Microalgae diversity in Aedes aegypti larvae guts and breeding sites in Nakhon Si Thammarat, Thailand revealed by light microscopy and metabarcoding

Authors: Promprao, Jeerisuda Country: Thailand DOI: 10.3897/mbmg.9.152948 Published: Jan. 1, 2025 Source: Metabarcoding and Metagenomics OpenAlex: View in OpenAlex

Collection: Pensoft Publishers

Keywords: Aedes aegypti · Topics: Algal biology and biofuel production, Insect and Arachnid Ecology and Behavior, Microbial Community Ecology and Physiology

Aedes aegypti poses a significant threat by transmitting diseases like dengue, chikungunya and Zika, leading to high morbidity and mortality worldwide. In recent years, the role of microalgae in mosquito larvicidal activity has gained attention due to their role as a key mosquito nutritional resource. Understanding microalgal communities in water from breeding sites and Ae. aegypti larval guts might be beneficial for implementing mosquito control strategies. The purpose of this work was to investigate the diversity of microalgae in the guts and breeding sites of Ae. aegypti larvae in Nakhon Si Thammarat, Thailand, using light microscopy and metabarcoding. Results showed a total of 27 algal genera from this study. Ten genera were identified using light microscopy and an additional 21 genera were identified through 23S metabarcoding. Four genera, Tetradesmus, Nannochloropsis, Monoraphidium and Leptolyngbya, were detected by both approaches. Two genera, Tetradesmus and Leptolyngbya, were present in all guts and water samples. Spearman’s correlation analysis, alpha diversity and beta diversity demonstrated a high degree of compositional similarity between gut samples and water samples collected from breeding sites. The results indicated that Ae. aegypti larvae could consume nearly all the microalgae in their breeding habitat. Information provided in this study would help choose microalgae that could potentially be a biocontrol agent for further development of eco-friendly products for the future management of mosquito larvae.

Time period:

View raw JSON from API

Found an error? Please report to login@optimap.science.