Antibiotic use and bacterial transmission are responsible for the emergence, spread and persistence of antimicrobial-resistant (AR) bacteria, but their relative contribution likely differs across varying socio-economic, cultural, and ecological contexts. To better understand this interaction in a multi-cultural and resource-limited context, we examine the distribution of antimicrobial-resistant enteric bacteria from three ethnic groups in Tanzania. Household-level data (n = 425) was collected and bacteria isolated from people, livestock, dogs, wildlife and water sources (n = 62,376 isolates). The relative prevalence of different resistance phenotypes is similar across all sources. Multi-locus tandem repeat analysis (n = 719) and whole-genome sequencing (n = 816) of Escherichia coli demonstrate no evidence for host-population subdivision. Multivariate models show no evidence that veterinary antibiotic use increased the odds of detecting AR bacteria, whereas there is a strong association with livelihood factors related to bacterial transmission, demonstrating that to be effective, interventions need to accommodate different cultural practices and resource limitations.

Antimicrobial resistance (AMR) is a growing and significant threat to public health on a global scale. Escherichia coli comprises Gram-negative, fecal-borne pathogenic and commensal bacteria that are frequently associated with antibiotic resistance. AMR E. coli can be ingested via food, water and direct contact with fecal contamination. We estimated the prevalence of AMR Escherichia coli from select drinking water sources in northern Tanzania. Water samples (n = 155) were collected and plated onto Hi-Crome E. coli and MacConkey agar. Presumptive E. coli were confirmed by using a uidA PCR assay. Antibiotic susceptibility breakpoint assays were used to determine the resistance patterns of each isolate for 10 antibiotics. Isolates were also characterized by select PCR genotyping and macro-restriction digest assays. E. coli was isolated from 71 % of the water samples, and of the 1819 E. coli tested, 46.9 % were resistant to one or more antibiotics. Resistance to ampicillin, streptomycin, sulfamethoxazole, tetracycline, and trimethoprim was significantly higher (15–30 %) compared to other tested antibiotics (0–6 %; P < 0.05). Of the β-lactam-resistant isolates, bla TEM-1 was predominant (67 %) followed by bla CTX-M (17.7 %) and bla SHV-1 (6.0 %). Among the tetracycline-resistant isolates, tet(A) was predominant (57.4 %) followed by tet(B) (24.0 %). E. coli isolates obtained from these water sources were genetically diverse with few matching macro-restriction digest patterns. Water supplies in northern Tanzania may be a source of AMR E. coli for people and animals. Further studies are needed to identify the source of these contaminants and devise effective intervention strategies.

The aim of this study was to identify the replicon types of plasmids, conjugation efficiencies, and the complement of antibiotic resistance genes for a panel of multidrug resistantE. coliisolates from surface waters in northern Tanzania. Standard membrane filtration was used to isolate anduidAPCR was used to confirm the identity of strains asE. coli. Antibiotic susceptibility was determined by breakpoint assay and plasmid conjugation was determined by filter-mating experiments. PCR and sequencing were used to identify resistance genes and PCR-based replicon typing was used to determine plasmid types. Filter mating experiments indicated conjugation efficiencies ranged from 10⁻¹to 10⁻⁷. Over 80% of the donor cells successfully passed their resistance traits and eleven different replicon types were detected (IncI1, FIC, P, FIIA, A/C, FIB, FIA, H12, K/B B/O, and N). IncF plasmids were most commonly detected (49% of isolates), followed by types IncI1 and IncA/C. Detection of these public health-relevant conjugative plasmids and antibiotic resistant traits in Tanzanian water suggests the possible pollution of these water sources from human, livestock, and wild animal wastes and also shows the potential of these water sources in the maintenance and transmission of these resistance traits between environments, animals, and people.

One of the major challenges facing investigators in the microbiome field is turning large numbers of reads generated by next-generation sequencing (NGS) platforms into biological knowledge. Effective analytical workflows that guarantee reproducibility, repeatability, and result provenance are essential requirements of modern microbiome research. For nearly a decade, several state-of-the-art bioinformatics tools have been developed for understanding microbial communities living in a given sample. However, most of these tools are built with many functions that require an in-depth understanding of their implementation and the choice of additional tools for visualizing the final output. Furthermore, microbiome analysis can be time-consuming and may even require more advanced programming skills which some investigators may be lacking. We have developed a wrapper named iMAP (Integrated Microbiome Analysis Pipeline) to provide the microbiome research community with a user-friendly and portable tool that integrates bioinformatics analysis and data visualization. The iMAP tool wraps functionalities for metadata profiling, quality control of reads, sequence processing and classification, and diversity analysis of operational taxonomic units. This pipeline is also capable of generating web-based progress reports for enhancing an approach referred to as review-as-you-go (RAYG). For the most part, the profiling of microbial community is done using functionalities implemented in Mothur or QIIME2 platform. Also, it uses different R packages for graphics and R-markdown for generating progress reports. We have used a case study to demonstrate the application of the iMAP pipeline. The iMAP pipeline integrates several functionalities for better identification of microbial communities present in a given sample. The pipeline performs in-depth quality control that guarantees high-quality results and accurate conclusions. The vibrant visuals produced by the pipeline facilitate a better understanding of the complex and multidimensional microbiome data. The integrated RAYG approach enables the generation of web-based reports, which provides the investigators with the intermediate output that can be reviewed progressively. The intensively analyzed case study set a model for microbiome data analysis.

Across pastoralist groups, dairy products often fulfill major nutritional, economic, and socio-cultural functions. These contributions are jeopardized by poor milk quality with studies among pastoralist groups showing dairy products can harbour a long list of pathogens. These potential risks underscore the need for more effective dairy hygiene interventions. Here, we determine how health messages advocating the “novel” method of pasteurization versus boiling, and administered in narrative versus technical formats, can have an impact on hygiene practices and milk quality in Maasai pastoralists. Four Maasai villages in northern Tanzania were purposively selected to receive intervention strategies that varied in message format (narrative or technical) and heat treatment advocated (boiling or pasteurization). Census lists were used to randomly select 30–35 households in each village (N = 125). Across three visits, milk hygiene knowledge and attitudes were monitored, hygiene practices were directly measured by smart thermometers that recorded heat treatment, and milk quality was determined by calculating total bacterial counts (TBCs) (N = 1007). Compared to initial levels, TBCs in the pasteurization-narrative village (N = 33) exhibited a 73.4% decrease (OR 0.148–0.480) after 7 days and a 59.1% decrease (OR 0.216–0.734) after 14 days. The boiling-narrative (N = 28) exhibited a significant decrease at 7 days (− 68.8%, OR 0.161–0.606), but this decrease was not significant after 14 days (− 35.5%, OR 0.322–1.253). There were no significant decreases for the pasteurization-technical (N = 29) or boiling-technical (N = 31) villages after 7 or 14 days. In addition, narrative health formats led to significantly greater retention of health messages and peer-to-peer sharing. Interventions to improve milk quality in pastoralist and other livestock-dependent communities may benefit from enabling the “novel” method of pasteurization. More broadly, our results suggest that the use of narrative messages can promote healthy behaviours when cultural norms are contrary to best health practices as well as enhance the sustainability and scalability of interventions targeted at hard-to-reach populations, including most pastoralist communities.

Meat from wildlife species (bushmeat) represents a major source of dietary protein in low- and middle-income countries where humans and wildlife live in close proximity. Despite the occurrence of zoonotic pathogens in wildlife, their prevalence in bushmeat remains unknown. To assess the risk of exposure to major pathogens in bushmeat, a total of 3784 samples, both fresh and processed, were collected from three major regions in Tanzania during both rainy and dry seasons, and were screened by real-time PCR for the presence of DNA signatures of Bacillus anthracis (B. anthracis), Brucella spp. (Brucella) and Coxiella burnetii (Coxiella). The analysis identified DNA signatures of B. anthracis (0.48%), Brucella (0.9%), and Coxiella (0.66%) in a total of 77 samples. Highest prevalence rates of B. anthracis, Brucella, and Coxiella were observed in wildebeest (56%), dik-dik (50%), and impala (24%), respectively. Fresh samples, those collected during the rainy season, and samples from Selous or Serengeti had a greater relative risk of being positive. Microbiome characterization identified Firmicutes and Proteobacteria as the most abundant phyla. The results highlight and define potential risks of exposure to endemic wildlife diseases from bushmeat and the need for future investigations to address the public health and emerging infectious disease risks associated with bushmeat harvesting, trade, and consumption.