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Mwasi, L. S.

Publications and source records attributed to Mwasi, L. S..

2 recordsLinked to original sources

Mitochondrial DNA Variation in the D-LOOP and ND Loci identified in the Kenyan Population: Potential Implications for precision Oncology

BackgroundPrecision oncology is dominated by studies focused on nuclear genomic alterations, leaving mitochondrial DNA (mtDNA) variation excluded from routine clinical genomic testing. However, mitochondria regulate oxidative phosphorylation (OXPHOS), reactive oxygen species (ROS) production, apoptosis, and metabolic reprogramming pathways that are central to chemotherapy response. Methods468 Complete mitochondrial genomes from Kenyan individuals representing diverse ethnic groups were analyzed. Seven variants associated with effect on cancer treatment were identified. These include; m.310T>C(D-loop), m.10398A>G (MT-ND3), m.13708G>A (MT-ND5), m.16189T>C, m.13928G>C, m9055G>A and m.16519T>C (D-loop). Allele frequencies and distribution were assessed. ResultsThe coding-region variants (m.10398A>G and m.13708G>A) occur in Complex I subunits and are associated with altered oxidative phosphorylation efficiency and ROS production. The control-region variants (m.16189T>C and m.16519T>C) influence mtDNA replication and copy number. These variants have been implicated in differential response to chemotherapeutic agents including platinum-based therapies and anthracyclines. m.13928G>C sits in the MT-CYB gene and could possibly affect mitochondrial respiratory function; this variant could influence how tumors respond to therapies that rely on apoptosis or ROS generation.m.9055G>A is a MT-ATP6 variant classified as benign in mitochondrial disease but may represent a marker of haplogroup background rather than a direct cancer driver. While m.310T>C itself does not encode a protein, its location in the regulatory D-loop influences mitochondrial function, which can affect how tumor cells respond to chemotherapies that rely on mitochondrial-mediated apoptosis or oxidative stress. ConclusionPharmacogenomic relevant mitochondrial variants are present in the Kenyan population. With the rise of cancer burden in Kenya there is a need carry out more studies to understand the impact of these variations on cancer treatment. This can inform the integration of mtDNA analysis into precision oncology strategies in African populations.

genomics↗

Identification and genetic characterization of Jingmen tick virus from ticks sampled in select regions of Kenya; 2022-2024

Jingmen tick virus (JMTV), an emerging segmented RNA virus classified as an ungrouped flavivirus, poses a growing public health concern globally. Known for its association with febrile illnesses and wide host range, JMTV has been detected in Rhipicephalus, Hyalomma, and Amblyomma ticks collected from cattle, goats, sheep, camels, and chickens in pastoral regions of Kenya, including Baringo, Mandera, Malindi, Lamu, Mombasa, Wajir, Isiolo, and West Pokot. Using viral metagenomics next-generation sequencing, this study analysed adult ticks (n=1547, 72 pools). A total of 53% (38/72) pools were positive for at least one viral pathogen, with JMTV detected in 87% (33/38) of these pools across all study sites. Phylogenetic analyses revealed evidence of distinct Kenyan JMTV strains, with sequence segments from Malindi and Wajir clustering uniquely in their own clade; suggesting potential localised evolutionary pressures. Time calibrated phylogeny for the segment 1(RdRp) suggested varied ancestral origins and evolutionary relationships for the JMTV strains. MEME, BUSTED and FUBAR methods implemented in the Data-Monkey, unanimously identified codon 290 in segment 1 and 30 in segment 4 to be undergoing episodic positive selection. Recombination analysis performed using the RDP4 recombination detection tool indicated a recombination event in segment 2 of the Lamu JMTV strain that was confirmed by seven detection methods and visualised in BootScan. These findings suggest that Kenyan JMTV strains are undergoing positive selection, potentially driven by unique ecological and host factors. Segmented genome evidence of recombination highlights the increasing viruss potential for antigenic diversity. Host diversity and virus phylogenetic patterns underscore the zoonotic potential and its capacity for regional spread, emphasizing the critical need for enhanced vector surveillance. Temporal and ecological drivers like seasonal tick activity and livestock movement warrant investigation to elucidate JMTV transmission dynamics. Prioritizing tick-borne virus surveillance in Kenya will strengthen public health strategies and mitigates emerging viral risks.

evolutionary biology↗