@article {813, title = {The integrated genomic surveillance system of Andalusia (SIEGA) provides a One Health regional resource connected with the clinic.}, journal = {Sci Rep}, volume = {14}, year = {2024}, month = {2024 Aug 19}, pages = {19200}, abstract = {

The One Health approach, recognizing the interconnectedness of human, animal, and environmental health, has gained significance amid emerging zoonotic diseases and antibiotic resistance concerns. This paper aims to demonstrate the utility of a collaborative tool, the SIEGA, for monitoring infectious diseases across domains, fostering a comprehensive understanding of disease dynamics and risk factors, highlighting the pivotal role of One Health surveillance systems. Raw whole-genome sequencing is processed through different species-specific open software that additionally reports the presence of genes associated to anti-microbial resistances and virulence. The SIEGA application is a Laboratory Information Management System, that allows customizing reports, detect transmission chains, and promptly alert on alarming genetic similarities. The SIEGA initiative has successfully accumulated a comprehensive collection of more than 1900 bacterial genomes, including Salmonella enterica, Listeria monocytogenes, Campylobacter jejuni, Escherichia coli, Yersinia enterocolitica and Legionella pneumophila, showcasing its potential in monitoring pathogen transmission, resistance patterns, and virulence factors. SIEGA enables customizable reports and prompt detection of transmission chains, highlighting its contribution to enhancing vigilance and response capabilities. Here we show the potential of genomics in One Health surveillance when supported by an appropriate bioinformatic tool. By facilitating precise disease control strategies and antimicrobial resistance management, SIEGA enhances global health security and reduces the burden of infectious diseases. The integration of health data from humans, animals, and the environment, coupled with advanced genomics, underscores the importance of a holistic One Health approach in mitigating health threats.

}, keywords = {Animals, Drug Resistance, Bacterial, Genome, Bacterial, Genomics, Humans, One Health, Virulence Factors, Whole Genome Sequencing}, issn = {2045-2322}, doi = {10.1038/s41598-024-70107-0}, author = {Casimiro-Soriguer, Carlos S and Perez-Florido, Javier and Robles, Enrique A and Lara, Mar{\'\i}a and Aguado, Andrea and Rodr{\'\i}guez Iglesias, Manuel A and Lepe, Jose A and Garc{\'\i}a, Federico and P{\'e}rez-Alegre, M{\'o}nica and And{\'u}jar, Elo{\'\i}sa and Jim{\'e}nez, Victoria E and Camino, Lola P and Loruso, Nicola and Ameyugo, Ulises and Vazquez, Isabel Mar{\'\i}a and Lozano, Carlota M and Chaves, J Alberto and Dopazo, Joaquin} } @article {744, title = {Highly accurate whole-genome imputation of SARS-CoV-2 from partial or low-quality sequences.}, journal = {Gigascience}, volume = {10}, year = {2021}, month = {2021 12 02}, abstract = {

BACKGROUND: The current SARS-CoV-2 pandemic has emphasized the utility of viral whole-genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and, therefore, useless sequences. Viral sequences evolve in the context of a complex phylogeny and different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data.

RESULTS: We have developed the impuSARS application, which takes advantage of the enormous number of SARS-CoV-2 genomes available, using a reference panel containing 239,301 sequences, to produce missing data imputation in viral genomes. ImpuSARS was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing), showing great fidelity when reconstructing the original sequences, recovering the lineage with a 100\% precision for almost all the lineages, even in very poorly covered genomes (<20\%).

CONCLUSIONS: Imputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. ImpuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole-genome sequencing.

}, keywords = {Genome, Viral, Phylogeny, SARS-CoV-2, Whole Genome Sequencing}, issn = {2047-217X}, doi = {10.1093/gigascience/giab078}, author = {Ortuno, Francisco M and Loucera, Carlos and Casimiro-Soriguer, Carlos S and Lepe, Jose A and Camacho Martinez, Pedro and Merino Diaz, Laura and de Salazar, Adolfo and Chueca, Natalia and Garc{\'\i}a, Federico and Perez-Florido, Javier and Dopazo, Joaquin} }