Integrating network analysis with in vivo-in situ manipulation to elucidate microbiome dynamics in Aedes albopictus.

Abstract

Host-associated microbiomes have significant impacts on host biology and physiology, but the underlying processes governing their structure and assembly are not well understood. One approach to better understanding those process is the use of computationally driven modeling tools, such as network analysis to identify patterns of cooccurring taxa across microbiomes. Those patterns can then be tested to identify taxa that are potentially more important in the overall structuring and assembly processes. Here, we used network analysis to explore cooccurrence patterns within the microbiome of Aedes albopictus. We identified important nodes in the network using the centrality metrics of node degree and betweenness. Among the nodes with the highest centrality values, more ITS ASVs were present than 16S ASVs. We then tested the network analysis predictions in vivo/in situ in A. albopictus. A series of exclusion experiments were used to manipulate environmental microbiome source pools by filtering the source pool by cell size. Our results show that including microbial eukaryotes, such as fungi, in the source pool affects microbiome assembly and structure in A. albopictus, which aligns with the network analyses predictions of this system. To our knowledge, this is the first study to integrate microbial network centrality analysis with in vivo/in situ validation using filtration-based microbial community exclusion.