Search Results (80)

Background: Background: Endometriosis affects 10% of women of reproductive age. Despite the well-known association between endometriosis and infertility, the mechanisms underlying this association remain to be elucidated. Methods: Implantation and pregnancy success rates were evaluated by a retrospective study of patients that underwent IVF using euploid embryos comparing healthy vs. endometriosis patients. To study the early embryo–endometrial dialogue, an interactome network was constructed using public RNAseq data from normal secretory-phase endometrial samples and day-5 blastocyst. Public bulk and single-cell RNAseq data from endometrial samples of endometriosis patients were used to detect alterations in the interactome. Results: Endometriosis patients required significantly more IVF attempts compared to those without endometrial pathologies; however, once pregnancy was achieved, the evolution of both groups was similar. The interactome network between normal endometrium and day-5 blastocyst showed a significant enrichment of pathways associated with tissue remodelling, angiogenesis, and immune regulation, which were altered in endometriosis patients. Endometriosis patients also presented an increased frequency and activation of NK, CD4⁺, and CD8⁺ cells, which interfere with embryo–endometrial dialogue. Conclusions: We identified key molecular processes affected by endometriosis specifically involved in the early interaction between the blastocyst, decidual, and resident immune cells, that may underline the reported fertility problems associated with endometriosis. Full article

Micro- and nanoplastic particles (MNPLs) present in the environment have recently become a potential health hazard factor due to the ability to penetrate living organisms, their organs, and cells. MNPLs interact with and absorb chemicals and elements, including metals, such as iron, copper, and zinc, and transport them into the cells. The cells subsequently respond with the altered gene expression profiles. In this study, we applied freely accessible online bioinformatic tools to draw out the sets of genes modulated by the metal ions and MNPLs. We focused on the gene interactome as revealed by The Comparative Toxicogenomics Database (CTD). To achieve a deeper insight into the biological processes that are potentially modulated, the retrieved CTD lists of genes, whose expression was influenced by MNPLs and metals, were subsequently analyzed using online tools: Metascape and String database. The genes from the revealed networks were arranged into functional clusters, annotated mainly as inflammation and immune system activity, regulation of apoptosis, oxidative stress response, Wingless-related Integration Site (WNT) signaling and ferroptosis. The complexity of the interactions between the gene sets altered by MNPLs and metal ions illustrates their pleiotropic effects on living systems. Full article

The field of bacterial systems biology is rapidly advancing beyond static genomic analyses, and moving toward dynamic, integrative approaches that connect genetic variation with cellular function. This review traces the progression from genome-wide association studies (GWAS) to multi-omics frameworks that incorporate transcriptomics, proteomics, and interactome mapping. We emphasize recent breakthroughs in high-resolution transcriptomics, including single-cell, spatial, and epitranscriptomic technologies, which uncover functional heterogeneity and regulatory complexity in bacterial populations. At the same time, innovations in proteomics, such as data-independent acquisition (DIA) and single-bacterium proteomics, provide quantitative insights into protein-level mechanisms. Experimental and AI-assisted strategies for mapping protein–protein interactions help to clarify the architecture of bacterial molecular networks. The integration of these omics layers through quantitative trait locus (QTL) analysis establishes mechanistic links between single-nucleotide polymorphisms and systems-level phenotypes. Despite persistent challenges such as bacterial clonality and genomic plasticity, emerging tools, including deep mutational scanning, microfluidics, high-throughput genome editing, and machine-learning approaches, are enhancing the resolution and scope of bacterial genetics. By synthesizing these advances, we describe a transformative trajectory toward predictive, systems-level models of bacterial life. This perspective opens new opportunities in antimicrobial discovery, microbial engineering, and ecological research. Full article

As a pivotal model organism in Lepidoptera research, the silkworm (Bombyx mori) holds significant importance in life science due to its economic value and biotechnological applications. Advancements in proteomics and bioinformatics have enabled substantial progress in characterizing the B. mori proteome. Systematic screening and identification of protein–protein interactions (PPIs) have progressively elucidated the molecular mechanisms governing key biological processes, including viral infection, immune regulation, and growth development. This review comprehensively summarizes traditional PPI detection techniques, such as yeast two-hybrid (Y2H) and immunoprecipitation (IP), alongside emerging methodologies such as mass spectrometry-based interactomics and artificial intelligence (AI)-driven PPI prediction. We critically analyze the strengths, limitations, and technological integration strategies for each approach, highlighting current field challenges. Furthermore, we elaborate on the molecular regulatory networks of Bombyx mori nucleopolyhedrovirus (BmNPV) from multiple perspectives: apoptosis and cell cycle regulation; viral protein invasion and trafficking; non-coding RNA-mediated modulation; metabolic reprogramming; and host immune evasion. These insights reveal the dynamic interplay between viral replication and host defense mechanisms. Collectively, this synthesis aims to provide a robust theoretical foundation and technical guidance for silkworm genetic improvement, infectious disease management, and the advancement of related biotechnological applications. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder marked by dopaminergic neuronal loss, α-synuclein aggregation, and chronic neuroinflammation. Recent evidence suggests that exosomal microRNAs (miRNAs)—small, non-coding RNAs encapsulated in extracellular vesicles—are key regulators of PD pathophysiology and promising candidates for biomarker development and therapeutic intervention. Exosomes facilitate intercellular communication, cross the blood–brain barrier, and protect miRNAs from degradation, rendering them suitable for non-invasive diagnostics and targeted delivery. Specific exosomal miRNAs modulate neuroinflammatory cascades, oxidative stress, and synaptic dysfunction, and their altered expression in cerebrospinal fluid and plasma correlates with disease onset, severity, and progression. Despite their translational promise, challenges persist, including methodological variability in exosome isolation, miRNA profiling, and delivery strategies. This review integrates findings from preclinical models, patient-derived samples, and systems biology to delineate the functional impact of exosomal miRNAs in PD. We propose mechanistic hypotheses linking miRNA dysregulation to molecular pathogenesis and present an interactome model highlighting therapeutic nodes. Advancing exosomal miRNA research may transform the clinical management of PD by enabling earlier diagnosis, molecular stratification, and the development of disease-modifying therapies. Full article

HIV-1 Tat acts as a central molecular switch governing the transition between viral latency and active replication, making it a pivotal target for HIV-1 functional cure strategies. By binding to the viral long terminal repeat (LTR) and hijacking host transcriptional machinery, Tat dynamically regulates RNA polymerase II processivity to alter viral transcription states. Recent studies reveal its context-dependent variability: while Tat recruits chromatin modifiers and scaffolds non-coding RNAs to stabilize epigenetic silencing in latently infected cells, it also triggers rapid transcriptional amplification upon cellular activation. This review systematically analyzes the bistable regulatory mechanism of Tat and investigates advanced technologies for reprogramming this switch to eliminateviral reservoirs and achieve functional cures. Conventional approaches targeting Tat are limited by compensatory viral evolution and poor bioavailability. Next-generation interventions will employ precision-engineered tools, such as AI-optimized small molecules blocking Tat-P-TEFb interfaces and CRISPR-dCas9/Tat chimeric systems, for locus-specific LTR silencing or reactivation (“block and lock” or “shock and kill”). Advanced delivery platforms, including brain-penetrant lipid nanoparticles (LNPs), enable the targeted delivery of Tat-editing mRNA or base editors to microglial reservoirs. Single-cell multiomics elucidates Tat-mediated clonal heterogeneity, identifying “switchable” subpopulations for timed interventions. By integrating systems-level Tat interactomics, epigenetic engineering, and spatiotemporally controlled delivery, this review proposes a roadmap to disrupt HIV-1 persistence by hijacking the Tat switch, ultimately bridging mechanistic insights to clinical applications. Full article

Recent work has identified biomphalysin (BM) protein from the snail Biomphalaria glabrata as a cytolytic toxin against the Schistosoma mansoni parasite. Ex vivo interactome studies further evidenced BM’s ability to bind bacterial outer membrane proteins, but its specific antibacterial mechanisms and selectivity remain unclear. Accordingly, this study aims to elucidate the interaction between BM and two model bacteria with distinct cell surface architectures: Escherichia coli (Gram−) and Micrococcus luteus (Gram+). Employing a multiscale approach, we used in vivo single-molecule force spectroscopy (SMFS) to probe molecular interactions at the single cell level. Combined with cell aggregation assays, immunoblotting and Atomic Force Microscopy (AFM) imaging, SMFS results evidenced a selective interaction of BM from snail plasma with M. luteus but not E. coli. Exposure of M. luteus to BM compromised cell surface integrity and induced cell aggregation. These effects correlated with a patch-like distribution of BM on M. luteus reminiscent of pore-forming toxins, as revealed by the anti-BM antibody-functionalized AFM tip. Overall, this work highlights the utility of SMFS in dissecting host–pathogen molecular dialogs. It reveals BM’s selective action against M. luteus, potentially via surface clustering, and it shows spatially heterogeneous responses to the toxin within and between individual cells. Full article

Parkinson’s disease (PD) is a complex neurodegenerative disorder lacking effective disease-modifying treatments. In this study, we integrated large-scale protein–protein interaction networks with a multi-modal graph neural network (GNN) to identify and prioritize multi-target drug repurposing candidates for PD. Network analysis and advanced clustering methods delineated functional modules, and a novel Functional Centrality Index was employed to pinpoint key nodes within the PD interactome. The GNN model, incorporating molecular descriptors, network topology, and uncertainty quantification, predicted candidate drugs that simultaneously target critical proteins implicated in lysosomal dysfunction, mitochondrial impairment, synaptic disruption, and neuroinflammation. Among the top hits were compounds such as dithiazanine, ceftolozane, DL-$\alpha$-tocopherol, bromisoval, imidurea, medronic acid, and modufolin. These findings provide mechanistic insights into PD pathology and demonstrate that a polypharmacology approach can reveal repurposing opportunities for existing drugs. Our results highlight the potential of network-based deep learning frameworks to accelerate the discovery of multi-target therapies for PD and other multifactorial neurodegenerative diseases. Full article

KRAS mutations are major drivers of human cancers, yet how distinct mutations rewire protein interactions and metabolic pathways to promote tumorigenesis remains poorly understood. To address this, we systematically mapped the protein interaction networks of wild-type KRAS and three high-frequency oncogenic mutants (G12C, G12D, and G12V) using TurboID proximity labeling coupled with quantitative proteomics. Bioinformatic analysis revealed mutant-specific binding partners and metabolic pathway alterations, including significant enrichment in insulin signaling, reactive oxygen species regulation, and glucose/lipid metabolism. These changes collectively drive tumor proliferation and immune evasion. Comparative analysis identified shared interactome shifts across all mutants: reduced binding to LZTR1, an adaptor for KRAS degradation, and enhanced recruitment of LAMTOR1, a regulator of mTORC1-mediated growth signaling. Our multi-dimensional profiling establishes the first comprehensive map of KRAS-mutant interactomes and links specific mutations to metabolic reprogramming. These findings provide mechanistic insights into KRAS-driven malignancy and highlight LZTR1 and LAMTOR1 as potential therapeutic targets. The study further lays a foundation for developing mutation-specific strategies to counteract KRAS oncogenic signaling. Full article

This research proposes to systematically investigate the cardioprotective mechanisms of Pericarpium Trichosanthis injection (PTI) against acute myocardial ischemia through an integrated approach combining ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) constituent profiling, UNIFI database-assisted component identification, network pharmacology-guided target prediction, molecular docking verification, and in vivo experimental validation. The multimodal methodology is designed to comprehensively uncover the therapeutic benefits and molecular pathways underlying this traditional Chinese medicine formulation. Methods: UPLC-Q-TOF/MS and the UNIFI database were used in conjunction with a literature review to screen and validate the absorbed components of PTI. Using network pharmacology, we constructed protein-protein interaction (PPI) networks for pinpointing prospective therapeutic targets. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify potential signaling pathways. In vivo experiments were conducted to investigate the mechanisms by which PTI ameliorated isoproterenol-induced myocardial injury in rats. All animal experiments have adhered to ARRIVE guidelines. Results: UPLC-Q-TOF/MS revealed 11 core active components in PTI. Network pharmacology prioritization identified pseudoaspidin, ciryneol C, cynanoside M, daurinol, and n-butyl-β-D-fructopyranoside as central bioactive constituents within the compound-target interaction network. Topological analysis of the protein interactome highlighted AKT1, EGFR, MMP9, SRC, PTGS2, STAT3, BCL2, CASP3, and MAPK3 as the most interconnected nodes with the highest betweenness centrality. Pathway enrichment analysis established the PI3K/Akt signaling cascade as the principal mechanistic route for PTI’s cardioprotective effects. Molecular docking simulations demonstrated high-affinity interactions between characteristic components (e.g., cynanoside M, darutigenol) and pivotal targets including PTGS2, MAPK3, CASP3, and BCL2. In vivo investigations showed PTI treatment markedly attenuated myocardial tissue degeneration and collagen deposition (p < 0.05), normalized electrocardiographic ST-segment deviations, and suppressed pro-inflammatory cytokine production (IL-6, TNF-α). The formulation concurrently reduced circulating levels of cardiac injury indicators (LDH, cTnI) and oxidative stress parameters (ROS, MDA), Regarding apoptosis regulation, PTI reduced Bax, caspase-3, and caspase-9, while elevating Bcl-2 (p < 0.05), effectively inhibiting myocardial cell apoptosis with all therapeutic outcomes reaching statistical significance. These findings highlight PTI’s protective effects against myocardial injury through multi-target modulation of inflammation, oxidation, and apoptosis. Conclusions: PTI exerts its therapeutic effects in treating acute myocardial ischemia by regulating and suppressing inflammatory responses, and inhibiting cardiomyocyte apoptosis. Full article

Background/Objectives: The MAST kinases are ancient AGC kinases associated with many human diseases, such as cancer, diabetes, and neurodevelopmental disorders. We set out to describe the origins and diversification of MAST kinases from a structural and bioinformatic perspective to inform future research directions. Methods: We investigated MAST-lineage kinases using database and sequence analysis. We also estimate the functional consequences of disease point mutations on protein stability by integrating predictive algorithms and AlphaFold. Results: Higher-order organisms often have multiple MASTs and a single MASTL kinase. MAST proteins conserve an AGC kinase domain, a domain of unknown function 1908 (DUF), and a PDZ binding domain. D. discoideum contains MAST kinase-like proteins that exhibit a characteristic insertion within the T-loop but do not conserve DUF or PDZ domains. While the DUF domain is conserved in plants, the PDZ domain is not. The four mammalian MASTs demonstrate tissue expression heterogeneity by mRNA and protein. MAST1-4 are likely regulated by 14-3-3 proteins based on interactome data and in silico predictions. Comparative ΔΔG estimation identified that MAST1-L232P and G522E mutations are likely destabilizing. Conclusions: We conclude that MAST and MASTL kinases diverged from the primordial MAST, which likely operated in both biological niches. The number of MAST paralogs then expanded to the heterogeneous subfamily seen in mammals that are all likely regulated by 14-3-3 protein interaction. The reported pathogenic mutations in MASTs primarily represent alterations to post-translational modification topology in the DUF and kinase domains. Our report outlines a computational basis for future work in MAST kinase regulation and drug discovery. Full article

Background/Objectives: Non-small cell lung cancer (NSCLC) is the most common type of cancer, with lung adenocarcinoma (LUAD) as the predominant subtype. Despite advancements in targeted therapies, many NSCLC patients still experience poor outcomes due to treatment resistance and disease progression. Genomic instability (GI), a hallmark of cancer, defined as the increased tendency of DNA mutations and alterations, is closely linked to cancer initiation, progression, and resistance to therapy. Emerging evidence suggests that long non-coding RNAs (lncRNAs)—molecules longer than 200 nucleotides that do not encode proteins but regulate gene expression—play critical roles in cancer biology and are associated with GI. However, the relationship between GI and lncRNA expression in LUAD remains poorly understood. Methods: In this study, we analyzed the transcript profiles of lncRNAs and mRNAs from LUAD samples in The Cancer Genome Atlas (TCGA) database and classified them based on their Homologous Recombination Deficiency (HRD) score. The HRD score is an unweighted sum of three independent DNA-based measures of genomic instability: loss of heterozygosity, telomeric allelic imbalance, and large-scale transitions. We then performed a differential gene expression analysis to identify lncRNAs and mRNAs that were either upregulated or downregulated in samples with high HRD scores compared to those with low HRD scores. Following this, we conducted a correlation analysis to assess the significance of the association between HRD scores and the expression of both lncRNAs and mRNAs. Results: We identified 30 differentially expressed lncRNAs and 200 mRNAs associated with genomic instability. Using an RNA interactome database from sequencing experiments, we found evidence of interactions between GI-associated lncRNAs (GI-lncRNAs) and GI-associated mRNAs (GI-mRNAs). Further investigation showed that some GI-lncRNAs play regulatory and functional roles in LUAD and other diseases. We also found that GI-lncRNAs have potential as prognostic biomarkers, particularly when integrated with HRD stratification. The expression of specific GI-lncRNAs was associated with primary therapy response and immune infiltration in LUAD. Additionally, we identified existing drugs that could modulate GI-lncRNAs, offering potential therapeutic strategies to address GI in LUAD. Conclusions: Our findings suggest that GI-associated lncRNAs could serve as valuable biomarkers for LUAD prognosis and therapeutic response. Furthermore, modulating these lncRNAs presents potential treatment avenues to address genomic instability in LUAD. Full article

Plants face an array of environmental stresses, including both abiotic and biotic stresses. These stresses significantly impact plant lifespan and reduce agricultural crop productivity. Abiotic stresses, such as ultraviolet (UV) radiation, high and low temperatures, salinity, drought, floods, heavy metal toxicity, etc., contribute to widespread crop losses globally. On the other hand, biotic stresses, such as those caused by insects, fungi, and weeds, further exacerbate these challenges. These stressors can hinder plant systems at various levels, including molecular, cellular, and development processes. To overcome these challenges, multi-omics computational approaches offer a significant tool for characterizing the plant’s biomolecular pool, which is crucial for maintaining homeostasis and signaling response to environmental changes. Integrating multiple layers of omics data, such as proteomics, metabolomics, ionomics, interactomics, and phenomics, simplifies the study of plant resistance mechanisms. This comprehensive approach enables the development of regulatory networks and pathway maps, identifying potential targets for improving resistance through genetic engineering or breeding strategies. This review highlights the valuable insights from integrating multi-omics approaches to unravel plant stress responses to both biotic and abiotic factors. By decoding gene regulation and transcriptional networks, these techniques reveal critical mechanisms underlying stress tolerance. Furthermore, the role of secondary metabolites in bio-based products in enhancing plant stress mitigation is discussed. Genome editing tools offer promising strategies for improving plant resilience, as evidenced by successful case studies combating various stressors. On the whole, this review extensively discusses an advanced multi-omics approach that aids in understanding the molecular basis of resistance and developing novel strategies to improve crops’ or organisms’ resilience to abiotic and biotic stresses. Full article

Aquaporins are transmembrane proteins that mediate the transport of water, as well as various ions and molecules. In plants, they play a critical role in numerous processes, including stress adaptation, nutrition, cellular communication, and transpiration. Therefore, understanding the function and interactions of these proteins with others—known as interactomes—is of significant agronomic and biological interest. This study aims to analyse the interactome of all aquaporins in Arabidopsis thaliana L. using two distinct databases, STRING and BioGRID. After analysing both interactomes, a wide range of interactions were identified between each aquaporin and a diverse array of proteins, including nutrient transporters for ammonium, potassium, phosphorus, sulphur, copper, and sugars; proteins related to responses to abiotic stresses; proteins mediating vesicle membrane fusion, such as synaptobrevins and syntaxins; ubiquitinases; kinases; and other transmembrane proteins. These extensive connections further underscore the critical importance of aquaporins in numerous biological processes, positioning them as central modulators and integration points for cellular and systemic responses in plants. Full article

HOX genes play essential roles in patterning the anteroposterior axis of animal embryos and in the formation of various organs. In mammals, there are 39 HOX genes organized into four clusters (HOXA–D) located on different chromosomes. In relationship with their orderly arrangement along the chromosomes, these genes show nested expression patterns which imply that embryonic territories co-express multiple HOX genes along the main body axis. Interactomic database entries, as well as a handful of publications, support that some HOX proteins can form homodimers or interact with other HOX proteins. However, the consequences of HOX protein interactions have been poorly investigated and remain largely elusive. In this study, we compiled a repository of all HOX–HOX interactions from available databases, and taking HOXA1, HOXA2, and HOXA5 as examples, we investigated the capacity of HOX proteins to form homo- and heterodimers. We revealed that while the DNA-binding domain, the homeodomain, is not necessary for HOXA1 homodimerization, the nuclear localization of the dimerization is dependent on the homeodomain, particularly the integrity of the third helix of HOXA1. Furthermore, we demonstrated that HOXA1 can influence the localization of HOXA1 when it is deprived of the homeodomain, increasing its abundance in the chromatin-containing fraction. Moreover, HOXA1 nuclear homodimerization occurs independently of the integrity of the hexapeptide and, consequently, of its well-known interactor, the homeodomain protein PBX. These results hint at a potential involvement of dimerization in the complex landscape of HOX regulatory mechanisms. Full article