Biology subjects

Omar, K. M.

Publications and source records attributed to Omar, K. M..

3 recordsLinked to original sources

bioRxiv2023

Investigating Antimicrobial Resistance Genes in Kenya, Uganda and Tanzania Cattle Using Metagenomics

Antimicrobial resistance (AMR) is a growing problem in African cattle production systems, posing a threat to human and animal health and the associated economic value chain. However, there is a poor understanding of the resistomes in small-holder cattle breeds in East African countries. This study aims to examine the distribution of Antimicrobial Resistance Genes (ARGs) in Kenya, Tanzania, and Uganda cattle using a metagenomics approach. We used the SqueezeMeta-Abricate (assembly-based) pipeline to detect ARGs and benchmarked this approach using the Centifuge-AMRplusplus (read-based) pipeline to evaluate its efficiency. Our findings reveal a significant number of ARGs of critical medical and economic importance in all three countries, including resistance to drugs of last resort such as carbapenems, suggesting the presence of highly virulent and antibiotic-resistant bacterial pathogens (ESKAPE) circulating in East Africa. Shared ARGs such as aph(6)-id (aminoglycoside phosphotransferase), tet (tetracycline resistance gene), sul2 (sulfonamide resistance gene) and cfxA_gen (betalactamase gene) were detected. Assembly-based methods revealed fewer ARGs compared to read-based methods, indicating the sensitivity and specificity of read-based methods in resistome characterization. Our findings call for further surveillance to estimate the intensity of the antibiotic resistance problem and wider resistome classification. Effective management of livestock and antibiotic consumption is crucial in minimizing antimicrobial resistance and maximizing productivity, making these findings relevant to stakeholders, agriculturists, and veterinarians in East Africa and Africa at large.

bioinformatics↗

bioRxiv2023

Expression Level Analysis of ACE2 Receptor Gene in African-American and Non-African-American COVID-19 Patients

BackgroundThe COVID-19 pandemic caused by SARS-CoV-2 has spread rapidly across the continents. While the incidence of COVID-19 has been reported to be higher among African-American individuals, the rate of mortality has been lower compared to that of non-African-Americans. ACE2 is involved in COVID-19 as SARS-CoV-2 uses the ACE2 enzyme to enter host cells. Although the difference in COVID-19 incidence can be explained by many factors such as low accessibility of health insurance among the African-American community, little is known about ACE2 expression in African-American COVID-19 patients compared to non-African-American COVID-19 patients. The variable expression of genes can contribute to this observed phenomenon. MethodologyIn this study, transcriptomes from African-American and non-African-American COVID-19 patients were retrieved from the sequence read archive and analyzed for ACE2 gene expression. HISAT2 was used to align the reads to the human reference genome, and HTseq-count was used to get raw gene counts. EdgeR was utilized for differential gene expression analysis, and enrichR was employed for gene enrichment analysis. ResultsThe datasets included 14 and 33 transcriptome sequences from COVID-19 patients of African-American and non-African-American descent, respectively. There were 24,092 differentially expressed genes, with 7,718 upregulated (log fold change > 1 and FDR 0.05) and 16,374 downregulated (log fold change -1 and FDR 0.05). The ACE2 mRNA level was found to be considerably downregulated in the African-American cohort (p-value = 0.0242, p-adjusted value = 0.038). ConclusionThe downregulation of ACE2 in the African-American cohort could indicate a correlation to the low COVID-19 severity observed among the African-American community.

genetics↗

bioRxiv2022

Molecular Phylogenetics of HIV-1 Subtypes in African Populations: A Case Study of Sub-Saharan African Countries

Despite advances in antiretroviral therapy that have revolutionized HIV-1 disease management, effective control of the HIV-1 infection pandemic remains elusive. Increased HIV-1 infection rates and genetic diversity in Sub-Saharan African countries pose a challenge in HIV-1 clinical management. This study provides a picture of HIV-1 genetic diversity and its implications for HIV-1 disease spread and the effectiveness of therapies in Africa. Whole-genome sequences of HIV-1 were obtained from Genbank using the accession numbers from 10 African countries with high HIV-1 prevalence. Alignment composed of the query and reference sequences retrieved from the Los Alamos database. The alignment file was viewed and curated in Aliview. Phylogenetic analysis was done by constructing a phylogenetic tree using the maximum likelihood method implemented in IQ-TREE. The clustering pattern of the studied countries showed both homogeneous clustering and heterogeneous clustering with all Zambia sequences clustering with HIV-1 subtype-C indicating local distribution of only subtype-C. Sequences from nine countries showed heterogeneous clustering along with different subtypes as well as individual clustering of the sequences away from references suggesting cross border genetic exchange. Sequences from Kenya and Nigeria clustered with almost all the HIV-1 subtypes suggesting high HIV-1 genetic diversity in Kenya and Nigeria as compared to other African countries. Our results indicate that there is the presence of subtype-specific HIV-1 polymorphisms and interactions during border movements.

genomics↗