Defining the bacterial microbiome of ticks in Chongwe and Chisamba Districts of Zambia

Background: The microbiome composition of an arthropod vector may impede the growth of some pathogens, aid colonisation by pathogens or affect vector behaviour in ways that impact the transmission of pathogens. In Zambia, little is known of the microbial communities hosted by ticks and how pathogens...

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Main Authors: Malala Mulavu, Cynthia Sipho Khumalo, Lavel Moonga, Kyoko Hayashida, Benjamin Mubemba, Katendi Changula, Edgar Simulundu, Walter Muleya, Simbarashe Chitanga
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Infectious Medicine
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Online Access:http://www.sciencedirect.com/science/article/pii/S2772431X24000455
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author Malala Mulavu
Cynthia Sipho Khumalo
Lavel Moonga
Kyoko Hayashida
Benjamin Mubemba
Katendi Changula
Edgar Simulundu
Walter Muleya
Simbarashe Chitanga
author_facet Malala Mulavu
Cynthia Sipho Khumalo
Lavel Moonga
Kyoko Hayashida
Benjamin Mubemba
Katendi Changula
Edgar Simulundu
Walter Muleya
Simbarashe Chitanga
author_sort Malala Mulavu
collection DOAJ
description Background: The microbiome composition of an arthropod vector may impede the growth of some pathogens, aid colonisation by pathogens or affect vector behaviour in ways that impact the transmission of pathogens. In Zambia, little is known of the microbial communities hosted by ticks and how pathogens like Rickettsia play a role in the microbiome composition. Objective: This study sought to determine the microbiome of Rickettsia-negative and Rickettsia-positive ticks in selected districts of Zambia. Methods: This was a cross-sectional study carried out on 94 ticks collected from cattle in Chongwe and Chisamba districts. The overall prevalence of Rickettsia spp. was detected using PCR amplification of the ompB gene. Thereafter, both Rickettsia-negative and positive ticks underwent 16S rRNA gene amplification and Illumina high-throughput sequencing. Data was analysed using QIIME2 analysis pipeline. Results: The prevalence of Rickettsia was found to be 47.9% (45/94) with prevalence in Amblyomma at 78.5% (22/28), Hyalomma at 68.9% (20/29) and Rhipicephalus having the lowest at 8.1% (3/37). Proteobacteria, Firmicutes, Actinobacteriota and Euryachaeota were the most common phyla, while endosymbionts were uncommonly detected in the ticks. Further analysis showed significant differences in microbiome composition based on Rickettsia detection status (p=0.001) and location (p=0.001), based on the alpha diversity Shannon index, Bray Curtis beta diversity and PERMANOVA, whilst differences according to life stage, tick species and genus was only shown based on the Bray Curtis beta diversity and PERMANOVA analysis. Conclusion: Ultimately, this study provides valuable insights into the structure of the tick microbiome in parts of Zambia and how it is affected by the presence of Rickettsia.
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spelling doaj-art-5594fff7d2f54d698c0e055a91046bc52025-08-20T02:49:35ZengElsevierInfectious Medicine2772-431X2024-12-013410013110.1016/j.imj.2024.100131Defining the bacterial microbiome of ticks in Chongwe and Chisamba Districts of ZambiaMalala Mulavu0Cynthia Sipho Khumalo1Lavel Moonga2Kyoko Hayashida3Benjamin Mubemba4Katendi Changula5Edgar Simulundu6Walter Muleya7Simbarashe Chitanga8Department of Biomedical Sciences, School of Health Sciences, University of Zambia, P.O Box 50110, Lusaka 10101, ZambiaDepartment of Biomedical Sciences, School of Veterinary Medicine, University of Zambia, P.O Box 32379, Lusaka 10101, ZambiaDepartment of Paraclinical Studies, School of Veterinary Medicine, University of Zambia, P.O Box 32379, Lusaka 10101, ZambiaDivision of Collaboration and Education, Research Center for Zoonosis Control, Hokkaido University, Kita 18, Nishi 9, Kita-ku, Sapporo 060-0818, JapanDepartment of Wildlife Sciences, School of Natural Resources, Copperbelt University, P.O Box 21692, Kitwe 50100, ZambiaDepartment of Paraclinical Studies, School of Veterinary Medicine, University of Zambia, P.O Box 32379, Lusaka 10101, ZambiaDepartment of Disease Control, School of Veterinary Medicine, University of Zambia, P.O Box 32379, Lusaka 10101, Zambia; Macha Research Trust, P.O. Box 630166, Choma 20100, ZambiaDepartment of Biomedical Sciences, School of Veterinary Medicine, University of Zambia, P.O Box 32379, Lusaka 10101, Zambia; Corresponding authors.Department of Biomedical Sciences, School of Health Sciences, University of Zambia, P.O Box 50110, Lusaka 10101, Zambia; Department of Preclinical Studies, School of Veterinary Medicine, University of Namibia, Private Bag 13301, Windhoek 10005, Namibia; School of Life Sciences, University of KwaZulu-Natal, Private Bag X54001, Durban 4041, South Africa; Corresponding authors.Background: The microbiome composition of an arthropod vector may impede the growth of some pathogens, aid colonisation by pathogens or affect vector behaviour in ways that impact the transmission of pathogens. In Zambia, little is known of the microbial communities hosted by ticks and how pathogens like Rickettsia play a role in the microbiome composition. Objective: This study sought to determine the microbiome of Rickettsia-negative and Rickettsia-positive ticks in selected districts of Zambia. Methods: This was a cross-sectional study carried out on 94 ticks collected from cattle in Chongwe and Chisamba districts. The overall prevalence of Rickettsia spp. was detected using PCR amplification of the ompB gene. Thereafter, both Rickettsia-negative and positive ticks underwent 16S rRNA gene amplification and Illumina high-throughput sequencing. Data was analysed using QIIME2 analysis pipeline. Results: The prevalence of Rickettsia was found to be 47.9% (45/94) with prevalence in Amblyomma at 78.5% (22/28), Hyalomma at 68.9% (20/29) and Rhipicephalus having the lowest at 8.1% (3/37). Proteobacteria, Firmicutes, Actinobacteriota and Euryachaeota were the most common phyla, while endosymbionts were uncommonly detected in the ticks. Further analysis showed significant differences in microbiome composition based on Rickettsia detection status (p=0.001) and location (p=0.001), based on the alpha diversity Shannon index, Bray Curtis beta diversity and PERMANOVA, whilst differences according to life stage, tick species and genus was only shown based on the Bray Curtis beta diversity and PERMANOVA analysis. Conclusion: Ultimately, this study provides valuable insights into the structure of the tick microbiome in parts of Zambia and how it is affected by the presence of Rickettsia.http://www.sciencedirect.com/science/article/pii/S2772431X24000455MicrobiomeRickettsiaVectorsTickZambiaPathogens
spellingShingle Malala Mulavu
Cynthia Sipho Khumalo
Lavel Moonga
Kyoko Hayashida
Benjamin Mubemba
Katendi Changula
Edgar Simulundu
Walter Muleya
Simbarashe Chitanga
Defining the bacterial microbiome of ticks in Chongwe and Chisamba Districts of Zambia
Infectious Medicine
Microbiome
Rickettsia
Vectors
Tick
Zambia
Pathogens
title Defining the bacterial microbiome of ticks in Chongwe and Chisamba Districts of Zambia
title_full Defining the bacterial microbiome of ticks in Chongwe and Chisamba Districts of Zambia
title_fullStr Defining the bacterial microbiome of ticks in Chongwe and Chisamba Districts of Zambia
title_full_unstemmed Defining the bacterial microbiome of ticks in Chongwe and Chisamba Districts of Zambia
title_short Defining the bacterial microbiome of ticks in Chongwe and Chisamba Districts of Zambia
title_sort defining the bacterial microbiome of ticks in chongwe and chisamba districts of zambia
topic Microbiome
Rickettsia
Vectors
Tick
Zambia
Pathogens
url http://www.sciencedirect.com/science/article/pii/S2772431X24000455
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