Brucellosis is an infectious zoonosis that has huge economic and public health implications globally. The disease is prevalent in humans, livestock and wildlife in Sub-Saharan Africa. A cross-sectional study was conducted between 6 May 2017 and 31 July 2020 during which 1712 sera from 175 cattle herds in five districts from Southern, Western and Eastern Provinces of Zambia were collected and screened against brucellosis. The Rose Bengal Test (RBT) and competitive Enzyme-linked Immuno Assay (c-ELISA) were used in serial testing for the detection of antibodies against Brucella species. A total of 127 animals from 37 herds tested positive, giving overall individual animal and herd-level seroprevalences of 7.53% (95% CI: 6.28–8.78%) and 21.14% (95% CI: 15.0–27.2%), respectively. Namwala district had the highest herd seroprevalence (33.9%, 95% CI: 21.6–46.1%), while Lundazi did not record any seropositivity. Comparably, Southern Province had the highest individual animal (8.97%, 95% CI: 7–11%) and herd-level (28.5%, 95% CI: 20.3–36.7%) seroprevalences, although this was not statistically significant. Within Southern Province, higher seropositivity was observed in Namwala district (OR: 8.55; CI: 2.66–27.44), among female animals (OR: 2.48; CI: 1.38–4.46) and in those aged 11 years and above (OR: 2.67; CI: 1.34–5.34) as well as in gravid cows (OR: 4.34; CI: 2.08–8.92). Seropositivity was also observed among some animals with hygromas (OR: 6.5; CI: 0.45–94.08) and those with a history of abortion (OR: 1.13; CI: 0.18–7.28) although the findings were not statistically significant. Brucella seroprevalence among traditional cattle in Zambia remains high. Control programs against bovine brucellosis must be introduced to reduce its impact on human health and animal production.

The challenges posed by antibiotic-resistant pathogens have continued to increase worldwide, particularly in resource-limited countries. Human-livestock interactions are implicated in the complex AMR causal web. A cross-sectional study was conducted in four districts of Lusaka Province, Zambia to determine the antibiotic resistance patterns, ESBL production of E. coli isolated from stool samples of broiler poultry farm workers, and to assess poultry farmers' antibiotic resistance awareness. Sixty-six human stool samples were collected and processed for E. coli isolation, antibiotic resistance testing, and screened for ESBL production. In addition, 80 farmers were assessed for their level of awareness on antibiotic resistance. A total of 58 single E. coli isolates were obtained which showed high (87.9%) resistance to tetracycline, trimethoprim/sulfamethoxazole (48.3%), and ampicillin (46.8%); followed by nalidixic acid (19.0%), ciprofloxacin (12.1%), cefotaxime (8.6%) and chloramphenicol (5.2%). The prevalence of AMR E. coli was 67.2%, and 29.3% were MDR. Two (3.4%) isolates were identified to be ESBL producers, harboring the CTX-M gene. The study results also showed that broiler farmers were aware and knowledgeable of antibiotic resistance, although knowledge about its impact on human health was low. This study demonstrated the presence of resistant and ESBL producing E. coli among poultry farm workers.

Structural variants (SV) have been linked to important bovine disease phenotypes, but due to the difficulty of their accurate detection with standard sequencing approaches, their role in shaping important traits across cattle breeds is largely unexplored. Optical mapping is an alternative approach for mapping SVs that has been shown to have higher sensitivity than DNA sequencing approaches. The aim of this project was to use optical mapping to develop a high-quality database of structural variation across cattle breeds from different geographical regions, to enable further study of SVs in cattle. To do this we generated 100X Bionano optical mapping data for 18 cattle of nine different ancestries, three continents and both cattle sub-species. In total we identified 13,457 SVs, of which 1,200 putatively overlap coding regions. This resource provides a high-quality set of optical mapping-based SV calls that can be used across studies, from validating DNA sequencing-based SV calls to prioritising candidate functional variants in genetic association studies and expanding our understanding of the role of SVs in cattle evolution.

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Structural variants (SV) have been linked to several important bovine disease phenotypes, but due to the difficulty of their accurate detection with standard sequencing approaches, their role in shaping economically important traits across global cattle breeds is largely unexplored. Optical mapping is an alternative approach for mapping SVs that has been shown to have higher sensitivity than DNA sequencing approaches. The aim of this project was to use optical mapping to develop a high quality database of structural variation across cattle breeds from different geographical regions and origins, to enable further studies of the important roles of SV in cattle. To do this we generated 100X Bionano optical mapping data for 18 cattle of nine different ancestries, three continents and covering both major cattle lineages. In total we identified 13,457 SVs, of which 1,200 putatively overlap a coding region. This resource therefore provides a high-quality set of optical mapping-based SV calls that can be used across studies, from validating DNA sequencing based SV calls to prioritising candidate functional variants in genetic association studies and expanding our understanding of the role of SVs in the evolution of cattle.