Facing multidrug resistant (MDR) bacterial pathogens is one of the most important challenges for our society. The spread of highly virulent and resistant pathogens can be described using molecular typing technologies; in particular, whole genome sequencing (WGS) data can be used for molecular typing purposes with high resolution. WGS data analysis can explain the spatiotemporal patterns of pathogen transmission. However, the transmission between compartments (human, animal, food, environment) is very complex. Interoperable and curated metadata are a key requirement for fully understanding this complexity. In addition, high quality sequence data are a key element between centres using WGS data for diagnostic and epidemiological applications. We aim to describe steps to improve WGS data analysis and to implement a molecular surveillance platform allowing integration of high resolution WGS typing data and epidemiological data.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.4414/smw.2018.14693 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
LD-informed deep learning for Alzheimer's gene loci detection using WGS data.
Alzheimers Dement (N Y)
January 2025
Indiana Alzheimer Disease Research Center and Center for Neuroimaging, Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis Indiana USA.
Introduction: The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.
View Article and Find Full Text PDFTargeted sputum sequencing for rapid and broad drug resistance of Mycobacterium tuberculosis.
Infection
January 2025
Institute of Population Health Sciences, National Health Research Institutes, No. 35, Keyan Road, Zhunan Town, Miaoli County, 35053, Taiwan.
Purpose: Rapid detection of drug resistance in Mycobacterium tuberculosis (Mtb) from clinical samples facilitates the timely provision of optimal treatment regimens for tuberculosis (TB) patients.
Methods: In November, 2023, the WHO released its second catalogue of resistance-conferring mutations in Mtb. Utilizing this information, we developed a single 17-plex PCR assay covering 16 key resistance genes and modified thermo-protection buffer to amplify 30 kbp DNA directly from sputum samples for nanopore sequencing.
Antimicrobial resistance profiles and molecular epidemiology of isolates from Scottish bovine mastitis cases.
Epidemiol Infect
January 2025
Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
are opportunistic pathogens which can cause mastitis in dairy cattle. mastitis often has a poor cure rate and can lead to the development of chronic infection, which has an impact on both health and production. However, there are few studies which aim to fully characterize by whole-genome sequencing from bovine mastitis cases.
View Article and Find Full Text PDFBackground: The transmission of Salmonella spp. to human through the consumption of contaminated food products of animal origin, mainly poultry is a significant global public health concern. The emerging multidrug resistant (MDR) clones of non-typhoidal Salmonella (NTS) serovars, have spread rapidly worldwide both in humans and in the food chain.
View Article and Find Full Text PDFOn the ability to extract MLVA profiles of Vibrio cholerae isolates from WGS data generated with Oxford Nanopore Technologies.
BMC Res Notes
January 2025
Center for Applied Molecular Technologies (CTMA), Institute of Clinical and Experimental Research (IREC), Université catholique de Louvain (UCLouvain), Brussels, Belgium.
Objective: Multiple-Locus Variable Number of Tandem Repeats (VNTR) Analysis (MLVA) is widely used to subtype pathogens causing foodborne and waterborne disease outbreaks. The MLVAType shiny application was previously designed to extract MLVA profiles of Vibrio cholerae isolates from whole-genome sequencing (WGS) data, and provide backward compatibility with traditional MLVA typing methods. The previous development and validation work was conducted using short (pair-end 300 and 150 nt long) reads from Illumina MiSeq and Hiseq sequencing.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!