Biology subjects

Mbabazi, M.

Publications and source records attributed to Mbabazi, M..

4 recordsLinked to original sources

bioRxiv2026

Pulmonary Tuberculosis Is Associated with Body Site-Specific Alterations in the Respiratory and Gut Microbiome in Uganda

Abstract Background: Tuberculosis is a major infectious disease whose effects may extend beyond the lungs to influence microbial communities at other body sites. Although studies have reported alterations in the respiratory and gut microbiomes of people with TB, evidence from sub-Saharan Africa remains limited, and the extent to which these alterations differ between body sites is not fully understood. This study characterized sputum and stool microbiomes among Ugandan adults with pulmonary TB and those without TB. Methods: We conducted a cross-sectional study involving 200 participants, comprising 150 adults with pulmonary TB and 50 contacts, at Mulago National Referral Hospital in Kampala, Uganda. Sputum and stool samples were profiled using 16S rRNA gene sequencing. Following quality control and contaminant removal, within-sample diversity was assessed using multiple alpha diversity indices. Beta diversity was evaluated using distance-based methods, with group differences assessed by permutational multivariate analysis of variance (PERMANOVA) and homogeneity of dispersion tests. Differentially abundant taxa were identified using ANCOM-BC2. Results: After quality control, 135 sputum and 151 stool samples were retained for downstream analysis. In sputum, microbial richness estimators Chao1 and ACE were lower among TB cases than controls, whereas differences in overall community composition were not statistically significant after correction for multiple testing. In stool, several richness and diversity measures differed between groups, and beta-diversity analyses detected differences in community composition. However, TB cases exhibited greater within-group dispersion, and the sequencing platform contributed substantially to variation in stool microbial profiles. In multivariable analyses, the sequencing platform was the only factor independently associated with stool community composition after correction for multiple testing. Differential-abundance analyses identified body site-specific taxonomic associations with TB, including differences involving Streptococcus, Parvimonas, and Actinobacillus in sputum, and Dorea, Lachnoclostridium, and Turicibacter in stool. Conclusion: Pulmonary TB was associated with differences in microbial richness and the abundance of specific taxa in both sputum and stool, but evidence for overall community composition differences varied by body site and was influenced by dispersion and sequencing platform. These findings highlight the importance of examining both respiratory and gut microbial communities in TB research. Longitudinal studies using standardized sequencing methods are needed to clarify how these patterns change during treatment and whether they have diagnostic or clinical relevance.

genomics↗

bioRxiv2026

Whole-genome characterization of Plasmodium falciparum population structure and drug resistance across Uganda and neighboring countries

Uganda has one of the world's highest malaria burdens, but parasite population structure and connectivity have not been characterized nationally with whole-genome data. We analyzed 249 monoclonal Plasmodium falciparum genomes from 26 sentinel sites across Uganda in 2023 and compared them with publicly available genomes from five neighboring countries. Genetic diversity was high and differentiation low in Uganda, but identity-by-descent detected limited structure. This was most pronounced in the low-transmission southwest, where parasites shared ancestry and recent relatedness with isolates from western Tanzania. Selection scans identified signals at loci associated with resistance to artemisinins and their partner drugs, and to chloroquine and antifolates. The strongest signal was at PfPX1 where the PIN haplotype (L1222P, M1701I, D1705N) reached 70% prevalence nationwide, but selection was carried by PIN haplotypes that had additionally acquired D384A, largely confined to northern and eastern Uganda. A second substitution at the same codon, D384Y, formed a haplotype shared across the Tanzanian border. PfKelch13 variants were partitioned across multiple backgrounds, consistent with repeated independent emergence, and C469Y was enriched on the PfPX1 D384A-PIN background. These genomes provide a 2023 baseline for tracking potential mediators of drug resistance and support coordinated genomic surveillance across Uganda and its neighbors.

genomics↗

bioRxiv2026

PfPHAST: Plasmodium falciparum Public Health Amplicon Sequencing Tool, a Streamlined Panel for Malaria Genomic Surveillance

Genomic tools can support malaria control policy through surveillance of Plasmodium falciparum populations, tracking antimalarial drug resistance, pfhrp2/3 deletions that compromise rapid diagnostic tests, and selection at the circumsporozoite protein (PfCSP) vaccine target, as well as through molecular correction of therapeutic efficacy studies (TES). Multiplex Amplicons for Drug, Diagnostic, Diversity, and Differentiation Haplotypes using Targeted Resequencing (MAD4HatTeR), a comprehensive amplicon sequencing panel covering up to 276 targets, supports these applications but is tailored to research rather than routine programmatic use. We developed P. falciparum Public Health Amplicon Sequencing Tool (PfPHAST), a 56-target derivative of MAD4HatTeR spanning drug resistance loci, pfhrp2/3 deletion, PfCSP genotyping, non-falciparum species identification, and 20 high-heterozygosity microhaplotype loci for TES classification. We compared PfPHAST and MAD4HatTeR using laboratory strain controls, including two-strain dilution series and a five-strain mixture, across parasite densities of 100 to 10,000 parasites/L. At matched per-target depth, PfPHAST achieved a higher quality-control pass rate than MAD4HatTeR (94.4% versus 90.0%) and distributed reads more evenly across targets. The panels showed comparable recall and precision for drug resistance codons and microhaplotypes, reaching near-complete recall above 40% within-sample allele frequency (WSAF) at all densities, with reduced sensitivity for minor alleles below 10% WSAF at low parasite density in both panels. Observed and expected WSAF correlated strongly for both panels, and both resolved a five-strain polyclonal mixture, including a 5% minor strain. By concentrating sequencing capacity on targets of greatest programmatic relevance, PfPHAST offers a scalable, lower-cost alternative to comprehensive research panels without sacrificing performance on shared targets, complementing MAD4HatTeR for routine molecular malaria surveillance.

genomics↗

bioRxiv2024

Gut microbial profiling of COVID-19 patients in Uganda

BackgroundWhile COVID-19 spread globally, the role of the gut microbiota in patient outcomes has remained an area of exploration especially in resource limited settings. This study aimed to comprehensively profile the gut microbiome among Ugandan COVID-19 patients and infer potential implications. MethodsNasopharyngeal swabs, stool, clinical and demographic data were collected from COVID-19 confirmed cases at the COVID-19 isolation and treatment centers in Kampala and Entebbe, Uganda, during the first and second waves of the pandemic in Uganda (i.e., 2020 and 2021, respectively). SARS-CoV-2 presence in the swab samples was confirmed by quantitative real-time RT-PCR assays. 16S rRNA metagenomic next-generation sequencing was performed on the DNA extracted from the stool samples, followed by bioinformatics analysis. Machine learning was used to determine microbes that were associated with disease severity. ResultsWe observed varied gut microbial composition between COVID-19 patients and healthy controls. Potentially pathogenic bacteria such as Klebsiella oxytoca, Salmonella enterica and Serratia marcescens had an increased presence in COVID-19 disease states, especially severe cases. Enrichment of opportunistic pathogens, such as Enterococcus species, and depletion of beneficial microbes, like Alphaproteobacteria, was observed between mild and severe cases. Machine learning identified age and microbes such as Ruminococcaceae, Bacilli, Enterobacteriales, porphyromonadaceae, and Prevotella copri as predictive of severity. ConclusionThese findings suggest that the microbiome plays a role in the dynamics of SARS-CoV-2 infection in African patients. The shift in abundance of specific microbes can moderately predict severity of COVID-19 in this population. Their direct or indirect roles in determining severity should be investigated further for potential therapeutic interventions.

bioinformatics↗