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Detection and monitoring of insect traces in bioaerosols.
Pumkaeo, Panyapon; Takahashi, Junko; Iwahashi, Hitoshi.
  • Pumkaeo P; Division of Science of Biological Resources, United Graduate School of Agricultural Science, Gifu University, Gifu, 1-1 Yanagido, Japan.
  • Takahashi J; National Institute of Advanced Industrial Science and Technology (AIST), Health and Medical Research Institute, Tsukuba, Ibaraki, Japan.
  • Iwahashi H; Department of Applied Life Science, Faculty of Applied Biological Sciences, Gifu University, Gifu, 1-1 Yanagido, Japan.
PeerJ ; 9: e10862, 2021.
Article en En | MEDLINE | ID: mdl-33614291
ABSTRACT
Studies on bioaerosols have primarily focused on their chemical and biological compositions and their impact on public health and the ecosystem. However, most bioaerosol studies have only focused on viruses, bacteria, fungi, and pollen. To assess the diversity and composition of airborne insect material in particulate matter (PM) for the first time, we attempted to detect DNA traces of insect origin in dust samples collected over a two-year period. These samples were systematically collected at one-month intervals and categorized into two groups, PM2.5 and PM10, based on the aerodynamic diameter of the aerosol particles. Cytochrome-c oxidase I (COI) was the barcoding region used to identify the origins of the extracted DNA. The airborne insect community in these samples was analyzed using the Illumina MiSeq platform. The most abundant insect sequences belonged to the order Hemiptera (true bugs), whereas order Diptera were also detected in both PM2.5 and PM10 samples. Additionally, we inferred the presence of particulates of insect origin, such as brochosomes and integument particles, using scanning electron microscopy (SEM). This provided additional confirmation of the molecular results. In this study, we demonstrated the benefits of detection and monitoring of insect information in bioaerosols for understanding the source and composition. Our results suggest that the PM2.5 and PM10 groups are rich in insect diversity. Lastly, the development of databases can improve the identification accuracy of the analytical results.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Año: 2021 Tipo del documento: Article