Consumption of food that is contaminated by microorganisms, chemicals, and toxins may lead to significant morbidity and mortality, which has negative socioeconomic and public health implications. Monitoring and surveillance of microbial diversity along the food value chain is a key component for hazard identification and evaluation of potential pathogen risks from farm to the consumer. The aim of this study was to determine the microbial diversity in meat and meat products from different enterprises and meat types in South Africa. Samples (n = 2017) were analyzed for Yersinia enterocolitica, Salmonella species, Listeria monocytogenes, Campylobacter jejuni, Campylobacter coli, Staphylococcus aureus, Clostridium perfringens, Bacillus cereus, and Clostridium botulinum using culture-based methods. PCR was used for confirmation of selected pathogens. Of the 2017 samples analyzed, microbial ecology was assessed for selected subsamples where next generation sequencing had been conducted, followed by the application of computational methods to reconstruct individual genomes from the respective sample (metagenomics). With the exception of Clostridium botulinum, selective culture-dependent methods revealed that samples were contaminated with at least one of the tested foodborne pathogens. The data from metagenomics analysis revealed the presence of diverse bacteria, viruses, and fungi. The analyses provide evidence of diverse and highly variable microbial communities in products of animal origin, which is important for food safety, food labeling, biosecurity, and shelf life limiting spoilage by microorganisms.

Zoonoses: a potential obstacle to the growing wildlife industry of Namibia

Meat products have been implicated in many listeriosis outbreaks globally, however there is a dearth of information on the diversity of L. monocytogenes isolates circulating in food products in South Africa. The aim of this study was to investigate the population structure of L. monocytogenes isolated in the meat value chain within the South African market. Based on whole-genome sequence analysis, a total of 217 isolates were classified into two main lineage groupings namely lineages I (n = 97; 44.7%) and II (n = 120; 55.3%). The lineage groups were further differentiated into IIa (n = 95, 43.8%), IVb (n = 69, 31.8%), IIb (n = 28, 12.9%), and IIc (n = 25, 11.5%) sero-groups. The most abundant sequence types (STs) were ST204 (n = 32, 14.7%), ST2 (n = 30, 13.8%), ST1 (n = 25, 11.5%), ST9 (n = 24, 11.1%), and ST321 (n = 21, 9.7%). In addition, 14 clonal complex (CCs) were identified with over-representation of CC1, CC3, and CC121 in “Processed Meat-Beef”, “RTE-Poultry”, and “Raw-Lamb” meat categories, respectively. Listeria pathogenic islands were present in 7.4% (LIPI-1), 21.7% (LIPI-3), and 1.8% (LIPI-4) of the isolates. Mutation leading to premature stop codons was detected in inlA virulence genes across isolates identified as ST121 and ST321. The findings of this study demonstrated a high-level of genomic diversity among L. monocytogenes isolates recovered across the meat value chain control points in South Africa.

A confirmed case of human brucellosis motivated an investigation into the potential source of infection in Namibia. Since domestic animals are principal sources of Brucella infection in humans, 1692 serum samples were screened from sheep, goats and cattle from 4 presumably at-risk farms and 900 springbok (Antidorcas marsupialis) serum samples from 29 mixed farming units for Brucella antibodies by the Rose-Bengal test (RBT) and positive cases confirmed by complement fixation test (CFT). To assess the prevalence of human brucellosis, 137 abattoir employees were tested for Brucella antibodies using the standard tube agglutination test (STAT) and by enzyme linked immunosorbent assay (ELISA). Cattle and sheep from all 4 farms were negative by RBT and CFT but 2 of the 4 farms (Ba and C) had 26/42 and 12/285 seropositive goats, respectively. Post mortem examination of seropositive goats revealed no gross pathological lesions typical of brucellosis except enlarged mesenteric and iliac lymph nodes seen in a single buck. Culture for brucellae from organs of seropositive animals was negative. None of the wildlife sera tested positive by either RBT or CFT. Interviews revealed that besides the case that prompted the investigation, a family and another person from other farms with confirmed brucellosis shared a common history of consumption of unpasteurised goat milk, home-made goat cheese and coffee with raw milk and prior contact with goats, suggesting goats as the likely source of infection. All 137 abattoir employees tested negative by STAT, but 3 were positive by ELISA. The 3 abattoir workers were clinically normal and lacked historical connections with clinical cases. Although goats are often associated with B. melitensis, these studies could not explicitly implicate this species owing to cross-reactivity with B. abortus, which can also infect goats. Nevertheless, these data reinforce the need for a better National Control Programme for brucellosis in Namibia.

Processed meat is a target in meat adulteration for economic gain. This study demonstrates a molecular and bioinformatics diagnostic pipeline, utilizing the mitochondrial 16S ribosomal RNA (rRNA) gene, to determine processed meat product mislabeling through Next-Generation Sequencing. Nine pure meat samples were collected and artificially mixed at different ratios to verify the specificity and sensitivity of the pipeline. Processed meat products (n = 155), namely, minced meat, biltong, burger patties, and sausages, were collected across South Africa. Sequencing was performed using the Illumina MiSeq sequencing platform. Each sample had paired-end reads with a length of ±300 bp. Quality control and filtering was performed using BBDuk (version 37.90a). Each sample had an average of 134,000 reads aligned to the mitochondrial genomes using BBMap v37.90. All species in the artificial DNA mixtures were detected. Processed meat samples had reads that mapped to the Bos (90% and above) genus, with traces of reads mapping to Sus and Ovis (2–5%) genus. Sausage samples showed the highest level of contamination with 46% of the samples having mixtures of beef, pork, or mutton in one sample. This method can be used to authenticate meat products, investigate, and manage any form of mislabeling.

Staphylococcus aureus, including methicillin-resistant strains, has been detected in food products of animal origin globally. Limited data have been reported on the factors contributing to antibiotic resistance of food-borne pathogens in South Africa. The primary aim of this study was to determine the prevalence of S. aureus, including antibiotic-resistant strains, in poultry meat products as well as the evaluation of potential risk factors for contamination of poultry meat products with antibiotic-resistant S. aureus isolates. A cross-sectional investigation was conducted in municipalities located across the nine provinces of South Africa, which included abattoirs, meat processing facilities, retail outlets and cold stores at the major ports of entry into South Africa. Staphylococcus aureus isolates obtained from various poultry meat products were tested for susceptibility to 14 antibiotic compounds representing 10 antibiotic classes using the Kirby–Bauer disc diffusion method. Potential risk factors were evaluated using a logistic regression model. Of the 311 samples tested, 34.1% (n = 106) were positive for S. aureus (95% confidence interval [CI], 28.9% – 39.7%). Seventy-two of the 106 isolates were randomly selected for antibiotic sensitivity testing. Twenty-one per cent (n = 15) of the isolates selected for sensitivity testing were methicillin-resistant strains (95% CI, 12.2% – 32.0%). Multi-drug resistance was detected in 22.2% (n = 16) of these isolates tested (95% CI, 13.3% – 33.6%). Origin of the product (p = 0.160), type of meat product (p = 0.962), type of facility (p = 0.115) and facility hygiene practices (p = 0.484) were not significantly associated with contamination of poultry meat products with methicillin-resistant strains. The study provides baseline data for further studies on antibiotic resistance risk assessments for food-borne pathogens, including S. aureus, which should guide the implementation plans of the South African National Antimicrobial Resistance Strategy Framework, 2017–2024.