Cinkovich, S. | Search bioRxiv

bioRxiv2024

Characterization of West Nile virus Koutango lineage from Phlebotomine Sandflies in Kenya 2021

The West Nile virus (WNV), primarily transmitted by mosquitoes, is one of the most widespread flaviviruses globally, with past outbreaks occurring in the USA and Europe. Recent studies in parts of Africa, including Kenya, have identified the West Nile virus Koutango lineage (WN-KOUTV) among phlebotomine sandfly populations, however, our understanding of this virus remains limited. Hence, this study aimed to characterize WN-KOUTV from phlebotomine sandflies. Sandflies were sampled between 12-16th March 2021 from six villages in Baringo South, Kenya, using CDC light traps. Female sandflies were taxonomically identified and pooled based on genus. Virus isolation was performed in Vero cells. Viral genome was determined using next-generation sequencing. Phylogenetic and molecular clock analyses were done to decipher the viruss evolutionary relationships. Comparative analyses of amino acid sequences were performed to determine variations. Protein modeling in Pymol was conducted to elucidate variations in key protein regions. Evolutionary pressure analysis investigated the selection pressures on the virus. In vitro experiments were done to investigate the virus growth kinetics in mammalian (Vero-E6) and mosquito (C636) cells. We report the isolation of WN-KOUTV from Salabani Baringo South, Kenya. The isolated WN-KOUTV clustered with previously identified WN-KOUTV strains. Comparative analysis revealed unique amino acid at NS5 653. Diversifying pressure was acting NS3 267 of the WN-KOUTV lineage. WN-KOUTV replicates efficiently in Vero-E6 and C636 cells comparable to West Nile virus Lineage 1a, isolated from mosquitoes. The isolation of WN-KOUTV in sandflies points to them as potential vectors, however, vector competence studies would confirm this. The efficient replication in mammalian and mosquito cell lines elucidated its adaptability to host and vector. We speculate the close genetic relationship of WN-KOUTV strains is enabled by the bird migratory route between East and West Africa. If proven, this may point to a potential future pandemic pathway for this virus.

microbiology↗

bioRxiv2023

Detection of pathogenic bacteria in ticks from Isiolo and Kwale counties of Kenya using metagenomics.

Ticks are arachnid ectoparasites which rank second only to mosquitoes in the transmission of human diseases including bacteria responsible for anaplasmosis, ehrlichiosis, spotted fevers, and Lyme disease among other febrile illnesses. Due to paucity of data on bacteria transmitted by ticks in Kenya, this study undertook a bacterial metagenomic-based characterization of ticks collected from Isiolo, a semi-arid pastoralist County in Eastern Kenya, and Kwale, a coastal County with monsoon climate on the southern Kenyan border with Tanzania. A total of 2,918 ticks belonging to 3 genera and 10 species were pooled and screened in this study. Tick identification was confirmed through the sequencing of Cytochrome C Oxidase Subunit 1 (COI) gene. Bacterial 16S rRNA gene PCR amplicons obtained from the above samples were sequenced using the MinION (Oxford Nanopore Technologies) platform. The resulting reads were demultiplexed in Porechop, followed by trimming and filtering in Trimmomatic before clustering using Qiime2-VSearch. A SILVA database pretrained naive Bayes classifier was used to taxonomically classify the Operational Taxonomic Units (OTUs). The bacteria of clinical interest detected in pooled tick assays were as follows: Rickettsia spp. 59.43% of pools, Coxiella burnetii 37.88%, Proteus mirabilis 5.08%, Cutibacterium acnes 6.08% and Corynebacterium ulcerans 2.43%. These bacteria are responsible for spotted fevers, query fever (Q-fever), urinary tract infections, skin and soft tissue infections, eye infections and diphtheria-like infections in humans, respectively. P. mirabilis, C. acnes and C. ulcerans were detected only in Isiolo. Additionally, COI sequences allowed for the identification of Rickettsia and Coxiella species to strain level in some of the pools. Diversity analysis revealed that the tick genera had high levels of Alpha diversity but the differences between the microbiomes of the three tick genera studied were not significant. The detection of Cutibacterium acnes, commonly associated with human skin flora suggests that the ticks may have contact with humans potentially exposing them to bacterial infections. The findings in this study highlight the need for further investigation into the viability of these bacteria and the competency of ticks to transmit them. Clinicians in these high-risk areas also need to be appraised for them to include Rickettsial diseases and Q-fever as part of their differential diagnosis.

bioinformatics↗