Salmonella remains a major cause of human disease worldwide, particularly in developing countries, where they are a leading cause of morbidity and mortality.^1,2 In Africa, Salmonella disease is largely associated with non-invasive gastrointestinal infections; however, a sizable amount of the disease is also caused by invasive infections. In Africa, invasive Salmonella infections are associated with both typhoidal and non-typhoidal Salmonella.^3,4 Surveillance and laboratory characterisation of Salmonella is important to monitor prevalence and trends in Salmonella infections. Recent trends in public health microbiology have shown an evolution towards whole-genome sequencing (WGS) as the methodology of choice for laboratory investigation of infectious diseases. Globally, many public health institutions have transitioned to WGS as their primary methodology for characterisation of bacterial pathogens, and this has included Salmonella.^5,6,7 The World Health Organization has endorsed genomics and WGS approaches to investigate various communicable diseases.^8,9

The National Institute for Communicable Diseases (NICD) (https://www.nicd.ac.za/) is a national public health institute for South Africa, providing disease surveillance, specialised diagnostic services, outbreak response, public health research, and capacity building to support the government’s response to communicable disease threats. The Centre for Enteric Diseases (CED), NICD, performs surveillance on pathogens associated with diarrhoea and enteric fever, and is involved with investigation and response to enteric disease outbreaks. The CED also provides specialised reference laboratory testing for enteric bacteria and viruses. In addition, the CED plays a part in national laboratory-based surveillance for human isolates of Salmonella,¹⁰ whereby isolates of Salmonella are received from more than 200 public and private clinical microbiology laboratories throughout South Africa. Suspected or laboratory-confirmed cases of enteric fever and clinical laboratory identifications of Salmonella isolates are ‘notifiable medical conditions’ in South Africa and it is thus mandatory for these to be reported to the Department of Health.¹¹ The CED performs routine WGS on all Salmonella isolates received. Whole-genome sequencing data are analysed to confirm the identification of isolates with respect to genus, species and serovar, and further characterise the isolates with respect to multilocus sequence typing (MLST) and presence of antimicrobial resistance (AMR) determinants. Furthermore, WGS data is also submitted to the public EnteroBase platform (https://enterobase.warwick.ac.uk/species/index/senterica),¹² where data are further interrogated using core-genome MLST (cgMLST) to investigate for clusters of genetically related cases (predictive of possible outbreaks) and to complement epidemiological investigation of outbreaks. Before implementation of WGS, presumptive Salmonella isolates were identified using traditional phenotypic microbiological methods, which included VITEK identification and serotyping performed according to the White-Kauffmann-Le Minor Scheme.^13,14 This would have been followed by molecular subtyping of isolates, on selected isolates only (mostly associated with outbreak investigations), using methods such as pulsed-field gel electrophoresis analysis and multiple-locus variable-number tandem-repeats analysis.^13,14,15,16

In 2020, CED implemented WGS for routine surveillance of clinical isolates of Salmonella. We now present the results of this WGS implementation and summarise key findings following analysis of isolates from 2020 to 2023. We report on the number of isolates sequenced, predominant serovars and subspecies identified, significant strains identified, notable AMR profiles identified, clusters identified, and outbreaks investigated.

The CED, NICD, is a member of the regional PulseNet Africa laboratory network (https://www.pulsenetafrica.org/), which forms part of the PulseNet International network (http://www.pulsenetinternational.org/), a global molecular subtyping network for foodborne disease surveillance. The CED has always followed standardised molecular subtyping methodologies as suggested by PulseNet International, of which in years gone by, the suggested primary methodology was pulsed-field gel electrophoresis analysis. The CED has published extensively on the use of these older (traditional) molecular subtyping methodologies for routine surveillance activities and for investigation of outbreaks involving enteric bacterial pathogens, which have included the use of pulsed-field gel electrophoresis analysis,^15,22 multiple-locus variable-number tandem-repeats analysis,^14,16 and MLST (using Sanger sequencing of polymerase chain reaction-amplified genes).^13,14

In late 2015, CED took the first step towards the use of WGS for analysis of enteric pathogens. This coincided with the establishment of the NICD SCF facility equipped with Illumina MiSeq next-generation sequencing equipment. Our first WGS activities investigated a cluster of Listeria monocytogenes cases reported from the Western Cape province, South Africa, 2015. This analysis was timely, as the steering committee of the PulseNet International network was in discussions to start with implementation of WGS, of which the vision of the network for implementation of WGS was later published in 2017.²³ In 2020, CED terminated the use of all older (traditional) molecular subtyping methodologies (pulsed-field gel electrophoresis and multiple-locus variable-number tandem-repeats analysis), and implemented the use of WGS analysis for routine surveillance and analysis of all clinical isolates of enteric bacterial pathogens, including the Salmonella. This was needed in order to align with trends in public health microbiology showing the evolution towards WGS as the primary methodology for laboratory investigation of infectious disease. Globally, many public health institutions and reference laboratories have transitioned to WGS as their primary methodology for characterisation of bacterial pathogens.^5,6,7

We experienced very few challenges with our implementation of WGS. The reasons probably have been that we implemented well-established and well-validated methodologies, and we were supported by a well-established and well-equipped SCF with dedicated core staff, including bioinformatics support. Whole-genome sequencing all starts with a good quality DNA extraction from bacteria. We used good quality DNA extraction kits to produce quality in our DNA extractions. This then eliminated almost all further problems in downstream sequencing steps, including library preparation. The quality of our sequence data outputs were mostly excellent. On rare occasions, we would encounter assembled data which failed minimum quality thresholds. The quality metrics for our assembled data include an N50 value that must be > 20 kb and number of contigs that must be < 300. For assembled data that fail quality checks, the sample is subjected to a repeated round of sequence analysis, and this usually corrects the quality issue. We rarely encountered contamination problems in our analysis of sequence data. If contamination was encountered, then a repeat DNA extraction on a new pure culture and a new sequence analysis solved the problem. On rare occasions, species identification tools would 100% identify sequence data as a non-Salmonella species, and in these situations, presumptive laboratory identifications would be updated to reflect the WGS identification.

Importantly, the implementation of any new laboratory testing methodology must be accompanied by validation data and other checks associated with good laboratory practice. As such, our WGS analysis is accredited as per the international ISO 15189 standard, and we are regularly audited by the South African National Accreditation System, the official laboratory accreditation body of South Africa. Validation of our WGS analysis is continuously affirmed by annual participation in two external WGS Quality Assessment Schemes, one managed by the National Institute for Public Health and the Environment, the Netherlands, in collaboration with the European Centre for Disease Control,²⁴ and the other managed by the National Food Institute, Technical University of Denmark.²⁵

In the last 5 years, next-generation sequencing technology has advanced rapidly, resulting in shorter turnaround times to WGS results and higher accuracy of sequencing data. In parallel, costs of next-generation sequencing and WGS have also decreased dramatically over recent years, making the technology more affordable and cost-effective for use in public health laboratories. Year-on-year decrease in WGS costs has also been noted by CED, NICD, where the cost to perform Illumina WGS on a single Salmonella isolate in January 2020 as compared to the cost in December 2023 decreased by 51.8%. In South Africa, the costs associated with Illumina sequencing is generally more affordable as compared to many other African countries (anecdotal evidence). To some extent, this affordability in South Africa can probably be attributed to the presence of an official Illumina product distributor in the country, namely Separations (https://separations.co.za/). This not only ensures the affordability of reagents and consumables but also ensures rapid order and delivery of said reagents and consumables, timely maintenance and repair of Illumina equipment, and overall good customer support.

Of the 8006 Salmonella isolates analysed using WGS, 130 distinctive Salmonella serovars and subspecies were identified (Figure 1). Salmonella Enteritidis and Salmonella Typhimurium (5701/8006; 71.2%) were the most prevalent, which aligns with global trends.^5,26,27 The following serovars or subspecies completed our top (most common) eight: Salmonella Typhi, S. enterica subspecies salamae, Salmonella Isangi, Salmonella Dublin, Salmonella Muenchen, and Salmonella Infantis. For Salmonella Enteritidis, this serovar was associated with the majority of our cluster and outbreak investigations (Table 1), and was mostly associated with a low prevalence of AMR (Table 2). Among Salmonella Typhimurium, the ST313 variant was commonly encountered (269/1430; 18.8%). The ST313 variants are known to be highly associated with Salmonella bloodstream infections in Africa.²⁸ Our reported ST313 variants were mostly (232/269; 86.2%) pan-susceptible (Figure 5), which was an interesting finding, considering that literature reports ST313 variants as typically multidrug-resistant.²⁸ For Salmonella Typhimurium, 109/1430 (7.6%) of our isolates were of the monophasic variant, of which this variant has emerged globally to become an important pandemic variant with increasing AMR,^27,29 and increasingly associated with foodborne disease outbreaks.³⁰ For Salmonella Typhi, most (414/482; 85.9%) of our isolates were of the H58 haplotype (genotype 4.3.1) strain (Figure 2). The H58 haplotype is a globally dominant variant of Salmonella Typhi and commonly associated with AMR.³¹ We were able to identify the H58 haplotype using the EnteroBase cgMLST hierarchical cluster assignment tool, where HC50:202 is known to be indicative of the H58 haplotype. Among our Salmonella Typhi H58 haplotype strains, most (411/414; 99.3%) showed AMR determinants associated with ≥ 4 classes of antimicrobials, commonly including the following resistome: bla_TEM-1B, catA1, sul1, sul2, dfrA7. Salmonella Typhi was often associated with our cluster and outbreak investigations (Table 1). A notable investigation involved Salmonella Typhi cases in 2020 to 2022, associated with an outbreak among illegal gold miners, likely resulting from the consumption of contaminated groundwater while working in a gold mine shaft (Table 1).³² Salmonella enterica subspecies salamae (279/8006; 3.5%) was our fourth most prevalent Salmonella serovar/subspecies. The S. enterica subspecies salamae isolates were genetically diverse, with no evidence to suggest any clonal spread (data not shown). Our S. enterica subspecies salamae data were a surprise finding, considering that they are mostly reported from environmental and animal (mostly cold-blooded animals like reptiles) sources, and are generally considered less pathogenic for humans.³³ The prevalence of this subspecies in South Africa has previously not been reported. Historically, before the use of WGS analysis, we would have a large contingent of Salmonella isolates reported as ‘Salmonella species’, because the traditional serotyping methodologies (using antisera) were sometimes inconclusive in making a call on subspecies or serovar. Now with the use of WGS analysis tools, Salmonella characterisation is more complete and more accurate, and is now able to more accurately identify S. enterica subspecies salamae. These isolates were mostly cultured from stool specimens of patients. Unfortunately, no further information was available about these cases, as no follow-up investigations were conducted for these. Also, we are not able to speculate on any possible environmental or zoonotic source for this subspecies, as no further investigations were conducted.

Salmonella Isangi (167/8006; 2.1%) was our fifth most prevalent Salmonella serovar or subspecies. Salmonella Isangi represents an emerging pathogen in South Africa. However, globally, Salmonella Isangi is an uncommon serovar. Very few (n = 409) Salmonella Isangi isolates have been reported in the EnteroBase database (as of 27 March 2025), with most of the cases (203/409; 49.6%) reported from South Africa. Among all the serovars or subspecies in South Africa, Salmonella Isangi showed the highest prevalence of AMR (Table 2). Most Salmonella Isangi (159/167; 95.2%) showed AMR determinants associated with ≥ 7 classes of antimicrobials, including ESBL genes (bla_OXA-1, bla_OXA-10, bla_CTX-M-15, bla_TEM-63, bla_DHA). Globally (including South Africa), Salmonella Isangi are typically multidrug-resistant, and are often associated with hospital outbreaks.^34,35,36,37 There is a pressing need for studies to identify the reservoir and transmission pathway for Salmonella Isangi, as this serotype is very capable of acquiring and retaining extensive drug resistance, and once introduced into the hospital environment, it appears to happily thrive and cause lengthy hospital outbreaks.³⁵ Salmonella Dublin (114/8006; 1.4%) was our sixth most prevalent Salmonella serovar or subspecies. Globally, Salmonella Dublin is a relatively uncommon cause of human infections. Salmonella Dublin is host-adapted to cattle, so is most prevalent in cattle and cow’s raw milk cheese. Countries that produce large volumes of cheese (such as France) often show an increased prevalence of Salmonella Dublin.^38,39 Salmonella Muenchen (108/8006; 1.3%) was our seventh most prevalent Salmonella serovar or subspecies. This prevalence aligns with a global reported prevalence of 1.2%, where globally, Salmonella Muenchen is listed as the 13th most prevalent Salmonella serovar.²⁷ Salmonella Muenchen is a relatively uncommon cause of human infections globally and there are also very few documented reports of outbreaks associated with Salmonella Muenchen. Salmonella Infantis (98/8006; 1.2%) was our eighth most prevalent Salmonella serovar or subspecies. Salmonella Infantis is currently perhaps the biggest mover and shaker among the global Salmonella population, gaining increased global prevalence over recent years.⁴⁰ Salmonella Infantis has become the fourth most prevalent Salmonella serovar causing human infections among European Union member countries.⁴¹ Salmonella Infantis is among the most frequently isolated Salmonella serovar in poultry in Europe and the United States.⁴¹ Globally, Salmonella Infantis is currently listed as the third most prevalent Salmonella serovar, with a global reported Salmonella prevalence of 6.6%.²⁷ Interestingly, the population structure of South African Salmonella Infantis has been shown to differ substantially from Salmonella Infantis isolated elsewhere globally.⁴²