Long-term trends in housefly (Musca domestica L.) insecticide resistance in China.

Controlling housefly populations relies on the use of insecticides, which inevitably leads to the development of resistance. A better and more comprehensive understanding of the spatial and temporal distribution of resistance could guide the control of houseflies. However, most studies on housefly resistance in China are scattered and poorly coordinated. We collected resistance data from houseflies in the published literature and from the vector biomonitoring system of the Chinese Center for Disease Control and Prevention. A 5- or 10-year resolution was used to study the temporal dynamics of resistance to five commonly used insecticides: deltamethrin, permethrin, beta-cypermethrin, dichlorvos, and propoxur. ArcGIS was used to visualize their spatial distributions. The correlation between year and resistance coefficient was determined using SPSS 26.0 and RStudio to explore the changes in resistance over the years. A total of 2128 data were included in this study, ranging from 1982 to 2022, based on which we found significant increases in resistance over the past forty years for the five studied insecticides. Among them, pyrethroids had the most strikingly elevated resistance level and were mainly distributed in the northern and southeastern coastal areas. Dichlorvos and propoxur had intermediate increases in resistance, and most of these increases were identified in North China and the Yangtze River. Housefly resistance to commonly used insecticides in China is increasing and spatially heterogeneous. This finding also highlights the necessity of continuous routine surveillance of housefly resistance, which could guide future housefly control operations and slow the development of resistance.

Transcriptome analysis of Kunming mice responses to the bite of Xenopsylla cheopis.

BACKGROUND: Flea bites could trigger a series of complex molecular responses in the host. However, our understanding of the responses at the molecular level is still relatively limited. This study quantifies the changes in gene expression in mice after flea bites by RNA sequencing (RNA-seq) from their spleens, revealing the potential biological effects of host response to flea bites. METHODS: RNA-seq was used for transcriptome analysis to screen for differentially expressed genes (DEGs) between the control mice group and the flea bite mice group. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed on DEGs. Protein-protein interaction (PPI) network analysis on DEGs related to immune processes was performed. Finally, we randomly selected several genes from the screened DEGs to validate the results from the transcriptome data by real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR). RESULTS: A total of 521 DEGs were identified, including 277 upregulated and 244 downregulated. There were 258 GO terms significantly enriched by upregulated DEGs and 419 GO terms significantly enriched by downregulated DEGs. Among the upregulated DEGs, 22 GO terms were associated with immune cells (e.g., B cells and T cells) and immune regulatory processes, while among the downregulated DEGs, 58 GO terms were associated with immune cells and immune regulatory processes. Through PPI analysis, we found that CD40 molecules with significantly downregulated expression levels after flea bites may play an important role in host immune regulation. Through KEGG pathway enrichment analysis, a total of 26 significantly enriched KEGG pathways were identified. The RT-qPCR analysis results indicated that the transcriptome sequencing results were reliable. CONCLUSIONS: Through in-depth analysis of transcriptome changes in mice caused by flea bites, we revealed that flea bites could stimulate a series of biological and immunological responses in mice. These findings not only provided a deeper understanding of the impact of flea bites on the host but also provided a basis for further research on the interaction between ectoparasites and the host. We believe that digging deeper into the significance of these transcriptome changes will help reveal more about the adaptive response of the host to ectoparasites.