Biology subjects

Jjingo, D.

Publications and source records attributed to Jjingo, D..

5 recordsLinked to original sources

bioRxiv2024

High KIR diversity in Uganda and Botswana children living with HIV

Killer-cell immunoglobulin-like receptors (KIRs) are essential components of the innate immune system found on the surfaces of natural killer (NK) cells. The KIRs encoding genes are located on chromosome 19q13.4 and are genetically diverse across populations. KIRs are associated with various disease states including HIV progression, and are linked to transplantation rejection and reproductive success. However, there is limited knowledge on the diversity of KIRs from Uganda and Botswana HIV-infected paediatric cohorts, with high endemic HIV rates. We used next-generation sequencing technologies on 312 (246 Uganda, 66 Botswana) samples to generate KIR allele data and employed customised bioinformatics techniques for allelic, allotype and disease association analysis. We show that these sample sets from Botswana and Uganda have different KIRs of different diversities. In Uganda, we observed 147 vs 111 alleles in the Botswana cohort, which had a more than 1 % frequency. We also found significant deviation towards homozygosity for the KIR3DL2 gene for both rapid (RPs) and long-term non-progressors (LTNPs)in the Ugandan cohort. The frequency of the bw4-80I ligand was also significantly higher among the LTNPs than RPs (8.9 % Vs 2.0%, P-value: 0.032). In the Ugandan cohort, KIR2DS4*001 (OR: 0.671, 95 % CI: 0.481-0.937, FDR adjusted Pc=0.142) and KIR2DS4*006 (OR: 2.519, 95 % CI: 1.085-5.851, FDR adjusted Pc=0.142) were not associated with HIV disease progression after adjustment for multiple testing. Our study results provide additional knowledge of the genetic diversity of KIRs in African populations and provide evidence that will inform future immunogenetics studies concerning human disease susceptibility, evolution and host immune responses.

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↗

bioRxiv2023

A deep population reference panel of tandem repeat variation

Tandem repeats (TRs) represent one of the largest sources of genetic variation in humans and are implicated in a range of phenotypes. Here we present a deep characterization of TR variation based on high coverage whole genome sequencing from 3,550 diverse individuals from the 1000 Genomes Project and H3Africa cohorts. We develop a method, EnsembleTR, to integrate genotypes from four separate methods resulting in high-quality genotypes at more than 1.7 million TR loci. Our catalog reveals novel sequence features influencing TR heterozygosity, identifies population-specific trinucleotide expansions, and finds hundreds of novel eQTL signals. Finally, we generate a phased haplotype panel which can be used to impute most TRs from nearby single nucleotide polymorphisms (SNPs) with high accuracy. Overall, the TR genotypes and reference haplotype panel generated here will serve as valuable resources for future genome-wide and population-wide studies of TRs and their role in human phenotypes.

genomics↗

bioRxiv2021

Genetic Diversity of Bundibugyo Ebolavirus from Uganda and the Democratic Republic of Congo

BackgroundThe Ebolavirus is one of the deadliest viral pathogens which was first discovered in the year 1976 during two consecutive outbreaks in the Democratic Republic of Congo and Sudan. Six known strains have been documented. The Bundibugyo Ebolavirus in particular first emerged in the year 2007 in Uganda. This outbreak was constituted with 116 human cases and 39 laboratory confirmed deaths. After 5 years, it re-emerged and caused an epidemic for the first time in the Democratic Republic of Congo in the year 2012 as reported by the WHO. Here, 36 human cases with 13 laboratory confirmed deaths were registered. Despite several research studies conducted in the past, there is still scarcity of knowledge available on the genetic diversity of Bundibugyo Ebolavirus. We undertook a research project to provide insights into the unique variants of Bundibugyo Ebolavirus that circulated in the two epidemics that occurred in Uganda and the Democratic Republic of Congo Materials and MethodsThe Bioinformatics approaches used were; Quality Control, Reference Mapping, Variant Calling, Annotation, Multiple Sequence Alignment and Phylogenetic analysis to identify genomic variants as well determine the genetic relatedness between the two epidemics. Overall, we used 41 viral sequences that were retrieved from the publicly available sequence database, which is the National Center for Biotechnology and Information Gen-bank database. ResultsOur analysis identified 14,362 unique genomic variants from the two epidemics. The Uganda isolates had 5,740 unique variants, 75 of which had high impacts on the genomes. These were 51 frameshift, 15 stop gained, 5 stop lost, 2 missense, 1 synonymous and 1 stop lost and splice region. Their effects mainly occurred within the L-gene region at reference positions 17705, 11952, 11930 and 11027. For the DRC genomes, 8,622 variant sites were identified. The variants had a modifier effect on the genome occurring at reference positions, 213, 266 and 439. Examples are C213T, A266G and C439T. Phylogenetic reconstruction identified two separate and unique clusters from the two epidemics. ConclusionOur analysis provided further insights into the genetic diversity of Bundibugyo Ebolavirus from the two epidemics. The Bundibugyo Ebolavirus strain was genetically diverse with multiple variants. Phylogenetic reconstruction identified two unique variants. This signified an independent spillover event from a natural reservoir, rather a continuation from the ancestral outbreak that initiated the resurgence in DRC in the year 2012. Therefore, the two epidemics were not genetically related.

genomics↗

bioRxiv2021

Phylogenomic analysis of Uganda influenza type-A viruses to assess their relatedness to the vaccine strains and other Africa viruses: a molecular epidemiology study.

BackgroundGenetic characterisation of circulating influenza viruses is essential for vaccine selection and mitigation of viral transmission. The current scantiness of viral genomic data and underutilisation of advanced molecular analysis methods on influenza viruses circulating in Africa has limited their extensive study and representation in the global influenza ecology. We aimed to sequence influenza type-A viruses (IAVs) that previously circulated in Uganda and characterised their genetic relatedness to the vaccine viruses and publicly available Africa IAVs. MethodsThis was an observational study nested to the Uganda national influenza surveillance programme. We used Next-generation sequencing to locally generate genomes from 116 A(H1N1)pdm09 and 118 A(H3N2) viruses collected between 2010 and 2018 from 7 districts across Uganda. A total of 206 hemagglutinin (HA), 207 neuraminidase (NA), and 213 matrix protein (MP) sequences were genetically compared to the WHO-recommended vaccines and other viruses isolated from Africa since 1994. Viral temporal and spatial divergence and circulating genetic clades were characterised using phylogenetic methods. FindingsWe successfully generated gene sequences for 91{middle dot}9% (215/234) viruses. Uganda A(H1N1)pdm09 and A(H3N2) virus HA, NA, and MP proteins had 96{middle dot}36-99{middle dot}09%, 96{middle dot}49-99{middle dot}39%, and 97{middle dot}48-99{middle dot}95% amino acid similarity, respectively, to vaccines recommended from 2010 through 2020. The local viruses incorporated amino acid substitutions (AAS) in their antigenic, receptor binding, and glycosylation sites each year causing them to antigenically drift away from vaccines. For seasons when vaccine formulations differed, Uganda IAV antigenic sites had 1-2 extra AAS relative to the Southern than Northern hemisphere vaccine viruses. All Uganda IAVs carried the adamantine-resistance marker S31N but not the neuraminidase inhibitor (NAI) resistance markers H274Y and H275Y. However, some A(H1N1)pdm09 viruses had permissive substitutions V234I, N369K, and V241I typical of NAI-resistant viruses. The 2017-2018 A(H1N1)pdm09 viruses belonged to global genetic clade 6B.1, while the A(H3N2) viruses isolated in 2017 belonged to clades 3C.2a and 3C.3a. Uganda IAVs obtained before 2016 clustered distinctly from other Africa viruses while later viruses mixed with other Africa, especially Kenya and Congo, and global viruses. Several unique viral lineages (bootstrap >90) persisted in Uganda and other countries for 1-3 years. InterpretationThe study reveals Uganda as part of the global influenza ecology with continuous importation, antigenic drift, and extensive local transmission of IAVs, presenting a potential risk of future outbreaks. For a country with limited health resources and where social distancing is not sustainable, viral prevention by vaccination should be prioritized. The notable viral diversity in Africa is a warning to countries to broaden and incorporate genome analysis in routine surveillance to monitor circulating and detect new viruses. This knowledge can inform virus selection for vaccine production and assist in developing cost-effective virus control strategies. FundingThis work was supported by the Makerere University-Uganda Virus Research Institute Centre of Excellence for Infection and Immunity Research and Training (MUII). MUII is supported through the Developing Excellence in Leadership, Training and Science (DELTAS) Africa Initiative (Grant no. 107743). The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS), Alliance for Accelerating Excellence in Science in Africa (AESA), and supported by the New Partnership for Africas Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust (Grant no. 107743) and the UK Government. The work was also funded in part by a Wellcome Trust grant (102975).

evolutionary biology↗