Cryopreservation of mosquito microbiota for use in microcosm experiments

Abstract

Mosquitoes develop in a wide range of aquatic habitats containing highly diverse and variable bacterial communities that shape both larval and adult traits, including the capacity of adult females of some mosquito species to vector disease-causing organisms to humans. However, while most mosquito studies control for host genotype and environmental conditions, the impact of microbiota variation on phenotypic outcomes of mosquitoes is often unaccounted for. The inability to conduct reproducible intra- and inter-laboratory studies of mosquito-microbiota interactions has also greatly limited our ability to identify microbial targets for mosquito-borne disease control. Here, we developed an approach to isolate and cryopreserve microbial communities derived from mosquito larval rearing environments in the lab and field. We then validated the use of our approach to generate experimental microcosms colonized by standardized lab- and field-derived microbial communities. Our results overall reveal minimal effects of cryopreservation on the recovery of bacteria when directly compared with isolation from non-cryopreserved fresh material. Our results also reveal improved reproducibility of microbial communities in replicate microcosms generated using cryopreserved stocks over fresh material. Altogether, these results provide a critical next step toward the standardization of mosquito studies to include larval rearing environments colonized by defined microbial communities. They also lay the foundation for long-term studies of mosquito-microbe interactions and the identification and manipulation of taxa with potential to reduce mosquito vectorial capacity.

A cryopreservation method to recover laboratory- and field-derived bacterial communities from mosquito larval habitats

“…The same tests were then used to compare patterns of alpha and beta diversity among replicates of the same sample groups. Input files for the QIIME pipeline as well as raw data files and R code for statistical analyses have been deposited in the Dryad Digital Repository [https://doi.org/10.5061/dryad.dfn2z354z] [41].…”