Gut microbiome composition, not alpha diversity, is associated with survival in a natural vertebrate population

Abstract

Background: The vertebrate gut microbiome (GM) can vary substantially across individuals within the same natural population. Although there is evidence linking the GM to health in captive animals, very little is known about the consequences of GM variation for host fitness in the wild. Here, we explore the relationship between faecal microbiome diversity, body condition, and survival using data from the long-term study of a discrete natural population of the Seychelles warbler (Acrocephalus sechellensis) on Cousin Island. To our knowledge, this is the first time that GM differences associated with survival have been fully characterised for a natural vertebrate species, across multiple age groups and breeding seasons.

Results: We identified substantial variation in GM community structure among sampled individuals, which was partially explained by breeding season (5% of the variance), and host age class (up to 1% of the variance). We also identified significant differences in GM community membership between adult birds that survived, versus those that had died by the following breeding season. Individuals that died carried increased abundances of taxa that are known to be opportunistic pathogens, including several ASVs in the genus Mycobacterium. However, there was no association between GM alpha diversity (the diversity of bacterial taxa within a sample) and survival to the next breeding season, or with individual body condition. Additionally, we found no association between GM community membership and individual body condition.

Conclusions: These results demonstrate that components of the vertebrate GM can be associated with host fitness in the wild. However, further research is needed to establish whether changes in bacterial abundance contribute to, or are only correlated with, differential survival; this will add to our understanding of the importance of the GM in the evolution of host species living in natural populations.

Keywords: Acrocephalus sechellensis; Fitness; Gut microbiome; Life history; Microbial diversity.

Fig. 1

The relative abundance (%) of bacterial phyla in Seychelles warbler gut microbiome samples. Each vertical bar represents a separate faecal sample. Samples are categorised by age class (nestling, fledgling, sub-adult, or adult) and are ordered according to the abundance of Proteobacteria. N = 470 samples from 370 individuals in total: nestlings = 12, fledglings = 65, old fledglings = 45, sub-adults = 107 and adults = 241 samples, respectively. Phyla with a median relative abundance of less than 1% are collapsed into the category “Other”

Fig. 2

Variation in gut microbiome composition across sampling periods in the Seychelles warbler. Principal Components Analysis (PCA) of Euclidean distances calculated using A CLR-transformed ASV abundances or B PhILR-transformed abundances. Each point represents a unique gut microbiome sample (N = 450). Samples were taken from 309 individuals. Principal components one and two explained 6.91% and 4.14% of the variation in gut microbiome structure in the CLR analysis, and 20.58% and 10.44% in the PhILR analysis, respectively

Fig. 3

Principal components analysis (PCA) of Euclidean distances between the gut microbiomes of adult Seychelles warblers that survived (blue) versus those that had died (yellow) by the next breeding season. Each point represents a sample taken from a different individual. Euclidean distances are based on CLR-transformed abundances of ASVs. Principal components one and two explained 7.51% and 4.01% of the variation in GM community structure, respectively. N = 148 samples/individuals were included in the analysis (127 individuals survived, 21 individuals died)

Fig. 4

Differentially abundant Amplicon Sequencing Variants (ASVs) in the gut microbiome of adult Seychelles warblers that survived versus those that died by the next breeding season. N = 148 adult individuals were included in the analysis (127 individuals survived, 21 individuals died). Points represent the log fold change (effect size) of individual bacterial ASVs—only those with significant effect sizes (P_adj < 0.05) are shown. A positive log fold change indicates that an ASV is more abundant in individuals that survived (right), and a negative log fold change indicates a higher abundance in individuals that died by the next season (left). Bars represent 95% confidence intervals derived from the ANCOM-BC model. ASVs are classified by bacterial order on the y-axis and are coloured by phylum. Results of differential abundance tests and ASV taxonomies are presented in full in Additional file 1: Table S5