Comparative and Functional Genomics最新文献

Klebsiella pneumoniae is a Gram-negative, facultatively anaerobic member of the Enterobacteriaceae that functions both as a gut commensal and a major opportunistic pathogen implicated in severe hospital and community-acquired infections. The rapid global expansion of antimicrobial-resistant K. pneumoniae lineages, particularly ESBL- and carbapenemase-producing strains, poses an escalating public health threat by eroding available treatment options. This study investigated the genomic architecture and resistance mechanisms of K. pneumoniae isolates recovered from urinary tract infections, wound infections, and cervical cancer cases across Ghana, Togo, and Benin. Eight isolates were subjected to antimicrobial susceptibility profiling and whole genome sequencing using the Illumina MiSeq platform after DNA extraction via the Zymo protocol. Comprehensive genomic analyses including MLST, resistance gene detection (Abricate), phylogenetic reconstruction (iTOL), genomic island prediction (IslandViewer), genome structural analysis (Proksee), and statistical interrogation in R (v4.4.0) were performed to characterize genetic diversity and identify determinants of antimicrobial resistance. The isolates exhibited heterogeneous but overlapping resistance profiles, extensive carriage of AMR genes, and the presence of multiple genomic islands enriched for integrases, transposases, and antibiotic resistance cassettes. MLST and SNP-based comparisons revealed both clonal clusters and genetically divergent lineages, while recombination analysis indicated mutation-driven evolution with lineage-specific recombination hotspots. Conserved gene orientation patterns and regions of atypical GC content further suggested historical acquisition of mobile genetic elements, including plasmid integrations and resistance islands. Collectively, these findings demonstrate the high genomic plasticity, multidrug-resistant phenotypes, and dynamic evolutionary processes shaping K. pneumoniae populations circulating in West Africa. The study underscores the urgent need for continuous regional genomic surveillance to guide treatment policies and limit the further dissemination of high-risk AMR clones.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with tumor microenvironment (TME) heterogeneity playing a critical role in disease progression and therapeutic response. Immune escape (IE) mechanisms facilitate tumor evasion from host immune surveillance, yet their characterization at the single-cell level in CRC is incomplete. This study integrated single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic data from multiple public cohorts to systematically explore IE-related signatures in CRC. We identified major and minor cell populations within the TME and performed differential gene expression analysis. Using high-dimensional weighted gene coexpression network analysis (hdWGCNA), we identified gene modules correlated with IE activity. Subsequent survival analysis across six independent cohorts revealed Gamma-glutamylcyclotransferase (GGCT) as a novel prognostic biomarker associated with poor survival. Functional enrichment analysis indicated GGCT′s involvement in critical oncogenic pathways. Furthermore, GGCT expression correlated with altered immune infiltration profiles and stromal components, suggesting its role in modulating the immunosuppressive TME. Additionally, GGCT demonstrated potential predictive value for response to immunotherapy across multiple datasets. Our findings highlight GGCT as a key player in CRC immune evasion and a promising therapeutic target.

Emerging evidence highlights the pivotal role of KISS1 in cancer metastasis; however, there remains a dearth of pancancer analyses, particularly concerning immunotherapy. Here, we conducted a comprehensive investigation of KISS1 across various cancers, with a specific focus on breast cancer, using TCGA and GTEx datasets. We observed a tissue context-dependent role function of KISS1 in tumor metastasis, which exhibited suppressive effects in various tumors but promoted the metastatic phenotype in breast cancer. Our study revealed a noteworthy disparity between KISS1 expression at the mRNA and protein levels, indicating potential posttranslational modifications within cancer cells. Moreover, KISS1 is significantly associated with immune cell infiltration and immunosuppressive cells, suggesting its crucial role in modulating tumor immunotherapy. Intriguingly, our investigation also elucidated KISS1’s involvement in promoting breast cancer metastasis, thereby providing valuable insights into the molecular underpinnings of this process. Furthermore, we validated the presence of posttranslational modifications of KISS1 in breast cancer, adding to our understanding of its role in tumorigenesis. By shedding light on the tissue context-dependent function of KISS1 and its implications for immunotherapy, our pancancer study offers novel perspectives on the oncogenic roles of KISS1 and provides potential avenues for the development of targeted therapies and diagnostic biomarkers.

Cellular action potential is characterized by a particular sequence of depolarizing and repolarizing ion currents regulated by ion channels. Genetic mutations in these channels disrupt the essential movement of ions, such as Na+, Ca++, and K+, across the cell membrane, leading to dangerous arrhythmias and sudden cardiac death (SCD). Most cases of unexplained SCD are caused by pathogenic variants in genes linked to channelopathies and cardiomyopathy. Genetic investigations might aid in confirming the clinical diagnosis based solely on observations. Other advantages of genetic studies are clinical management of the patient, family screening, appropriate genetic counseling, and risk assessment for family members. This study was conducted to investigate the genetic cause of early-onset SCD in two Iranian families. Whole-exome sequencing was performed on the probands from each family, and the Illumina DRAGEN haplotype variant calling system was used to identify variants in each patient. Here, we identified rare heterozygous missense variants in the RYR2 and SCN5A genes, which are linked to cardiac channelopathies. Alignment studies reveal that the mutated residues are conserved across humans and primates, underscoring their crucial role in protein function. Previously reported associations between these mutations and channelopathy pathogenesis have been confirmed in the present study. This study provides valuable insights for genetic counseling of families with a history of sudden death.

Prostate cancer (PCa) is a major malignancy affecting men and is a significant contributor to global male mortality. Over the past decade, several new treatments for advanced PCa have been approved; however, opportunities remain for the development of novel therapeutic strategies. Therefore, in this study, we developed an integrated bioinformatics pipeline to identify potential therapeutic targets and repurposed drugs using RNA-seq datasets, aiming to advance treatment options for PCa. Using the LIMMA approach, 458 common differentially expressed genes (cDEGs) were analyzed from three publicly available microarray datasets, leading to the identification of 15 hub genes (HubGs) through a protein–protein interaction (PPI) network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed their critical roles in PCa, and lower expressions of five HubGs (BIRC5, CDCA5, CENPF, NUSAP1, and TK1) correlated with better survival. All of these genes could potentially serve as biomarkers for the detection and therapy of PCa. Following that, we considered these possible genes as targets for drugs, performed docking analysis with 255 meta-drug agents, and identified the top 10 candidate drugs (adapalene, ergotamine, imatinib, dutasteride, vistusertib, risperidone, zafirlukast, irinotecan hydrochloride, drospirenone, and telmisartan). Finally, we evaluated the binding stability of the top-ranked three complexes—BIRC5–adapalene, BIRC5–imatinib, and TK1–ergotamine—through a 100 nanoseconds (ns) molecular dynamics (MD) simulation conducted using NAMD. The analysis revealed consistent stability across all complexes. This study uniquely combines multidataset transcriptomic integration, HubG prioritization, and MD validation to propose novel biomarker–drug pairings for PCa. The findings offer promising leads for future experimental and clinical validation.