Asian Pac J Cancer Prev. 2025 Jul 1;26(7):2511-2520. doi: 10.31557/APJCP.2025.26.7.2511.

ABSTRACT

BACKGROUND: Colorectal cancer (CRC) is intricately influenced by dysregulated microRNAs (miRNAs) targeting the Wnt signaling pathway, a phenomenon pivotal in CRC initiation and progression. The exploration of miRNA-Wnt interactions holds promise for innovative therapeutic strategies in CRC treatment.

METHODS: a comprehensive list of genes influenced by dysregulated miRNAs targeting the Wnt pathway was compiled. High-scoring genes from the miRDB database underwent further analysis. Protein-protein interaction networks were constructed using Cytoscape and StringApp 2.0, with hub proteins identified through MCC, MNC, DMNC, and Degree algorithms. Gene ontology, KEGG enrichment analysis, CytoCluster, and promoter motif analysis were employed to characterize gene functions, associations, dysregulated clusters, and regulatory elements.

RESULTS: Protein-protein interaction networks unveiled 15 central hub proteins, including EP300, , NRAS, NF1, CCND1, SMAD4, SOCS7, SOCS6, NECAP1, MBTD1, ACVR1C, ESR1, CREBBP, and PIK3CA. Gene ontology and KEGG analysis revealed their involvement in critical biological processes, cellular components, and molecular functions. CytoCluster analysis identified dysregulated miRNA-targeted gene clusters linked to cancer-related pathways. Promoter motif analysis provided insights into regulatory elements governing hub protein expression.

CONCLUSION: The identified hub proteins, enriched in cancer-related pathways, offer potential therapeutic targets. These findings pave the way for future research, enhancing our ability to develop targeted interventions for improved outcomes in CRC treatment.

PMID:40729072 | DOI:10.31557/APJCP.2025.26.7.2511

Curr Issues Mol Biol. 2025 Jul 21;47(7):575. doi: 10.3390/cimb47070575.

ABSTRACT

Vibrio parahaemolyticus is a pathogenic bacterium widely distributed in marine environments, posing significant threats to aquatic organisms and human health. The overuse and misuse of antibiotics has led to the development of multidrug- and pan-resistant V. parahaemolyticus strains. There is an urgent need for novel antibacterial therapies with innovative mechanisms of action. In this work, a genome-scale metabolic network model (GMSN) of V. parahaemolyticus, named VPA2061, was reconstructed to predict the metabolites that can be explored as potential drug targets for eliminating V. parahaemolyticus infections. The model comprises 2061 reactions and 1812 metabolites. Through essential metabolite analysis and pathogen-host association screening with VPA2061, 10 essential metabolites critical for the survival of V. parahaemolyticus were identified, which may serve as key candidates for developing new antimicrobial strategies. Additionally, 39 structural analogs were found for these essential metabolites. The molecular docking analysis of the essential metabolites and structural analogs further investigated the potential value of these metabolites for drug design. The GSMN reconstructed in this work provides a new tool for understanding the pathogenic mechanisms of V. parahaemolyticus. Furthermore, the analysis results regarding the essential metabolites hold profound implications for the development of novel antibacterial therapies for V. parahaemolyticus-related disease.

PMID:40729044 | DOI:10.3390/cimb47070575

Acta Neuropathol. 2025 Jul 29;150(1):10. doi: 10.1007/s00401-025-02913-3.

ABSTRACT

Development of therapeutic approaches that target specific microglia responses in amyotrophic lateral sclerosis (ALS) is crucial due to the involvement of microglia in ALS progression. Our study identifies the predominant microglia subset in human ALS primary motor cortex and spinal cord as an undifferentiated phenotype with dysregulated respiratory electron transport. Moreover, we find that the interferon response microglia subset is enriched in donors with aggressive disease progression, while a previously described potentially protective microglia phenotype is depleted in ALS. Additionally, we observe an enrichment of non-microglial immune cell, mainly NK/T cells, in the ALS central nervous system, primarily in the spinal cord. These findings pave the way for the development of microglia subset-specific therapeutic interventions to slow or even stop ALS progression.

PMID:40728732 | DOI:10.1007/s00401-025-02913-3

J Proteome Res. 2025 Jul 29. doi: 10.1021/acs.jproteome.5c00278. Online ahead of print.

ABSTRACT

Protein phosphorylation, a key post-translational modification, is central to cellular signaling and disease pathogenesis. The development of high-throughput proteomics pipelines has led to the discovery of large numbers of phosphorylated protein motifs and sites (phosphosites) across many eukaryotic species. However, the majority of phosphosites are reported from human samples, with most species having a few experimentally confirmed or computationally predicted phosphosites. Furthermore, only a small fraction of the characterized human phosphoproteome has an annotated functional role. A common way of predicting functional phosphosites is through conservation-based sequence analysis, but large-scale evolutionary studies are scarce. In this study, we explore the conservation of 20,751 confident human phosphosites across 100 eukaryotic species and investigate the evolution of associated protein domains and kinases. We categorize protein functions based on phosphosite conservation patterns and demonstrate the importance of conservation analysis in identifying organisms suitable as biological models for studying conserved signaling pathways relevant to human biology and disease. Finally, we use human protein sequences as a reference for propagating over 1,000,000 potential phosphosites to other eukaryotes. Our results can improve proteome annotations of several species and help direct research aimed at exploring the evolution and functional relevance of phosphorylation.

PMID:40728433 | DOI:10.1021/acs.jproteome.5c00278

MedComm (2020). 2025 Jul 27;6(8):e70300. doi: 10.1002/mco2.70300. eCollection 2025 Aug.

ABSTRACT

This study aimed to investigate the efficacy, safety, and predictors of camrelizumab combined with carboplatin and nab-paclitaxel as first-line setting for patients with extensive-stage small-cell lung cancer (ES-SCLC). Camrelizumab plus carboplatin and nab-paclitaxel were administrated every 3 weeks for four to six cycles, followed by maintenance camrelizumab until intolerable toxicity or disease progression. The primary endpoint was 6-month progression-free survival (PFS) rate and secondary endpoints were objective response rate (ORR), disease control rate (DCR), PFS, overall survival (OS), and safety. We conducted the whole-exome and transcriptomic sequencing on available tumor samples to explore the potential predictive biomarkers. A total of 60 patients were included. Primary endpoint was met with 6-month PFS rate of 52.2%. The median PFS and OS were 7.1 and 18.1 months, respectively. The confirmed ORR and DCR were 73.3% and 93.3%, respectively. No unexpected adverse events were observed. Exploratory analysis showed that MUC17 alterations or high NEUROG1 expression were correlated with markedly shorter PFS and OS. Deeper investigation of transcriptomic data reveals two subsets with distinct immune features and therapeutic vulnerabilities. Collectively, this trial suggested that camrelizumab plus carboplatin and nab-paclitaxel might be an alternative first-line setting for ES-SCLC. Integration of multiomic data could highlight the complex mechanisms underlying chemo-immunotherapy responses.

PMID:40727251 | PMC:PMC12301171 | DOI:10.1002/mco2.70300

Curr Opin Syst Biol. 2023 Dec;36:100482. doi: 10.1016/j.coisb.2023.100482. Epub 2023 Oct 31.

ABSTRACT

Anthropogenic carbon emissions are driving rapid changes to the earth's climate, disrupting whole ecosystems and endangering the stability of human society. Innovations in engineered microbial fermentation enable the fossil resource-free production of fuels, commodity chemicals, and materials, thereby reducing the carbon emissions associated with these products. Microorganisms have been engineered to catabolize sustainable sources of carbon and energy (i.e., plant biomass, plastic waste, and one-carbon feedstocks) and biosynthesize carbon-neutral or carbon-negative products. These engineering efforts exploit and optimize natural biological pathways or generate unnatural pathways which can biosynthesize chemicals that have not yet been accessed using synthetic chemistry. Recent advances in microbial fermentation seek not only to maximize the titer, rate, and yield of desired products, but also to tailor microbial catabolism to utilize inexpensive feedstocks. Ultimately, these advances aim to lower the cost of bioproduction so that microorganism-derived chemicals can be economically competitive with fossil-derived chemicals.

PMID:40726999 | PMC:PMC12302915 | DOI:10.1016/j.coisb.2023.100482

Front Immunol. 2025 Jul 14;16:1543529. doi: 10.3389/fimmu.2025.1543529. eCollection 2025.

ABSTRACT

INTRODUCTION: Ovarian cancer (OVCA) has a five-year survival rate of approximately 45%, with little improvement over recent decades. Although anti-PD-L1 therapies have shown substantial efficacy in other solid tumors, their effectiveness in OVCA has been limited. These treatments target only membranous and soluble forms of PD-L1, without addressing nuclear-localized PD-L1. The role of nuclear PD-L1 in OVCA chemoresistance, however, remains largely unexplored. In this study, we examined the prognostic significance of nuclear PD-L1 and its interactions with plasma gelsolin (pGSN) and CD8+ T cells within the tumor microenvironment.

METHODS: Using immunofluorescence, we quantified nuclear PD-L1, pGSN, and additional markers in OVCA samples. Statistical analyses and machine learning approaches were employed to assess associations between marker expression, patient outcomes, and chemoresistance.

RESULTS: Increased nuclear PD-L1 was associated with disease recurrence, chemoresistance and poor overall survival. Although CD8+ T cells provided survival benefits to patients, elevated PD-L1 hindered these benefits resulting in shortened disease free (DFS) and overall survival (OS). Co-expression of PD-L1 and pGSN was also associated with shortened DFS, OS and chemoresistance.

DISCUSSION: These findings indicate that nuclear PD-L1 serves as a poor prognostic marker in OVCA, being associated with tumor recurrence, chemoresistance, and reduced overall survival. Targeting nuclear PD-L1 may represent a novel therapeutic strategy to improve outcomes in patients with OVCA.

PMID:40726982 | PMC:PMC12301380 | DOI:10.3389/fimmu.2025.1543529

J Proteome Res. 2025 Jul 29. doi: 10.1021/acs.jproteome.5c00203. Online ahead of print.

ABSTRACT

Poor therapeutic indexes are a principal cause of drug attrition during development. To develop multiomic methods for elucidating potentially targetable mechanisms of drug toxicity, we performed profiling of the response to subtoxic and toxic doses of l-Asparaginase (ASNase) in immune-compromised mice. ASNase is an enzyme-drug approved for the treatment of pediatric acute lymphoblastic leukemia (ALL) but too toxic for use in adults, making it an ideal test case. We collected 20-μL whole blood samples longitudinally, processed them to plasma, and extracted three molecule types (metabolites, lipids, and proteins) from each sample. We then analyzed the extracts using multiple reaction monitoring (MRM) of 500+ water-soluble metabolites, 750+ lipids, and 375 peptides on a triple quadrupole LC-MS/MS platform. Metabolites, lipids, and peptides that were modulated in a dose-dependent manner appeared to converge on antioxidation, inflammation, autophagy, and cell death pathways, prompting the hypothesis that inhibiting one or more of those pathways might decrease ASNase toxicity while preserving anticancer activity. The present studies were not designed to address therapeutic index directly, because efficacy was not studied. We provide here a streamlined, three-in-one LC-MS/MS workflow for targeted metabolomics, lipidomics, and proteomics and, as a proof of principle, demonstrate its ability to generate new hypotheses about mechanisms of ASNase toxicity.

PMID:40726195 | DOI:10.1021/acs.jproteome.5c00203

Bioinformatics. 2025 Jul 1;41(7):btaf398. doi: 10.1093/bioinformatics/btaf398.

ABSTRACT

SUMMARY: Legionella pneumophila has significantly contributed to multiple cases of pneumonia with a high rate of mortality globally. Its ability to exploit host mechanisms through several expressed virulence factors poses challenges for diagnosis, treatment, and outbreak control. To address this, we developed LegionProfiler, a computational tool that swiftly identifies virulence factor protein domains within genome assemblies of Legionella pneumophila serogroup 1 isolates and classifies them into high- or low-virulence groups. LegionProfiler automates the probing of genome assemblies for virulence-associated protein domains and determines the isolate's potential to cause severe pneumonia infection. The LegionProfiler workflow is made available through a user-friendly interface to enhance technical control of infectious sources and adds important insights to the general epidemiology of clinical isolates. It could also support the development of targeted therapeutic strategies that will improve patient treatment.

AVAILABILITY AND IMPLEMENTATION: LegionProfiler is freely accessible as a web service at https://legionprofiler.uni-muenster.de, and can also be run locally in a Docker container. The source code can be found at https://imigitlab.uni-muenster.de/heiderlab/legionprofiler or at Zenodo (DOI: 10.5281/zenodo.15592325).

PMID:40726111 | DOI:10.1093/bioinformatics/btaf398

Plant J. 2025 Jul;123(2):e70349. doi: 10.1111/tpj.70349.

ABSTRACT

Growth-limiting droughts (GLD) impair tissue expansion and delay developmental transitions but are often not considered as stressors, as many physiological traits are only slightly altered relative to well-watered counterparts. Concurrently, cell size, biochemical makeup, and transcriptome profiles vary along the leaf blade in accordance with the partitioning of distinct functions to spatially defined regions of the leaf. This suggests that because different parts of the leaf have underlying differences in their transcriptome profiles, they might respond to GLD in distinctive ways. Moreover, how antagonistic stressors influence physiology and gene expression in different zones of leaves is an open question. In this study, we profiled growth, anatomy, and gas exchange in Asian rice (Oryza sativa) leaves developed in well-watered and GLD conditions, with or without a secondary heat shock. We dissected leaves into seven equal-length segments for transcriptome analysis in these conditions. We hypothesized that GLD would make the leaves more sensitive to heat shock and would disrupt the underlying heterogeneity of the leaf transcriptome. GLD plants were more strongly affected by heat shock with respect to gas exchange and the number and types of genes that were differentially expressed and that these differences varied along the leaf blade. We developed an eFP browser tool with these data to facilitate exploration and hypothesis testing. These findings show that even mild drought treatments are sufficient to impact responses to antagonistic stressors and that substantial within-organ variance exists with respect to stress responses.

PMID:40726041 | DOI:10.1111/tpj.70349

Genes (Basel). 2025 Jul 17;16(7):832. doi: 10.3390/genes16070832.

ABSTRACT

BACKGROUND: Dendritic cells (DCs) play an important role as a bridge between innate and adaptive immunity, and changes in gene expression of DCs during the immune response to Mycobacterium tuberculosis (M.tb) may affect the development of tuberculosis.

METHODS: Using systems biology methods, mRNA and miRNA expression profile data of DCs infected with M.tb were obtained. A total of 1398 differentially expressed mRNAs and 79 differentially expressed miRNAs were identified, and a corresponding miRNA-mRNA regulatory network was constructed using Cytoscape 3.9.1 software. The functional annotations and pathway classifications of the miRNA-mRNA network were identified using the DAVID tool. Then, the key pathway modules in the miRNA-mRNA network were screened and subjected to PPI network analysis to identify hub nodes. Subsequently the miRNA/mRNA axis was determined, validated by qRT-PCR, and evaluated through ROC curve analysis.

RESULTS: The TNF signaling pathway and the Tuberculosis pathway were key pathway modules, with miR-34a-3p/TNF and miR-190a-3p/IL1B being the greatest correlations with the two pathway modules. qRT-PCR results showed that IL1B and miR-190a-3p exhibited significant differences in both the H37Ra and BCG infection groups. The AUC of two factors (IL1B and miR-190a-3p) was 0.9561 and 0.9625, respectively, showing high sensitivity and specificity.

CONCLUSIONS: Consequently, miR-190a-3p/IL1B might be a good candidate marker to characterize the immune response of DCs to M.tb and a transition signal from innate to adaptive immunity.

PMID:40725488 | DOI:10.3390/genes16070832

Genes (Basel). 2025 Jul 11;16(7):814. doi: 10.3390/genes16070814.

ABSTRACT

BACKGROUND/OBJECTIVES: Cardiac aging involves the progressive structural and functional decline of the myocardium. Endurance training is a well-recognized non-pharmacological intervention that counteracts this decline, yet the molecular mechanisms driving exercise-induced cardiac rejuvenation remain inadequately elucidated. This study aimed to identify key effector genes and regulatory pathways by integrating human cardiac aging transcriptomic data with multi-omic exercise response datasets.

METHODS: A systems biology framework was developed to integrate age-downregulated genes (n = 243) from the GTEx human heart dataset and endurance-exercise-responsive genes (n = 634) from the MoTrPAC mouse dataset. Thirty-seven overlapping genes were identified and subjected to Enrichr for pathway enrichment, KEA3 for kinase analysis, and ChEA3 for transcription factor prediction. Candidate effector genes were ranked using ToppGene and ToppNet, with integrated prioritization via the FLAMES linear scoring algorithm.

RESULTS: Pathway enrichment revealed complementary patterns: aging-associated genes were enriched in mitochondrial dysfunction and sarcomere disassembly, while exercise-responsive genes were linked to protein synthesis and lipid metabolism. TTN, PDK family kinases, and EGFR emerged as major upstream regulators. NKX2-5, MYOG, and YBX3 were identified as shared transcription factors. SMPX ranked highest in integrated scoring, showing both functional relevance and network centrality, implying a pivotal role in mechano-metabolic coupling and cardiac stress adaptation.

CONCLUSIONS: By integrating cardiac aging and exercise-responsive transcriptomes, 37 effector genes were identified as molecular bridges between aging decline and exercise-induced rejuvenation. Aging involved mitochondrial and sarcomeric deterioration, while exercise promoted metabolic and structural remodeling. SMPX ranked highest for its roles in mechano-metabolic coupling and redox balance, with X-inactivation escape suggesting sex-specific relevance. Other top genes (e.g., KLHL31, MYPN, RYR2) form a regulatory network supporting exercise-mediated cardiac protection, offering targets for future validation and therapy.

PMID:40725470 | DOI:10.3390/genes16070814

Genes (Basel). 2025 Jun 27;16(7):753. doi: 10.3390/genes16070753.

ABSTRACT

BACKGROUND: Deficiency of IL-36 Receptor Antagonist (DITRA) is a rare monogenic autoinflammatory disease, characterized by dysregulation of IL-36 signaling and phenotypically classified as a subtype of generalized pustular psoriasis.

OBJECTIVES: This study aimed to explore the role of potentially coding and non-coding RNAs (ncRNAs) in the IL36RN interactome to identify putative pathogenic mechanisms, biomarkers, and therapeutic targets for DITRA.

METHODS: A systems biology approach was applied using the STRING database to construct the IL36RN protein-protein interaction network. Key ncRNA interactions were identified using RNAInter. The networks were visualized and analyzed with Cytoscape v3 and the CytoHubba plugin to identify central nodes and interaction hubs. Pathway enrichment analysis was then performed to determine the biological relevance of candidate ncRNAs and genes.

RESULTS: Analysis identified thirty-eight ncRNAs interacting with the IL36RN network, including six lncRNAs and thirty-two miRNAs. Of these, thirty-three were associated with key DITRA-related signaling pathways, while five remain to be validated. Additionally, seven protein-coding genes were highlighted, with three (TINCR, PLEKHA1, and HNF4A) directly implicated in biological pathways related to DITRA. Many of the identified ncRNAs have prior associations with immune-mediated diseases, including psoriasis, supporting their potential relevance in DITRA pathogenesis.

CONCLUSIONS: This study provides novel insights into the ncRNA-mediated regulation of IL36RN and its network in the context of DITRA. The findings support the potential utility of specific ncRNAs and genes, such as TINCR, PLEKHA1, and HNF4A, as key genomic elements warrant further functional characterization to confirm their mechanistic roles and may inform biomarker discovery and targeted therapeutic development in DITRA.

PMID:40725409 | DOI:10.3390/genes16070753

Int J Mol Sci. 2025 Jul 21;26(14):6996. doi: 10.3390/ijms26146996.

ABSTRACT

Polypharmacology, the rational design of small molecules that act on multiple therapeutic targets, offers a transformative approach to overcome biological redundancy, network compensation, and drug resistance. This review outlines the scientific rationale for polypharmacology, highlighting its success across oncology, neurodegeneration, metabolic disorders, and infectious diseases. Emphasis is placed on how polypharmacological agents can synergize therapeutic effects, reduce adverse events, and improve patient compliance compared to combination therapies. We also explore how computational methods-spanning ligand-based modeling, structure-based docking, network pharmacology, and systems biology-enable target selection and multi-target ligand prediction. Recent advances in artificial intelligence (AI), particularly deep learning, reinforcement learning, and generative models, have further accelerated the discovery and optimization of multi-target agents. These AI-driven platforms are capable of de novo design of dual and multi-target compounds, some of which have demonstrated biological efficacy in vitro. Finally, we discuss the integration of omics data, CRISPR functional screens, and pathway simulations in guiding multi-target design, as well as the challenges and limitations of current AI approaches. Looking ahead, AI-enabled polypharmacology is poised to become a cornerstone of next-generation drug discovery, with potential to deliver more effective therapies tailored to the complexity of human disease.

PMID:40725243 | DOI:10.3390/ijms26146996

Int J Mol Sci. 2025 Jul 20;26(14):6966. doi: 10.3390/ijms26146966.

ABSTRACT

Spinal cord injury (SCI) remains one of the toughest obstacles in neuroscience and regenerative medicine due to both severe functional loss and limited healing ability. This article aims to provide a key integrative, mechanism-focused review of the molecular landscape of SCI and the new disruptive therapy technologies that are now evolving in the SCI arena. Our goal is to unify a fundamental pathophysiology of neuroinflammation, ferroptosis, glial scarring, and oxidative stress with the translation of precision treatment approaches driven by artificial intelligence (AI), CRISPR-mediated gene editing, and regenerative bioengineering. Drawing upon advances in single-cell omics, systems biology, and smart biomaterials, we will discuss the potential for reprogramming the spinal cord at multiple levels, from transcriptional programming to biomechanical scaffolds, to change the course from an irreversible degeneration toward a directed regenerative pathway. We will place special emphasis on using AI to improve diagnostic/prognostic and inferred responses, gene and cell therapies enabled by genomic editing, and bioelectronics capable of rehabilitating functional connectivity. Although many of the technologies described below are still in development, they are becoming increasingly disruptive capabilities of what it may mean to recover from an SCI. Instead of prescribing a particular therapeutic fix, we provide a future-looking synthesis of interrelated biological, computational, and bioengineering approaches that conjointly chart a course toward adaptive, personalized neuroregeneration. Our intent is to inspire a paradigm shift to resolve paralysis through precision recovery and to be grounded in a spirit of humility, rigor, and an interdisciplinary approach.

PMID:40725213 | DOI:10.3390/ijms26146966

Int J Mol Sci. 2025 Jul 19;26(14):6946. doi: 10.3390/ijms26146946.

ABSTRACT

Gramicidin S (GS), an antimicrobial peptide (AMP), exhibits broad-spectrum activity against bacteria and cancer cells but is limited in clinical use due to its cytotoxicity toward eukaryotic cells. Lipid-based delivery systems may overcome this limitation; in this study, we proposed and tested simple and promising lipid formulations, including dipalmitoylphosphatidylcholine (DPPC), cardiolipin (CL), and cholesterol (CHOL). We evaluated the interactions of these lipid membranes with GS by assessing membrane fluidity, dielectric permittivity, dielectric losses, dielectric relaxation frequency, and static dielectric constant. Among these, membrane fluidity and dielectric permittivity were the most sensitive to GS, showing significant changes in the formulation containing 90 mol% DPPC and 10 mol% CHOL when exposed to 20 μM GS. Notably, although membrane fluidity changed in a dose-dependent manner following GS binding, the liposomes still supported relatively high GS concentrations-up to 80 μM-which is important for future high-dose GS applications. Additionally, we performed preliminary cytotoxicity tests comparing free GS with liposome-carried GS using the tested lipid compositions and observed a significant reduction in GS-associated toxicity on L929 cell line. This study provides new insights into GS-membrane interactions and supports the rational design of AMP nanocarriers for biomedical applications.

PMID:40725193 | DOI:10.3390/ijms26146946

Int J Mol Sci. 2025 Jul 18;26(14):6925. doi: 10.3390/ijms26146925.

ABSTRACT

Redox signaling is central to plant adaptation, influencing metabolic regulation, stress responses, and developmental processes through thiol-based oxidative post-translational modifications (oxiPTMs) of redox-sensitive proteins. These modifications, particularly those involving cysteine (Cys) residues, act as molecular switches that alter protein function, structure, and interactions. Advances in mass spectrometry-based redox proteomics have greatly enhanced the identification and quantification of oxiPTMs, enabling a more refined understanding of redox dynamics in plant cells. In parallel, the emergence of computational modeling, artificial intelligence (AI), and machine learning (ML) has revolutionized the ability to predict redox-sensitive residues and characterize redox-dependent signaling networks. This review provides a comprehensive synthesis of methodological advancements in redox proteomics, including enrichment strategies, quantification techniques, and real-time redox sensing technologies. It also explores the integration of computational tools for predicting S-nitrosation, sulfenylation, S-glutathionylation, persulfidation, and disulfide bond formation, highlighting key models such as CysQuant, BiGRUD-SA, DLF-Sul, and Plant PTM Viewer. Furthermore, the functional significance of redox modifications is examined in plant development, seed germination, fruit ripening, and pathogen responses. By bridging experimental proteomics with AI-driven prediction platforms, this review underscores the future potential of integrated redox systems biology and emphasizes the importance of validating computational predictions, through experimental proteomics, for enhancing crop resilience, metabolic efficiency, and precision agriculture under climate variability.

PMID:40725172 | DOI:10.3390/ijms26146925

Int J Mol Sci. 2025 Jul 18;26(14):6920. doi: 10.3390/ijms26146920.

ABSTRACT

Phenothiazines, mainly known for their antipsychotic activity, have recently attracted attention as potential compounds with anticancer and immunomodulatory activity In this study, 20 new quinobenzothiazines (MJ1-MJ20) were synthesized and their effects on normal cell lines (BEAS-2B, NHDF) and cancer cell lines (HCT116, MCF7, A549, SH-SY5Y, U2OS) were investigated. The studies included cytotoxicity assessment, analysis of the expression of genes (BCL2, AIFM2, MDM2) and pro-inflammatory cytokines (IL6, IL8) using the RT-qPCR method, and prediction of biological activity using the PASS platform. The results indicate that the compounds MJ19 and MJ20 have the greatest effect on the induction of pro-inflammatory (IL6, IL8) and antiapoptotic (BCL2, MDM2) genes, suggesting their potential use in therapies for inflammatory and autoimmune diseases. Gene expression analysis showed that compound MJ2 in BEAS-2B cells significantly induced the expression of AIFM2, a protein responsible for protecting against ferroptosis, while moderately increasing the expression of BCL2 and MDM2, suggesting a potential role for MJ2 in the modulation of protective mechanisms of healthy cells, e.g., avoiding apoptosis death. These results emphasize the potential of quinobenzothiazines as multifunctional bioactive compounds, which require further studies to determine their mechanisms of action and specificity.

PMID:40725171 | DOI:10.3390/ijms26146920

Int J Mol Sci. 2025 Jul 18;26(14):6923. doi: 10.3390/ijms26146923.

ABSTRACT

Humulus lupulus L. (hop) is a multipurpose crop valued for its essential role in beer production and for its bioactive compounds with recognized medicinal properties. Otherwise, climate change represents a major challenge to agriculture, particularly impacting the cultivation of crops with stenoecious characteristics, such as hop. This highlights the urgent need to enhance crop resilience to adverse environmental conditions. The phytohormone abscisic acid (ABA) is a key regulator of plant responses to abiotic stress, yet the ABA signaling pathway remains poorly characterized in hop. Harnessing the publicly available hop genomics resources, we identified eight members of the PYRABACTIN RESISTANCE 1 LIKE ABA receptor family (HlPYLs). Phylogenetic and gene structure analyses classified these HlPYLs into the three canonical ABA receptor subfamilies. Furthermore, all eight HlPYLs are likely functional, as suggested by the protein sequence visual analysis. Expression profiling indicates that ABA perception in hop is primarily mediated by the HlPYL1-like and HlPYL8-like subfamilies, while the HlPYL4-like group appears to play a more limited role. Structure modeling and topology predictions of HlPYL1b and HlPYL2 provided insights into their potential functional mechanisms. To assess the physiological relevance of ABA signaling in hop, we evaluated the impact of exogenous ABA application during the ex vitro acclimatization phase. ABA-treated plants exhibited more robust growth, reduced stress symptoms, and improved acclimatization success. These effects were associated with reduced leaf transpiration and enhanced stomatal closure, consistent with ABA-mediated drought tolerance mechanisms. Altogether, this study provides the first comprehensive characterization of ABA receptor components in hop and demonstrates the practical utility of ABA in improving plant performance under ex vitro conditions. These findings lay the groundwork for further functional studies and highlight ABA signaling as a promising target for enhancing stress resilience in hop, with broader implications for sustainable agriculture in the face of climate change.

PMID:40725169 | DOI:10.3390/ijms26146923

Int J Mol Sci. 2025 Jul 15;26(14):6767. doi: 10.3390/ijms26146767.

ABSTRACT

Investigating the volatiles isolated from a commercial spirulina (Arthrospira platensis) dietary supplement by gas chromatography-olfactometry (GC-O) in combination with an aroma extract dilution analysis (AEDA) resulted in 29 odor events with flavor dilution (FD) factors between 8 and 2048. Identification experiments, including various offline and online fractionation approaches, led to the structure assignment of 30 odorants, among which the most potent were sweaty 2- and 3-methylbutanoic acid (FD 2048), roasty, earthy, shrimp-like 2-ethyl-3,5-dimethylpyrazine (FD 2048), vinegar-like acetic acid (FD 1024), and floral, violet-like β-ionone (FD 1024). Static headspace dilution analysis revealed sulfuric, cabbage-like methanethiol (FD factor ≥ 32) as an additional potent odorant. In summary, 31 important spirulina odorants were identified in this study, and 14 were reported for the first time as spirulina constituents. Our data will provide a basis for future odor optimization of spirulina-based food products.

PMID:40725014 | DOI:10.3390/ijms26146767