The mosquito species Aedes aegypti is one of the main vectors of arboviruses, including dengue, Zika and chikungunya. Considering the deficiency or absence of vaccines to prevent these diseases, vector control remains an important strategy. The use of plant natural product-based insecticides constitutes an alternative to chemical insecticides as they are degraded more easily and are less harmful to the environment, not to mention their lower toxicity to non-target insects. This review details plant species and their secondary metabolites that have demonstrated insecticidal properties (ovicidal, larvicidal, pupicidal, adulticidal, repellent and ovipositional effects) against the mosquito, together with their mechanisms of action. In particular, essential oils and some of their chemical constituents such as terpenoids and phenylpropanoids offer distinct advantages. Thiophenes, amides and alkaloids also possess high larvicidal and adulticidal activities, adding to the wealth of plant natural products with potential in vector control applications.

Metabolomics is a powerful tool in the analysis and identification of metabolites responsible for biological properties. Regarding natural product chemistry, it constitutes a potential strategy to streamline the classic and laborious process of isolating natural products, which often involves the re-isolation and identification of known compounds. In this contribution, we establish a mass spectrometry-based metabolomics strategy to discover compounds with larvicidal activity against Aedes aegypti. We analyse the Brazilian plant Annona crassiflora using different platforms to annotate the active compounds in different extracts/fractions of various plant parts. The MetaboAnalyst and GNPS platforms, which consider LC-MS and LC-MS/MS data, respectively, were chosen to identify compounds that differentiate active and inactive samples. Bio-guided isolation was subsequently performed to confirm compound activity. Results proved the capacity of metabolomics to predict metabolite differences between active and inactive samples using LC-MS and LC-MS/MS data. Moreover, we discuss the limitations, possibilities, and strategies to have a broad view of vast data.

Dengue is a neglected disease, present mainly in tropical countries, with more than 5.2 million cases reported in 2019. Vector control remains the most effective protective measure against dengue and other arboviruses. Synthetic insecticides based on organophosphates, pyrethroids, carbamates, neonicotinoids and oxadiazines are unattractive due to their high degree of toxicity to humans, animals and the environment. Conversely, natural-product-based larvicides/insecticides, such as essential oils, present high efficiency, low environmental toxicity and can be easily scaled up for industrial processes. However, essential oils are highly complex and require modern analytical and computational approaches to streamline the identification of bioactive substances. This study combined the GC-MS spectral similarity network approach with larvicidal assays as a new strategy for the discovery of potential bioactive substances in complex biological samples, enabling the systematic and simultaneous annotation of substances in 20 essential oils through LC50 larvicidal assays. This strategy allowed rapid intuitive discovery of distribution patterns between families and metabolic classes in clusters, and the prediction of larvicidal properties of acyclic monoterpene derivatives, including citral, neral, citronellal and citronellol, and their acetate forms (LC50 < 50 µg/mL).