Hurdles in the evolutionary epidemiology of Angiostrongylus cantonensis: Pseudogenes, incongruence between taxonomy and DNA sequence variants, and cryptic lineages

Abstract

Angiostrongylus cantonensis, the rat lungworm, is a zoonotic pathogen that is one of the leading causes of eosinophilic meningitis worldwide. This parasite is regarded as an emerging pathogen with a global range expansion out of southeastern Asia post‐WWII. To date, molecular systematic/phylogeographic studies on A. cantonensis have mainly used two mitochondrial (mtDNA) markers, cytochrome c oxidase 1 ( CO1) and cytochrome b ( CYTB), where the focus has largely been descriptive in terms of reporting local patterns of haplotype variants. In order to look for more global evolutionary patterns, we herein provide a collective phylogenetic assessment using the six available whole mtDNA genome samples that have been tagged as A. cantonensis, A. malaysiensis, or A. mackerrasae along with all other GenBank CO1 and CYTB partial sequences that carry these species identifiers. The results reveal three important complications that researchers will need to be aware of, or will need to resolve, prior to conducting future molecular evolutionary studies on A. cantonensis. These three problems are (i) incongruence between taxonomic identifications and mtDNA variants (haplotypes or whole mtDNA genome samples), (ii) the presence of a CYTB mtDNA pseudogene, and (iii) the need to verify A. mackerrasae as a species along with other possible cryptic lineages, of which there is suggestive evidence (i.e., A. cantonensis could be a species complex). We provided a discussion of how these complications are hurdles to our understanding of the global epidemiology of angiostrongyliasis. We call for future studies to be more explicit in morphological traits used for identifications (e.g., provide measurements). Moreover, it will be necessary to repeat prior morphological and life‐history studies while simultaneously using sequence data in order to assess possible associations between critical epidemiological data (e.g., biogeography, virulence/pathology, host species use) and specific lineages.