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Characterizing microbial diversity and resistome in urban sewage using shotgun metagenomics in Kampala, Uganda

Published onJun 13, 2023
Characterizing microbial diversity and resistome in urban sewage using shotgun metagenomics in Kampala, Uganda

Background & Objectives: Recently, antimicrobial-resistant (AMR) infections have shown up as the leading threat to human health, having 700,000 directly attributed estimated deaths per year worldwide. For Africa, Antimicrobial resistance data is still not available for 42.6% – quite a big number, of the countries. In absence of a collaborative and joint global response, the figure is approximated to rise to 10 million annual deaths worldwide by 2050. Therefore, there is a need for availing AMR surveillance information and urban sewage is attractive because it is rich in sampling material from large and mostly healthy populations. The project seeks to identify and characterize antibiotic-resistant bacteria in urban sewage and to determine the urban sewage resistome. 

Methodology: This will be a cross-sectional study where samples will be collected from the open and closed sewers because not all households are connected to the piped system. This will be done during the wet and dry seasons to account for the population’s behaviour during both seasons. The samples will be subjected to Metagenomic Next-Generation sequencing. The resultant data will be subjected to a metagenomic analysis pipeline using customized scripts. Both Alpha and Beta diversities will be calculated over the taxonomic profile after which identification of environment-associated biomarker taxa will be performed. metaMLST will then be used to characterize bacterial species at the strain level. Metagenomes for each sample will then be de novo assembled using MEGAHIT. The resulting contigs will then be secondary assembled using Minimus2.  The resulting contigs will be used to predict bacterial genes using the Prodigal tool. Abricate will be used to identify antibiotic resistance and virulence genes by comparing the obtained contigs against the Comprehensive Antibiotic Resistance Database and virulence factor database respectively.

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