A 16S Next Generation Sequencing Based Molecular and Bioinformatics Pipeline to Identify Processed Meat Products Contamination and Mislabelling

Simple Summary

Meat adulteration and fraud encompasses the deliberate fraudulent addition or substitution of proteins of animal or plant origin in edible products primarily for economic gain. The mitochondrial 16S ribosomal (rRNA) gene was used to identify species that are present in pure and processed meat samples. The meat samples were sequenced using an Illumina sequencing platform, and bioinformatics analysis was carried out for species identification. The results indicated that pork was the major contaminant in most of the meat samples. The bioinformatics pipeline demonstrated its specificity through identification of species specific and quantification of the contamination levels across all samples. Food business operators and regulatory sectors can validate this method for food fraud checks and manage any form of mislabeling in the animal or plant protein food ecosystem.

Abstract

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.

Early transmission of SARS-CoV-2 in South Africa: An epidemiological and phylogenetic report

OBJECTIVES

The Network for Genomic Surveillance in South Africa (NGS-SA) was formed to investigate the introduction and understand the early transmission dynamics of the SARS-CoV-2 epidemic in South-Africa.

DESIGN

This paper presents the first results from this group, which is a molecular epidemiological study of the first 21 SARS-CoV-2 whole genomes sampled in the first port of entry - KwaZulu-Natal (KZN) - during the first month of the epidemic. By combining this with calculations of the effective reproduction number (R), it aimed to shed light on the patterns of infections in South Africa.

RESULTS

Two of the largest provinces - Gauteng and KZN - had a slow growth rate for the number of detected cases, while the epidemic spread faster in the Western Cape and Eastern Cape. The estimates of transmission potential suggested a decrease towards R = 1 since the first cases and deaths, but a subsequent estimated R average of 1.39 between 6-18 May 2020. It was also demonstrated that early transmission in KZN was associated with multiple international introductions and dominated by lineages B1 and B. Evidence for locally acquired infections in a hospital in Durban within the first month of the epidemic was also provided.

CONCLUSION

The COVID-19 pandemic in South Africa was very heterogeneous in its spatial dimension, with many distinct introductions of SARS-CoV2 in KZN and evidence of nosocomial transmission, which inflated early mortality in KZN. The epidemic at the local level was still developing and NGS-SA aimed to clarify the dynamics in South Africa and devise the most effective measures as the outbreak evolved.

Whole Genome Sequencing of SARS-CoV-2: Adapting Illumina Protocols for Quick and Accurate Outbreak Investigation during a Pandemic

The COVID-19 pandemic has spread very fast around the world. A few days after the first detected case in South Africa, an infection started in a large hospital outbreak in Durban, KwaZulu-Natal (KZN). Phylogenetic analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes can be used to trace the path of transmission within a hospital. It can also identify the source of the outbreak and provide lessons to improve infection prevention and control strategies. This manuscript outlines the obstacles encountered in order to genotype SARS-CoV-2 in near-real time during an urgent outbreak investigation. This included problems with the length of the original genotyping protocol, unavailability of reagents, and sample degradation and storage. Despite this, three different library preparation methods for Illumina sequencing were set up, and the hands-on library preparation time was decreased from twelve to three hours, which enabled the outbreak investigation to be completed in just a few weeks. Furthermore, the new protocols increased the success rate of sequencing whole viral genomes. A simple bioinformatics workflow for the assembly of high-quality genomes in near-real time was also fine-tuned. In order to allow other laboratories to learn from our experience, all of the library preparation and bioinformatics protocols are publicly available at protocols.io and distributed to other laboratories of the Network for Genomics Surveillance in South Africa (NGS-SA) consortium.

Early transmission of SARS-CoV-2 in South Africa: An epidemiological and phylogenetic report

Background

The emergence of a novel coronavirus, SARS-CoV-2, in December 2019, progressed to become a world pandemic in a few months and reached South Africa at the beginning of March. To investigate introduction and understand the early transmission dynamics of the virus, we formed the South African Network for Genomics Surveillance of COVID (SANGS_COVID), a network of ten government and university laboratories. Here, we present the first results of this effort, which is a molecular epidemiological study of the first twenty-one SARS-CoV-2 whole genomes sampled in the first port of entry, KwaZulu-Natal (KZN), during the first month of the epidemic. By combining this with calculations of the effective reproduction number (R), we aim to shed light on the patterns of infections that define the epidemic in South Africa.

Methods

R was calculated using positive cases and deaths from reports provided by the four major provinces. Molecular epidemiology investigation involved sequencing viral genomes from patients in KZN using ARCTIC protocols and assembling whole genomes using meticulous alignment methods. Phylogenetic analysis was performed using maximum likelihood (ML) and Bayesian trees, lineage classification and molecular clock calculations.

Findings

The epidemic in South Africa has been very heterogeneous. Two of the largest provinces, Gauteng, home of the two large metropolis Johannesburg and Pretoria, and KwaZulu-Natal, home of the third largest city in the country Durban, had a slow growth rate on the number of detected cases. Whereas, Western Cape, home of Cape Town, and the Eastern Cape provinces the epidemic is spreading fast. Our estimates of transmission potential for South Africa suggest a decreasing transmission potential towards R=1 since the first cases and deaths have been reported. However, between 06 May and 18 May 2020, we estimate that R was on average 1.39 (1.04 - 2.15, 95% CI). We also demonstrate that early transmission in KZN, and most probably in all main regions of SA, was associated with multiple international introductions and dominated by lineages B1 and B. The study also provides evidence for locally acquired infections in a hospital in Durban within the first month of the epidemic, which inflated early mortality in KZN.

Interpretation

This first report of SANGS_COVID consortium focuses on understanding the epidemic heterogeneity and introduction of SARS-CoV-2 strains in the first month of the epidemic in South Africa. The early introduction of SARS-CoV-2 in KZN included caused a localized outbreak in a hospital, provides potential explanations for the initially high death rates in the province. The current high rate of transmission of COVID-19 in the Western Cape and Eastern Cape highlights the crucial need to strength local genomic surveillance in South Africa.

Funding

UKZN Flagship Program entitled: Afrocentric Precision Approach to Control Health Epidemic, by a research Flagship grant from the South African Medical Research Council (MRC-RFA-UFSP-01-2013/UKZN HIVEPI, by the the Technology Innovation Agency and the the Department of Science and Innovation and by National Human Genome Re- search Institute of the National Institutes of Health under Award Number U24HG006941. H3ABioNet is an initiative of the Human Health and Heredity in Africa Consortium (H3Africa).

Haplo-block structure of Southern African village chicken populations inferred using genome-wide SNP data

This study investigated the haplo-block structure, haplotype sharing, and diversity in extensively raised chicken populations of Southern Africa. Two hundred ninety village chickens from Malawi (N = 30), South Africa (N = 132), and Zimbabwe (N = 128) were included in the study, from which 649, 2104, and 2442 haplo-blocks were observed, respectively. The majority of haplo-blocks were smaller than 25 kb in size and only five blocks were more than 2000 kb in size. The low chromosomal coverage of haplo-blocks observed across the genome suggests that multiple recombination events fragmented the ancestral haplo-blocks into smaller sizes. Haplo-block sharing was observed between populations with 2325 haplo-blocks common between Zimbabwe and Malawi and 2689 between South Africa and Zimbabwe. Haplotype sharing allows transferability of genomic tools between these extensively raised chicken populations of Southern Africa. The unique haplo-blocks could have originated from isolated evolution taking place in specific agro-ecological zones. Quantitative trait loci analysis revealed that genes related to body composition were spanned by these haplo-blocks. Body composition traits are important for village chicken populations, which have to harness poor quality feed obtained from the environment to meet their maintenance and production needs.