DNA-barcoding of non-biting midge larvae (chironomidae) in heavy metal polluted ponds

Chironomids, or non-biting midges (Chironomidae), belong to the order of true flies (Diptera), and are frequently used as bio-indicators of water quality, where higher diversity levels reflect less polluted habitats. However, the identification of chironomids (as well as other freshwater invertebrates) is done using morphological characters, a process that can be difficult and time- consuming. With the use of the taxonomic identification tool DNA barcoding, it is possible to identify the specimens to genus or species level without the use of morphological identifications which often difficult and time-consuming. In this study, DNA barcoding using the mitochondrial (mt) DNA the cytochrome oxidase 1 gene (CO1) was used to identify chironomid larvae from seven different ponds in Wales in relationship to sediment and water environmental characteristics. Chironomid larvae, sediment and water samples were taken from five ponds in Parys Mountain, an old copper mine in northern Wales, and from two ponds in Cwm-Idwal in Snowdonia Natural Park. Because of the history of the mining site, four ponds from Parys Mountain were suspected to be polluted. Environmental conditions (pH, dissolved oxygen, conductivity, salinity and temperature), magnetic susceptibility (MS) and isothermal remanent magnetisation (IRM), and presence of heavy metals were analysed to characterize the sites and to understand the effect on chironomid larvae diversity and community structure. Chironomid larvae were DNA-barcoded and the genetic and community structure for each pond were calculated and analysed in relationship with environmental conditions, magnetic characteristics and presence of heavy metals. A total of 15 genera of chironomids were found among the seven ponds. The results indicated a significant difference between suspected non-polluted ponds (WAPM1,WACI1,WACI2) and most of the suspected polluted ponds (WAPM2,WAPM3,WAPM4,WAPM5); MS and IRM analyses showed no significant differences among the seven ponds (p=0.206 and p=0.653, respectively). Results of the analysis of both the sediments and water samples showed a higher concentration of heavy metals in the suspected polluted ponds than in the suspected non-polluted ones. However, a significant difference was found in the community structure of chironomid larvae among the ponds by using ANOSIM analysis (p= 0.001). The suspected polluted ponds had in lower diversity compared to the suspected non-polluted ones. In conclusion, there seems to be a correlation between the chironomid larvae diversity and community structure with the environmental composition of the ponds. This study represents the first DNA barcoding study of chironomids in polluted and non-polluted ponds in Wales and show that this technique is an efficient way for estimating insect diversity and community structure in relation with water quality biomonitoring.