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Proteomics

Proteomics: explore 89 source-linked works published from 2024 to 2026, with original documents and citations.

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Early hepatic protein responses to dietary restriction-refeeding in Japanese quail: A proteomic investigation.

Feed intake and refeeding after nutrient scarcity induce rapid metabolic adaptations in the poultry liver; however, hepatic proteomic recovery pathways in the early hours post-refeeding remain poorly defined. This study aimed to characterize early liver protein signatures in Japanese quail (Coturnix japonica) recovering from nutritional stress under two refeeding conditions. Eighteen 12-week-old male quails (245.20 ± 0.213 g) were assigned to three groups (n = 6): control fed ad libitum (12.13 MJ/kg), 24 h feed deprivation followed by 6 h refeeding, and 24 h low metabolizable energy (6.30 MJ/kg) diet followed by 6 h refeeding. In total, 854 proteins were identified, of which 515 met the filtering criteria. The low metabolizable energy refeeding showed higher abundance of proteins linked to ATP binding and carbohydrate/carboxylic acid metabolism, alongside detoxification-related proteins, while suppressing translation/RNA-binding machinery and antioxidant pathways. Feed-deprived refeeding enriched in oxidative phosphorylation and mitochondrial complex I assembly with reduced cytoplasmic translation, NMD-related components, and sulfur compound metabolism. A direct comparison indicated divergent recovery strategies: low metabolizable energy refeeding mainly reflected oxidoreductase activity and translation initiation, whereas feed-deprived refeeding potentially enriched mitochondrial ATP production and glutathione-based defenses. Our analysis indicate that 6 h of refeeding initiates an early, incomplete recovery toward hepatic homeostasis, with the severity of prior nutritional restriction dictating distinct liver metabolic priorities. Collectively, these findings might provide a preliminary understanding of the hepatic mechanisms involved in recovery from nutrient deprivation and may help in the development of feeding strategies for managing metabolic recovery in poultry. However, these findings should be considered hypothesis-generating pending further validation.

Animals↗

Addressing lignin composition and content via Arabidopsis arogenate dehydratase knockout and over-expression genotypes.

Following the down-selection of 14 Arabidopsis thaliana arogenate dehydratase (ADT) knockout and over-expression (OE) genotypes, the most highly contrasting quadruple knockout adt3/4/5/6 and ADT OE genotypes were subjected to proteomics, metabolomics, and scanning electron microscopy (SEM) analyses as needed, with results compared to Columbia wild-type (WT). The basal adt3/4/5/6 stem cross-sections, ∼70% lignin content reduced, exhibited buckled vessel cell walls and partially detached xylary fibers, in contrast to WT and ADT4m/5 m OE genotypes that did not. Anatomical defects primarily resulted from guaiacyl lignin level reductions in vessels with concomitant increased stem syringyl:guaiacyl (S/G) ratios. Phenylpropanoid and various upstream shikimate-chorismate pathway enzyme abundances, as well as specific monolignol oxidases (laccases/peroxidases), generally increased in adt3/4/5/6 at different stem and rosette leaf growth/development stages, relative to WT. Opposite effects were largely observed with the ADT5m OE genotype. By contrast, flavonoid and glucosinolate pathway enzyme amounts varied. Such enzyme abundance increases were overall unproductive as adt3/4/5/6 was unable to restore WT, ADT4 OE, ADT5 OE, ADT5m OE, and ADT4m/5 m OE secondary metabolite (lignin, phenylpropanoid, lignan, flavonoid, phenolic acid, and glucosinolate) levels. Conversely, ADT OE genotypes did not significantly increase programmed lignin levels or alter S/G compositions. In sum, proteomics analyses of adt3/4/5/6 and adt5 'perceived' that lignin and low molecular weight secondary metabolite amounts were not at 'programmed' levels as for WT and ADT OE genotypes but observed increases in relevant pathway protein abundances were futile. Notably though, proteomics analyses did not lead to predicting that lignin and associated biochemical pathways would have reduced metabolite levels, relative to WT and ADT OE genotypes. Genotype adt3/4/5/6, possibly the highest lignin level reduced genotype reported, did not utilize other phenolics to compensate. By contrast, the differential temporal and spatial deposition of cell wall oxidases again indicate the exquisite control over lignin deposition, and our lack of knowledge of precise lignin structure and assembly in subcellular regions of the lignified cell walls.

Lignin↗

Protein isolation markedly enhances in vitro digestibility, nutritional quality, and bioactivity of fungal mycelial proteins.

Fungal mycelial proteins are promising sustainable protein sources, yet their nutritional utilization is often limited by structural constraints. This study systematically evaluated the effects of protein isolation on the proteomic composition, gastrointestinal digestion behavior, amino acid utilization, and bioactivity of Pleurotus citrinopileatus mycelial proteins. Quantitative proteomics identified 3591 proteins, of which 3374 were shared between mycelial flour (PCMF) and protein isolate (PCMPI), indicating that PCMPI primarily represents the soluble proteome fraction. In vitro digestion revealed that PCMPI exhibited significantly higher digestibility (93.98%) than PCMF (42.98%) (p&#xa0;<&#xa0;0.05), reaching levels comparable to whey protein isolate. Enhanced enzymatic accessibility in PCMPI promoted rapid peptide generation during the gastric phase and efficient amino acid release during the intestinal phase, resulting in higher peptide (634.76&#xa0;mg/g) and free amino acid levels (341.69&#xa0;mg/g) at the digestion endpoint. Consequently, PCMPI achieved a balanced amino acid profile with a PDCAAS of 1.0. Moreover, its digestion products exhibited stronger antioxidant activity (IC&#x2085;&#x2080;&#xa0;=&#xa0;8.36&#xa0;mg/mL) and ACE inhibitory activity (IC&#x2085;&#x2080;&#xa0;=&#xa0;15.65&#xa0;mg/mL) compared with PCMF. Mechanistically, protein isolation disrupted the cell wall matrix, shifting digestion from a structure-limited to an accessibility-driven regime. Collectively, these findings demonstrate that protein isolation markedly enhances the digestibility, nutritional quality, and functional potential of mycelial proteins, supporting their application as high-value sustainable protein ingredients.

Digestion↗

Evaluation of pilocarpine effects on sweat proteome.

BACKGROUND: Sweat is increasingly recognized as a valuable, non-invasive biofluid for biomarker discovery, yet its composition depends on the stimulation method. This study aimed to determine how pharmacological induction with pilocarpine compares to physiologically induced sweat through exercise in shaping the sweat proteome. RESULTS: We analyzed thermoregulatory sweat from exercise, pilocarpine-induced sweat, and combined pilocarpine plus exercise sweat. Total protein concentrations were similar across conditions, but pilocarpine markedly increased proteomic diversity, with combined pilocarpine plus exercise sweat showing the highest number of identifications. The core sweat proteome remained stable, while pilocarpine selectively enriched low-abundance proteins involved in vesicular trafficking, cytoskeletal remodelling, and metabolism. Proteins linked to the canonical M3-Gq-PLC-Ca2+ pathway, including AQP5, CALML5, and CLIC1, were consistently enriched, confirming cholinergic activation. Pilocarpine-induced sweat also contained plasma-derived and immune-related proteins, reflecting enhanced secretion and reduced ductal reabsorption. CONCLUSIONS: Exercise yields a physiologically relevant but less complex proteome, pilocarpine-induced sweat produces a pharmacologically enriched yet biased profile, and combined pilocarpine plus exercise sweat maximizes protein detection at the expense of interpretability. These findings highlight the critical impact of stimulation paradigm on sweat proteomics and provide a reference framework for biomarker research. SIGNIFICANCE: This study employed LC-MS/MS to systematically characterize eccrine sweat and delineate how stimulation paradigms-exercise, pilocarpine, and their combination-shape its proteomic landscape. By demonstrating that pharmacological induction profoundly alters protein diversity and composition compared to physiologically induced sweat, these findings establish a critical benchmark for sweat-based biomarker research and highlight the need for paradigm-aware sampling strategies in clinical and translational contexts. Nonetheless, several methodological constraints warrant consideration: the limited sample size (five individuals per group), the exclusive inclusion of women under combined oral contraceptive treatment (21 active pills followed by 7 pill-free days), which restricts extrapolation to naturally cycling women, and the focus on healthy young adults (18-25&#xa0;years), limiting generalizability to older or clinically heterogeneous populations. Despite these limitations, this work provides a foundational framework for optimizing sweat collection protocols and advancing precision approaches in non-invasive diagnostics.

Pilocarpine↗

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗

Gastrointestinal digestion governs insect protein hydrolysis and predicted bioactive peptide release: Species-dependent implications for functional food applications.

This study investigates the digestion of insect proteins and the release of predicted bioactive peptides during human gastrointestinal digestion. Using the Infogest in vitro model, mealworm, cricket, and black soldier fly larvae (BSFL) proteins were digested and analyzed through discovery proteomics and bioinformatics to identify predicted bioactive peptides. Sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) quantified insect proteins including predicted bioactive peptide precursor proteins, the precursors of predicted bioactive peptides. Results indicated that gastrointestinal digestion strongly influences peptide release, with the gastric phase exhibiting a richer predicted bioactive peptide profile than the small intestinal phase. Many predicted bioactive peptides were rapidly hydrolysed under small intestine conditions, which may lead to reduced stability or diminished activity in vivo, potentially explaining why certain peptides show strong bioactivity in vitro but limited effects in vivo. Additionally, predicted bioactive peptide release varied by insect species, influenced by genetic factors and peptide abundance. These findings highlight the importance of species selection and consideration of proteolytic digestion patterns in optimizing insect-derived bioactive peptides for functional foods and nutraceutical applications.

Animals↗

Proteome-level evidence that tebuconazole, both alone and in interaction with thiacloprid, affects epigenetic events in bumblebee heads.

Tebuconazole, a widely used ergosterol biosynthesis-inhibiting fungicide, can affect nontargets, especially when combined with insecticides. We employed label-free quantitative proteomics to investigate the effects of long-term exposure to sublethal concentrations (100&#xa0;&#x3bc;g/L) of tebuconazole, either by itself or alongside the neonicotinoid thiacloprid (100&#xa0;&#x3bc;g/L), on the heads of Bombus terrestris workers. A Bayesian factor power analysis revealed that the experiment produced conclusive proteomic results. Tebuconazole treatment revealed eleven differentially abundant proteins, which increased elevenfold with thiacloprid. The proteins that changed in the same direction in both treatments suggest the occurrence of epigenetic events because they are involved in histone trimethylation (H3K4me3), pre-mRNA processing, and folate (vitamin B9) metabolism. Following co-exposure, the abundance of histone H2A.V and its associated proteins was affected. Two important detoxification-related proteins, CYP6BE1 and CYP6AQ1 (honey bee homologs), were identified, as well as proteins that suggest hormonal and neurotoxic effects. Overall, this study suggests that tebuconazole affects key epigenetic processes in bumblebee heads at the proteome level, though this was not confirmed at the biological level or through orthogonal methods. The tested chemicals were previously found to affect trimethylations, but not H3K4me3. We suggest analyzing the different trimethylations, their interplay, and associated hallmarks, such as folate levels. SIGNIFICANCE: The effects of pesticides and their combinations on organisms can be unexpected until they are examined using modern, complex methods. High-throughput proteomics can provide data on important biochemical processes affected by pesticides, offering a different perspective to that at the expression level. Despite their low acute toxicity, a group of fungicides that inhibit (ergo)sterol biosynthesis (EBI or SBI) are considered dangerous to pollinators, including bumblebees. This is due to the increasing toxicity of insecticides through the inhibition of cytochrome P450 detoxification enzymes. We found that tebuconazole had a similar effect on epigenetic events when used alone or in combination with the insecticide thiacloprid. Key proteins suggest that H3K4 histone trimethylation (H3K4me3) was impacted. To our knowledge, this expands the existing evidence suggesting that tebuconazole/triazole fungicides affect histone trimethylation H3K27me3. Since literature shows that thiacloprid affects H3K9me3, it is possible that thiacloprid and tebuconazole interact in these epigenetic events that affect each other. Overall, our results suggest that tebuconazole affects proteins involved in histone trimethylation, pre-mRNA processing, and folate metabolism. These are all hallmarks of epigenetic processes and were further extended by the co-exposure of tebuconazole and thiacloprid to more differently abundant proteins. Additionally, the results provide data on cytochrome P450s of the CYP6 family, which act as detoxifying proteins, as well as proteins that indicate hormonal and neurotoxic effects in bumblebee heads. Finally, the results of the Bayesian power analysis confirmed the meaningfulness of the proteomic data analyzed in this study. If the new findings obtained at the proteome level are verified by different methods, the full extent of the side effects of tebuconazole can be revealed.

Animals↗

Proteomics-based analysis of the defense mechanisms of disease-resistant grass carp against Aeromonas veronii.

Sustainable aquaculture of grass carp (Ctenopharyngodon idella, GC) is consistently threatened by bacterial diseases, particularly those caused by Aeromonas veronii. A disease-resistant grass carp (DR-GC) has been developed by backcrossing female gynogenetic GC with normal male GC, exhibiting improved resistance. However, the systemic molecular mechanisms of DR-GC defending against Aeromonas veronii infection remain largely unexplored. Here, a label-free quantitative proteomics approach was employed to systematically compare proteomic profiles across five tissues (intestine, liver, muscle, skin, and kidney) in DR-GC and GC under healthy and infected conditions. The intestine was identified as the central defense tissue, exhibiting the highest number of differentially abundant proteins (DAPs). In DR-GC, A0A3N0YEK7 (small ribosomal subunit protein eS28), A0A3N0YGT8 (ATP synthase-coupling factor 6) and A0A3N0YNS7 (apolipoprotein A-I) were significantly upregulated in intestine, while D5KZW6 (GCHV-induced protein), A0A3N0Z0A1 and Q8JH84 (hemoglobin subunit alpha) were significantly dysregulated across multiple tissues, which playing the critical roles in defense mechanisms at the protein level. Furthermore, cytochrome P450-associated pathways, cytosolic DNA-sensing and RIG-I-like receptor signaling pathways were identified as crucial coordinators mediating immune and metabolic responses. This study provides the first comprehensive proteomic view of multi-tissue defense mechanisms in DR-GC, and identifies key DAPs and pathways for subsequent functional validation.

Animals↗

On-filter fractionation by empFASP improves identification of membrane peptides in proteomic experiments.

Membrane proteins remain among the most analytically challenging targets in bottom-up proteomics due to their limited solubility and low abundance of protease-accessible sites within transmembrane domains. In addition, hydrophobic peptides are frequently lost during detergent removal and the on-filter processing steps. Here, we present empFASP, a straightforward on-filter-fractionation-based modification of the enhanced filter-aided sample preparation (eFASP) workflow that enhances recovery of membrane-embedded peptides otherwise lost during digestion and cleanup. The method combines controlled on-filter inversion with sequential ethyl acetate extraction at defined pH values, enabling recovery of peptide material retained on the filter and redistributed into detergent micelles. Compared with SP3 and SP4 in HEK293T lysates, empFASP increased unique hydrophobic peptide identifications by up to 48% and increased the proportion of detected transmembrane peptides. Application to mouse mitochondrial membranes and phosphatidylethanolamine-deficient and PE-containing Escherichia coli membranes showed that the additional fractions of empFASP contribute complementary recovery of hydrophobic and membrane-associated peptides, with the strongest gains observed at the peptide level. Because empFASP requires no specialized reagents or instrumentation, it can be readily implemented in standard proteomics workflows to improve coverage of membrane-embedded regions. SIGNIFICANCE: The empFASP (enhanced membrane peptide) workflow offers a practical solution to one of the persistent limitations in membrane proteomics-the underrepresentation of hydrophobic and transmembrane peptides in standard digests. By integrating simple pH-controlled extractions into an on-filter format, empFASP recovers peptides otherwise lost through adsorption or detergent micelle retention, substantially improving coverage of the membrane proteome. This method expands the analytical reach of bottom-up proteomics without requiring specialized instrumentation, making it immediately applicable for studies of membrane topology, protein-lipid interactions, and the structural consequences of altered membrane composition.

Proteomics↗

Transpulmonary proteomic gradient analysis in women with pulmonary arterial hypertension associated with systemic sclerosis.

This study investigated proteomic alterations in the pulmonary circulation of patients with pulmonary arterial hypertension associated with systemic sclerosis (PAH-SSc) by analyzing the transpulmonary protein gradient and comparing the proteomic profiles with systemic sclerosis (SSc) without PAH. Twenty women were included (10 PAH-SSc, 64.6&#xa0;&#xb1;&#xa0;10.8&#xa0;years; 10 SSc, 62.8&#xa0;&#xb1;&#xa0;11.5&#xa0;years). The transpulmonary gradient was defined as the difference in biomarker concentrations between wedge-position and pulmonary artery blood samples. Peptides were analysed using liquid chromatography-mass spectrometry, and differentially abundant proteins were identified with Proteome Discoverer. Protein-protein interaction networks were generated with STRING and visualized in Cytoscape. A total of 270 proteins were detected, with no significant transpulmonary gradient alterations. However, patients with PAH-SSc showed distinct proteomic profiles compared to SSc. Multivariate analysis identified 48 differentially abundant proteins in pulmonary artery plasma, with 15 overrepresented and 33 downregulated in PAH-SSc. Among these, the downregulation of transforming growth factor-beta-induced protein ig-h3 (TGF&#x3b2;I/ig-h3) points to a potential involvement of the TGF-&#x3b2;-related extracellular matrix remodelling pathway in PAH-SSc. However, further validation in larger and independent cohorts is required before its relevance as a biomarker or therapeutic target can be established. In conclusion, while no transpulmonary proteomic gradient was observed, the proteomic profiles of PAH-SSc and SSc were different. The profile in PAH-SSc was characterized by differences in immune response, lipid metabolism, and hemostatic proteins. SIGNIFICANCE: This study offers the first proteomic characterization of the transpulmonary gradient in PAH-SSc and SSc. Although no differences in the gradient were found, the pulmonary artery plasma proteome of PAH-SSc patients showed a distinct pattern compared to SSc. Several proteins associated with immune function, haemostasis, and cellular processes were altered, which may indicate specific pathophysiological features of PAH-SSc or suggest how lung dysfunction develops in SSc. Targeting dysregulated proteins like TGF&#x3b2;I/ig-h3 or addressing immune-coagulation imbalances may support future research studies. Overall, these findings refine the molecular profile of PAH-SSc and provide a basis for future large-scale studies aimed at clarifying disease mechanisms and identifying clinically relevant molecular signatures.

Humans↗

Early proteomic and metabolic signatures of liver and eye in OAT-deficient mice.

Ornithine aminotransferase (OAT) deficiency causes hyperornithinemia and gyrate atrophy (GA) of the choroid and retina, a rare inherited retinal degeneration. To understand the early molecular changes that make the eye susceptible to damage, we performed quantitative proteomic and metabolomic profiling of liver, retina, and retinal pigment epithelium and choroid (RPE/Cho) from OAT-deficient (Oatrhg) mice prior to detectable vision impairment. In addition to reduced OAT expression and elevated ornithine, methylation-related metabolites such as N(6)-methyl-lysine were altered in all examined tissues of Oatrhg mice. In the liver, excess ornithine was directed into urea cycle metabolism, together with altered expression of detoxification enzymes and histone H2B proteins. In contrast, the retina showed minimal proteomic changes but pronounced alterations in amino acid pathways that support glutamate homeostasis. The RPE/Cho demonstrated the most extensive proteomic changes, particularly in mitochondrial metabolism, cytoskeleton, and extracellular matrix, along with changes in metabolites involved in lysine metabolism, energy metabolism, and antioxidant capacity. Incubation with 13C lysine demonstrated that lysine was primarily degraded in RPE/Cho but not the retina, and ornithine enhanced lysine degradation in an OAT-dependent manner. Together, these findings highlight common and tissue-specific impacts of OAT on the liver and ocular tissues and provide insight into early molecular changes that contribute to the selective vulnerability of the eye in GA. Proteomics data are available via ProteomeXchange (PXD063614) and metabolomics data via MassIVE repository (MSV000101103).

Animals↗

Multiomic insights into fungal polylactic acid degradation: Metabolic adaptation and hydrolytic mechanisms of Sporobolomyces pararoseus.

Polylactic acid (PLA), a biodegradable polyester from renewable resources, is a sustainable alternative to petrochemical plastics. However, its environmental degradation is inefficient naturally, requiring specific microbial activities. While bacterial PLA-degrading mechanisms are well documented, fungal degrading systems-particularly their molecular mechanisms-are underexplored.We isolated Sporobolomyces pararoseus ZRQ01 from the gut microbiota of PLA-fed mealworms. This fungal strain noticeably degraded PLA in PLA-containing medium supplemented with 2% glucose. Biodegradation assays revealed 22.8% loss of the PLA film weight after 35&#xa0;days of incubation, and scanning electron microscopy confirmed extensive surface erosion and pore formation. Integrated transcriptomic and proteomic analyses, together with the reference genome of S. pararoseus ZRQ01, revealed that S. pararoseus ZRQ01 upregulates hydrolytic enzymes at both transcript and protein levels to cleave PLA into lactic acid. After lactic acid is transferred into S. pararoseus ZRQ01 cells by monocarboxylate transporters with increased abundance, it is assimilated by pathways of pyruvate metabolism and the TCA cycle with increased protein abundance. Intriguingly, upregulation of genes in autophagy-related and MAPK signaling pathways underscores an adaptive stress response potentially supporting cellular homeostasis and degradation-related gene expression. Our results highlight S. pararoseus ZRQ01's metabolic potential for bioremediation and offer insights into fungal bioplastic degradation pathways.

Polyesters↗

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP&#xa0;+&#xa0;AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗

Temporal proteomic analysis reveals a three-phase adaptation strategy in Phytophthora cinnamomi during salinity stress.

Phytophthora cinnamomi, a highly invasive hemibiotrophic oomycete, threatens global agriculture, forestry, and native ecosystems. Although drought and temperature effects on P. cinnamomi-host interactions are well studied, current knowledge of abiotic stress responses in P. cinnamomi remains largely centered on infection and phytopathology, with limited molecular insight into the pathogen's direct response to salinity independent of its host. To address this gap, we combined growth assays, time-resolved proteomics, and network analysis to define how P. cinnamomi responds and adapts to salinity exposure. Growth assays showed that NaCl-modified agar enhanced mycelial expansion in a concentration-dependent manner, with 100&#xa0;mM NaCl significantly increasing growth at 48, 72, and 96&#xa0;h compared with controls, while 50&#xa0;mM NaCl remained comparable to control conditions. Temporal proteomic analysis of 100&#xa0;mM NaCl treatment at 0, 1, 6, 12, and 24&#xa0;h post treatment revealed dynamic shifts in protein abundance. Early induction of ROS (Reactive Oxygen Species)-detoxifying enzymes, including glutathione S-transferases and peroxidases, was consistent with ROS-specific staining assays. Network analysis identified modules enriched for redox regulation, ATP generation, ion transport, and translational control, highlighting multi-layered adaptation to elevated NaCl levels. Notably, clusters of conserved hypothetical proteins were strongly upregulated, indicating unexplored stress tolerance components in Phytophthora species. Here, we propose that P. cinnamomi rapidly activates a three-phase strategy involving metabolism readjustments, redox defenses, and cellular structure alterations under salinity conditions. With increasing soil salinization due to climate change, our study provides first mechanistic insights into P. cinnamomi's adaptive plasticity and ecological resilience to abiotic stress. SIGNIFICANCE: This study represents the first temporal proteomic analysis of salinity stress adaptation in Phytophthora cinnamomi, revealing a sophisticated three-phase adaptation strategy. This research fundamentally advances our understanding of how this globally destructive plant pathogen, P. cinnamomi, maintains environmental resilience. Our findings reveal proteome remodelling as a mechanistic framework for understanding stress tolerance in oomycetes, a group of microorganisms responsible for some of the world's most destructive agricultural and forest diseases. Our results show proteins involved in emergency damage control through metabolic recalibration to sustained adaptation. These findings have relevance for predicting pathogen behavior under climate change scenarios, where increasing soil salinity threatens agricultural productivity while simultaneously enhancing pathogen survival and virulence. Understanding how P. cinnamomi responds to prolonged salinity exposure may inform targeted biocontrol strategies and improve predictive models of disease pressure in salt-affected agricultural regions. The temporal analysis framework we present offers a broadly applicable approach for understanding microbial stress adaptation, with implications extending beyond plant pathology to environmental microbiology and biotechnology applications where stress tolerance is paramount.

Phytophthora↗

Proteomic and phosphoproteomic profiles of time-dependent dynamic changes in LPS-induced macrophage polarization.

The temporal proteomic and phosphoproteomic reprogramming during early M1 macrophage polarization (0-6&#xa0;h) remains poorly understood. We performed time-resolved proteomic and phosphoproteomic analyses of LPS-stimulated RAW264.7 macrophages at seven time points within 6&#xa0;h. Time-clustering of differentially expressed molecules revealed two patterns: initial change with partial recovery, and sustained dysregulation. Upregulated proteins and phosphorylation sites were enriched in the Rho GTPase signaling pathway, T-cell receptor signaling pathway, NF-&#x3ba;B cascade, osteoclast differentiation pathway, and antiviral immune pathway. Downregulated pathways were associated with cell cycle regulation, chromatin remodeling, RNA metabolism, and mRNA processing, indicating resource reallocation to prioritize acute inflammatory responses. Kinase-substrate network analysis confirmed the mitogen-activated protein kinase (MAPK), cyclin-dependent kinase (CDK), protein kinase B (AKT), and ribosomal S6 kinase (RSK) families as core upstream phosphorylation regulators. Integrated analysis revealed synergistic and antagonistic relationships between proteomic and phosphoproteomic changes. This study provides a temporal molecular atlas of M1 polarization, delineating inflammatory signaling dynamics and offering a basis for therapeutic target discovery in inflammatory diseases. SIGNIFICANCE: Macrophage M1 polarization is a central event in innate immune defense against pathogenic invasion, yet its dysregulation is a pivotal driver of the onset and progression of a broad spectrum of inflammation-associated disorders, spanning autoimmune diseases, infectious conditions and inflammatory bone diseases, making the dissection of its molecular regulatory mechanisms an urgent research priority in immunology and translational medicine. Dynamic molecular events within 0-6&#xa0;h after LPS stimulation are critical for initiating and shaping M1 inflammatory activation, yet systematic time-resolved proteomic and phosphoproteomic profiling remains insufficient.In this study, we comprehensively characterized temporal proteome and phosphoproteome changes at seven consecutive time points during macrophage polarization, clarified two distinct dynamic molecular patterns, identified core signaling pathways and key kinase regulators involved in inflammatory reprogramming, and uncovered the leading role of post-translational phosphorylation modifications in initiating polarization. This work delineates the time-series molecular atlas of early macrophage activation, provides novel insights into the temporal regulatory mechanism of inflammatory signaling networks, and lays a solid experimental foundation for exploring new intervention targets and regulatory nodes in clinical translational research.

Lipopolysaccharides↗

Plasma proteomics reveal SERPINA1 and CD59 as candidate biomarkers for COVID-19 severity stratification and prognosis prediction.

BACKGROUND: COVID-19 has been closely associated with coagulation abnormalities. However, existing biomarkers, including D-dimer and fibrin degradation products (FDP), exhibit limited accuracy in stratifying disease severity and predicting long-term clinical outcomes. OBJECTIVES: This study aimed to use proteomic analysis to identify plasma biomarkers associated with COVID-19 severity and prognosis, and validate their predictive utility for mortality and thromboembolic complications. METHODS: Plasma proteomic profiles were analyzed across three COVID-19 severity classes. Differential expression analysis and functional analysis were performed. Clustering analysis was used to identify proteins correlated with disease severity. Candidate biomarkers were validated in an independent cohort. Predictive performance of the biomarkers for mortality, sepsis and venous thromboembolism was evaluated using bootstrap-corrected ROC analyses and multivariable regression analyses. RESULTS: Proteomic analysis revealed progressive involvement of the coagulation and complement pathway with increasing disease severity. SERPINA1 and CD59 were identified as candidate biomarkers and exhibited significantly higher plasma levels in severe cases. Bootstrap-corrected ROC analyses demonstrated strong predictive performance: SERPINA1 achieved AUCs of 0.775 and 0.924 for 30-day and 12-month mortality, and CD59 achieved AUCs of 0.720 for sepsis; the combined model further improved prediction of 12-month mortality (AUC 0.946) and sepsis (AUC 0.904), outperforming D-dimer and FDP. Multivariable regression confirmed their independent prognostic value. CONCLUSION: This exploratory study identifies SERPINA1 and CD59 as candidate prognostic biomarkers in COVID-19, highlighting the role of coagulation and complement-related pathways in disease severity and warranting further prospective validation.

Humans↗

From prediction to mechanism: Explainable AI uncovers plasma and CSF proteomic signatures of Alzheimer's disease.

Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 2082 modality specific samples, all analysed internally within ADNI. Phase 1 analysed plasma using a 119 analyte NULISA and targeted UPENN panel (n&#xa0;=&#xa0;727; 216&#xa0;CE, 511 controls). Phase 2 extended the analysis to CSF using SOMAscan7k, TMT-MS and targeted SET2, with Elecsys A&#x3b2;42, A&#x3b2;40, total tau and p-tau181 as anchor biomarkers. Only SOMAscan was subject-independent relative to Phase 1 plasma; TMT-MS and SET2 overlapped with Phase 1 for 96.0% and 97.7% of subjects and therefore are not independent replication cohorts. Under subject-level splits with fold internal preprocessing, we compared Elastic Net, Explainable Boosting Machines and gradient boosted trees with SHAP-based explanations. Among the candidate pipelines, we selected the pipeline with the highest held-out test ROC AUC for each platform; the selected values were 0.927 in plasma and 0.954-0.973 across the three CSF datasets. Because the same held out test performance was used for pipeline selection and headline reporting, these are optimistically selected single-holdout estimates, not unbiased estimates of generalizable or clinical performance. Explanations identified five recurring biological axes within ADNI: cholinergic (ACHE), tau/14-3-3 (YWHAG, YWHAZ, YWHAB, YWHAE), neuro-axonal (NEFL, NEFH), microglial/complement (CHIT1, SMOC1, CHI3L1, C7, CFH) and synaptic (NPTXR, NPTX2, DLG4, SYT5, VSNL1, ELAVL2). CSF analyses showed synaptic vesicle-cycle enrichment (q&#xa0;=&#xa0;2&#xa0;&#xd7;&#xa0;10-6), and CSF YWHAG correlated strongly with total tau (&#x3c1;&#xa0;=&#xa0;0.87). Cross-fluid directional concordance was modest overall (54-57%) but increased to 73-80% among mapped analyte/protein rows reaching q&#xa0;<&#xa0;0.05 in CSF. These findings provide hypothesis-generating, internally supported evidence within ADNI. Independent external cohorts with locked pipelines are required to evaluate generalizable performance and biological reproducibility; the overlapping TMT-MS and SET2 analyses should not be interpreted as independent replication.

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