Elucidating the Beta-Diversity of the Microbiome: from Global Alignment to Local Alignment

Quantitative comparison among microbiomes can link microbial beta diversity to environmental features, thus enabling prediction of ecosystem properties or dissection of host-microbiome interaction. However, to compute beta-diversity, current methods mainly employ the entire community profiles of taxa or functions, which can miss the subtle differences caused by low-abundance community members that may play crucial roles in the properties of interest. In this work, I review the distance metrics and search engines that we developed to match microbiomes at a large scale based on whole-community-level similarities, as well as their limitations in tackling the microbiome changes caused by less abundant community features. Then I propose the concept of microbiome local alignment, including an algorithm to measure microbiome similarity on specific fractions of biodiversity and an indexing strategy for rapidly fetching microbiome local-alignment matches from the data repository.

Automated summary

This study reviews the distance metrics and search engines developed for matching microbiomes on a large scale, as well as their limitations in addressing microbiome changes caused by low-abundance community members. The concept of microbiome local alignment and an algorithm for measuring microbiome similarity on specific fractions of biodiversity are proposed.