Biology subjects

Hazelhurst, S.

Publications and source records attributed to Hazelhurst, S..

12 recordsLinked to original sources

bioRxiv2026

Participant engagement and feedback in microbiome projects: a case of AWI-Gen 2

Returning individualized microbiome results in ways that are ethical, comprehensible, and useful remains under-explored in African settings. We nested a multi-site, mixed-methods study within the AWI-Gen Wave 2 gut microbiome sub-study of 1,801 women aged 42 - 86 years to engage the participants and provide feedback. All (1,001) participants from Agincourt and Soweto (South Africa) and Nairobi (Kenya) were invited to feedback meetings: 496 from Agincourt, 87 from Soweto, and 195 from Nairobi responded. Engagement strategies were tailored by site (small-group and home-based sessions, visual metaphors, Foldscopes, and local-language delivery). Using semi-structured discussions and structured observations analysed thematically in MAXQDA under COREQ, five cross-cutting themes emerged: (1) understanding of microbiome reports, (2) emotional responses to feedback, (3) perceived health relevance, (4) trust in research institutions, and (5) suggestions for improving engagement. Culturally grounded explanations and local-language facilitation enhanced comprehension and perceived relevance; English-heavy sessions were associated with more confusion. Most participants expressed satisfaction and described planned or enacted dietary and lifestyle changes, while frustration centred on long delays between sampling and feedback. Trust increased with transparency and individualized return of results but was often conditional on minimizing burdensome procedures such as repeat blood sampling (phlebotomy) and ensuring timely feedback. Engagement was feasible and low-cost (approximately USD 29-59 per participant) with site-specific resource needs. Limitations included constrained generalizability beyond the three study sites. Returning individualized microbiome findings in community settings in Africa is acceptable, feasible, and can motivate health-promoting behaviours when delivered promptly and in culturally and linguistically appropriate ways. IMPORTANCEMicrobiome studies rarely return individualized results in low-resource settings due to concerns about appropriate feedback and associated costs. This gap risks eroding trust and diminishing research impact. In three African communities, tailored feedback on gut microbiome profiles was provided to 778 women. By documenting a costed, multi-site engagement model and the themes influencing acceptance and actionability, this work offers a practical framework for ethically returning complex -omics results at scale in underrepresented populations - advancing scientific equity and strengthening community trust in microbiome research.

scientific communication and education↗

bioRxiv2024

Expanding the human gut microbiome atlas of Africa

Population studies are crucial in understanding the complex interplay between the gut microbiome and geographical, lifestyle, genetic, and environmental factors. However, populations from low- and middle-income countries, which represent [~]84% of the world population, have been excluded from large-scale gut microbiome research. Here, we present the AWI-Gen 2 Microbiome Project, a cross-sectional gut microbiome study sampling 1,803 women from Burkina Faso, Ghana, Kenya, and South Africa. By intensively engaging with communities that range from rural and horticultural to urban informal settlements and post-industrial, we capture population diversity that represents a far greater breadth of the worlds population. Using shotgun metagenomic sequencing, we find that study site explains substantially more microbial variation than disease status. We identify taxa with strong geographic and lifestyle associations, including loss of Treponema and Cryptobacteroides species and gain of Bifidobacterium species in urban populations. We uncover a wealth of prokaryotic and viral novelty, including 1,005 new bacterial metagenome-assembled genomes, and identify phylogeography signatures in Treponema succinifaciens. Finally, we find a microbiome signature of HIV infection that is defined by several taxa not previously associated with HIV, including Dysosmobacter welbionis and Enterocloster sp. This study represents the largest population-representative survey of gut metagenomes of African individuals to date, and paired with extensive clinical biomarkers, demographic data, and lifestyle information, provides extensive opportunity for microbiome-related discovery and research.

microbiology↗

bioRxiv2022

H3AGWAS : A portable workflow for Genome Wide Association Studies

BackgroundGenome-wide association studies (GWAS) are a powerful method to detect associations between variants and phenotypes. A GWAS requires several complex computations with large data sets, and many steps may need to be repeated with varying parameters. Manual running of these analyses can be tedious, error-prone and hard to reproduce. ResultsThe H3AGWAS workflow from the Pan-African Bioinformatics Network for H3Africa is a powerful, scalable and portable workflow implementing pre-association analysis, implementation of various association testing methods and postassociation analysis of results. ConclusionsThe workflow is scalable -- laptop to cluster to cloud (e.g., SLURM, AWS Batch, Azure). All required software is containerised and can run under Docker on Singularity.

bioinformatics↗

bioRxiv2022

FPGA Acceleration of GWAS Permutation Testing

MotivationGenome-wide association studies (GWASs) analyse genetic variation over the genomes of many individuals in an attempt to identify single nucleotide polymorphisms (SNPs) associated with complex phenotypes. To capture a large amount of genetic variation and increase the chance of detecting associated SNPs, modern GWASs include millions of SNPs sampled from thousands of individuals. The cumulative probability of false associations increases with the number of SNPs included in the analysis. A GWAS, therefore, needs to control the number of false associations. Permutation testing is a straightforward and accurate method of controlling the false positive rate, but it is very computationally expensive (and slow) so there is a need for a permutation testing accelerator that can process modern GWAS datasets in reasonable time. ResultsFPGAs (Field-Programmable Gate Arrays) are reconfigurable integrated circuits which provide a high level of parallelisation that can be harnessed to accelerate GWAS permutation testing. This work presents an accessible FPGA-based tool (designed to run on a cloud-based AWS EC2 FPGA instance) that accelerates GWAS permutation testing for continuous phenotypes. The tool implements two known GWAS permutation testing algorithms: maxT permutation testing and adaptive permutation testing. The speed of the FPGA-based tool was compared to the speed of PLINK (a popular CPU-based tool) running on 40 Intel Xeon 4114 CPU cores using an imputed breast cancer dataset of 13.7 million SNPs sampled from 3652 individuals. For 1000 maxT permutations, the FPGA-based algorithms run time was 22 minutes while PLINKs run time was almost 7 days; for 100 million adaptive permutations, the FPGA-based algorithms run time was 325 minutes and PLINKs run time was about 8.5 days. For 700 million adaptive permutations of the same dataset (an almost unfeasible workload for PLINK running on a 40-core CPU) the run time of the FPGA-accelerated algorithm was 33 hours. AvailabilityAn EC2 AMI (FPGA_perm) in the us-east-1 region is available. Instructions, source code and sample data are available at https://github.com/witseie/fpgaperm.

bioinformatics↗

bioRxiv2021

Single nucleotide polymorphism induces divergent dynamic patterns in CYP3A5: a microsecond scale biomolecular simulation of variants identified in Sub-Saharan African populations

Pharmacogenomics aims to reveal variants associated with drug response phenotypes. Genes whose roles involve the absorption, distribution, metabolism, and excretion of drugs, are highly polymorphic between populations. High coverage whole genome sequencing showed that a large proportion of the variants for these genes are rare in African populations. This study investigates the impact of such variants on protein structure to assess their functional importance. We use genetic data of CYP3A5 from 458 individuals from sub-Saharan Africa to conduct a structural bioinformatics analysis. Five missense variants were modeled and microsecond scale molecular dynamics simulations were conducted for each, as well as for the CYP3A5 wildtype, and the Y53C variant, which has a known deleterious impact on enzyme activity. The binding of ritonavir and artemether to CYP3A5 variant structures was also evaluated. Our results showed different conformational characteristics between all the variants. No significant structural changes were noticed. However, the genetic variability acts on the plasticity of the protein. The impact on drug binding may be drug dependant. We conclude that rare variants hold relevance in determining the pharmacogenomics properties of populations. This could have a significant impact on precision medicine applications in sub-Saharan Africa.

bioinformatics↗

bioRxiv2020

Genetic-substructure and complex demographic history of South African Bantu speakers

South Eastern Bantu-speaking (SEB) groups constitute more than 80% of the population in South Africa. Despite clear linguistic and geographic diversity, the genetic differences between these groups have not been systematically investigated. Based on genome-wide data of over 5000 individuals, representing eight major SEB groups, we provide strong evidence for fine-scale population structure that broadly aligns with geographic distribution and is also congruent with linguistic phylogeny (separation of Nguni, Sotho-Tswana and Tsonga speakers). Although differential Khoe-San admixture plays a key role, the structure persists after Khoe-San ancestry-masking. The timing of admixture, levels of sex-biased gene flow and population size dynamics also highlight differences in the demographic histories of individual groups. The comparisons with five Iron Age farmer genomes further support genetic continuity over [~]400 years in certain regions of the country. Simulated trait genome-wide association studies further show that the observed population structure could have major implications for biomedical genomics research in South Africa.

genomics↗

bioRxiv2020

The extent and impact of variation in ADME genes in sub-Saharan African populations

Investigating variation in genes involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs are key to characterising pharmacogenomic (PGx) relationships. ADME gene variation is relatively well characterised in European and Asian populations, but African populations are under-studied - which has implications for safe and effective drug use in Africa. The genetic diversity of ADME genes across sub-Saharan African populations is large. The Southern African population cluster is most distinct from that of far West Africa. PGx strategies based on European variants will be of limited use in African populations. Although established variants are important, PGx must take into account the full range of African variation. This work urges further characterisation of variants in African populations including in vitro and in silico studies, and to consider the unique African ADME landscape when developing precision medicine guidelines and tools for African populations. Author summaryThe ADME genes are a group of genes that play a key role in absorption, distribution, metabolism and excretion of drugs. Variations in these genes can have a significant impact on drug safety and efficacy. Africa has a high level of genetic variation and is under-studied in drug development, which makes study of variations in these genes in African populations very important. Using a new data set of 458 high-coverage genomes from across Africa, we characterise the extent and impact of variation in the ADME genes, looking at both single nucleotide and copy number variations. We identified 343,368 variants, including 40,692 novel variants, and 930 coding variants which are predicted to have high impact on function. Our discovery curves indicate that there will be considerable value in sequencing more African genomes. Moreover, relatively few of these novel variants are captured on common genotyping arrays. We show that there is considerable diversity within Africa in some important genes, and this will have significant consequences for the emerging field of precision medicine in Africa.

genetics↗

bioRxiv2020

Short- and long-read metagenomics of South African gut microbiomes reveal a transitional composition and novel taxa

Human gut microbiome research focuses on populations living in high-income countries or on the other end of the spectrum, namely non-urban agriculturalist and hunter-gatherer societies. The scarcity of research between these extremes limits our understanding of how the gut microbiota relates to health and disease in the majority of the worlds population. We present the first study evaluating gut microbiome composition in transitioning South African populations using short- and long-read sequencing. We analyzed stool samples from adult females (age 40 - 72) living in rural Bushbuckridge municipality (n=118) or urban Soweto (n=51) and find that these microbiomes are taxonomically intermediate between those of individuals living in high-income countries and traditional communities. We demonstrate that reference collections are incomplete for characterization of microbiomes of individuals living outside high-income countries, resulting in artificially low species-level beta diversity measurements. To improve reference databases, we generated complete genomes of undescribed taxa, including Treponema, Lentisphaerae, and Succinatimonas species. Our results suggest that the gut microbiome in South African populations do not exist along a simple "western-nonwestern" axis and that these populations contain microbial diversity that remains to be described.

genomics↗

bioRxiv2020

In silico study of the spike protein from SARS-CoV-2 interaction with ACE2: similarity with SARS-CoV, hot-spot analysis and effect of the receptor polymorphism

The spread of COVID-19 caused by the SARS-CoV-2 outbreak has been growing since its first identification in December 2019. The publishing of the first SARS-CoV-2 genome made a valuable source of data to study the details about its phylogeny, evolution, and interaction with the host. Protein-protein binding assays have confirmed that Angiotensin-converting enzyme 2 (ACE2) is more likely to be the cell receptor through which the virus invades the host cell. In the present work, we provide an insight into the interaction of the viral spike Receptor Binding Domain (RBD) from different coronavirus isolates with host ACE2 protein. By calculating the binding energy score between RBD and ACE2, we highlighted the putative jump in the affinity from a progenitor form of SARS-CoV-2 to the current virus responsible for COVID-19 outbreak. Our result was consistent with previously reported phylogenetic analysis and corroborates the opinion that the interface segment of the spike protein RBD might be acquired by SARS-CoV-2 via a complex evolutionary process rather than a progressive accumulation of mutations. We also highlighted the relevance of Q493 and P499 amino acid residues of SARS-CoV-2 RBD for binding to human ACE2 and maintaining the stability of the interface. Moreover, we show from the structural analysis that it is unlikely for the interface residues to be the result of genetic engineering. Finally, we studied the impact of eight different variants located at the interaction surface of ACE2, on the complex formation with SARS-CoV-2 RBD. We found that none of them is likely to disrupt the interaction with the viral RBD of SARS-CoV-2.

bioinformatics↗

bioRxiv2020

Gut Microbiome Profiling of a Rural and Urban South African Cohort Reveals Biomarkers of a Population in Lifestyle Transition

BackgroundComparisons of traditional hunter-gatherers and pre-agricultural communities in Africa with urban and suburban Western North American and European cohorts have clearly shown that diet, lifestyle and environment are associated with gut microbiome composition. Yet, little is known about the gut microbiome composition of most African adults. South Africa comprises a richly diverse ethnolinguistic population that is experiencing an ongoing epidemiological transition and concurrent spike in the prevalence of obesity, largely attributed to a shift towards more Westernized diets and increasingly inactive lifestyle practices. To better characterize the microbiome of African adults living in more mainstream lifestyle settings and to investigate associations between the microbiome and obesity, we conducted a pilot study in two South African cohorts that are representative of urban and rural populations. The study was designed collaboratively with community leaders. As the rate of overweight and obesity is particularly high in women, we collected single time-point stool samples from 170 HIV-negative women (51 at Soweto; 119 at Bushbuckridge), performed 16S rRNA gene sequencing on these samples and compared the data to concurrently collected anthropometric data. ResultsWe found the overall gut microbiome of our cohorts to be reflective of their ongoing epidemiological transition. Specifically, our results show a relatively higher than expected abundance of Western gut-associated taxa such as Barnesiella and the presence of Bifidobacteria and Bacteroides together with the more traditionally non-Western gut-associated Prevotella, Treponema and Succinivibrio. Interestingly, we observed a relatively higher abundance of the Melainabacteria, Vampirovibrio, a predatory bacterium, in the rural cohort. We also found Prevotella, despite its generally high prevalence relative to all taxa present in the cohort, to be associated with obesity. ConclusionsAltogether, this work identifies putative microbial features associated with host health in a historically understudied community. Furthermore, we note the crucial role of community engagement to the success of a study in an African setting, the importance of more population-specific studies to inform targeted interventions as well as present a basic foundation for future research in this regard.

microbiology↗

bioRxiv2018

Runs of Homozygosity in sub-Saharan African populations provide insights into a complex demographic and health history

The study of runs of homozygosity (ROH), contiguous regions in the genome where an individual is homozygous across all sites, can shed light on the demographic history and cultural practices. We present a fine-scale ROH analysis of 1679 individuals from 28 sub-Saharan African (SSA) populations along with 1384 individuals from 17 world-wide populations. Using high-density SNP coverage, we could accurately obtain ROH as low as 300Kb using PLINK software. The analyses showed a heterogeneous distribution of autozygosity across SSA, revealing a complex demographic history. They highlight differences between African groups and can differentiate between the impact of consanguineous practices (e.g. among the Somali) and endogamy (e.g. among several Khoe-San groups1). The genomic distribution of ROH was analysed through the identification of ROH islands and regions of heterozygosity (RHZ). These homozygosity cold and hotspots harbour multiple protein coding genes. Studying ROH therefore not only sheds light on population history, but can also be used to study genetic variation related to the health of extant populations.

genomics↗

bioRxiv2017

Assessing Runs of Homozygosity: A comparison of SNP Array and Whole Genome Sequence low coverage data

Runs of Homozygosity (ROH) are sequences that arise when identical haplotypes are inherited from each parent. Since their first detection due to technological advances in the late 1990s, ROHs have been shedding light on human population history and deciphering the genetic basis of monogenic and complex traits and diseases. ROH studies have predominantly exploited SNP array data, but are gradually moving to whole genome sequence (WGS) data as it becomes available. WGS data, covering more genetic variability, can add value to ROH studies, but require additional considerations during analysis. Using SNP array and low coverage WGS data from 1885 individuals from 20 world populations, our aims were to compare ROH from the two datasets and to establish software conditions to get comparable results, thus providing guidelines for combining disparate datasets in joint ROH analyses. Using the PLINK Homozygosity functions, we found that by allowing 3 heterozygous SNPs per window when dealing with WGS low coverage data, it is possible to establish meaningful comparisons between data using the two technologies.

genomics↗