ABSTRACT
We have applied the sensitize-train-hack-community model to build awareness of and capacity in bioinformatics in Kenya. Open science is the practice of science openly and collaboratively, with tools, techniques, and data freely shared to facilitate reuse and collaboration. Open science is not a mandatory curriculum course in schools, whereas bioinformatics is relatively new in some African regions. Open science tools can significantly enhance bioinformatics, leading to increased reproducibility. However, open science and bioinformatics skills, especially blended, are still lacking among students and researchers in resource-constrained regions. We note the need to be aware of the power of open science among the bioinformatics community and a clear strategy to learn bioinformatics and open science skills for use in research. Using the OpenScienceKE framework-Sensitize, Train, Hack, Collaborate/Community-the BOSS (Bioinformatics and Open Science Skills) virtual events built awareness and empowered researchers with the skills and tools in open science and bioinformatics. Sensitization was achieved through a symposium, training through a workshop and train-the-trainer program, hack through mini-projects, community through conferences, and continuous meet-ups. In this paper, we discuss how we applied the framework during the BOSS events and highlight lessons learnt in planning and executing the events and their impact on the outcome of each phase. We evaluate the impact of the events through anonymous surveys. We show that sensitizing and empowering researchers with the skills works best when the participants apply the skills to real-world problems: project-based learning. Furthermore, we have demonstrated how to implement virtual events in resource-constrained settings by providing Internet and equipment support to participants, thus improving accessibility and diversity.
ABSTRACT
BACKGROUND AND METHODS: To investigate virus diversity in hot zones of probable pathogen spillover, 54 oral-fecal swabs were processed from five bat species collected from three cave systems in Kenya, using metagenome sequencing. RESULTS: Viruses belonging to the Astroviridae, Circoviridae, Coronaviridae, Dicistroviridae, Herpesviridae and Retroviridae were detected, with unclassified viruses. Retroviral sequences were prevalent; 74.1% of all samples were positive, with distinct correlations between virus, site and host bat species. Detected retroviruses comprised Myotis myotis, Myotis ricketti, Myotis daubentonii and Galidia endogenous retroviruses, murine leukemia virus-related virus and Rhinolophus ferrumequinum retrovirus (RFRV). A near-complete genome of a local RFRV strain with identical genome organization and 2.8% nucleotide divergence from the prototype isolate was characterized. Bat coronavirus sequences were detected with a prevalence of 24.1%, where analyses on the ORF1ab region revealed a novel alphacoronavirus lineage. Astrovirus sequences were detected in 25.9%of all samples, with considerable diversity. In 9.2% of the samples, other viruses including Actinidia yellowing virus 2, bat betaherpesvirus, Bole tick virus 4, Cyclovirus and Rhopalosiphum padi virus were identified. CONCLUSIONS: Further monitoring of bats across Kenya is essential to facilitate early recognition of possibly emergent zoonotic viruses.
