Search Results (6,339)

Rhodococcus species display remarkable metabolic versatility and adaptation to extreme environments, yet their antimicrobial potential remains largely unexplored, particularly in strains representing undescribed genomic lineages. This study investigated whether the genome of Rhodococcus sp. GB-02, a strain isolated from Antarctic soil, encodes antimicrobial peptides with demonstrable activity against clinically relevant pathogens. Hybrid genome assembly revealed a 6.58 Mb high-quality draft genome belonging to a previously undescribed genomic lineage within the genus Rhodococcus, based on average nucleotide identity and digital DNA–DNA hybridization analyses. Genome mining identified 20 biosynthetic gene clusters, predominantly non-ribosomal peptide synthetases, several of which showed low or no similarity to known pathways. Eight putative antimicrobial peptides (AMPs) were computationally predicted; among these, three lacked detectable homology to sequences in current databases, and experimental validation of one predicted peptide, designated Peptide 5764, demonstrated antibacterial activity at high micromolar concentrations against Gram-positive and Gram-negative pathogens and concentration-dependent inhibition of biofilm formation, particularly in Pseudomonas aeruginosa. However, Peptide 5764 exhibited considerable hemolytic activity at antibacterial concentrations, indicating that optimization for membrane selectivity will be required before therapeutic application. These findings establish Rhodococcus sp. GB-02 as an underexplored Antarctic lineage with a diverse biosynthetic repertoire and provide proof-of-concept that genome-guided AMP prediction can identify experimentally active peptide scaffolds from this lineage. Full article

The spatial pattern of building damage produced by an earthquake carries information that classical building-by-building vulnerability indices cannot capture. This study presents one of the first frameworks to use Topological Data Analysis (TDA), a set of methods that quantify the “shape” of data, to characterise the spatial topology of seismic damage across an urban building inventory. Using the geo-referenced centroids of buildings as a point cloud, a sequence of connectivity graphs (a Vietoris–Rips filtration) is built at increasing distance scales, and persistent homology is used to track which spatial features appear and disappear. From this we extract four interpretable descriptors: Betti numbers (the numbers of connected building clusters and of enclosed gaps), persistence entropy (a measure of how disordered the damage pattern is), total persistence (the combined lifespan of all topological features), and the Wasserstein-2 distance (how far the post-earthquake pattern has moved from the intact pre-earthquake pattern). These descriptors form a physics-informed feature vector that is used to predict the building-cluster damage state. The developed framework was trained, tested, and validated on 1490 buildings over seven post-earthquake scenarios. Lognormal fragility parameters were estimated with maximum likelihood estimation, and an Artificial Neural Network (ANN) and a Random Forest (RF) were retrained on the same 593-building training dataset for comparison. On the 847-building benchmark, the TDA framework reached 93.3% accuracy (95% CI: 91.4–94.9%), F1 = 0.921 (0.902–0.940), and AUC = 0.933, using a stratified 70/15/15 split (training = 593, validation = 127, test = 127). This is a 6.0-percentage-point gain over the retrained ANN and a 12.1-percentage-point gain over the HAZUS-MH index (McNemar p = 0.017). Damage was recorded on the six EMS-98 states DS0–DS5, with DS4 and DS5 merged into a single class to give a five-class taxonomy, and building-type-specific inter-storey drift ratio thresholds were validated against EN 1998-3 (Eurocode 8 Part 3). Exact Rips computation is practical only for clusters up to about 2000 buildings; for larger populations, a CGAL (Computational Geometry Algorithms Library)-based sparse approximation with O(N log N) cost is recommended. It seems that the topological descriptions of the damage field may provide predictive information above and beyond that given by density and ground motion intensity and offer a reproducible tool for post-earthquake screening. Full article

The solitary predatory wasp Rhynchium brunneum is an important natural enemy of lepidopteran pests. In the present study, we systematically identified its chemosensory gene families, comprising 11 odorant-binding proteins (OBPs), 9 chemosensory proteins (CSPs), 147 odorant receptors (ORs), 21 gustatory receptors (GRs) and 28 ionotropic receptors (IRs). Multiple sequence alignment confirmed that OBPs and CSPs contain conserved cysteines motifs. Further alignment analysis revealed that certain genes within the GR family form high similarity clusters (up to 81%) on the same chromosome, indicative of recent tandem duplications. The IR family displays a dispersed similarity gradient (31–87%) and the OR family shows a broader spectrum (18–78%), suggesting a composite history of both recent and ancient duplication events. Phylogenetic and selection pressure analyses indicated that OBPs and CSPs are highly conserved within the Eumeninae, whereas ORs, GRs, and IRs have undergone lineage-specific expansions. All orthologous gene pairs shared with the social wasp Vespa mandarinia are subject to purifying selection (Ka/Ks < 1), consistent with evolutionary constraint. Numerous species-specific genes were also detected. The observed patterns suggest the hypotheses about ecological adaptations such as specific prey pheromones, location of suitable nesting sites, and so on. Resolving these relative contributions will require broader taxon sampling and functional validation assays. These results in the present study provide a genomic resource for chemosensory gene characterization in Vespidae and a foundation for future olfactory-based pest management strategies. Full article

Q fever is a zoonotic disease associated with reproductive losses in ruminants. This study investigated a 2025 outbreak on a Boer goat breeding farm in South Korea and compared its molecular characteristics with those of a separate 2024 outbreak. Conventional PCR targeting the IS1111 insertion element was used to test 87 goats, three female farm dogs, and four barn-level composite environmental samples. Positive goat samples underwent multiple-locus variable-number tandem-repeat analysis and multispacer sequence typing. Coxiella burnetii was detected in 60 of 87 goats (69.0%) and in one environmental sample, whereas dogs were negative. Two multiple-locus variable-number tandem-repeat profiles were identified among four goat samples, and two goats from different barns shared a profile provisionally designated MST77-like because it clustered near, but was not identical to, the MST77 reference profile. After movement restrictions, oxytetracycline treatment, environmental management, and serial monitoring, 11 of 57 previously positive goats remained positive at the second screening, and none of these 11 goats tested positive at the final examination. Complete herd clearance and the independent effect of antimicrobial treatment could not be confirmed because previously negative goats were not retested and no untreated comparison group was available. These findings support farm-wide testing, strengthened biosecurity, and follow-up monitoring. Full article

Background: Apulia and neighbouring Southern Italian regions present a complex genetic stratification shaped by historical migrations. Phenylketonuria (PKU), caused by PAH mutations, serves as an excellent model for molecular epidemiology. This study maps the geographical distribution of PAH variants in a large Southern Italian cohort, evaluating their correlation with clinical phenotypes and long-term Body Mass Index (BMI). Methods: A retrospective cohort study was conducted on 344 patients followed for at least 10 years. Genetic characterization evolved from Sanger to Next-Generation Sequencing, and patients were stratified into micro-geographic clusters. Results: The genetic landscape was dominated by three ancestral variants (c.1208C>T, c.1066-11G>A, c.898G>T), accounting for 58% of the allelic pool. Significant micro-geographic polarization was observed: c.1222C>T clustered in Central–Northern Apulia, mirroring historical Norman-Swabian migration, whereas c.441+5G>T enriched in Southern Apulia. At final follow-up, classic PKU adult patients exhibited a four-fold increased risk of obesity (p < 0.05), driven by severe null alleles that necessitate a lifelong dependency on engineered low-protein foods. Conclusions: PAH mutational stratification serves as a contemporary reflection of historical migratory maps. Incorporating regional and genotypic mapping provides a precision medicine framework to anticipate phenotype severity, optimize therapeutic management, and tailor long-term obesity risk monitoring. Full article

Enterovirus alphacoxsackie (EV-A) is a highly diverse viral species containing at least 25 serotypes with diverse biological and clinical characteristics. EV-A can cause diseases ranging from asymptomatic infections to severe neurological disorders, as well as mucocutaneous diseases such as hand, foot, and mouth disease. 2A, a cysteine protease expressed by EV-A, plays critical roles in virus–host interactions. Although 2A orthologs of different EV-A serotypes share consistent protease-catalytic motifs and cleavage patterns, they show functional diversity in interacting with cellular proteins, probably due to distinct protease-independent activities determined by the single amino acid polymorphisms (SAPs) among different 2A orthologs. However, routine sequence alignment and phylogenetic analysis can hardly identify the key SAP sites (kSAPs) contributing to the functional variance, mainly due to the high conservation of the proteins and the unequal weight of SAPs in determining protein function. Herein, we developed Single Amino Acid Polymorphism Statistics (SAAPS), an information-entropy (IE)-based algorithmic pipeline, to identify the functional kSAPs of EV-A 2A. The core principle of the algorithm is that the IE of the kSAPs can be neither too low (highly conserved sites not leading to variance) nor too high (random neutral mutations). Using SAAPS, we identified 56 kSAPs from 2A of 25 EV-A serotypes. Based on the kSAPs, the 2As can be clustered into three major groups with a few outliers, which was distinct from the clustering generated by phylogenetic analysis using the whole amino acid sequences. Functional verification with transcriptomic profiles of HEK-293T cells expressing different 2A variants revealed closer alignment of kSAP clustering than phylogenetic clustering. Notably, EV-A89, an outlier identified by kSAP clustering but not phylogenetic clustering, showed a unique expression pattern with an altered shift in the molecular weight, which suggested that it was related to three SAPs identified by SAAPS. This study presents SAAPS as a useful tool for prioritizing functionally relevant SAPs to guide mechanistic discovery and can be applied to highly conserved proteins like EV-A 2A. Full article

The detection of antibiotic resistance genes (ARGs) in wastewater is commonly based on targeted PCR assays, limiting analysis to predefined genes. Consequently, the structure of wastewater resistomes often remains poorly characterised. Targeted enrichment sequencing offers an alternative approach for comprehensive resistome profiling. A panel targeting 2786 ARGs was applied to eight influent–effluent wastewater samples collected over one year from a large wastewater treatment plant in central Italy. Sequencing data were analysed at both the ARG and Antimicrobial Agent Categories (AACs) levels, and seasonal variation was explored using a ratio-based clustering approach. Overall, 743 ARGs were detected in both influents and effluents, with 84% of them. The resistome showed a strongly uneven structure, with a limited number of highly abundant ARGs accounting for ~60% of total abundance, while more than 500 genes were detected at ultra-low abundance. Thirty-five AACs were represented. Seasonal resistome profiles were generally stable, although winter samples showed a distinct enrichment pattern involving multiple ARGs, particularly tetracycline-associated ARGs. This structure was evident in influents becoming less defined in effluents. Targeted enrichment sequencing provided a broader view of the wastewater resistome, revealing a large pool of ARGs and seasonal patterns that would likely remain undetected using conventional PCR-based approaches. Full article

The Aquilegia ecalcarata (A. ecalcarata) complex is a valuable evolutionary model for studying parallel evolution, introgression, and incomplete lineage sorting. Deciphering this complexity requires evidence from multiple genomic compartments. While substantial nuclear and chloroplast resources exist, mitochondrial genome data, which capture the maternally inherited evolutionary history, have been absent for this group. Using long-read sequencing data, this study assembled and comprehensively characterized the mitochondrial genomes of five representative taxa within the A. ecalcarata complex. Comparative analyses reveal that the two spurless lineages, A. ecalcarata clade A and clade B, do not form a monophyletic group based on mitochondrial phylogeny. Instead, each clusters with a different spurred relative, consistent with the independent evolution of spur loss. This finding is further supported by collinearity patterns, gene content, and lineage-specific MTPT distributions. By providing the first mitochondrial genomic resource for this group, this study offers independent organellar evidence for the multiple origins of spurless phenotype in the A. ecalcarata complex. Full article

Background: Ancient DNA (aDNA) research is one of the biological fields that has been transformed by the development of next-generation sequencing (NGS). To date, Illumina sequencing has dominated aDNA research. However, its high costs are driving the adoption of alternative sequencing platforms. Combining data generated on different platforms may introduce artifacts arising from platform-specific errors. This study systematically compared the performance of four sequencing platforms (Illumina NovaSeq 6000, GeneMind SURFSeq 5000, Salus Evo, and MGI DNBSEQ-G400) for whole-genome aDNA sequencing using the same set of six samples and libraries. Methods: Single-stranded libraries, prepared with and without enzymatic damage repair, were generated from six human aDNA specimens recovered from Phanagoria polis and sequenced on all four platforms. Data were subsampled to equal read counts per library, mapped to the human reference genome, and compared using standard NGS quality metrics. Population genetic analyses, including principal component analysis (PCA) and ADMIXTURE, were performed to assess potential platform-specific biases. Results: All platforms produced raw sequencing data of acceptable quality. Only minor differences were observed among platforms in standard NGS metrics. The MGI platform showed a shift toward longer sequenced fragment lengths compared with Illumina and the Illumina-like platforms. Post-mortem damage patterns, particularly C>T substitutions, were highly consistent across all platforms. PCA and ADMIXTURE analyses revealed no evidence of platform-specific bias: results from all platforms clustered tightly together, and platform choice had no significant effect on ancestry component estimates. Conclusions: Our findings demonstrate that the GeneMind, Salus, and MGI sequencing platforms are comparable to Illumina for paleogenomic research. Moreover, aDNA datasets generated on these platforms can be combined for downstream analyses without introducing detectable bias. However, the fragment-size shift observed on the MGI platform warrants caution and adaptation when working with highly degraded or low-endogenous-content samples. Full article

In this paper, we reported a wild strain Z68, isolated from Tibet, was identified as Flammulina yunnanensis based on ITS sequence and phylogenetic analysis. Optimal condition for its mycelial growth (maltose, yeast extract, magnesium sulfate, 20 °C and pH 7.0–8.0) and fruiting ability was confirmed. Its fruiting bodies contained 25.1 g/100 g protein and 19.80 g/100 g of 16 amino acids, with iron, potassium and zinc, contents significantly higher than these in the controls F. fennae and F. velutipes. Significantly, whole-genome sequencing and comparative analysis of iron-metabolism gene families were performed between F. yunnanensis, F. fennae and F. velutipes to elucidate the basis of its notably elevated iron content, revealing most single copied and conserved iron-related gene families and two-fold expanded iron permease FTR1 in F. yunnanensi, which is the iron–sulfur cluster assembly protein family. Sequence, topology (DeepTMHMM), and structural-confidence (ColabFold/AlphaFold2) analyses of FTR1 identified six species-specified physicochemical substitutions, of which a charge reverse at the intracellular channel (Glu→Lys) and a polar-to-nonpolar change in the TM3 pore (Ser→Ala) were predicted to enhance iron transport efficiency. These suggested a possible two-tier mechanism underlying the elevated iron content of F. yunnanensis, combining gene-family expansion and predicted functional fine-tuning of the FTR1 permease. This study provided insight for biological characterization, domestication, and the molecular basis of iron enrichment in a F. yunnanensis Z68. Full article

Bovine viral diarrhea virus (BVDV) is a major cause of economic losses in the global cattle industry. This study investigated the clinical involvement and genetic diversity of BVDV in clinically affected cattle from the Thrace region in Türkiye, a critical border area with the European Union. A total of 533 nasal and rectal swabs were collected from 26 farms exhibiting clinical respiratory disease or diarrhea and analyzed using real-time RT-PCR. Positive samples were further characterized by sequencing and phylogenetic analysis to determine viral genotypes and subgenotypes. BVDV RNA was detected in 9 out of 26 farms (34.6%), with an overall positivity rate of 17.8% (95/533). Statistical analysis revealed significant associations between PCR positivity and both sampling year (p < 0.05) and animal age (p < 0.05). Genetic analysis of partial 5′-UTR sequences identified nine Pestivirus bovis subgenotype 1a strains, one Pestivirus bovis subgenotype 1f, and one Pestivirus brazilense. The Pestivirus bovis 1a strains clustered distinctly from previously reported Turkish BVDV-1 isolates, showing 97.32–99.11% nucleotide similarity with strains from Türkiye, Germany, China, Japan, the USA, Iran, and Argentina. Among the 533 samples tested, one Pestivirus brazilense isolate was identified, indicating its rare occurrence in the studied population despite targeted screening. This study represents the first report of Pestivirus brazilense in the Thrace region of Türkiye, expanding its known geographic range. The epidemiological data and genetic diversity analysis of BVDV strains characterized in this study offer critical insights for refining BVDV control programs, informing regional risk assessment, and supporting vaccine development. Full article

Accurate species identification is essential for biodiversity studies, ecological monitoring, and biosecurity, but current molecular approaches rely on PCR amplification, which requires universal primers. Here, we evaluated the possibility of primer-free species identification via direct RNA sequencing (dRNA-seq) by using Oxford Nanopore Technology (ONT). Total RNA isolated from three major eukaryotic kingdoms—fungal (Tuber magnatum Picco 1788), plant (Corylus avellana L. 1753), and animal (Eisenia fetida Savigny 1826) specimens—was sequenced without reverse transcription and PCR amplification. Taxonomic assignments based on similarity to ribosomal nuclear (fungi and animals) and chloroplast (plant) transcripts enabled reliable host species identification. Ribosomal RNA reads dominated the datasets and supported accurate identification of the target organisms, while additional sequences revealed associated microbiota and co-occurring taxa. Notably, dRNA-seq successfully detected symbiotic bacteria in E. fetida and latent fungal infection in C. avellana, highlighting the method sensitivity. However, the complex organization of nuclear ribosomal gene clusters may complicate taxonomic assignment in plants, underscoring the need for improved analytical pipelines. Overall, our results provide proof of concept that dRNA-seq enables primer-independent species identification while simultaneously providing insights into the host microbiomes. Direct sequencing of naturally present RNA molecules generated sufficient sequence information for species identification across different taxonomic kingdoms, indicating the technical feasibility of the developed technique. Further validation using larger biological datasets and direct comparisons with conventional sequencing methods will determine its wider applicability as an innovative and complementary species identification approach. Full article

People counting is one of the key tasks in intelligent monitoring systems. However, accurately counting people in dynamic environments can be extremely challenging. This is especially true in mobile robot applications, where challenges such as a moving camera, varying conditions, and a limited field of view due to environmental obstacles arise. In such scenarios, the people counting task primarily involves visually detecting and grouping individuals to determine the total number of unique people. This paper presents a people counting algorithm based on visual people detection and clustering. The method utilizes the You Only Look Once (YOLO) detector to identify the bounding boxes of detected individuals and extract features from their corresponding regions of interest (ROIs). Additionally, the dimension of the extracted features is reduced using an encoder and clustered to distinguish individuals, with the number of clusters serving as an estimate of the number of people. The method was tested on a dataset containing 45 independent sequences with a total of 19,350 RGB images, complete with metadata for people detection and re-identification. This dataset encompasses various settings, particularly scenarios featuring mobile robots moving and capturing frames in indoor environments. The experiments demonstrate the effectiveness of the proposed method in different configurations. The best results were achieved using the YOLOv10n detector combined with K-means or SK-means clustering, yielding a Mean Absolute Error ($MAE$) of 1.11. The proposed encoder-based method significantly reduces clustering time and operates effectively within the limited resources available on mobile robotic platforms such as the Jetson Nano. Full article

Breast cancer remains one of the most prevalent malignancies affecting women worldwide and continues to be a leading cause of cancer-related morbidity and mortality. Patients may present with either localized or advanced disease, with clinical outcomes increasingly influenced by molecular subtype and genetic profile. This review highlights the key genetic factors involved in breast cancer, current diagnostic and therapeutic strategies, and promising emerging approaches that may shape future clinical management. Breast cancer diagnosis typically involves clinical breast examination, imaging techniques such as mammography and ultrasound, and confirmatory biopsies. Genetic mutations in specific genes are strongly linked to the development, progression, and metastasis of the disease. Treatment options for localized breast cancer continue to include surgery (lumpectomy or mastectomy) and radiotherapy, combined with systemic therapies tailored to tumor biology, such as endocrine therapy, human epidermal growth factor receptor 2 (HER2)-targeted therapy, and cyclin-dependent kinase (CDK)4/6 inhibitors. For advanced or metastatic breast cancer, recent therapeutic advances include the use of immunotherapy (e.g., immune checkpoint inhibitors), Poly (ADP-ribose) polymerase (PARP) inhibitors for Breast Cancer gene (BRCA)-mutated cancers, antibody–drug conjugates, and novel targeted agents, which have significantly improved patient outcomes in selected populations. Recent findings in breast cancer genetics have highlighted the critical role of germline and somatic mutations, particularly in genes such as BRCA1, BRCA2, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), and TP53, in driving tumor initiation, progression, and therapeutic response. Molecular profiling and next-generation sequencing technologies have enabled more precise tumor classification and facilitated the development of personalized treatment strategies. Despite these advances, treatment resistance and disease recurrence remain major challenges, particularly in aggressive subtypes such as triple-negative breast cancer. Consequently, ongoing research is exploring alternative and complementary approaches, including nanotechnology-based drug delivery systems, gene editing techniques such as clustered regularly interspaced short palindromic repeats-Cas9 (CRISPR-associated protein 9) (CRISPR-Cas9), cancer vaccines, and the integration of traditional and plant-derived compounds. These strategies aim to enhance therapeutic efficacy, reduce systemic toxicity, and overcome resistance mechanisms. Full article

The developmental cycle of Pholiota nameko can be divided into four stages: the mycelial stage (JS), the primordium stage (FH), the growth stage (SZ), and the maturity stage (CS). In this study, transcriptome sequencing was performed on P. nameko at these four stages, followed by the screening of differentially expressed genes and functional annotation via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. By integrating the annotation results of all differentially expressed genes (DEGs), we screened for candidate genes potentially correlated with the growth and development of P. nameko. The expression levels of these candidate genes were then compared using real-time quantitative PCR (RT-qPCR) to identify those with the highest expression. The results showed that in the FH vs. CS and SZ vs. CS comparisons, DEGs were mainly enriched in pathways related to protein processing, fatty acid metabolism, and linoleic acid metabolism, suggesting that alterations in these specific metabolic pathways may be closely associated with the growth and development of P. nameko. Through analysis based on upregulation and log₂ fold change (log₂FC) values, further screening identified 13 candidate genes, and the gene Cluster-7415.13 with the highest expression level was preliminarily screened out through RT-qPCR analysis. This gene may be potentially involved in processes such as rapid cell expansion, cell wall synthesis, nutrient absorption, and active growth-stage metabolism. Full article