The emergence of SARS-CoV-2 variants of concern has prompted the need for near real-time genomic surveillance to inform public health interventions. In response to this need, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info, a platform that currently tracks over 40 million combinations of PANGO lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials, and the general public. We describe the interpretable and opinionated visualizations in the variant and location focussed reports available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data, and the server infrastructure that enables widespread data dissemination via a high performance API that can be accessed using an R package. We present a case study that illustrates how outbreak.info can be used for genomic surveillance and as a hypothesis generation tool to understand the ongoing pandemic at varying geographic and temporal scales. With an emphasis on scalability, interactivity, interpretability, and reusability, outbreak.info provides a template to enable genomic surveillance at a global and localized scale.
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http://dx.doi.org/10.21203/rs.3.rs-1723829/v1 | DOI Listing |
Front Genet
January 2025
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States.
Recent advancements in deep learning, particularly large language models (LLMs), made a significant impact on how researchers study microbiome and metagenomics data. Microbial protein and genomic sequences, like natural languages, form a , enabling the adoption of LLMs to extract useful insights from complex microbial ecologies. In this paper, we review applications of deep learning and language models in analyzing microbiome and metagenomics data.
View Article and Find Full Text PDFFront Cell Infect Microbiol
January 2025
One Health Brazilian Resistance Project (OneBR), São Paulo, Brazil.
From a One Health perspective, dogs and cats have begun to be recognized as important reservoirs for clinically significant multidrug-resistant bacterial pathogens. In this study, we investigated the occurrence and genomic features of ESβL producing Enterobacterales isolated from dogs, in the province of Imbabura, Ecuador. We identified four isolates expressing ESβLs from healthy and diseased animals.
View Article and Find Full Text PDFCureus
December 2024
Department of Clinical Research, University of San Luis Potosí, San Luis Potosí, MEX.
Background: In large-scale molecular studies, a protocol that generates high yields and quality DNA for future polymerase chain reaction (PCR) assays is needed. The collection of buccal cells by cytobrush may represent an efficient, noninvasive, and inexpensive method for obtaining genetic material from school populations. The aim of this study was to develop a method to obtain genomic DNA from buccal cells of schoolchildren, and the DNA was extracted immediately after collecting the buccal cell samples and after storing the samples for 8 months at -20 °C to establish the feasibility of the method for epidemiological studies.
View Article and Find Full Text PDFFront Immunol
January 2025
Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia.
Human rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap by employing immunoinformatics techniques for the design of a multi-epitope-based vaccine against HRV-C.
View Article and Find Full Text PDFWellcome Open Res
December 2024
Human Genetics, Wellcome Sanger Institute, Hinxton, England, CB10 1SA, UK.
Birth cohort studies involve repeated surveys of large numbers of individuals from birth and throughout their lives. They collect information useful for a wide range of life course research domains, and biological samples which can be used to derive data from an increasing collection of omic technologies. This rich source of longitudinal data, when combined with genomic data, offers the scientific community valuable insights ranging from population genetics to applications across the social sciences.
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