<p>Invasive species represent a critical threat to ecosystems and ecological communities, causing changes through overwhelming predation as well as competing with native species for resources. Understanding the mechanisms behind invasive success is essential for understanding why they invade and the consequences of their invasions. Furthermore, invasive species, like all macroscopic organisms, harbour symbiotic and pathogenic microbes that constitute their microbiomes, which could explain invasive success. The complex ecological interaction networks within the microbiome can have a positive or negative impact on host abundance and dominance. These interactions may be significant for invasive species, where microbial influences acting on an exotic host can potentially drive the ecological success of an invasive population to the detriment of recipient communities. This thesis explores the microbiota of one of the most globally invasive species, the common wasp Vespula vulgaris, with the overall aim to investigate and characterise the microbiome of V. vulgaris, using metagenomics, bioinformatics and molecular techniques. The initial comparative microbiota study focused on three distinct life stages (larvae, worker and queen), from two ranges. This analysis revealed a core bacteriome community present in V. vulgaris. There was evidence of higher microbial diversity in wasp larvae compared with workers and queens. The Queen (gyne) microbiome revealed a more specific microbiome with absences of certain microbiota found in larvae and workers from the same nest, indicating a more distinctive microbiome. Interestingly, analysis of life stages between ranges showed significant dissimilarity in microbiomes, with microbiota loses, and acquisitions in the introduced New Zealand range. Using the same techniques, the microbiota of V. vulgaris and four hymenopteran hosts (Apis mellifera, Bombus terrestris, Vespula germanica and Linepithema humile), were comparatively analysed. The analysis investigated both shared microbiota and host specific microbiota. This analysis indicated the polyphagous V. vulgaris as having a diverse microbiome varying between nests and sites, indicating less specific microbiota in comparison to other hymenopteran hosts in this study. Vespid wasp colonies are known to occasionally crash in the presence of diseases; however, there is a lack of reliable evidence indicating pathogenic micro-organisms play an essential role in wasp colony dynamics. Incorporating knowledge gained in previous analyses, the next aim was to investigate V. vulgaris nests symptomatic of an infectious agent to discover the cause of pathology. Through molecular techniques, such as Illumina RNA-Seq, PCR and Sanger sequencing, the potential cause of infection and decline of diseased nests was examined. The metatranscriptomic comparison of diseased and healthy larvae highlighted five putative infectious agents. The bacteria Moellerella wisconsensis, Moku virus, Kashmir Bee Virus, Aspergillus and the microsporidian Vavraia culicis floridensis found in infected larvae, potentially causing pathology in the host. The first known instance of Moku virus, and potentially V. culicis floridensis and M. wisconsensis was documented as potential pathogens of V. vulgaris present in New Zealand. To test for potential virulence of these putative infectious agents, an infection study was carried out. Vespula vulgaris nests and larvae were orally infected in the lab using homogenised infected larvae. Subsequently, test and control larvae were sampled to conduct and quantify a time series analysis of infection using RT-qPCR using designed primers. This dissertation provided the first insight into the microbiome of V. vulgaris in the native and introduced range providing a baseline for further research. This analysis and the subsequent microbiota identified may play a role in wasp population dynamics, giving a better understanding of the observed thriving V. vulgaris population dynamics in New Zealand.</p>
A novel interference behaviour: invasive wasps remove ants from resources and drop them from a height