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We discuss genomic detection of Schmallenberg virus in both Culicoides midges and affected ruminants during June 2018–December 2019, demonstrating its circulation in Israel. This region is a geographic bridge between 3 continents and may serve as an epidemiologic bridge for potential Schmallenberg virus spread into Asia.

Background Genomic islands are associated with microbial adaptations, carrying genomic signatures different from the host. Some methods perform an overall test to identify genomic islands based on their local features. However, regions of different scales will display different genomic features. Results We proposed here a novel method “2SigFinder “, the first combined use of small-scale and large-scale statistical testing for genomic island detection. The proposed method was tested by genomic island boundary detection and identification of genomic islands or functional features of real biological data. We also compared the proposed method with the comparative genomics and composition-based approaches. The results indicate that the proposed 2SigFinder is more efficient in identifying genomic islands. Conclusions From real biological data, 2SigFinder identified genomic islands from a single genome and reported robust results across different experiments, without annotated information of genomes or prior knowledge from other datasets. 2SigHunter identified 25 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats from 27 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats, and detected 101 Phage and 28 HEG out of 130 Phage and 36 HEGs in S. enterica Typhi CT18, which shows that it is more efficient in detecting functional features associated with GIs.

Advanced molecular detection (AMD) refers to the integration of next-generation sequencing, epidemiologic, and bioinformatics data to drive public health actions. As new AMD technologies emerge, it is critical to ensure those methods are used in communities that are most affected by disease-induced illness and death. We describe strategies and opportunities for using AMD approaches to improve health in those communities, which include improving access to pathogen sequencing, increasing data linkages, and using pathogen sequencing for those diseases where sequencing technologies can provide the best health outcome. Such strategies can help address and prevent differences in health outcomes in various populations, such as rural and tribal communities, persons with underlying health issues, and other populations that experience higher risks for infectious disease.

Mammarenaviruses are noteworthy zoonotic pathogens, and the main reservoirs are rodent species. We report the detection of a novel mammarenavirus in 6/183 (3.3%) in necropsied European hedgehogs (Erinaceus europaeus) collected in Italy. The whole-genome sequence obtained for 4 strains revealed a marked genetic diversity but a monophyletic origin.

Background Studies indicate that gastric cancer (GC) incidence has decreased, whereas signet ring cell carcinoma (SRC) incidence has increased. However, recent trends in GC incidence are unclear. We used our hospital cancer registry to evaluate the changes in the incidence of GC, SRC, and non-SRC (NSRC) over time in comparison to changes in the H. pylori infection rates over time. Methods We identified 2532 patients with GC enrolled in our registry between January 2007 and December 2018 and statistically analyzed SRC and NSRC incidence. The H. pylori infection rate in patients with SRC was determined by serum anti- H. pylori antibody testing, urea breath test, biopsy specimen culture, and immunohistochemical analysis (IHC) of gastric tissue. Additionally, genomic detection of H. pylori was performed in SRCs by extracting DNA from formalin-fixed paraffin-embedded gastric tissue and targeting 16S ribosomal RNA of H. pylori. Results Overall, 211 patients had SRC (8.3%). Compared with patients with NSRC, those with SRC were younger ( P  <  0.001) and more likely to be female ( P  <  0.001). Time series analysis using an autoregressive integrated moving average model revealed a significant decrease in SRC ( P  <  0.001) incidence; NSRC incidence showed no decline. There was no difference in H. pylori infection prevalence between the SRC and NSRC groups. IHC and genomic methods detected H. pylori in 30 of 37 (81.1%) SRCs. Conclusions Reduction in H. pylori infection prevalence may be associated with the decrease in the incidence of SRC, which was higher than that of NSRC.

We sequenced sarbecovirus from Rhinolophus spp. bats in Bandarban District, Bangladesh, in a genomic surveillance campaign during 2022-2023. Sequences shared identity with SARS-CoV-1 Tor2, which caused an outbreak of human illnesses in 2003. Describing the genetic diversity and zoonotic potential of reservoir pathogens can aid in identifying sources of future spillovers.

Leptospirosis, caused by pathogenic Leptospira spp., is a widespread zoonotic disease worldwide. Early diagnosis is required for proper patient management and reducing leptospirosis morbidity and mortality.To summarize current literature regarding commonly used and new promising molecular approaches to Leptospira detection and diagnostic tests of human leptospirosis.The relevant articles in Leptospira and leptospirosis were retrieved from MEDLINE (PubMed) and Scopus.Several molecular techniques have been developed for diagnosis of human leptospirosis. Polymerase chain reaction-based techniques targeting on either lipL32 or 16S rRNA (rrs) gene are most commonly used to detect leptospiral DNA in various clinical specimens. Whole blood and urine are recommended specimens for suspected cases in the first (acute) and the second (immune) phases, respectively. Isothermal amplification with less expensive instrument is an alternative DNA detection technique that may be suitable for resource-limited laboratories.Detection of leptospiral DNA in clinical specimens using molecular techniques enhances sensitivity for diagnosis of leptospirosis. The efficient and robust molecular detection especially in the early leptospiremic phase may prompt early and appropriate treatment leading to reduced morbidity and mortality of patients with leptospirosis.

We report the detection and genomic characterization of chikungunya virus, an arbovirus, during a 2025 outbreak in Bolivia. We identified the circulating chikungunya virus lineage and the transmission dynamics by using genomic surveillance and phylogenetic analyses. Our findings highlight the utility of sustained genomic surveillance for monitoring emerging arboviruses.

Malignant catarrhal fever (MCF) is a fatal herpesvirus infection of domestic and wild ruminants, with a short and dramatic clinical course characterized primarily by high fever, severe depression, swollen lymph nodes, salivation, diarrhea, dermatitis, neurological disorders, and ocular lesions often leading to blindness. In the present study, fatal clinical cases of sheep associated malignant catarrhal fever (SA-MCF) were identified in cattle in the state of Karnataka. These cases were initially presented with symptoms of diarrhea, respiratory distress, conjunctivitis, and nasal discharges. Laboratory diagnosis confirmed the detection of ovine herpesvirus-2 (OvHV-2) genome in the peripheral blood samples of two ailing animals. The blood samples collected subsequently from sheep of the neighboring areas also showed presence of OvHV-2 genome indicating a nidus of infection in the region. The positive test results were further confirmed by nucleotide sequencing of the OIE approved portion of tegument gene as well as complete ORF8 region of the OvHV-2 genome. Phylogenetic analysis based on the sequence of the latter region indicated close genetic relationship with other OvHV-2 reported elsewhere in the world.

The functional annotation of the nonprotein-coding DNA of eukaryotic genomes is a problem of central importance. Phylogenetic footprinting methods, which attempt to identify functional regulatory regions by comparing orthologous genomic sequences of evolutionarily related species, have shown promising results. The main advantage of this class of approaches is that they do not require any knowledge of the regulating transcription factors. Here we describe a method called Enhancer Detection using only Genomic Information (EDGI), which integrates a traditional motif-discovery algorithm with a local permutation-clustering algorithm. Together, they can identify large regulatory elements (e.g., enhancers) as evolutionarily conserved order-independent clusters of short conserved motifs. We show that EDGI can distinguish between established sets of known enhancers and nonenhancers with 88% accuracy, rivaling predictions by methods that rely on the knowledge of the regulating transcription factors and their DNA-binding specificities. We tested EDGI's performance on a set of Drosophila genomes. Our results demonstrate that comparative genomic analysis of multiple closely related species has substantial power to identify key functional elements without additional biological knowledge.