Retrospective genome-wide comparisons of Salmonella enterica serovar Enteritidis from suspected outbreaks in Singapore

Rapid geographical source attribution of Salmonella enterica serovar Enteritidis genomes using hierarchical machine learning

Salmonella enterica serovar Enteritidis is one of the most frequent causes of Salmonellosis globally and is commonly transmitted from animals to humans by the consumption of contaminated foodstuffs. In the UK and many other countries in the Global North, a significant proportion of cases are caused by the consumption of imported food products or contracted during foreign travel, therefore, making the rapid identification of the geographical source of new infections a requirement for robust public health outbreak investigations. Herein, we detail the development and application of a hierarchical machine learning model to rapidly identify and trace the geographical source of S. Enteritidis infections from whole genome sequencing data. 2313 S. Enteritidis genomes, collected by the UKHSA between 2014-2019, were used to train a 'local classifier per node' hierarchical classifier to attribute isolates to four continents, 11 sub-regions, and 38 countries (53 classes). The highest classification accuracy was achieved at the continental level followed by the sub-regional and country levels (macro F1: 0.954, 0.718, 0.661, respectively). A number of countries commonly visited by UK travelers were predicted with high accuracy (hF1: >0.9). Longitudinal analysis and validation with publicly accessible international samples indicated that predictions were robust to prospective external datasets. The hierarchical machine learning framework provided granular geographical source prediction directly from sequencing reads in <4 min per sample, facilitating rapid outbreak resolution and real-time genomic epidemiology. The results suggest additional application to a broader range of pathogens and other geographically structured problems, such as antimicrobial resistance prediction, is warranted.

Characterisation of Salmonella Enteritidis ST11 and ST1925 Associated with Human Intestinal and Extra-Intestinal Infections in Singapore

Salmonella Enteritidis is a major foodborne pathogen worldwide. In this study, a total of 276 S. enteritidis isolates, collected between 2016 and 2017 from human, food and farm/slaughterhouse samples, were studied to enhance the understanding of the epidemiology of human salmonellosis in Singapore. Results showed all 276 isolates belonged either to ST1925 (70.3%) or ST11 (29.7%), with ST11 being significantly more frequent in extra-intestinal isolates and chicken isolates. Food isolates, most of which were from poultry, showed the highest prevalence of resistance (33–37%) against beta-lactams or beta-lactams/beta-lactamase inhibitor combination (ampicillin, piperacillin and ampicillin/sulbactam). The analysis showed the detection of genes associated with resistance to aminoglycoside genes (99.6%), tetracycline (55.1%), and beta-lactams (14.9%) of all isolates. Nine types of plasmids were found in 266 isolates; the most common incompatibility group profiles were IncFIB(S)-IncFII(S)-IncX1 (72.2%) and IncFIB(S)-IncFII(S) (15.8%). Most plasmid harbouring isolates from chicken (63.6%, 14/22) and from human (73.8%, 175/237) shared the same plasmid profile (IncFIB(S)-IncFII(S)-IncX1). SNP analysis showed clustering of several isolates from poultry food products and human isolates, suggesting phylogenetic relatedness among these isolates. Lastly, this study provides important epidemiological insights on the application of phenotypic and next-generation sequencing (NGS) tools for improved food safety and public health surveillance and outbreak investigation of S.enteritidis.

Distribution of Salmonella Serovars in Humans, Foods, Farm Animals and Environment, Companion and Wildlife Animals in Singapore

We analyzed the epidemiological distribution of Salmonella serovars in humans, foods, animals and the environment as a One-Health step towards identifying risk factors for human salmonellosis. Throughout the 2012-2016 period, Salmonella ser. Enteritidis was consistently the predominating serovar attributing to >20.0% of isolates in humans. Other most common serovars in humans include Salmonella ser. Stanley, Salmonella ser. Weltevreden, Salmonella ser. Typhimurium and Salmonella ser. 4,5,12:b:-(dT+). S. Enteritidis was also the most frequent serovar found among the isolates from chicken/chicken products (28.5%) and eggs/egg products (61.5%) during the same period. In contrast, S. Typhimurium (35.2%) and Salmonella ser. Derby (18.8%) were prevalent in pork/pork products. S. Weltevreden was more frequent in seafood (19.2%) than others (≤3.0%). Most isolates (>80.0%) from farms, companion and wildlife animals belonged to serovars other than S. Enteritidis or S. Typhimurium. Findings demonstrate the significance of a One-Health investigative approach to understand the epidemiology Salmonella for more effective and integrated surveillance systems.

Salmonella in Retail Food and Wild Birds in Singapore-Prevalence, Antimicrobial Resistance, and Sequence Types

Non-typhoidal salmonellosis is a leading cause of foodborne zoonosis. To better understand the epidemiology of human salmonellosis, this study aimed to determine the prevalence, antimicrobial resistance and sequence types of Salmonella in retail food and wild birds (proximity to humans) in Singapore. We analyzed 21,428 cooked and ready-to-eat food and 1,510 residual faecal samples of wild birds collected during 2010–2015. Thirty-two Salmonella isolates from food and wild birds were subjected to disc diffusion and multi-locus sequence typing (MLST). Salmonella was isolated from 0.08% (17/21,428) of food and 0.99% (15/1510) of wild birds. None of the isolates from wild birds (n = 15) exhibited phenotypic resistance, while the isolates from food (47.1%, 8/17) showed a high prevalence of phenotypic resistance to, at least, one antimicrobial. These findings suggested that the avian Salmonella isolates had been subjected to less antimicrobial selection pressure than those from food samples. MLST revealed specific sequence types found in both food and wild birds. The study can guide future studies with whole-genome analysis on a larger number of isolates from various sectors for public health measures.

Whole-genome sequencing of the rare Salmonella enterica serovar Anfo isolated from food handlers

Field investigations were conducted after a small cluster of food poisoning involving six cases was reported. While no stool samples were available from the cases for microbiological testing, Salmonella species was found to be present in the stools of food handlers with gastroenteritis symptoms. Four Salmonella isolates recovered from the food handlers were retrospectively investigated at the genome level using whole-genome sequencing (WGS). WGS showed that S. Anfo (antigenic formulae 39:y:1,2), a rarely isolated serovar, caused infections in the food handlers. S. Anfo analysed in this study contained virulence factors required for causing disease. They did not contain any antibiotic resistance genes or plasmid. The epidemiologically related isolates differed to each other by a maximum of one single nucleotide polymorphism. WGS was useful in identifying rare Salmonella serovars and it is potentially more cost-effective than traditional serotyping methods. It can also confidently group epidemiologically related isolates belonging to S. Anfo.