘systems modeling’ workflow for KDD. Methods: This framework includes the data collection of a composition model (various research models), processing model (proteomics) and analytical model (bioinformatics, artificial intelligence/machine leaning and pattern evaluation), knowledge presentation, and feedback loops for hypothesis generation and validation. We applied this workflow to study pancreatic ductal adenocarcinoma (PDAC). Results: We identified the common proteins between human PDAC and various research models in vitro (cells, spheroids and organoids) and in vivo (mouse mice). Accordingly, we hypothesized potential translational targets on hub proteins and the related signaling pathways, PDAC-specific proteins and signature pathways, and high topological proteins. Conclusions: This systems modeling workflow can be a valuable method for KDD, facilitating knowledge discovery in translational targets in general, and in particular to PADA in this case.

Proteomes doi: 10.3390/proteomes13020019

Authors: Siyu Zhu Feng Liu Hao Wang Yongqian Zhang

Background: Deinococcus radiodurans, renowned for its exceptional resistance to radiation, provides a robust model for elucidating cellular stress responses and DNA repair mechanisms. Previous studies have established PprI as a key regulator contributing to radiation resistance through its involvement in DNA damage repair pathways, oxidative stress response, and metabolic regulation. Methods: Building upon these foundations, our study employs label-free quantitative (LFQ) proteomics coupled with high-resolution mass spectrometry to systematically map pprI deletion protein networks by comparing the global proteomic profiles of pprI knockout and wild-type D. radiodurans strains. Results: Under stringent screening criteria, we identified 719 significantly higher and 281 significantly lower abundant proteins in the knockout strain compared to wild-type strains. Functional analysis revealed that PprI deficiency disrupts homologous recombination (HR) repair, activates nucleotide excision repair (NER) and base excision repair (BER) as a compensatory mechanism, and impairs Mn/Fe homeostasis and carotenoid biosynthesis, leading to increased oxidative stress. Furthermore, PprI deficiency induces significant metabolic reprogramming, including impaired purine synthesis, compromised cell wall integrity, etc. Conclusions: These proteomic findings delineate the extensive regulatory network influenced by PprI, revealing coordinated perturbations across multiple stress response systems when PprI is absent.

Proteomes doi: 10.3390/proteomes13020018

Authors: Anu Jain Rafaela Muniz de Queiroz Jayanta K. Chakrabarty Karl A. T. Makepeace Carol Prives Lewis M. Brown

Background: We utilized data-independent acquisition (DIA) to study the poorly understood biology of Mdm2 and MdmX in a p53-null context. Mdm2 and MdmX form an E3-ligase complex that has as its most well-studied function the negative regulation of the tumor suppressor p53; however, it is also known to interact with many other proteins in a p53-independent manner. Methods: In this work, small-molecule and siRNA-based technology were used to modify Mdm2/MdmX activity in a human non-small-cell lung carcinoma cell line lacking p53 expression. Study of the proteome of these cells helped identify biological processes where Mdm2 and MdmX may play roles in a p53-independent manner. Proteins from H1299 cells, treated with the drug MEL23 or siRNA against Mdm2 or MdmX, were analyzed. Results: Protein ontology and function were analyzed, revealing which pathways are affected by modulation of the proteins that form the complex. Insights into how those functions are dependent on the activity of the complex also gained via comparisons among the three groups of samples. Conclusions: We selected a potential target from the DIA analysis and validated it by immunoblotting and qPCR, and this allows us to demonstrate a new interaction partner of the Mdm2-MdmX complex in human cells.

Proteomes doi: 10.3390/proteomes13020017

Authors: Xue Wang Fei Wang Archana S. Iyer Heather Knight Lori J. Duggan Yingli Yang Liang Jin Baoliang Cui Yupeng He Jan Schejbal Lucy A. Phillips Bohdan P. Harvey Sílvia Sisó Yu Tian

Understanding the heterogeneity of Rheumatoid Arthritis (RA) and identifying therapeutic targets remain challenging using traditional bulk transcriptomics alone, as it lacks the spatial and protein-level resolution needed to fully capture disease and tissue complexities. In this study, we applied Laser Capture Microdissection (LCM) coupled with mass spectrometry-based proteomics to analyze histopathological niches of the RA synovium, enabling the identification of protein expression profiles of the diseased synovial lining and sublining microenvironments compared to their healthy counterparts. In this respect, key pathogenetic RA proteins like membrane proteins (TYROBP, AOC3, SLC16A3, TCIRG1, and NCEH1), and extracellular matrix (ECM) proteins (PLOD2, OGN, and LUM) showed different expression patterns in diseased synovium compartments. To enhance our understanding of cellular dynamics within the dissected regions, we further integrated the proteomic dataset with single-cell RNA sequencing (scRNA-seq), and deduced cell type enrichment, including T cells, fibroblasts, NK cells, myeloid cells, B cells, and synovial endothelial cells. By combining high-resolution spatial proteomics and transcriptomic analyses, we provide novel insights into the molecular mechanisms driving RA, and highlight potential protein targets for therapeutic intervention. This integrative approach offers a more comprehensive view of RA synovial pathology, and mitigates the limitations of traditional bulk transcriptomics in target discovery.

Proteomes doi: 10.3390/proteomes13020016

Authors: Shivam Shukla Sean S. Lastorka Vladimir N. Uversky

Intrinsic disorder refers to protein regions that lack a fixed three−dimensional structure under physiological conditions, enabling conformational plasticity. This flexibility allows for diverse functions, including transient interactions, signaling, and phase separation via disorder-to-order transitions upon binding. Our study focused on investigating the role of intrinsic disorder and liquid−liquid phase separation (LLPS) in the human acrosome, a sperm-specific organelle essential for fertilization. Using computational prediction models, network analysis, Structural Classification of Proteins (SCOP) functional assessments, and Gene Ontology, we analyzed 250 proteins within the acrosomal proteome. Our bioinformatic analysis yielded 97 proteins with high levels (>30%) of structural disorder. Further analysis of functional enrichment identified associations between disordered regions overlapping with SCOP domains and critical acrosomal processes, including vesicle trafficking, membrane fusion, and enzymatic activation. Examples of disordered SCOP domains include the PLC-like phosphodiesterase domain, the t-SNARE domain, and the P-domain of calnexin/calreticulin. Protein–protein interaction networks revealed acrosomal proteins as hubs in tightly interconnected systems, emphasizing their functional importance. LLPS propensity modeling determined that over 30% of these proteins are high-probability LLPS drivers (>60%), underscoring their role in dynamic compartmentalization. Proteins such as myristoylated alanine-rich C-kinase substrate and nuclear transition protein 2 exhibited both high LLPS propensities and high levels of structural disorder. A significant relationship (p < 0.0001, R² = 0.649) was observed between the level of intrinsic disorder and LLPS propensity, showing the role of disorder in facilitating phase separation. Overall, these findings provide insights into how intrinsic disorder and LLPS contribute to the structural adaptability and functional precision required for fertilization, with implications for understanding disorders associated with the human acrosome reaction.

Proteomes doi: 10.3390/proteomes13020015

Authors: Hafiza Padinharayil Jinsu Varghese Pulikkottil Raphael Varghese Cornelia M. Wilson Alex George

Background: Despite advances in immunotherapy, non-small-cell lung carcinoma (NSCLC)’s clinical success is limited, possibly due to substantial immunological alterations in advanced cancer patients. This study examines the immunomodulatory effects of sEVs derived from lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) on T cells. Methods: SEVs were isolated from lung cancer cell lines and Jurkat-E6.1. SEV size and morphology were analyzed by NTA and TEM, respectively, while Western blotting confirmed sEV markers. SEV uptake was assessed, followed by resazurin assay, RNA isolation, quantification, cDNA preparation, RT-PCR, nano LC-MS, and bioinformatic analysis, before and after treating Jurkat-E6.1 cells with sEVs from A549 and SKMES1. Results: Cancer-derived sEVs were efficiently internalized by immune cells, reducing T-cell viability. The real-time PCR analysis showed downregulation of KI67, BCL2, BAX, TNFA, IL6, TGFβ, and IL10, suggesting reduced proliferation, dysregulated apoptosis, and impaired inflammatory and immunosuppressive signaling, and the upregulation of GZMB and IL2 suggests retained cytotoxic potential but possibly dysfunctional T-cell activation. Proteomic analysis revealed 39 differentially abundant proteins (DAPs) in ADC-treated T cells and 276 in SCC-treated T cells, with 19 shared DAPs. Gene Ontology (GO) analysis of these DAPs highlighted processes such as sEV biogenesis, metabolic pathways, and regulatory functions, with ADC sEVs influencing NAD metabolism, ECM binding, and oxidoreductase activity, while SCC sEVs affected mRNA stability, amino acid metabolism, and cadherin binding. The cytoplasmic colocalization suggests the presence of these proteins in the cellular and extracellular lumen, indicating the potential of further release of these proteins in the vesicles by T cells. Conclusion: Lung cancer-derived sEVs regulate T-cell activities through immunoregulatory signaling. The molecular interactions between sEVs and immune cells can reveal novel tumor immune regulatory mechanisms and therapeutic targets.

Proteomes doi: 10.3390/proteomes13020014

Authors: Ahmed Maklad Mohammed Sedeeq Kaveh Baghaei Richard Wilson John A. Heath Nuri Gueven Iman Azimi

Background: Medulloblastoma (MB) is the most aggressive paediatric brain cancer, highlighting the urgent need for new diagnostic and prognostic biomarkers and improved treatments to enhance patient outcomes. Our previous study identified LIN28B, an RNA-binding protein, as a potential diagnostic and prognostic marker for MB and a pharmacological target to inhibit MB cell proliferation and stemness. However, the specific role of LIN28B and its mechanism of action in MB had not been studied. Methods: This study assessed LIN28B’s role in Daoy MB cells using siRNA-mediated silencing. LIN28B silencing was achieved with Dharmacon ON-TARGETplus SMARTpool and confirmed by Western blotting. Proliferation and protein assays evaluated the cell metabolic activity and viability. A proteomics analysis was conducted to examine the effect of LIN28B knockdown on the MB cell protein expression profile. The intracellular lipid droplets were assessed using the Nile Red Staining Kit, and nucleolar B23 protein levels were assessed by immunofluorescence. Both were visualised with a high-content IN Cell Analyser 2200. Results: Effective LIN28B silencing (>80%) was achieved in each experiment. LIN28B knockdown reduced the MB cell viability, impaired ribosome biogenesis, and promoted cellular lipid accumulation, as supported by proteomics and cell-based assays. Conclusions: This study highlights LIN28B as a promising target for regulating MB cell growth, ribosomal biogenesis, and lipid metabolism.

Proteomes doi: 10.3390/proteomes13020013

Authors: Priya Thapa Jun Guo Kajol Pradhan Dibya Thapa Sudhakar Madhavarapu Jing Zou Jesse Potts Hui Li Joshua O’Hair Chen Wang Suping Zhou Yong Yang Tara Fish Theodore W. Thannhauser

Background: Tomatoes are self-pollinating plants, and successful fruit set depends on the production of functional pollen within the same flower. Our previous studies have shown that the ‘Black Vernissage’ tomato variety exhibits greater resilience to heat stress in terms of pollen productivity compared to the ‘Micro-Tom’ variety. Pollen productivity is determined by meiotic activity during microsporogenesis and the development of free microspores during gametogenesis. This study focused on identifying heat stress (HS)-induced proteomes in pollen mother cells (PMCs) and microspores. Methods: Tomato plants were grown under two temperature conditions: 26 °C (non-heat-treated control) and 37 °C (heat-treated). Homogeneous cell samples of meiotic PMCs (prior to the tetrad stage) and free microspores were collected using laser capture microdissection (LCM). The heat-induced proteomes were identified using tandem mass tag (TMT)–quantitative proteomics analysis. Results: The enrichment of the meiotic cell cycle in PMCs and the pre-mitotic process in free microspores confirmed the correlation between proteome expression and developmental stage. Under HS, PMCs in both tomato varieties were enriched with heat shock proteins (HSPs). However, the ‘Black Vernissage’ variety exhibited a greater diversity of HSP species and a higher level of enrichment compared to the ‘Micro-Tom’ variety. Additionally, several proteins involved in gene expression and protein translation were downregulated in PMCs and microspores of both varieties. In the PMC proteomes, the relative abundance of proteins showed no significant differences between the two varieties under normal conditions, with very few exceptions. However, HS induced significant differential expression both within and between the varieties. More importantly, these heat-induced differentially abundant proteins (DAPs) in PMCs are directly involved in meiotic cell division, including the meiosis-specific protein ASY3 (Solyc01g079080), the cell division protein kinase 2 (Solyc11g070140), COP9 signalosome complex subunit 1 (Solyc01g091650), the kinetochore protein ndc80 (Solyc01g104570), MORC family CW-type zinc finger 3 (Solyc02g084700), and several HSPs that function in protecting the fidelity of the meiotic processes, including the DNAJ chaperone (Solyc04g009770, Solyc05g055160), chaperone protein htpG (Solyc04g081570), and class I and class II HSPs. In the microspores, most of the HS-induced DAPs were consistently observed across both varieties, with only a few proteins showing significant differences between them under heat stress. These HS-induced DAPs include proteases, antioxidant proteins, and proteins related to cell wall remodeling and the generation of pollen exine. Conclusions: HS induced more dynamic proteomic changes in meiotic PMCs compared to microspores, and the inter-varietal differences in the PMC proteomes align with the effects of HS on pollen productivity observed in the two varieties. This research highlights the importance of the cell-type-specific proteomics approach in identifying the molecular mechanisms that are critical for the pollen developmental process under elevated temperature conditions.

Proteomes doi: 10.3390/proteomes13010012

Authors: Mohini Singh Prashant Kumar Tiwari Vivek Kashyap Sanjay Kumar

Extracellular vesicles (EVs) are lipid-bound vesicles secreted by cells, including exosomes, microvesicles, and apoptotic bodies. Proteomic analyses of EVs, particularly in relation to cancer, reveal specific biomarkers crucial for diagnosis and therapy. However, isolation techniques such as ultracentrifugation, size-exclusion chromatography, and ultrafiltration face challenges regarding purity, contamination, and yield. Contamination from other proteins complicates downstream processing, leading to difficulties in identifying biomarkers and interpreting results. Future research will focus on refining EV characterization for diagnostic and therapeutic applications, improving proteomics tools for greater accuracy, and exploring the use of EVs in drug delivery and regenerative medicine. In this review, we provide a bird’s eye view of various challenges, starting with EV isolation methods, yield, purity, and limitations in the proteome analysis of EVs for identifying protein targets.

Proteomes doi: 10.3390/proteomes13010011

Authors: Frode Selheim Elise Aasebø Håkon Reikvam Øystein Bruserud Maria Hernandez-Valladares

Acute myeloid leukemia (AML) is an aggressive bone marrow malignancy that can be cured only by intensive chemotherapy possibly combined with allogeneic stem cell transplantation. We compared the pretreatment proteomic profiles of AML cells derived from 50 patients at the time of first diagnosis with normal CD34+ bone marrow cells. A comparison based on all AML and CD34+ normal cell populations identified 121 differentially abundant proteins that showed at least 2-fold differences, and these proteins included several markers of neutrophil differentiation (e.g., TLR2, the integrins ITGM and ITGX, and downstream mediators including RHO GTPase, S100A8, S100A9, S100A22). However, the expression of these 121 proteins varied between patients, and a subset of 28 patients was characterized by increased long-term AML-free survival, signs of myeloid AML cell differentiation, and favorable genetic abnormalities. These two main patient subsets (28 with differentiation versus 22 with fewer signs of differentiation) also differed with regard to the phosphorylation of 16 differentially abundant proteins. Furthermore, we also classified our patients based on their expression of 16 proteins involved in the regulation of iron metabolism/ferroptosis and showing differential expression when comparing AML cells and normal CD34+ cells. Among the 22 patients with less favorable prognosis, we could then identify a genetically heterogeneous subset characterized by adverse prognosis (i.e., death from primary resistance/relapse) and an iron metabolism/ferroptosis protein profile showing similarities with normal CD34+ cells. We conclude that proteomic profiles differ between AML and normal CD34+ cells; especially, proteomic differences reflecting differentiation and regulation of iron metabolism/ferroptosis are associated with risk of relapse after intensive conventional therapy.

Proteomes doi: 10.3390/proteomes13010010

Authors: Despoina P. Kiouri Georgios C. Batsis Christos T. Chasapis

Background: The interaction network between the human host proteins and the proteins of the gut bacteria is essential for the establishment of human health, and its dysregulation directly contributes to disease development. Despite its great importance, experimental data on protein–protein interactions (PPIs) between these species are sparse due to experimental limitations. Methods: This study presents a deep learning-based framework for predicting PPIs between human and gut bacterial proteins using structural data. The framework leverages graph-based protein representations and variational autoencoders (VAEs) to extract structural embeddings from protein graphs, which are then fused through a Bi-directional Cross-Attention module to predict interactions. The model addresses common challenges in PPI datasets, such as class imbalance, using focal loss to emphasize harder-to-classify samples. Results: The results demonstrated that this framework exhibits robust performance, with high precision and recall across validation and test datasets, underscoring its generalizability. By incorporating proteoforms in the analysis, the model accounts for the structural complexity within proteomes, making predictions biologically relevant. Conclusions: These findings offer a scalable tool for investigating the interactions between the host and the gut microbiota, potentially yielding new treatment targets and diagnostics for disorders linked to the microbiome.

Proteomes doi: 10.3390/proteomes13010009

Authors: Eldi Sulaj Felix L. Sandell Linda Schwaigerlehner Gorji Marzban Juliane C. Dohm Renate Kunert

Background: Chinese hamster ovary (CHO) cells are extensively used in the pharmaceutical industry for producing complex proteins, primarily because of their ability to perform human-like post-translational modifications. However, the efficiency of high-quality protein production can vary significantly for monoclonal antibody-producing cell lines, within the CHO host cell lines or by extrinsic factors. Methods: To investigate the complex cellular mechanisms underlying this variability, a phosphoproteomics analysis was performed using label-free quantitative liquid chromatography after a phosphopeptide enrichment of recombinant CHO cells producing two different antibodies and a tunicamycin treatment experiment. Using MaxQuant and Perseus for data analysis, we identified 2109 proteins and quantified 4059 phosphosites. Results: Significant phosphorylation dynamics were observed in nuclear proteins of cells producing the difficult-to-produce 2G12 mAb. It suggests that the expression of 2G12 regulates nuclear pathways based on increases and decreases in phosphorylation abundance. Furthermore, a substantial number of changes in the phosphorylation pattern related to tunicamycin treatment have been detected. TM treatment affects, among other phosphoproteins, the eukaryotic elongation factor 2 kinase (Eef2k). Conclusions: The alterations in the phosphorylation landscape of key proteins involved in cellular processes highlight the mechanisms behind stress-induced cellular responses.

Proteomes doi: 10.3390/proteomes13010008

Authors: Kathrine Danner Aakjær Pedersen Line Thopholm Andersen Mads Heiselberg Camilla Agerskov Brigsted Freja Lyngs Støvring Louise Mailund Mikkelsen Sofie Albrekt Hansen Christian Enrico Rusbjerg-Weberskov Mette Lübeck Simon Gregersen Echers

Background: During the initial steps of green biorefining aimed at protein recovery, endogenous proteins and enzymes, along with, e.g., phytochemical constituents, are decompartmentalized into a green juice. This creates a highly dynamic environment prone to a plethora of reactions including oxidative protein modification and deterioration. Obtaining a fundamental understanding of the enzymes capable of exerting antioxidant activity ex vivo could help mitigate these reactions for improved product quality. Methods: In this study, we investigated perennial ryegrass (Lolium perenne var. Abosan 1), one of the most widely used turf and forage grasses, as a model system. Using size exclusion chromatography, we fractionated the green juice to investigate in vitro antioxidant properties and coupled this with quantitative bottom-up proteomics, GO-term analysis, and fraction-based enrichment. Results: Our findings revealed that several enzymes, such as superoxide dismutase and peroxiredoxin proteoforms, already known for their involvement in in vivo oxidative protection, are enriched in fractions displaying increased in vitro antioxidant activity, indicating retained activity ex vivo. Moreover, this study provides the most detailed characterization of the L. perenne proteome today and delivers new insights into protein-level partitioning during wet fractionation. Conclusions: Ultimately, this work contributes to a better understanding of the first steps of green biorefining and provides the basis for process optimization.

Proteomes doi: 10.3390/proteomes13010007

Authors: Christina Karakosta Martina Samiotaki Anastasios Bisoukis Konstantinos I. Bougioukas George Panayotou Dimitrios Papaconstantinou Marilita M. Moschos

Background: The purpose of this study was to detect proteomic alterations and corresponding signaling pathways involved in the formation of age-related cataract (ARC), diabetic cataract (DC), and post-vitrectomy cataract (PVC). Methods: Three sample types, the aqueous humor (AH), the anterior capsule (AC), and the content of the phaco cassette, were collected during phacoemulsification surgery. The samples were obtained from 12 participants without diabetes mellitus (DM), 11 participants with DM, and 7 participants without DM, with a history of vitrectomy surgery in the past 12 months. The Sp3 protocol (Single-Pot, Solid-Phase, Sample-Preparation) was used for the sample preparation. The recognition and quantification of proteins were carried out with liquid chromatography online with tandem mass spectrometry. The DIA-NN software was applied for the identification and quantification of peptides/proteins. Statistical analysis and data visualization were conducted on Perseus software. Data are available via ProteomeXchange. Results: A very rich atlas of the lens and AH proteome has been generated. Glycosaminoglycan biosynthesis and the non-canonical Wnt receptor signaling pathway were differentially expressed in ARC compared to both the DC and PVC groups. In the PVC group, complement activation was differentially expressed in AH samples, while glutathione metabolism and oxidoreductase activity were differentially expressed in AC samples. Microfilament motor activity, microtubule cytoskeleton organization, and microtubule binding were differentially expressed in the DC and PVC groups in both AH and AC samples. Conclusions: The results of this study expand the existing knowledge on pathways involved in the pathophysiology of cataract, and suggest possible important druggable targets for slower progression or even prevention of cataract.

Proteomes doi: 10.3390/proteomes13010006

Authors: Shantanu Gupta Daner A. Silveira José Carlos M. Mombach Ronaldo F. Hashimoto

The tumor suppressor p53, in its wild-type form, plays a central role in cellular homeostasis by regulating senescence, apoptosis, and autophagy within the DNA damage response (DDR). Recent findings suggest that wild-type p53 also governs ferroptosis, an iron-dependent cell death process driven by lipid peroxidation. Post-translational modifications of p53 generate proteoforms that significantly enhance its functional diversity in regulating these mechanisms. A key target in this process is the cystine/glutamate transporter (xCT), which is essential for redox balance and ferroptosis resistance. Additionally, p53-induced miR-34c-5p suppresses cancer cell proliferation and drug resistance by modulating Myc, an oncogene further influenced by non-coding RNAs like circular RNA NOTCH1 (CricNOTCH1) and long non-coding RNA MALAT1. However, the exact role of these molecules in ferroptosis remains unclear. To address this, we introduce the first dynamic Boolean model that delineates the influence of these ncRNAs and p53 on ferroptosis, apoptosis, and senescence within the DDR context. Validated through gain- and loss-of-function perturbations, our model closely aligns with experimental observations in cancers such as oral squamous cell carcinoma, nasopharyngeal carcinoma, and osteosarcoma. The model identifies crucial positive feedback loops (CricNOTCH1/miR-34c/Myc, MALAT1/miR-34c/Myc, and Myc/xCT) and highlights the therapeutic potential of using p53 proteoforms and ncRNAs to combat drug resistance and induce cancer cell death.

Proteomes doi: 10.3390/proteomes13010005

Authors: Michele Costanzo Marianna Caterino Lucia Santorelli

The rapid and substantial advancements in proteomic and metabolomic technologies have revolutionized our ability to investigate biological systems [...]

Proteomes doi: 10.3390/proteomes13010004

Authors: Zhongyuan Lin Jiantao Shu Yu Qin Dingding Cao Jiao Deng Pingfang Yang

Nelumbo nucifera is an aquatic plant with a high ornamental value due to its flower. Despite the release of several versions of the lotus genome, its annotation remains inefficient, which makes it difficult to obtain a more comprehensive knowledge when –omic studies are applied to understand the different biological processes. Focusing on the petaloid of the lotus flower, we conducted a comparative proteomic analysis among five major floral organs. The proteogenomic strategy was applied to analyze the mass spectrometry data in order to dig out novel proteoforms that are involved in the petaloids of the lotus flower. The results revealed that a total of 4863 proteins corresponding to novel genes were identified, with 227 containing single amino acid variants (SAAVs), and 72 originating from alternative splicing (AS) genes. In addition, a range of post-translational modifications (PTMs) events were also identified in lotus. Through functional annotation and homology analysis with 24 closely related plant species, we identified five candidate proteins associated with floral organ development, which were not identified by ordinary proteomic analysis. This study not only provides new insights into understanding the mechanism of petaloids in lotus but is also helpful in identifying new proteoforms to improve the annotation of the lotus genome.

Proteomes doi: 10.3390/proteomes13010003

Authors: Fei Wang Liang Jin Xue Wang Baoliang Cui Yingli Yang Lori Duggan Annette Schwartz Sterman Sarah M. Lloyd Lisa A. Hazelwood Neha Chaudhary Bhupinder Bawa Lucy A. Phillips Yupeng He Yu Tian

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterized by repetitive alveolar injuries with excessive deposition of extracellular matrix (ECM) proteins. A crucial need in understanding IPF pathogenesis is identifying cell types associated with histopathological regions, particularly local fibrosis centers known as fibroblast foci. To address this, we integrated published spatial transcriptomics and single-cell RNA sequencing (scRNA-seq) transcriptomics and adopted the Query method and the Overlap method to determine cell type enrichments in histopathological regions. Distinct fibroblast cell types are highly associated with fibroblast foci, and transitional alveolar type 2 and aberrant KRT5-/KRT17+ (KRT: keratin) epithelial cells are associated with morphologically normal alveoli in human IPF lungs. Furthermore, we employed laser capture microdissection-directed mass spectrometry to profile proteins. By comparing with another published similar dataset, common differentially expressed proteins and enriched pathways related to ECM structure organization and collagen processing were identified in fibroblast foci. Importantly, cell type enrichment results from innovative spatial proteomics and scRNA-seq data integration accord with those from spatial transcriptomics and scRNA-seq data integration, supporting the capability and versatility of the entire approach. In summary, we integrated spatial multi-omics with scRNA-seq data to identify disease-associated cell types and potential targets for novel therapies in IPF intervention. The approach can be further applied to other disease areas characterized by spatial heterogeneity.

Proteomes doi: 10.3390/proteomes13010002

Authors: Ayushi Mishra Vipin Kumar Sunil Kumar HariOm Singh Anchal Singh

Lymphatic filariasis (LF) continues to impact 657 million individuals worldwide, resulting in lifelong and chronic impairment. The prevalent anti-filarial medications—DEC, albendazole, and ivermectin—exhibit limited adulticidal efficacy. Despite ongoing LF eradication programs, novel therapeutic strategies are essential for effective control. This study examines the mechanism of action of Ocimum sanctum on the filarial parasites Setaria cervi via a synergistic biochemical and proteomics methodology. The ethanolic extract of Ocimum sanctum (EOS) demonstrated potential anti-filarial action in the MTT reduction experiment, with an LC50 value of 197.24 µg/mL. After EOS treatment, an elevation in lipid peroxidation (51.92%), protein carbonylation (48.99%), and NADPH oxidase (88.88%) activity, along with a reduction in glutathione (GSH) (−39.23%), glutathione reductase (GR) (−60.17%), and glutathione S transferase (GST) (−50.48%) activity, was observed. The 2D gel electrophoresis identified 20 decreased and 11 increased protein spots in the EOS-treated parasites relative to the control group. Additionally, in drug docking analysis, the EOS bioactive substances ursolic acid, rutin, and rosmarinic acid show a significant binding affinity with the principal differentially expressed proteins. This paper demonstrates, for the first time, that the anti-filarial efficacy of EOS is primarily facilitated by its impact on energy metabolism, antioxidant mechanisms, and stress response systems of the parasites.

Proteomes doi: 10.3390/proteomes13010001

Authors: Ousseynou Ben Diouf Antoine Gilbert Benoit Bernay Randi G. Syljuåsen Mihaela Tudor Mihaela Temelie Diana I. Savu Mamadou Soumboundou Cheikh Sall François Chevalier

Glioblastoma (GBM) is a devastating malignant brain tumor with a poor prognosis. GBM is associated with radioresistance. Post-translational modifications (PTMs) such as protein phosphorylation can play an important role in the cellular response to radiation. To better understand the early cellular activities after radiation in GBM, we carried out a phospho-proteomic study on the U251 cell line 3 h after X-ray irradiation (6Gy) and on non-irradiated cells. Our study showed a strong modification of proteoform phosphorylation in response to radiation. We found 453 differentially expressed phosphopeptides (DEPs), with 211 being upregulated and 242 being downregulated. A GO enrichment analysis of DEPs showed a strong enrichment of the signaling pathways involved in DNA damage response after irradiation and categorized them into biological processes (BPs), cellular components (CCs) and molecular functions (MFs). Certain accessions such as BRCA1, MDC1, H2AX, MDC1, TP53BP1 were dynamically altered in our fraction and are highly associated with the signaling pathways enriched after radiation.

Proteomes doi: 10.3390/proteomes12040037

Authors: Nicolai Bjødstrup Palstrøm Kristian Boje Nielsen Amanda Jessica Campbell Mette Soerensen Lars Melholt Rasmussen Jes Sanddal Lindholt Hans Christian Beck

Abdominal aortic aneurysm (AAA) is a life-threatening condition characterized by the weakening and dilation of the abdominal aorta. Few diagnostic biomarkers have been proposed for this condition. We performed mass spectrometry-based proteomics analysis of affinity-enriched plasma from 45 patients with AAA and 45 matched controls to identify changes to the plasma proteome and potential diagnostic biomarkers. Gene ontology analysis revealed a significant upregulation of the proteins involved in inflammation, coagulation, and extracellular matrix in AAA patients, while proteins related to angiogenesis were among those downregulated. Using recursive feature elimination, we identified a subset of 10 significantly regulated proteins that were highly predictive of AAA. A random forest classifier trained on these proteins achieved an area under the curve (AUC) of 0.93 [95% CI: 0.91–0.95] using cross-validation. Further validation in a larger cohort is necessary to confirm these results.

Proteomes doi: 10.3390/proteomes12040035

Authors: Jessica Wohlfahrt Jennifer Guergues Stanley M. Stevens

As the primary innate immune cells of the brain, microglia play a key role in various homeostatic and disease-related processes. To carry out their numerous functions, microglia adopt a wide range of phenotypic states. The proteomic landscape represents a more accurate molecular representation of these phenotypes; however, microglia present unique challenges for proteomic analysis. This study implemented a streamlined liquid- and gas-phase fractionation method with data-dependent acquisition (DDA) and parallel accumulation–serial fragmentation (PASEF) analysis on a TIMS-TOF instrument to compile a comprehensive protein library obtained from adult-derived, immortalized mouse microglia with low starting material (10 µg). The empirical library consisted of 9140 microglial proteins and was utilized to identify an average of 7264 proteins/run from single-shot, data-independent acquisition (DIA)-based analysis microglial cell lysate digest (200 ng). Additionally, a predicted library facilitated the identification of 7519 average proteins/run from the same DIA data, revealing complementary coverage compared with the empirical library and collectively increasing coverage to approximately 8000 proteins. Importantly, several microglia-relevant pathways were uniquely identified with the empirical library approach. Overall, we report a simplified, reproducible approach to address the proteome complexity of microglia using low sample input and show the importance of library optimization for this phenotypically diverse cell type.

Proteomes doi: 10.3390/proteomes12040036

Authors: Miyu Sakuyama Yuri Kominami Hideki Ushio

Sous vide, a cooking method that involves vacuum-sealed fish at low temperatures, yields a uniquely tender, easily flaked texture. Previous research on sous-vide tenderization has focused on thermal protein denaturation. On the other hand, the contribution of proteases, activated at low temperatures in fish meat, has been suggested. However, the details of protein degradation remain unclear. This study employed SDS-PAGE/immunoblot and peptidomic analysis of rainbow trout to assess proteolysis during sous-vide cooking. The results from SDS-PAGE and immunoblot analysis indicated reduced thermal aggregation of sarcoplasmic proteins and increased depolymerization of actin under low-temperature cooking conditions. A comparison of the peptidome showed that the proteolysis of myofibrillar proteins was accelerated during sous-vide cooking, with distinct proteases potentially activated at different cooking temperatures. Terminome analysis revealed the contribution of specific proteases at higher temperatures in rainbow trout. The results of this study demonstrate the thermal denaturation of sarcoplasmic proteins and proteolysis of myofibrillar proteins in rainbow trout meat during sous-vide cooking and its temperature dependence. The methodology in the present study could provide insights into the optimization of cooking conditions for different fish species, potentially leading to improved texture and quality of sous-vide products.

Proteomes doi: 10.3390/proteomes12040034

Authors: Janire Alonso-Puyo Oihane Izagirre-Fernandez Olatz Crende Jesús Seco-Calvo Ainhoa Fernandez-Atutxa Diego Fernandez-Lazaro Patricia Garcia-Gallastegi Begoña Sanz

Sarcopenia is linked to the decline in muscle mass, strength and function during aging. It affects the quality and life expectancy and can lead to dependence. The biological process underlying sarcopenia is unclear, but the proteins myostatin and follistatin are involved in the balance between muscle breakdown and synthesis. While myostatin promotes muscle breakdown, follistatin promotes muscle growth, but several works have shown an inconsistent association of these proteins with aging-related parameters in serum of older people. We aimed to know the evolution of these putative sarcopenia biomarkers along muscle aging in an in vitro model. We created and phenotyped a longitudinal murine model (C2C12 cells). Then, we analyzed the protein and genetic expression of myostatin and follistatin as well as the signaling pathway regulators mTOR and RPS6KB1. Myostatin and RPS6KB1 showed a similar tendency in both protein and genetic expression with aging (basal–up–down). Follistatin, on the other hand, shows the opposite tendency (basal–down–up). Regarding mTOR, the tendencies differ when analyzing proteins (basal–up–down) or genes (basal–down–down). Our work demonstrates a U-shape tendency for myostatin and follistatin and for the signaling pathway regulators. These results could be of the utmost importance when designing further research on seeking molecular biomarkers and/or targets for sarcopenia.

Proteomes doi: 10.3390/proteomes12040033

Authors: Ivo Fierro-Monti Klemens Fröhlich Christian Schori Alexander Schmidt

Proteogenomics integrates genomic and proteomic data to elucidate cellular processes by identifying variant peptides, including single amino acid variants (SAAVs). In this study, we assessed the capability of data-independent acquisition mass spectrometry (DIA-MS) to identify SAAV peptides in HeLa cells using various search engine pipelines. We developed a customised sequence database (DB) incorporating SAAV sequences from the HeLa genome and conducted searches using DIA-NN, Spectronaut, and Fragpipe-MSFragger. Our evaluation focused on identifying true positive SAAV peptides and false positives through entrapment DBs. This study revealed that DIA-MS provides reproducible and comprehensive coverage of the proteome, identifying a substantial proportion of SAAV peptides. Notably, the DIA-MS searches maintained consistent identification of SAAV peptides despite varying sizes of the entrapment DB. A comparative analysis showed that Fragpipe-MSFragger (FP-DIA) demonstrated the most conservative and effective performance, exhibiting the lowest false discovery match ratio (FDMR). Additionally, integrating DIA and data-dependent acquisition (DDA) MS data search outputs enhanced SAAV peptide identification, with a lower false discovery rate (FDR) observed in DDA searches. The validation using stable isotope dilution and parallel reaction monitoring (SID-PRM) confirmed the SAAV peptides identified by DIA-MS and DDA-MS searches, highlighting the reliability of our approach. Our findings underscore the effectiveness of DIA-MS in proteogenomic workflows for identifying SAAV peptides, offering insights into optimising search engine pipelines and DB construction for accurate proteomics analysis. These methodologies advance the understanding of proteome variability, contributing to cancer research and the identification of novel proteoform therapeutic targets.

Proteomes doi: 10.3390/proteomes12040032

Authors: Vikrant Rai

Non-healing diabetic foot ulcers (DFUs) not only significantly increase morbidity and mortality but also cost a lot and drain healthcare resources. Persistent inflammation, decreased angiogenesis, and altered extracellular matrix remodeling contribute to delayed healing or non-healing. Recent studies suggest an increasing trend of DFUs in diabetes patients, and non-healing DFYs increase the incidence of amputation. Despite the current treatment with offloading, dressing, antibiotics use, and oxygen therapy, the risk of amputation persists. Thus, there is a need to understand the molecular and cellular factors regulating healing in DFUs. The ongoing research based on proteomics and transcriptomics has predicted multiple potential targets, but there is no definitive therapy to enhance healing in chronic DFUs. Increased or decreased expression of various proteins encoded by genes, whose expression transcriptionally and post-transcriptionally is regulated by transcription factors (TFs) and microRNAs (miRs), regulates DFU healing. For this study, RNA sequencing was conducted on 20 DFU samples of ulcer tissue and non-ulcerated nearby healthy tissues. The IPA analysis revealed various activated and inhibited transcription factors and microRNAs. Further network analysis revealed interactions between the TFs and miRs and the molecular targets of these TFs and miRs. The analysis revealed 30 differentially expressed transcription factors (21 activated and 9 inhibited), two translational regulators (RPSA and EIF4G2), and seven miRs, including mir-486, mir-324, mir-23, mir-186, mir-210, mir-199, and mir-338 in upstream regulators (p < 0.05), while causal network analysis (p < 0.05) revealed 28 differentially expressed TFs (19 activated and 9 inhibited), two translational regulators (RPSA and EIF4G2), and five miRs including mir-155, mir-486, mir-324, mir-210, and mir-1225. The protein–protein interaction analysis revealed the interaction of various novel proteins with the proteins involved in regulating DFU pathogenesis and healing. The results of this study highlight many activated and inhibited novel TFs and miRs not reported in the literature so far, as well as the targeted molecules. Since proteins are the functional units during biological processes, alteration of gene expression may result in different proteoforms and protein species, making the wound microenvironment a complex protein interaction (proteome complexity). Thus, investigating the effects of these TFs and miRs on protein expression using proteomics and combining these results with transcriptomics will help advance research on DFU healing and delineate potential therapeutic strategies.

Proteomes doi: 10.3390/proteomes12040031

Authors: Valentina Rossio Joao A. Paulo

The yeast ATPase Cdc48 (known as p97/VCP in human cells) plays an important role in the Ubiquitin Proteasome System. VCP is essential for cancer cell proliferation, and its dysregulation has been implicated in several neurodegenerative diseases. Cdc48 functions by extracting ubiquitylated proteins from membranes, protein complexes and chromatin by often facilitating their proteasomal degradation. Specific adaptors or cofactors, primarily belonging to the UBX domain-containing protein family (which has seven members in Saccharomyces cerevisiae) recruit Cdc48 to ubiquitylated proteins. Here, we employed sample multiplexing-based quantitative mass spectrometry to profile global protein abundance in p97 adaptor deletion strains, specifically comparing seven single deletion strains of UBX domain-containing proteins and the Cuz1 deletion strain, which belongs to the zinc finger AN1-type domain protein family. We observed that each strain showed unique sets of differentially abundant proteins compared to the wild type. Our analysis also revealed a role for Ubx3 in maintaining wild type levels of mitochondrial proteins. Overall, we identified ~1400 differentially abundant proteins in the absence of a specific Cdc48 adaptor. This unique dataset offers a valuable resource for studying the functions of these adaptors, aiming to achieve a better understanding of the cellular processes regulated by Cdc48 itself and to deepen our understanding of the Ubiquitin Proteasome System.