Biology subjects

Muwonge, A.

Publications and source records attributed to Muwonge, A..

5 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↗

bioRxiv2025

A socio-ecological System Dynamics model of antimicrobial use and resistance

The concept of resource extraction in the context of antimicrobial resistance (AMR) is rarely explored. In this framework, antimicrobial susceptibility is viewed as a finite resource that is depleted through the use of antimicrobials --thus, AMR represents the exhaustion of this resource. In this work, we examine the system dynamics of AMR using causal loop diagrams to define both the structure and behaviour of two variants of the system. We then evaluate the robustness of the system dynamics models through sensitivity testing. The first model is inspired by a classic "Limits to Growth" structure, in which antimicrobial use practices depend on recent observations of treatment success or failure. The second differs by including AMR surveillance informing antimicrobial prescribing instead of anecdotal experience. The models consider one "bug-drug-mutation-context" combination at a time, but can be applied to different microbes, antimicrobials, and host populations in human or veterinary contexts. Multiparameter sensitivity analyses of relative fitness and timescale parameters were carried out on both model variants. Several key differences in model behaviour over time were observed between the socio-ecological Limits to Growth structure and the modified version in which human judgment, with its associated time lag, is bypassed. The models help explore the effects of human behaviour and associated time lags on patterns of population-level antimicrobial susceptibility over time, applying an established modelling technique in a novel context to generate new insights - notably that plateaux in AMR observed in the field could be in part due to human behaviour rather than purely evolutionary forces. The framing of antimicrobial susceptibility as a variably renewable natural resource is valuable not only as an avenue for alternative modelling approaches, but also as a more collaborative framing for public and policy engagement to promote sustainable management of this common pool resource.

microbiology↗

bioRxiv2021

Inferring livestock movement networks from archived data to support infectious disease control in developing countries

The use of network analysis to support livestock disease control in low middle-income countries (LMICs) has historically been hampered by the cost of generating empirical data in the absence of animal movement recording schemes. To fill this gap, methods which exploit freely available demographic and archived molecular data can be used to generate livestock networks based on gravity and phylogeographic modelling techniques, respectively. However, questions remain on the performance of these methods in capturing the topology of empirical networks. Here, we compare output from these network methodologies to a network constructed from either empirical data or randomly generated data. To facilitate this comparison, the spread of infectious diseases was simulated, it is this evaluation that demonstrates their potential utility to inform robust livestock disease control strategies. The molecular network was the closest approximation to the empirical network, both in relation to topological and epidemic characteristics, whereas size of epidemics in the gravity network tended to be larger, better agreement across all three networks was observed when; a) total nodes infected, b) percentage infection take off were compared. These methods consistently identified the same important animal movement and trade hotspots as the empirical networks. We therefore consider this proof-of-concept that demographic data such as censuses and archived molecular data could be repurposed to inform livestock disease management in LMICs. Author summaryLive animal movements in Africa represent a significant risk of transmission and spread of infectious diseases in livestock populations, and therefore, have direct implications on the food security of the continent. Here we explore the potential utility of available data to support control strategies, by comparing movement networks inferred from such data i.e. census and pathogen molecular data using gravity modelling and phylogeography respectively. Their utility is evaluated by comparing their topology and disease spread characteristics to empirical live animal movement. Based on our results, we posit that archived data can be repurposed to support infectious disease control on the African continent.

scientific communication and education↗

bioRxiv2020

A putative genomic map for resistance of Bos indicus cattle in Cameroon to bovine tuberculosis

Bovine Tuberculosis (bTB) caused by Mycobacterium bovis is a livestock disease of global economic and public health importance. There are currently no effective vaccines available for livestock and so control relies on animal level surveillance and pasteurisation of dairy products. A new alternative control approach is to exploit the genetic variability of the host; recent studies have demonstrated that breeding Bos taurus cattle for increased resistance to bTB is feasible. The utility of such an approach is still unknown for the Bos indicus cattle population. This study aims to assess genetic variation in bTB resistance and the underlying genomic architecture in Bos indicus breeds in Cameroon. We conducted a cross-sectional study of slaughter cattle in Cameroon and genotyped a sample of 213 cattle. Their genomic diversity was characterised using PCA, hierarchical clustering and admixture analysis. We assessed genetic variation in bTB resistance using heritability analysis and compared quantitative trait loci. Previous studies had found that breed was an important factor in explaining the epidemiology of bTB, with Fulani cattle appearing to be more susceptible than mixed breeds. However, we show that the apparent phenotypic differences in visual appearance between the breeds was not reflected by clear genomic differences. At the genetic level, cattle belonging to different hierarchical genomic clusters differed in their susceptibility to bTB. There was evidence of a genomic association between M. bovis infection status with specific SNPs. We highlight the need to understand the challenges faced by livestock in specific settings both in terms of pathogens and the environment, in addition to their intended purpose and how they fit into a defined management system. It is only at this point livestock keepers can then make informed breeding choices, not only for resistance to disease but also for increasing production.

genetics↗

bioRxiv2019

Resistance to change? The impact of group medication on AMR gene dynamics during commercial pig production

The anthropogenic selection of antimicrobial resistance (AMR) genes is under intense scrutiny, particularly in livestock production, where group antimicrobial administration is used to control disease. Whilst large epidemiological studies provide important data on the diversity and distribution of AMR genes, we have little insight into how group antimicrobial administration impacts AMR gene abundance and diversity within a system. Here, faecal microbiome and AMR gene dynamics were tracked for six months through a standard production cycle on a commercial pig unit. Our results demonstrate that specific AMR genes have reached an equilibrium across this farming system to the extent that the levels measured were maintained from suckling through to slaughter, despite increases in microbiome diversity in early development. These levels were not influenced by antibiotic use, either during the production cycle or following whole herd medication. Some AMR genes were found at levels higher than that of the bacterial 16S rRNA gene, indicating widespread distribution across the most common bacterial genera. The targeted AMR genes were also detected in nearby soil samples, several with decreasing abundance with increasing distance from the unit, demonstrating that the farm acts as a point source of AMR gene pollution. Metagenomic sequencing of a subset of samples identified 144 AMR genes, with higher gene diversity in the piglet samples compared to the sow samples. Critically, despite overwhelming and stable levels of resistance alleles against the main antimicrobials used on this farm, these compounds continue to control the bacterial pathogens responsible for production losses and compromised welfare.\n\nImportanceGroup antibiotic treatment has been used for decades to control bacterial diseases that reduce the productivity and compromise the welfare of livestock. Recent increases in antibiotic resistant infections in humans has resulted in concerns that antibiotic use in livestock may contribute to the development of untreatable bacterial infections in humans. There is however little understanding as to how the genes that bacteria require to become resistant to antibiotics respond during and after group antibiotic treatment of livestock, particularly in systems where high levels of antibiotics have been used for a prolonged period of time. We show that in such a system, levels of specific antibiotic resistance genes are high irrespective of group antibiotic treatments, whilst dramatic reductions in antibiotic use also fail to reduce the levels of these genes. These findings have important implications for public policy relating to the use of antibiotic in livestock farming.

microbiology↗