Challenges and opportunities of strain diversity in gut microbiome research

Abstract

Just because two things are related does not mean they are the same. In analyzing microbiome data, we are often limited to species-level analyses, and even with the ability to resolve strains, we lack comprehensive databases and understanding of the importance of strain-level variation outside of a limited number of model organisms. The bacterial genome is highly plastic with gene gain and loss occurring at rates comparable or higher than de novo mutations. As such, the conserved portion of the genome is often a fraction of the pangenome which gives rise to significant phenotypic variation, particularly in traits which are important in host microbe interactions. In this review, we discuss the mechanisms that give rise to strain variation and methods that can be used to study it. We identify that while strain diversity can act as a major barrier in interpreting and generalizing microbiome data, it can also be a powerful tool for mechanistic research. We then highlight recent examples demonstrating the importance of strain variation in colonization, virulence, and xenobiotic metabolism. Moving past taxonomy and the species concept will be crucial for future mechanistic research to understand microbiome structure and function.

Keywords: comparative genomics; gut microbiome; metagenomics; species concept; strain diversity.

Figure 1

(A) An alignment of individual Eggerthella lenta strain genomes demonstrates significant variation in presence/absence of large genetic islands within the species as a function of strain. Each track represents the genome of an individual strain and with shared regions indicated in black. (B) Pangenome size increases linearly with the number of genomes sequenced per species in gut microbes. Each point represents a species with the blue line representing a linear regression ±SE. Data for (A,B) reproduced from Bisanz et al. (2020) and Almeida et al. (2021), respectively.

Figure 2

Schematic representation of comparative genomics analysis to match genotype to phenotype. Phenotype A results from the variable presence of a gene (red), phenotype B from a SNP (blue), phenotype C from a structural variant (orange), and phenotype D from a combination of variants: the simultaneous presence of structural variation (orange) and a SNP (green).