The integrated genomic surveillance system of Andalusia (SIEGA) provides a One Health regional resource connected with the clinic

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: AMR; Epidemiology; One health; Resistances; Surveillance; Whole genome sequencing.

Figure 1

The SIEGA circuit. The different provinces that collect samples send them for extraction of DNA to the different reference laboratories, which is subsequently sent to the sequencing facilities and finally the resulting genomic data is uploaded in the central SIEGA data management system. The map of Andalusia was generated using mapSpain software from: https://ropenspain.github.io/mapSpain/articles/x02_mapasesp.html. The figure was generated with PowerPoint.

Figure 2

Phylogenies from Nextstrain viewers for: (A) Salmonella enterica, (B) Listeria monocytogenes, (C) Campylobacter jejuni, (D) Escherichia coli, (E) Legionella pneumophila and (F) Yersinia enterocolitica.

Figure 3

Y. enterocolitica GrapeTree representation, generated within the SIEGA application. Node labels represent ST (in some cases an ambiguous ST assignation occurred and more than one number is displayed) and node color correspond to the sampling month (a warm gradient has been used to better display the time scale). Numbers in the branches correspond to the allelic distances among nodes. The GrapeTree representation provides an intuitive visualization of the temporal scale of sampling and the genetic similarities among the samples. Using different labels from the metadata and the results tables, it is possible to obtain visual representations of many aspects of the epidemiology of the selected samples.

Figure 4

Observed frequency of potential multi-resistance cases found among the Salmonella samples sequenced. Number of samples in which from only one to up to 9 different AMR genes have been found.

Figure 5

Phylogenetic tree, based on allelic differences (log scale), of Salmonella enterica isolated from the same locality, grouped by allelic profile (the circle size correlates with the number of samples). Blue dots represent strains harboring the plasmid NZ_AJ437107, and the number inside each dot indicates the corresponding MLST for each sample.