Periodic Reporting for period 1 - SYMMUNITY (SYMbiosis, Microbiota and immUNITY)
Reporting period: 2019-04-01 to 2021-03-31
Symbiosis and sociality define the evolutionary success of life, but the large-scale synergy between hosts and microbiotas is poorly understood. The present project aims to develop a set of phylosymbiotic approaches to begin to understand how and why hosts have evolved in association with microbiota that shape host ecologies. In principal, microbiota can either evolve phylogenetically with the host diversification or evolve convergently with the host ecological adaptations. Social insects are interesting targets for phylosymbiotic analysis because microbiomes combine functions of nutrient supplementation, individual immunity and colony-level immunity. This applies most explicitly to the ants, which have huge species diversity (>14,000 species), massive ecological footprints (dominant in biomass in most terrestrial ecosystems), and high diversity in life styles (e.g. predatory, omnivory, herbivory). The overall goal of the project is to assemble and analyze metagenomic data for at least 50 ant species to understand 1) The evolutionary and functional dynamics of homologous or analogous microbiota across the family Formicidae (ants), and 2) the functional adaptations that have shaped immune defenses across the ant subfamilies and genera.
I have successfully characterized microbiomes from 60 ant species (50 different genera across 10 out of 12 total existing subfamilies) using 16S amplicon sequencing. The majority of microbiotas does not evolve phylogenetically with the their host diversification. There are two clades of ant species, representing four different genera (Camponotus, Polyrhachis, Myrmecina, Acanthomyrmex), that show significant signs of phylosymbiosis. Preliminary results further suggest that the host symbiotic bacteria belonging to Enterobacteriaceae is likely to be the candidate partners of these phylosymbiotic relationships. Additionally, there is an overall trend that diet specialization correlates with microbiota diversity, albeit insignificant with the present data. In general, the predatory strategies appear to maintain richer microbiota diversity than other diet strategies.
I have successfully characterized microbiomes from 60 ant species (50 different genera across 10 out of 12 total existing subfamilies) using 16S amplicon sequencing. The majority of microbiotas does not evolve phylogenetically with the their host diversification. There are two clades of ant species, representing four different genera (Camponotus, Polyrhachis, Myrmecina, Acanthomyrmex), that show significant signs of phylosymbiosis. Preliminary results further suggest that the host symbiotic bacteria belonging to Enterobacteriaceae is likely to be the candidate partners of these phylosymbiotic relationships. Additionally, there is an overall trend that diet specialization correlates with microbiota diversity, albeit insignificant with the present data. In general, the predatory strategies appear to maintain richer microbiota diversity than other diet strategies.
I have produced 16S rRNA libraries (V4 region) for three colonies per ant species wherever possible, and applied the state-of-the-art Amplicon Sequence Variants (ASVs, which represent sequence variants with one single nucleotide difference) principal to perform phylotype diversity analyses. I have built the core bioinformatic pipelines consisting of using QIIME2, R and shell scripts for metagenomic/amplicon sequencing data processing and analyses. All the related pipelines have been deposited in a GitHub repository (github.com/dinhe878/GAGA-Microbiome-Ampicon-Seq). Together with collaborators we have also built custom bioinformatic pipelines to process ant genomic data from the associated GAGA project (https://db.cngb.org/antbase/microbio/#en_sample). All the related pipelines have been deposited in another GitHub repository (github.com/dinhe878/GAGA-Metagenome-LGT).
Using the combination of hierarchical clustering (microbiome) and phylogenetics (ant phylogenome), I tested whether and where the phylosymbiotic signals (examining whether host phylogeny is congruent with microbiota composition similarity) could potentially exist across the Ant Tree of Life with amplicon sequencing data obtained. My analyses suggested that there are two ant phylogenetic clade where phylosymbiotic signal is significant (between Myrmecina and Acanthomyrmex; Camponotus and Polyrhachis). These signals indicate that these microbiota evolve phylogenetically with their host lineages regardless other biotic and abiotic factors of hosts.
Using a wide range of diversity indices, I investigated the potential correlations between microbiota compositions and hosts. Generally the results show very complex patterns with no obvious correlations detected between microbiotas and hosts’ traits, except the host diet specialization somewhat correlates with their microbiota variation. More specifically, predatory strategies appear leading to more diverse composition of the microbiota, i.e. higher microbiota alpha diversity.
Using the combination of hierarchical clustering (microbiome) and phylogenetics (ant phylogenome), I tested whether and where the phylosymbiotic signals (examining whether host phylogeny is congruent with microbiota composition similarity) could potentially exist across the Ant Tree of Life with amplicon sequencing data obtained. My analyses suggested that there are two ant phylogenetic clade where phylosymbiotic signal is significant (between Myrmecina and Acanthomyrmex; Camponotus and Polyrhachis). These signals indicate that these microbiota evolve phylogenetically with their host lineages regardless other biotic and abiotic factors of hosts.
Using a wide range of diversity indices, I investigated the potential correlations between microbiota compositions and hosts. Generally the results show very complex patterns with no obvious correlations detected between microbiotas and hosts’ traits, except the host diet specialization somewhat correlates with their microbiota variation. More specifically, predatory strategies appear leading to more diverse composition of the microbiota, i.e. higher microbiota alpha diversity.
The present project results showed that symbiotic microbes may be more likely to develop phylosymbiotic relationships in ants. This should, in principal, be applicable to all living organisms which all live symbiotically with other organisms one way or the other. However, the host-microbiota association is far more complex and the present dataset is likely still insufficient to capture the correlations that hide behind the complex interplays between ecological factors and host traits, which presents a major challenge for obtaining comprehensive collections of ecological data of species of interests. The current outcome of the project has significant implications that it is necessary to build a quality foundation of ecological dataset that will enable effective analyses to disentangle more meaningful host-microbiota relationships. These relationships hold potential keys towards our understanding of health and well-being of the hosts.