Genomic surveillance of Salmonella spp. in the Philippines during 2013–2014

Abstract

Background Increasing antimicrobial resistance (AMR) in Salmonella has been observed in the Philippines. We aimed to characterise the population and AMR mechanisms of Salmonella with whole genome sequencing (WGS) and compare it with laboratory surveillance methods. Methods The serotype, multilocus sequence type, AMR genes and relatedness between isolates were determined from the genomes of 148 Salmonella Typhi (S. Typhi) and 65 non-typhoidal Salmonella (NTS) collected by the Antimicrobial Resistance Surveillance Program during 2013–2014. Genotypic serotypes and AMR prediction were compared with phenotypic data. Results AMR rates in S. Typhi were low, with sparse acquisition of mutations associated with reduced susceptibility to fluoroquinolones or extended-spectrum beta-lactamases (ESBL) genes. By contrast, 75% of NTS isolates were insusceptible to at least one antimicrobial, with more than half carrying mutations and/or genes linked to fluoroquinolone resistance. ESBL genes were detected in five genomes, which also carried other AMR determinants. The population of S. Typhi was dominated by likely endemic genotype 3.0, which caused a putative local outbreak. The main NTS clades were global epidemic S. Enteritidis ST11 and S. Typhimurium monophasic variant (I,4,[5],12: i: -) ST34. Conclusion We provide the first genomic characterisation of Salmonella from the Philippines and evidence of WGS utility for ongoing surveillance.

Global diversity and antimicrobial resistance of typhoid fever pathogens: Insights from a meta-analysis of 13,000 Salmonella Typhi genomes

“…Overall, there were 36 countries with ≥20 genomes (total n=12,409 genomes, 95.7%) and 21 countries with ≥100 genomes (n=11,761 genomes, 90.7%) (see Supplementary file 4 ). Countries with the most genomes available (n≥100 each) were mainly those where local surveillance studies have utilised WGS for isolate characterisation: India ( Britto et al, 2020 ; da Silva et al, 2022 ), Bangladesh ( Rahman et al, 2020 ; da Silva et al, 2022 ), Nepal ( Britto et al, 2018 ; da Silva et al, 2022 ; Pham Thanh et al, 2016a ), Pakistan ( da Silva et al, 2022 ), Cambodia ( Kuijpers et al, 2017 ; Pham Thanh et al, 2016b ), Laos ( Wong et al, 2015 ), Vietnam ( Holt et al, 2011a ), Kenya ( Kariuki et al, 2021 ; Kariuki et al, 2010 ), Malawi ( Feasey et al, 2015 ), Zimbabwe ( Mashe et al, 2021 ; Thilliez et al, 2022 ), Ghana ( Park et al, 2018 ), Nigeria ( Ikhimiukor et al, 2022a ; Wong et al, 2016b ), Chile ( Maes et al, 2022 ), Samoa Sikorski et al, 2022 ; plus South Africa ( Smith et al, 2023 ), the Philippines ( Lagrada et al, 2022 ), United Kingdom, and United States, where Typhi isolates are sequenced as part of national surveillance programmes.…”

“…However, the population structures varied between individual countries in the region (see Figure 1b and Figure 1—figure supplement 3 ), with H58 accounting for nearly all isolates in Cambodia (98%, n=216/221, all lineage 1), Myanmar (94%, n=46/49, mixed lineages), and Singapore (n=4/4, mixed lineages), but largely absent from Indonesia (3%, n=2/65), Laos (4%, n=1/27), and the Philippines (0.5%, n=1/206). These latter countries showed distinct populations with multiple genotypes exceeding 5% frequency: 4.1 (26%, n=17/65), 3 (18%, n=12/65), 2.1 (15%, n=10/65), and 3.1.2 (12%, n=8/65) in Indonesia; 3.4 (44%, n=12/27), 3.5.2 (15%, n=4/27), 2.3.4 (11%, n=3/27), 3.2.1 (11%, n=3/27), and 4.1 (7%, n=2/27) in Laos; 3 (79%, n=163/206), 3.2.1 (11%, n=23/206), and 4.1 (7%, n=16/206) in the Philippines ( Lagrada et al, 2022 ).…”

“…However, ESBL genes were identified in n=32 non-4.3.1.1.P1 genomes, belonging to eight other genotypes ( Table 3 ). Several carried a bla CTX-M-15 ; these include instances with no other acquired AMR genes (genotype 3 in the Philippines [ Hendriksen et al, 2015b ; Lagrada et al, 2022 ]; genotype 4.3.1.2 in Iraq [ Nair et al, 2021 ]); one instance with chromosomally integrated AMR genes plus IncY plasmid-borne bla CTX-M-15 (genotype 2.5.1 in DRC; Phoba et al, 2017 ); and instances with a 4.3.1.1.P1-like profile carrying qnrS in the IncY plasmid and the MDR locus in the chromosome (n=4 4.3.1, India and Pakistan; n=1 4.3.1.1, Pakistan; see Table 3 ). However, overall, bla CTX-M-15 IncY plasmids were rare (n=1–4 genomes) in all genotype backgrounds except 4.3.1.1.P1 (total n=655), suggesting that the IncY bla CTX-M-15 plasmid has not been stably maintained in other Typhi lineages (see Table 3 ).…”

“…Salmonella were among the first pathogens to transition to routine sequencing by public health laboratories in high-income countries ( Chattaway et al, 2019 ; Stevens et al, 2022 ), and these systems often capture Typhi isolated from travel-associated typhoid infections, providing an informal mechanism for sentinel genomic surveillance of pathogen populations in typhoid endemic countries ( Ingle et al, 2019 ). More recently, WGS has been adopted for typhoid surveillance by national reference laboratories in endemic countries including the Philippines, Nigeria ( Okeke et al, 2022 ), and South Africa ( Lagrada et al, 2022 ), and PulseNet International is gradually transitioning to WGS ( Davedow et al, 2022 ; Nadon et al, 2017 ). Following the first global genomic snapshot study, which included nearly 2000 genomes of Typhi isolated from numerous typhoid prevalence and incidence studies conducted across Asia and Africa ( Wong et al, 2015 ), WGS has become the standard tool for characterising clinical isolates.…”

“…The genotyping framework, together with functionality for identifying AMR determinants and plasmid replicons, and generating clustering-based trees, is available within the online genomic epidemiology platform Typhi Pathogenwatch ( Argimón et al, 2021b ). This system is designed to facilitate genomic surveillance and outbreak analysis for Typhi, including contextualisation with global public data, by public health and research laboratories ( Argimón et al, 2021a ; Ikhimiukor et al, 2022a ; Lagrada et al, 2022 ) without requiring major investment in computational infrastructure or specialist bioinformatics training.…”