A bioinformatics approach to identifying Wolbachia infections in arthropods.

Jane Pascar,Christopher H Chandler

doi:10.7717/peerj.5486

Jane Pascar, Christopher H Chandler

Open Access

https://doi.org/10.7717/peerj.5486

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Abstract

Wolbachia is the most widespread endosymbiont, infecting >20% of arthropod species, and capable of drastically manipulating the host’s reproductive mechanisms. Conventionally, diagnosis has relied on PCR amplification; however, PCR is not always a reliable diagnostic technique due to primer specificity, strain diversity, degree of infection and/or tissue sampled. Here, we look for evidence of Wolbachia infection across a wide array of arthropod species using a bioinformatic approach to detect the Wolbachia genes ftsZ, wsp, and the groE operon in next-generation sequencing samples available through the NCBI Sequence Read Archive. For samples showing signs of infection, we attempted to assemble entire Wolbachia genomes, and in order to better understand the relationships between hosts and symbionts, phylogenies were constructed using the assembled gene sequences. Out of the 34 species with positively identified infections, eight species of arthropod had not previously been recorded to harbor Wolbachia infection. All putative infections cluster with known representative strains belonging to supergroup A or B, which are known to only infect arthropods. This study presents an efficient bioinformatic approach for post-sequencing diagnosis and analysis of Wolbachia infection in arthropods.

Highlights

Symbiotic relationships are ubiquitous in nature and can vary between parasitic, commensal, and mutualistic
All samples that tested positive were from samples that are in the class Insecta and representative of five orders: Coleoptera, Diptera, Hymenoptera, Hemiptera, and Lepidoptera
Wolbachia is a well-known endosymbiont of many arthropod species and while standard Wolbachia diagnostic techniques utilize various Wolbachia primers to confirm infection via polymerase chain reaction (PCR) (Simões et al, 2011) there are trade-offs that limit large scale surveys

Summary

Introduction

Symbiotic relationships are ubiquitous in nature and can vary between parasitic, commensal, and mutualistic. Wolbachia was first described in Culex pipiens (Hertig, 1936) and has since been identified in various clades of arthropods including Chelicerata (Werren & Windsor, 2000), Myriapoda (Mock et al, 2016), Crustacea (Bouchon, Rigaud & Juchault, 1998; Cordaux, Michel-Salzat & Bouchon, 2001; Cordaux et al, 2012), and Hexapoda (Werren & Windsor, 2000; Clark et al, 2001; Augustinos et al, 2011; Bing et al, 2014). Conservative estimates suggest that the frequency of Wolbachia infection in arthropods is at least 20% (Werren, 1997b; Werren & Windsor, 2000), while one study suggests a prevalence as high as 76% of arthropod species (Jeyaprakash & Hoy, 2000). How to cite this article Pascar and Chandler (2018), A bioinformatics approach to identifying Wolbachia infections in arthropods.

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