Search Results (1,191)

Background/Aims: While pathogenic germline variants play a critical role in pediatric cancer susceptibility, traditional clinical genetics primarily focuses on single-gene interpretations. Transitioning to a systems-level analysis of inherited variation can uncover shared biological vulnerabilities, informing genetic counseling, surveillance, and targeted therapeutics. This study aims to implement an unsupervised machine learning framework to identify and characterize Germline Mutation Signatures (GMS) across diverse pediatric malignancies, elucidating latent genomic patterns that reveal shared oncogenic mechanisms. Methods: We analyzed germline whole-exome and whole-genome sequencing (WES/WGS) data from a retrospective cohort of 420 pediatric cancer patients and matched non-cancer controls. Variants were deeply annotated to capture multi-dimensional features, including predicted pathogenicity, splice-site disruption, regulatory impact, population frequency, and sequence context. To enable robust modeling, we integrated an augmented feature set encompassing evolutionary constraint, loss-of-function intolerance, and compositionally normalized substitution spectra. These high-dimensional annotations were processed using a deep autoencoder for non-linear representation learning, followed by Gaussian Mixture Modeling (GMM) of the latent space. Results: The framework delineated 13 signatures (GMS1–GMS13), yielding an optimal Davies–Bouldin index of 1.051. These signatures map to fundamental biological processes, including DNA repair deficiencies, transcription-coupled damage, replication stress, and aberrant RNA regulation. Crucially, these GMSs transcend traditional tissue-of-origin classifications, manifesting across multiple distinct cancer types. This observation indicates convergent germline etiologies and suggests potential shared susceptibilities to pathway-directed therapies. Conclusions: The discovery of these cross-cancer signatures provides a scalable, biologically interpretable framework for decoding inherited pediatric cancer risk. While the therapeutic mapping networks identified are currently exploratory and serve as a hypothesis-generating foundation, this deep learning-driven paradigm establishes a robust basis for stratified precision medicine. Pending prospective clinical validation, this approach holds significant translational potential to move beyond single-gene paradigms toward unified, systems-level precision oncology strategies. Full article

Clostridium perfringens is a major foodborne pathogen in which the genomic localization of the enterotoxin gene, cpe, plays an important epidemiological role. In this study, four isolates associated with independent foodborne outbreaks in South Korea were analyzed using complete genome sequencing. All isolates were cpe-positive, including three strains carrying chromosomal cpe (c-cpe) and one strain carrying plasmid-borne cpe (p-cpe). To provide a broader genomic context, complete genomes retrieved from the National Center for Biotechnology Information database were also analyzed. Most cpe-positive strains carried p-cpe, whereas c-cpe strains were relatively uncommon. Whole-genome analysis revealed a distinct separation between c-cpe and p-cpe strains based on conserved core-genome features and virulence gene profiles. In c-cpe strains, the cpe gene was consistently located between the nadA–C operon and a downstream nucleobase transporter gene and was flanked by IS1470 family transposases, suggesting a conserved chromosomal structure and a possible vertical inheritance. Conversely, p-cpe strains carried cpe on conserved pCW3-like plasmids, indicating that horizontal gene transfer mediated by a specific plasmid lineage contributes to cpe dissemination across diverse genetic backgrounds. Overall, these findings show that cpe localization is associated with distinct genomic patterns in C. perfringens. Full article

Serratia marcescens has emerged as an important opportunistic pathogen in intensive care units (ICUs), where critically ill patients, invasive devices, antimicrobial exposure, and complex environmental reservoirs create favorable conditions for colonization, infection, and recurrent outbreaks. This narrative review synthesizes evidence from the past decade regarding the clinical and molecular epidemiology, environmental persistence, device-associated transmission, biofilm-mediated resistance, and infection-control strategies of S. marcescens in ICU settings. The literature was reviewed using an integrative approach informed by Ferrari’s narrative review framework, with thematic synthesis across clinical, microbiological, environmental, and genomic domains. Recent evidence indicates that ICU-associated S. marcescens infections frequently involve respiratory tract colonization, ventilator-associated pneumonia, bloodstream infection, urinary tract infection, and device-related transmission. Hospital water systems, sink drains, wet surfaces, ventilator circuits, reusable equipment, and contaminated antiseptic or liquid products may serve as persistent reservoirs, particularly when biofilm formation supports long-term survival and recurrent dissemination. At the molecular level, S. marcescens demonstrates substantial genomic diversity, intrinsic and acquired antimicrobial resistance, inducible AmpC β-lactamase activity, efflux-mediated tolerance, and plasmid-associated resistance gene transfer. This review particularly emphasizes the molecular determinants that enable S. marcescens to persist in ICU ecosystems, including AmpC-mediated β-lactam resistance, efflux-associated tolerance, quorum-sensing-regulated biofilm formation, plasmid-mediated horizontal gene transfer, and WGS-defined clonal transmission. Whole-genome sequencing, rapid molecular diagnostics, active surveillance, environmental sampling, and integrated infection-control bundles have become increasingly important for distinguishing clonal outbreaks from endemic transmission and guiding timely interventions. Emerging perspectives emphasize the need to combine antimicrobial stewardship, environmental engineering, respiratory-care auditing, anti-biofilm strategies, and AI-assisted real-time surveillance into adaptive ICU infection-control frameworks. Overall, S. marcescens should be regarded not merely as an episodic outbreak organism, but as a highly adaptable ICU-associated pathogen requiring multidisciplinary prevention strategies. Full article

Bacillus anthracis is endemic in the United States causing periodic outbreaks in wildlife and domestic animals. Currently, human anthrax cases in the U.S. are rare but were common in the 1950s–1960s due to industrial work with imported B. anthracis-contaminated animal products. Multiple-locus variable-number tandem repeat analysis (MLVA) initially differentiated B. anthracis into 89 genotypes and two major clades. Recently, whole-genome sequencing (WGS) was implemented to differentiate B. anthracis which allows for higher resolution and can eliminate risk of homoplasy. To assess the molecular diversity of U.S.-established isolates, we performed MLVA and WGS on 81 B. anthracis isolates from domestic animals or soil. By MLVA, most isolates (n = 58, 72%) were in the Western North America (WNA)/A1.a cluster. Isolates were also observed in the Ames (A3.b), Vollum (A4), and Group B clusters. Using WGS, two major clades (A and B) and four clusters (WNA, Ames, Vollum, Group B) were identified. The four WGS clusters correlated with previously established MLVA clusters (A1a, A3b, A4, and B1, respectively). Further differentiation of the WNA cluster showed that isolates collected from the same state generally clustered together and more broadly by region (west, central, Texas). In the current study, we provide an update on the genetic diversity of domestically established B. anthracis strains using MLVA and WGS. WGS was able to provide additional differentiation, particularly within the WNA cluster, which can lend assistance in epidemiological investigations. Full article

Background/Objectives: Advances in whole-genome sequencing (WGS) technology have led to the widespread adoption of WGS for investigating genetic diseases and traits in domestic animals. This has created a need for improved methods for prioritizing candidate causal variants. One way variants are prioritized is using variant annotators that predict variant effects based on their proximity to genomic features and effect on amino acid sequence. However, validation of variant annotators for domestic animal genomes is lacking. Methods: In this study, we calculated the agreement of three popular variant annotators, Ensembl Variant Effect Predictor (Ensembl-VEP), SnpEff, and ANNOVAR, across >58 million variants identified in 1065 horse genomes. Results: Comparisons showed that agreement across all three variant annotators was >90% when terminology was standardized. Terminology standardization was the most important factor affecting agreement, as agreement dropped to 0–67% when terminology was not standardized across variant annotators. Genomic context was also a major factor, as exonic, and specifically loss-of-function, variants showed lower agreement rates than intergenic variants. In addition to annotation agreement, differences in computational resource requirements were identified. ANNOVAR required ~28× more memory and ~1.5× more time than the next best tool. Conclusions: These results demonstrate that tool selection for annotating variants should not be based on a single metric; rather, a study’s needs and available computational resources should be considered when selecting the appropriate variant annotators(s) along with the standardization of terminology across annotators. These findings are a resource for guiding decisions on the use of variant annotators in domestic animals and suggest areas for improvement in the standardization of variant prioritization. Full article

Direct sputum targeted next-generation sequencing (tNGS) offers rapid resistance profiling without culture, but its concordance with isolate-based whole-genome sequencing (WGS) and phenotypic drug susceptibility testing (pDST) remains unclear. We compared tNGS (direct sputum) and WGS (cultured isolates) for 14 drugs’ resistance prediction in 68 culture-positive tuberculosis specimens, using pDST as reference. Performance for lineage concordance was also assessed. tNGS showed the highest rifampicin (RIF) sensitivity (90.9%) but the lowest specificity (65.2%); WGS achieved the best overall agreement (86.8%). For isoniazid, tNGS sensitivity was 82.6% vs. WGS 78.3%, but WGS specificity was higher (91.1% vs. 75.6%). tNGS outperformed WGS for ethambutol (EMB) sensitivity (80.0% vs. 40.0%). Both methods performed poorly for pyrazinamide (PZA) (agreement ~40%). Among 68 specimens, 51.5% had fully concordant resistance profiles; tNGS-only variants outnumbered WGS-only variants 2:1. Crucially, tNGS and WGS on the same 24 cultured isolates yielded identical results, proving that discrepancies arise from culture-driven clonal selection, not technical differences. Direct sputum tNGS suggests broader within-host resistance diversity that may be missed by culture, whereas WGS offers superior specificity. The two methods are complementary, with culture bias being the primary source of discordance. Full article

Background: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a critical public health threat because infections caused by this pathogen are associated with high morbidity, mortality, and limited effective therapeutic options. Whilst the majority of studies have concentrated on inter-patient bacterial transmission, within-host genomic analysis offers unprecedented resolution for tracking dynamic clone predominance, plasmid rearrangements, and microevolution under clinical selection pressures. Methods and Results: Whole-genome sequencing (WGS) of nine isolates recovered from oral and rectal swabs revealed an exceptional case of CRKP clonal turnover in an intensive care unit (ICU) patient. Three distinct high-risk clones were identified during the 18 days of surveillance: an initial ST101 (Clonal Group (CG) 101) strain (days 1–7) followed by concurrent colonization with ST395 (carrying bla_NDM-5) and ST512 lineages (both CG258, days 11–18). Conclusions: This study describes a rare instance of within-host heterogeneity of CRKP, involving three distinct STs spanning two CGs. Whole-genome analysis revealed potential structural rearrangements of resistance- and virulence-associated plasmids between coexisting lineages. These genomic shifts likely reflect rapid adaptation under the intense selective pressure of broad-spectrum antibiotic therapy, culminating in the persistence of a less virulent yet multidrug-resistant ST512 clone and a favorable clinical outcome with patient recovery. Full article

Genomic sequencing can reveal potentially life-threatening clinically actionable secondary findings in healthy individuals. Little is known about the spectrum and frequency of secondary findings in healthy people in Russia. Here, we analyzed whole-genome sequences of 42,826 healthy volunteers from urban populations across Russia, focusing on known pathogenic and likely pathogenic variants of 81 genes associated with treatable or preventable monogenic diseases listed in the American College of Medical Genetics and Genomics’ Secondary Findings recommendations (ACMG SF v3.2). Based on the ClinVar 20250421 version, secondary findings were detected in 1186 (2.76%) participants. Cancer phenotypes were the most common category of secondary findings present in 565 (1.32%) participants, followed by cardiovascular phenotypes (454 individuals, 1.05%). Genes harboring the most frequent variants were BRCA1 (151 variants), BRCA2 (100), RYR1 (93), and LDLR (71). In addition, we found 238 potential loss-of-function variants in dominant ACMG SF v3.2 list genes in 280 (0.65%) participants, which, if confirmed by orthogonal methods, could increase the frequency of secondary findings to 3.41%. A study of such depth and scale was performed for the first time in the Russian population. Full article

Background/Objectives: Vancomycin-resistant (VRE) and vancomycin-variable (VVE) Enterococcus spp. represent an increasing clinical challenge due to limited treatment options and the potential for undetected dissemination of such resistance genes. Data on Enterococci genomic epidemiology in healthcare settings remain rather limited. Our study aimed to investigate vancomycin resistance determinants in Enterococcus spp., clonal structure, and occurrence of VVE using whole-genome sequencing (WGS) in Latvia. Methods: Clinical isolates collected from hospitalised patients in two tertiary-level hospitals in Latvia (2021–2024) were analysed using WGS following routine laboratory identification. Vancomycin resistance determinants were identified in silico, along with MLST and cgMLST genotyping. Results: Of 532 sequenced isolates, 482 met the quality and inclusion criteria. E. faecalis (56.64%) and E. faecium (40.25%) predominated. Among 125 isolates carrying vancomycin resistance genes, vanB (54.40%) was the most frequent, followed by vanA (38.20%) and vanC (6.40%); vanC was restricted to E. gallinarum and E. casseliflavus. Vancomycin resistance was more prevalent in E. faecium (51.03%) than in E. faecalis (6.59%). cgMLST identified outbreak clusters among E. faecium ST80 and ST78 with complex type-specific resistance patterns and hospital specificity. E. faecalis showed polyclonal endemicity with the vanB gene present in different clades. Three (0.62%) vancomycin-variable E. faecium (VVE) isolates were identified in one hospital, harbouring vanA-type gene clusters comprising vanHAX but lacking the sensory gene vanS and the regulatory gene vanR. Conclusions: The VanB gene predominated in both hospitals, driven by clonal expansion of hospital-adapted E. faecium ST80/ST78, contrasting with earlier vanA predominance in Europe but aligning with recent regional vanB trends. The detection of VVE highlights clinically relevant genotype–phenotype discordance, underscoring the importance of integrating genomic surveillance with routine phenotypic testing to detect cryptic resistance and guide effective antimicrobial therapy. Full article

Cronobacter spp. are opportunistic foodborne pathogens that can cause neonatal meningitis, necrotizing enterocolitis, and sepsis. This study conducted a systematic contamination survey and whole-genome epidemiological analysis of 562 low-water-activity food samples in Hunan Province of China. The results showed an overall Cronobacter spp. detection rate of 41.99% (236/562), with spices exhibiting the highest contamination rate (60.06%), and with high-level contamination samples (>110 MPN/g) concentrated in this category. The 236 isolates comprised 6 species, 120 sequence types, and 39 clonal complexes, with C. sakazakii being the most frequently isolated species (64.83%) and high-risk clones ST4, ST1, ST148, and ST64 prevailing. Multiple virulence genes (TraJ, fur, rcsAB, rpoS) and antimicrobial resistance genes (qnrS1, blaTEM-1, blaCTX-M-55, blaLAP-2, aac(3)-IId, aadA2, tet(A), floR, mcr-9.1, sul2) were detected. Core genome multilocus sequence typing (cgMLST) identified two clustering patterns: Cluster C, whose genetic clustering was consistent with transmission associated with potential common upstream raw materials across different brands and provinces, and Cluster G, whose clustering suggested potential persistent colonization in the production environment across multiple batches of the same brand. This study elucidates the contamination characteristics of Cronobacter spp. in low-water-activity foods from Hunan Province and provides a basis for WGS-based active surveillance and supply chain traceability. Full article

Background/Objectives: Antimicrobial resistance (AMR), driven by high-risk bacterial pathogens, is a major healthcare threat. This scoping review mapped artificial intelligence/machine learning (AI/ML) and computational approaches integrated with whole-genome sequencing (WGS), genomic surveillance, rapid typing, epidemiological data, or clinical metadata for early warning of AMR outbreak clones. Methods: Following PRISMA-ScR guidance and the Population–Concept–Context (PCC) framework, PubMed/MEDLINE, Scopus, and Web of Science were searched for English-language studies published between 2010 and 2026. Eligible studies addressed AI/ML or computational approaches for AMR outbreak detection, clone surveillance, transmission analysis, or infection prevention and control (IPC). Results: Thirty-eight studies were grouped into five domains: genomic surveillance; rapid typing; resistance, risk-factor, and lineage prediction; transmission reconstruction; and IPC-oriented genomic epidemiology. AI/ML supported automation, isolate prioritization, typing triage, prediction, transmission modelling, and electronic health record (EHR)-linked route identification. Conclusions: AI/ML may enhance WGS-based AMR surveillance, but validation, dataset dependence, heterogeneity, and limited IPC outcome reporting remain key gaps. Full article

Background: Previous work from our group demonstrated an association between immunohistochemical detection of Human cytomegalovirus (HCMV) late antigen and poor event-free survival (EFS) in pediatric medulloblastoma. Whole-genome sequencing (WGS) further identified increased abundance of HCMV-aligned reads at the UL88 locus, particularly in Group 3 tumors, a molecular subgroup associated with aggressive clinical behavior and poor prognosis. Methods: We performed an integrated multi-omics analysis of pediatric medulloblastoma using WGS (n = 39) and RNA sequencing (RNA-seq; n = 28) datasets. RNA-seq data were filtered using stringent alignment criteria (MAPQ ≥ 20) and compared with fetal brain (n = 12), adult brain (n = 12), and HCMV-infected cell culture controls (n = 3). Only high-confidence uniquely aligned reads were retained to reduce nonspecific and multi-mapped viral alignments. Sequencing reads were aligned to the HCMV Merlin reference genome (NC_006273.2) using a standardized analytical pipeline. A subset of 28 cases with matched tumor WGS, tumor RNA-seq, and germline WGS data was used for integrated multi-omics analyses. Orthogonal validation analyses were performed in Group 3 tumors using independent genomic and transcriptomic approaches. Exploratory survival analyses were conducted in a combined cohort (n = 84) integrating genomic and immunohistochemical datasets. Results: Recurrent low-level HCMV-aligned molecular signals were identified across medulloblastoma datasets. Reads aligning to UL76, UL88, and UL99 were the most consistently detected HCMV-associated late-gene signals across RNA-seq and WGS datasets. A composite HCMV late-gene signature (UL76–UL88–UL99) showed higher levels in Group 3 tumors than in other molecular subgroups (p < 0.05 in WGS analyses). Orthogonal analyses demonstrated concordant low-level HCMV-associated genomic and transcriptomic signals enriched in tumors with MYC-associated activation and chromosome 17 imbalance. In the combined cohort (n = 84), elevated HCMV-associated signal assessed by immunohistochemistry and genomic profiling was associated with reduced EFS (median 55 vs. 147 months; log-rank p < 0.001). The subgroup classified as HCMV-high Group 3 demonstrated the strongest association with adverse outcome in exploratory multivariable analyses (HR = 6.43, p = 0.002). Conclusions: This study identifies recurrent low-level HCMV-associated genomic and transcriptomic signals across pediatric medulloblastoma datasets, with preferential enrichment in biologically aggressive Group 3 tumors. Although the extremely low abundance of viral-aligned reads precludes definitive evidence of productive viral infection, the reproducible detection of HCMV-associated molecular signatures across independent sequencing platforms supports further investigation into a potential oncomodulatory association in pediatric medulloblastoma. Additional validation using optimized viral detection methodologies, independent cohorts, and mechanistic studies will be necessary to clarify the biological and clinical significance of these findings. Full article

Background: The rapid rise in antimicrobial resistance (AMR) represents one of the most pressing global health challenges of the 21st century, threatening antibiotic effectiveness, compromising clinical outcomes, and undermining healthcare systems. Understanding how resistant pathogens emerge and spread across human, animal, and environmental sectors is essential for effective global response. Main body: This review evaluates traditional and advanced AMR detection methodologies, including phenotypic assays, molecular diagnostics, whole-genome sequencing (WGS), metagenomics, and biosensor-based technologies. It also highlights the role of bioinformatics tools, surveillance databases, and integrated platforms that support real-time analysis. Genomic surveillance provides unparalleled resolution for characterizing resistance mechanisms, transmission patterns, and evolutionary trajectories of multidrug-resistant organisms. Techniques such as WGS and metagenomics allow timely and precise identification of resistance genes, improving outbreak detection and strengthening antimicrobial stewardship. Despite these advantages, the adoption of genomic surveillance faces barriers in low- and middle-income countries, including high costs, limited infrastructure, insufficient technical expertise, and the lack of standardized data frameworks. Conclusions: Genomic surveillance is a transformative tool for combating AMR and strengthening global health systems. Effective implementation requires sustained investment, capacity-building, coordinated cross-sector collaboration, and commitment to the One Health approach to ensure equitable access and long-term global impact. Full article

Background: Persistent high-risk human papillomavirus (hrHPV) infection causes over 99% of cervical precancers and cancers worldwide, with HPV genotype 16 (HPV16) responsible for 50% of the cases. Latvia ranks among the top EU countries for cervical cancer incidence and mortality. In the general Latvian population, 4.2% of women are hrHPV-infected, mostly with HPV16. However, information on the circulating HPV16 isolates is missing. Objectives: To study the genomic variability of the Latvian HPV16 isolates, compare them with HPV16 in Europe and across the globe, reveal features associated with the severity of cervical disease and uncover eventual sequence changes due to the national HPV vaccination. Methods: DNA was extracted from the formalin-fixed paraffin-embedded cervical tissues of women diagnosed with cervical intraepithelial neoplasia (CIN) stages I-III and squamous cell carcinoma (SCC) grades 1–3, collected between 2012 and 2024. Samples positive for HPV16 were subjected to whole genome sequencing (WGS) on the Illumina platform (n = 16) or Sanger sequencing of the E6/E7 coding region (n = 31). A consensus HPV16 sequence was generated, and single nucleotide polymorphisms (SNPs) and eventual amino acid substitutions (AAS) were analysed. Results: Complete genomes of 16 HPV16 variants were reconstructed, with 13 related to the European sublineage A1 and 3 to the sublineage A2 references. Sequences showed high conservation; still 93 non-redundant variants were identified. The highest variability was observed for the capsid protein L2, and the lowest, for oncoprotein E7. The prevalence of SNPs and AAS in the Latvian HPV16 variants, specifically in capsid protein L1, did not increase with time, showing no effect of HPV vaccination. Associations between HPV16 sequence features and severity of cervical disease were limited to AAS E6:L90V, which was significantly more common in SCC grade 2/3 than in CINII/III cases (p = 0.015). Conclusions: Highly conserved HPV16 genomes circulating in Latvia harbour a series of unique as well as common nonsynonymous SNPs with respective AAS, with one, AAS E6:L90V, associating with disease severity. No HPV vaccine escape variants were detected. Deciphering complete genomes of HPV16 from CIN and SCC cases in Latvia informs public authorities performing HPV vaccination and is useful for the management of HPV-associated cervical diseases. Full article

Background: The rising prevalence of Extended-spectrum β-lactamase-producing (ESBL) Escherichia coli poses a significant threat to human and animal health. Methods: To address this, we conducted a longitudinal two-year One Health study to assess ESBL E. coli occurrence and distribution across dairy farms, surrounding environments, and urban wastewater in a peri-urban region of Western Canada. Results: A total of 546 presumptive ESBL E. coli were recovered, with the highest occurrence in wastewater influent (75.9%) and calf feces (73.6%), and lowest in soil (6.3%) and surface water (18.8%). Seasonal analysis showed a significantly higher occurrence in summer compared to spring. The bla_CTX-M-15 gene predominated (79%), followed by bla_TEM (28%) and bla_SHV (9%), with most isolates harboring multiple ESBL genes. Whole-genome sequencing of 387 isolates identified 75 resistance determinants spanning nine antimicrobial classes, including 24 β-lactamase genes and 10 CTX-M variants. Ninety-four sequence types (STs), including nine novel STs, were detected. The most common STs were ST648, ST69, and ST10, with distinct distributions across sources. Plasmid analysis revealed extensive diversity, with approximately half of the plasmid types shared across multiple sample types, indicating potential horizontal gene transfer. Over 200 virulence factors were identified, including toxin genes and Shiga toxin-associated genes, primarily in calf and surface water isolates. Phylogroups A and B1 dominated samples from dairy farms, and phylogroup B2 was restricted to wastewater and surface water. Conclusions: These findings identify the environment as a reservoir for ESBL E. coli and reveal the unexpected predominance of the emerging MDR ST648 lineage, rather than ST131, and reinforce the need for comprehensive integrated One Health surveillance. Full article