Journal of Mosquito Research 2024, Vol.14, No.1, 34-48 http://emtoscipublisher.com/index.php/jmr 41 Ecological modeling is an advanced method to analyze the effect of microorganisms on mosquito behavior. By developing mathematical models that take into account the interactions between microbes, mosquitoes, and the environment, it is possible to simulate changes in mosquito behavior under different conditions. This approach helps to gain a deeper understanding of the complex relationship between microbes and mosquito behavior and provides a scientific basis for mosquito control in ecosystems. Methods and techniques for studying microbial behavior towards mosquitoes involve a variety of fields such as microbial identification, behavioral experimental design, and data analysis (Raji and Potter, 2021). A deeper and more comprehensive understanding of the interactions between microbes and mosquito behavior can be achieved through the rational selection and application of these methods. Future research should continue to introduce new technological tools and incorporate interdisciplinary approaches to promote the continuous advancement of microbial research on mosquito behavior. 6 Case Analysis 6.1 Case one: the impact of gut microbiota on mosquito host seeking behavior Mosquitoes, as carriers of pathogens, pose a huge threat to human health. In recent years, scientists have found that the gut microbiota of mosquitoes may have a significant impact on their behavior in finding and selecting hosts. This discovery provides new possibilities for controlling disease transmission by regulating the microbial community of mosquitoes. Wang's research team discovered in 2011 that the gut microbiome of mosquitoes affects their adaptability and immunity (Figure 3), with different microbial communities observed at different developmental stages and influenced by diet, such as blood meal (Wang et al., 2011). This graph shows a sparse curve, with the x-axis representing the "Number of Reads Samples" and the y-axis representing the "Number of OTUs at 5% Distance". OTUs represent Operational Taxonomic Units, and in microbial ecology, OTUs are commonly used to refer to biological taxonomic units (such as species or populations). There are significant differences in the number of OTUs among different samples. The number of OTUs in habitat samples is the highest, indicating the highest microbial diversity. The number of OTUs in adult samples is generally lower than that in pupa samples, followed by larvae. The impact of food sources on diversity: Adult insect samples fed on sugar (1 day, 3 days, and 7 days) showed different OTUs, indicating that food sources have a significant impact on microbial diversity. As the adult age increases, the number of OTUs gradually increases. The impact of blood sucking on diversity: The number of OTUs in adults who have just consumed blood for 2 days is lower than that in sugar group adults, but as the time of blood sucking increases, the number of OTUs in adult samples of PBM at 4 and 7 days gradually increases. This may be related to physiological changes or microbial colonization after blood sucking. This sparse curve graph indicates significant differences in microbial diversity among samples from different developmental stages and food sources, particularly in habitat and developmental stages. Understanding these differences is of great value for in-depth research on the ecological and biological significance of insect microbial communities. Frankel Bricker et al. found in 2019 that a common gut fungus in mosquito larvae significantly affects microbial populations and host microbial interactions (Figure 4), affecting behavioral characteristics such as host seeking (Frankel Bricker et al., 2019). The figure compares the SCML Calibrated Counts of samples at different developmental stages under two different treatments. The horizontal axis represents the developmental stage, including larvae and adults, and the vertical axis represents the SCML calibrated counts. The legend lists two types of treatments: fungal treatment (Fungal) and non-fungal treatment (Non-Fungal). The red column represents fungal treatment, while the blue column represents non-fungal treatment. The SCML count of the fungal treatment group was slightly lower than that of the non-fungal treatment group, but the difference between the two was not significant (about 10000 counts). The overlapping error lines between the two groups indicate that during the larval stage, fungal and non-fungal treatments have a relatively small impact on SCML counting. Compared with the larval stage, the SCML count in the adult stage significantly decreased, indicating a lower number of microbial
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