Peste des petits ruminants (PPR) is a highly contagious viral disease of small ruminants caused by the peste des petits ruminants virus (PPRV), which is classified into four distinct genetic lineages (I-IV). A critical concern is the rapid and widespread expansion of lineage IV (LIV) across West Africa over the past decade. In this study, we generated full or partial genome sequence from 26 new PPRV samples, including historical (pre-2000) and recent African LIV isolates, offering the first opportunity to investigate the evolutionary history of LIV in Africa and identify genetic events potentially associated with its recent spread. These new sequences were aligned with 141 publicly available PPRV sequences to perform phylogenomic analyses. Results reveal that the most ancestral LIV group comprises strains circulating in Sub-Saharan Africa (designated clade LIVssa), providing new evidence for an African origin of lineage IV. Our results further indicate that PPRV strains linked to the recent West African expansion of LIV belong to a specific LIVssa subclade, termed NigB. We identified multiple signatures of selection pressure within the LIVssa sublineage, particularly in the NigB subclade. Several amino acid substitutions unique to LIVssa or NigB were detected, some of which may impact protein function and warrant prioritised investigation. While additional genomic data are required to confirm the association between the NigB subclade and the ongoing spread of LIV in West Africa, this expansion is alarming and demands intensified research efforts using integrative approaches. The evolutionary adaptations observed in LIVssa could undermine current disease control strategies in regions where PPR poses significant threats to food security and local economies.

Biofilms are structured microbial communities embedded within a self-produced extracellular polymeric substance matrix that promotes persistence under adverse environmental and host-associated conditions. Their clinical importance is primarily associated with increased antimicrobial tolerance, evasion of host immune responses, and persistence in chronic and medical device-associated infections. This review provides an integrated overview of the molecular and genetic determinants governing biofilm development, including surface attachment, matrix biosynthesis, quorum-sensing networks, cyclic-di-GMP signaling, maturation, and dispersal. The contribution of key matrix components, including polysaccharides, extracellular proteins, extracellular DNA, lipids, and water, is considered in relation to biofilm architecture, stability, and cellular adaptation. Clinically relevant biofilm-forming microorganisms, including Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, and Candida albicans, are major contributors to chronic infections, healthcare-associated infections, and infections associated with medical devices. The mechanisms contributing to reduced antimicrobial susceptibility in biofilms include restricted drug penetration, metabolic heterogeneity, persister-cell formation, efflux activity, stress-response pathways, and horizontal gene transfer. Conventional in vitro and in vivo biofilm models often fail to fully mimic the complex conditions present within the human host, thereby limiting the clinical translation and therapeutic relevance of experimental findings. In addition, emerging antibiofilm interventions, including quorum-sensing inhibitors, matrix-degrading enzymes, nanoparticle-based delivery systems, antimicrobial peptides, and bacteriophage therapy, are considered alongside the growing application of multi-omics and artificial intelligence for biomarker discovery and therapeutic target identification.

Phlebotomine sand flies are important vectors of various pathogens, including the Chandipura virus (CHPV), a neurotropic rhabdovirus associated with fatal pediatric encephalitis outbreaks in India. Gujarat, a CHPV-endemic region, lacks comprehensive molecular data on sand fly species. Accurate species identification is important for effective vector surveillance and control strategies. 2950 sand flies were collected from 14 districts using aspirators and traps. Morphological identification was performed by using standard taxonomic keys. DNA barcoding of the mitochondrial cytochrome c oxidase subunit I (COI) gene was performed using universal barcoding primers. Sequence alignment, phylogenetic analysis, and genetic divergence calculations were performed through MEGA and BOLD Systems databases. Seven species were identified: Sergentomyia babu, Se. punjabensis, Se. insularis, Se. bailyi, Se. shorttii, Phlebotomus argentipes, and Ph. papatasi. Phylogenetic clustering showed strong bootstrap support (>90%), confirming congruence between morphological and molecular identification. Intraspecific divergence was low (0.5 to 2.0%), while interspecific divergence was comparatively higher (5.4 to 18.9%), indicating a clear "barcode gap" that validated species boundaries. COI DNA barcoding reliably distinguished sand fly species from CHPV-endemic Gujarat. The study highlights the presence of epidemiologically relevant vectors, supports the use of molecular taxonomy in entomological surveillance, and emphasizes the need to expand DNA barcode reference libraries for Indian sand flies.

Cancer is a disease of somatic evolution driven by the sequential acquisition of genetic alterations that confer reproductive advantage. Understanding how tumors grow, diversify, and adapt to therapeutic pressure requires an integrated framework spanning evolutionary genomics, population genetics, and dynamical systems theory. This review synthesizes current knowledge on clonal dynamics, intratumor heterogeneity (ITH), and the mathematical tools used to model cancer progression, with direct implications for the design of precision oncology strategies. Neutral evolution and Darwinian selection jointly govern subclonal architecture, and quantitative metrics of ITH predict treatment failure with reproducible accuracy. Mathematical models including logistic growth equations, Lotka-Volterra competition systems, Wright-Fisher processes, and agent-based simulations have formalized these biological phenomena into tractable frameworks that yield clinically testable predictions. Fitness landscape theory explains how tumors navigate mutational space toward states of high adaptive fitness, while adaptive therapy protocols exploit competitive suppression between sensitive and resistant clones. Liquid biopsy technologies now provide real-time genomic surveillance aligned with model predictions, enabling monitoring without repeated tissue sampling. Integration of these computational and experimental approaches is accelerating the identification of actionable biomarkers and informing next-generation treatment scheduling. The convergence of tumor evolutionary biology and quantitative modeling represents a fundamental shift in oncology, from treating disease states to managing evolving ecosystems.

Dengue fever is a hyperendemic disease in Thailand caused by four distinct dengue virus serotypes (DENV-1 to 4) that co-circulate annually. Fluctuating endemic patterns make it difficult to predict outbreaks in hyperendemic regions. Additionally, the envelope protein is associated with cocirculation of several serotypes, cocirculation of different strains within the same genotype, and heterotypic dengue infection. To control dengue epidemiology, phylogenetic analysis of envelope gene sequences and geographic distribution should be conducted. In this report, we characterized 305 dengue envelope genes isolated from blood samples of dengue-infected Thai patients from 1999 to 2012. Phylogenetic tree analysis of the envelope gene nucleotide sequences of 305 strains revealed that they comprised 128 strains of DENV-1, classified as genotype I; 56 strains of DENV-2, classified as Asian I and cosmopolitan genotypes; 56 strains of DENV-3, classified as genotypes I, II, and III; and 65 strains of DENV-4, classified as genotypes I and II. The results attributed DENV-1 to 4 to distinct locations in Thailand, with recurrent circulation in the original region for similar periods. In addition, DENV-1 genotype I was the main strain circulating almost annually between 1999 and 2012, whereas DENV-2 Asian I was the predominant genotype isolated between 2010 and 2012. Taken together, all four serotypes may have co-circulated in Thailand from 1999 to 2012. DENV-1 to 4 were particularly homogeneous circulating genotypes. Therefore, the molecular diversity of the dengue envelope gene has been co-circulating in Thailand for over a decade.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) has emerged as a major global health threat due to its rapid dissemination and severely limited treatment options. Here, we report the phenotypic and genomic characterization of an ST656 K. pneumoniae clinical isolate carrying blaOXA-181 in China. Antimicrobial susceptibility testing confirmed carbapenem resistance, whereas the isolate remained susceptible to aztreonam, amikacin and trimethoprim/sulfamethoxazole, with a colistin MIC of ≤0.5 μg/mL. Whole-genome sequencing identified the blaOXA-181 gene on a 51,391-bp ColKP3/IncX3 plasmid co-harboring multiple resistance determinants. Conjugation assays yielded blaOXA-181 -positive transconjugants at a recovery frequency of 2 × 10[-4]. Following serial passage, blaOXA-181 was stably maintained for 100 generations. Comparative genomic analysis showed that the blaOXA-181-carrying plasmid shared a highly conserved backbone with plasmids from geographically diverse isolates, while KP413706 represents a distinct ST656 lineage. These findings expand the genomic evidence for blaOXA-181-carrying ST656 K. pneumoniae in China and underscore the urgent need for enhanced genomic surveillance and stringent infection control strategies.

Wastewater microbiomes provide valuable information on environmental processes and community health while supporting wastewater-based epidemiology. This study investigated relationships among wastewater source, seasonality and SARS-CoV-2 occurrence on microbial community dynamics in Aizawl, Mizoram, India, using full length 16S rRNA nanopore sequencing. Thirty wastewater samples collected from four domestic sewage sites and one sewage treatment plant influent across autumn, winter, summer and summer monsoon seasons were analyzed together with SARS-CoV-2 detection by RT qPCR. Taxonomic profiling revealed a core microbiome dominated by Bacillota, Pseudomonadota, Bacteroidota and Actinomycetota. Seasonal variation influenced community composition, with summer and monsoon samples showing increased abundances of Pseudomonadota and Bacteroidota, whereas autumn and winter samples were enriched in Bacillota. STP influent receiving mixed urban and industrial inputs exhibited greater taxonomic richness than predominantly domestic wastewater, whereas predominantly domestic wastewater showed higher community evenness. SARS-CoV-2-positive samples showed increased abundances of enteric and opportunistic bacterial genera, including Escherichia, Klebsiella and Acinetobacter, and displayed distinct community clustering patterns. LEfSe analysis identified microbial biomarkers associated with wastewater source, season and viral status, including Aliarcobacter, Segatella copri and Escherichia coli. Co-occurrence network analysis revealed a highly interconnected microbial community comprising 46 nodes and 383 significant associations, with Segatella and Streptococcus acting as major hub taxa. Functional prediction indicated the predominance of chemoheterotrophy, fermentation and nitrogen transformation pathways. These findings demonstrate that wastewater microbial communities exhibit distinct patterns across seasons, wastewater source types and SARS-CoV-2 detection status while maintaining a stable functional framework, highlighting their value for environmental surveillance.