塞内加尔基于蚊子的逆转录病毒和虫媒病毒检测:扩大异种监测范围。

IF 3.8 Q2 INFECTIOUS DISEASES
Marie Henriette Dior Ndione, El Hadji Ndiaye, Madeleine Dieng, Babacar Diouf, Safietou Sankhé, Diawo Diallo, Mouhamed Kane, Ndeye Marie Sene, Maimouna Mbanne, Faty Amadou Sy, Seynabou Mbaye Ba Souna Diop, Serge Freddy Moukaha Doukanda, Amadou Alpha Sall, Ousmane Faye, Ndongo Dia, Scott C Weaver, Oumar Faye, Mawlouth Diallo, Gamou Fall, Alioune Gaye, Moussa Moise Diagne
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引用次数: 0

摘要

背景:众所周知,蚊子是节肢动物传播病毒的载体,但它们作为非节肢动物传播病毒的被动携带者的作用仍未得到充分研究。异种监测是一种利用吸血节肢动物对宿主和病原体遗传物质进行取样的方法,已成为病毒生态学中的一种有价值的工具。在这项研究中,我们调查了来自塞内加尔的血食蚊子的病毒景观,并报告了首次检测到Jaagsiekte Sheep Retrovirus (JSRV)相关序列和enzotic Nasal Tumor Virus 2 (ENTV-2)相关序列,以及地方性虫媒病毒。我们的研究旨在探讨在复杂的生态系统中,蚊子是否可以作为哨兵来检测病原体和宿主来源的标志物。方法:2016 - 2019年在塞内加尔卢加、巴凯吉和凯杜古3个生态重点地区采集蚊虫。采集吸血蚊子,采用Illumina NextSeq550进行RNA提取和宏基因组测序。测序数据用CZ-ID和BLAST进行病毒鉴定。RT-qPCR检测旨在验证jsrv相关序列的存在,靶向包膜基因的保守区域和3'未翻译区域。利用MAFFT和IQ-TREE进行系统发育分析,将检测到的序列与全球外源和内源JSRV参考文献进行比较。结果:测序揭示了蚊子物种间广泛的病毒多样性,包括昆虫特异性病毒、虫媒病毒(西尼罗河病毒、Sindbis病毒、Bagaza病毒、Usutu病毒、Barkedji病毒)和两个逆转录病毒序列。在Barkedji(2019)的一个池中确认了一个JSRV相关序列,并在系统发育上与内源性JSRV聚类。从同一池中恢复了与中国致病菌株密切相关的几乎完整的ENTV-2基因组。其他病毒在已建立的非洲谱系内分组,支持持续的区域传播。讨论:本研究首次报道了在蚊子中检测到逆转录病毒序列,以及鉴定出活跃传播的虫媒病毒和昆虫特异性病毒,突出了蚊子作为环境哨兵的更广泛潜力。虽然蚊子不是逆转录病毒的生物载体,但它们通过血食捕获宿主来源的逆转录病毒物质和致病病毒基因组的能力增强了异种监测对监测牲畜-媒介-环境相互作用的价值。这些发现有助于在综合疾病监测方面做出更广泛的努力,并强调了将宏基因组学与分子诊断相结合在高风险生态环境中检测各种病毒信号的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mosquito-based detection of retroviruses and arboviruses in Senegal: expanding the scope of xenosurveillance.

Background: Mosquitoes are well-known vectors for arthropod-borne viruses, yet their role as passive carriers of non-arthropod-borne viruses remains underexplored. Xenosurveillance, a method that utilizes blood-feeding arthropods to sample host and pathogen genetic material, has emerged as a valuable tool in viral ecology. In this study, we investigated the viral landscape of blood-fed mosquitoes from Senegal and report the first detection of Jaagsiekte Sheep Retrovirus (JSRV)-related and Enzootic Nasal Tumor Virus 2 (ENTV-2)-related sequences, alongside endemic arboviruses. Our study aimed to investigate whether mosquitoes can serve as sentinels for detecting both pathogens and host-derived markers in complex ecosystems.

Methods: Mosquitoes were collected between 2016 and 2019 from three ecologically significant regions in Senegal (Louga, Barkedji, and Kedougou). Blood-fed mosquitoes were pooled and subjected to RNA extraction and metagenomic sequencing using Illumina NextSeq550. Sequencing data were analyzed with CZ-ID and BLAST for viral identification. RT-qPCR assays were designed to validate the presence of JSRV-related sequences, targeting conserved regions of the envelope gene and 3' untranslated region. Phylogenetic analysis was conducted using MAFFT and IQ-TREE to compare the detected sequence with global exogenous and endogenous JSRV references.

Results: Sequencing revealed a broad viral diversity across mosquito species, including insect-specific viruses, arboviruses (West Nile, Sindbis, Bagaza, Usutu, Barkedji), and two retroviral sequences. A JSRV-related sequence was confirmed in a pool from Barkedji (2019) and clustered phylogenetically with endogenous JSRV. A nearly complete ENTV-2 genome, closely related to pathogenic Chinese strains, was recovered from the same pool. Other viruses grouped within established African lineages, supporting persistent regional circulation.

Discussion: This study presents the first report of retroviral sequences detected in mosquitoes, alongside the identification of actively circulating arboviruses and insect-specific viruses, highlighting the broader potential of mosquitoes as environmental sentinels. While mosquitoes are not biological vectors for retroviruses, their ability to capture both host-derived retroviral material and pathogenic viral genomes through bloodmeals reinforces the value of xenosurveillance for monitoring livestock-vector-environment interactions. These findings contribute to broader efforts in integrated disease surveillance and underscore the utility of combining metagenomics with molecular diagnostics to detect diverse viral signals in high-risk ecological settings.

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