Tracking the distribution, genetic diversity and lineage of Brucella melitensis recovered from humans and animals in Egypt based on core-genome SNP analysis and in silico MLVA-16.

Brucellosis is one of the most common neglected zoonotic diseases globally, with a public health significance and a high economic loss in the livestock industry caused by the bacteria of the genus Brucella. In this study, 136 Egyptian Brucella melitensis strains isolated from animals and humans between 2001 and 2020 were analysed by examining the whole-core-genome single-nucleotide polymorphism (cgSNP) in comparison to the in silico multilocus variable number of tandem repeat analysis (MLVA-16). Almost all Egyptian isolates were belonging to the West Mediterranean clade, except two isolates from buffalo and camel were belonging to the American and East Mediterranean clades, respectively. A significant correlation between the human case of brucellosis and the possible source of infection from animals was found. It seems that several outbreak strains already existing for many years have been spread over long distances and between many governorates. The cgSNP analysis, in combination with epidemiological metadata, allows a better differentiation than the MLVA-16 genotyping method and, hence, the source definition and tracking of outbreak strains. The MLVA based on the currently used 16 markers is not suitable for this task. Our results revealed 99 different cgSNP genotypes with many different outbreak strains, both older and widely distributed ones and rather newly introduced ones as well. This indicates several different incidents and sources of infections, probably by imported animals from other countries to Egypt. Comparing our panel of isolates to public databases by cgSNP analysis, the results revealed near relatives from Italy. Moreover, near relatives from the United States, France, Austria and India were found by in silico MLVA.

Risk factors and Molecular genotyping of Brucella melitensis strains recovered from humans and their owned cattle in Upper Egypt.

Brucellosis is a zoonosis that has a devastating impact on the economy and public health, particularly in the Middle East, including Egypt. This study aimed to define risk factors associated with brucellosis in humans and in their cattle in Fayoum governorate - Upper Egypt. Also, molecular genotyping of recovered Brucella isolates from human cases and their cattle to assess the potential cross-species transmission in the study region. Data were obtained via double matched case-control studies for brucellosis in humans (106 cases and 160 controls) and in their cattle (78 cattle cases and 105 cattle controls). The results of multivariate regression analysis revealed that predictors of human brucellosis were animal-related occupations (OR 2.1, P 0.02), previous infection in other household members (OR 3.2, P 0.007), eating home-made soft cheese (OR 2.3, P 0.03), and exposure to cattle abortions (OR 6.9, P < 0.001). For cattle, predictors of brucellosis were maturity ≥2 years of age (OR 2.9, P 0.01), ≥2 animals reared by the same household (OR 3.7-6.9, P ≤ 0.001), and recent abortion (OR 15.2, P 0.01). Twelve Brucella isolates were recovered from eight human cases (7.5%, 8/106) and four cattle cases (6.2%, 4/65). All isolates were B. melitensis biovar 3. Analysis of the IS711 gene sequence revealed complete homology (100%) between isolates. Six virulence genes were utilized for virutyping: virB (100%), omp25 (100%), amiC (100%), ure (91.7%), wbkA (91.7%), and bvfA (75%). Virutyping revealed four virutypes: V1 (lack bvfA, 16.7%), V2 (harbored all genes, 66.7%), V3 (lack wbkA, 8.3%), and V4 (lack wbkA and ure, 8.3%). Repetitive extragenic palindromic PCR (REP-PCR) typing revealed two REP types. Combined REP-PCR/virulence genotyping revealed five different genotypes (G1-G5) for the detected isolates and a unique genotype for the reference strain (G6, B. melitensis bv3 Ether). Human and cattle isolates from the same household had matched genotypes. In conclusion, there were widespread risk factors among the cases studied. Health education for high-risk groups is essential for disease prevention, and combined REP-PCR/virulence genotyping is a quick tool for traceability, particularly in developing countries endemic with brucellosis as Egypt.

Tracking the Distribution of Brucella abortus in Egypt Based on Core Genome SNP Analysis and In Silico MLVA-16.

Brucellosis, caused by the bacteria of the genus Brucella, is one of the most neglected common zoonotic diseases globally with a public health significance and a high economic loss among the livestock industry worldwide. Since little is known about the distribution of B. abortus in Egypt, a total of 46 B. abortus isolates recovered between 2012-2020, plus one animal isolate from 2006, were analyzed by examining the whole core genome single nucleotide polymorphism (cgSNP) in comparison to the in silico multilocus variable number of tandem repeat analysis (MLVA). Both cgSNP analysis and MLVA revealed three clusters and one isolate only was distantly related to the others. One cluster identified a rather widely distributed outbreak strain which is repeatedly occurring for at least 16 years with marginal deviations in cgSNP analysis. The other cluster of isolates represents a rather newly introduced outbreak strain. A separate cluster comprised RB51 vaccine related strains, isolated from aborted material. The comparison with MLVA data sets from public databases reveals one near relative from Argentina to the oldest outbreak strain and a related strain from Spain to a newly introduced outbreak strain in Egypt. The distantly related isolate matches with a strain from Portugal in the MLVA profile. Based on cgSNP analysis the oldest outbreak strain clusters with strains from the UK. Compared to the in silico analysis of MLVA, cgSNP analysis using WGS data provides a much higher resolution of genotypes and, when correlated to the associated epidemiological metadata, cgSNP analysis allows the differentiation of outbreaks by defining different outbreak strains. In this respect, MLVA data are error-prone and can lead to incorrect interpretations of outbreak events.