Barcoding of Italian mosquitoes (BITMO): generation and validation of DNA barcoding reference libraries for native and alien species of Culicidae

Background: Mosquitoes (Culicidae), as disease vectors, represent a risk for human health worldwide. Repeated introductions of alien mosquito species and the spread of invasive species have been recorded in different countries. Traditionally, identification of mosquitoes relies on morphological observation. However, morphology-based identification is associated with a number of potential disadvantages, such as the high level of specialisation of the operator and its limited applicability to damaged samples. In these cases, species identification is achieved through molecular methods based on DNA amplification. Molecular-based taxonomy has also enabled the development of techniques for the study of environmental DNA (eDNA). Previous studies indicated the 16S mitochondrial ribosomal RNA (rRNA) gene as a promising target for this application; however, 16S rRNA sequences are available for only a limited number of mosquito species. In addition, although primers for the 16S rRNA gene were designed years ago, they are based on limited numbers of mosquito sequences. Thus, the aims of this study were to: (i) design pan-mosquito 16S rRNA gene primers; (ii) using these primers, generate a 16S rRNA gene mosquito reference library (with a focus on mosquitoes present in Italy); and (iii) compare the discriminatory power of the 16S rRNA gene with two widely used molecular markers, cytochrome c oxidase subunit 1 mitochondrial gene (COI) and internal transcribed spacer 2 (ITS2).

Methods: A total of six mosquito genera (28 mosquito species) were included in this study: Aedes (n = 16 species), Anopheles (5 species), Coquillettidia (1 species), Culex (3 species), Culiseta (2 species) and Uranotaenia (1 species). DNA was extracted from the whole mosquito body, and more than one specimen for each species was included in the analysis. Sanger sequencing was used to generate DNA sequences that were then analysed through the Barcode of Life Data Systems (BOLD). Phylogenetic analyses were also performed.

Results: Novel 16S rDNA gene, COI and ITS2 sequences were generated. The 16S rRNA gene was shown to possess sufficient informativeness for the identification of mosquito species, with a discriminatory power equivalent to that of COI.

Conclusions: This study contributes to the generation of DNA barcode libraries, focussed on Italian mosquitoes, with a significant increase in the number of 16S rRNA gene sequences. We hope that these novel sequences will provide a resource for studies on the biodiversity, monitoring and metabarcoding of mosquitoes, including eDNA-based approaches.