Identifying and Predicting Novelty in Microbiome Studies.

Xiaoquan Su,Zheng Sun,Gongchao Jing,Shi Huang,Jian Xu,Rob Knight,Antonio Gonzalez,Zengbin Wang,Honglei Wang,Jose Navas,Daniel Mcdonald,Margaret J Mcfall-Ngai

doi:10.1128/mbio.02099-18

Abstract

With the expansion of microbiome sequencing globally, a key challenge is to relate new microbiome samples to the existing space of microbiome samples. Here, we present Microbiome Search Engine (MSE), which enables the rapid search of query microbiome samples against a large, well-curated reference microbiome database organized by taxonomic similarity at the whole-microbiome level. Tracking the microbiome novelty score (MNS) over 8 years of microbiome depositions based on searching in more than 100,000 global 16S rRNA gene amplicon samples, we detected that the structural novelty of human microbiomes is approaching saturation and likely bounded, whereas that in environmental habitats remains 5 times higher. Via the microbiome focus index (MFI), which is derived from the MNS and microbiome attention score (MAS), we objectively track and compare the structural-novelty and attracted-attention scores of individual microbiome samples and projects, and we predict future trends in the field. For example, marine and indoor environments and mother-baby interactions are likely to receive disproportionate additional attention based on recent trends. Therefore, MNS, MAS, and MFI are proposed "alt-metrics" for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.IMPORTANCE We introduce two concepts to quantify the novelty of a microbiome. The first, the microbiome novelty score (MNS), allows identification of microbiomes that are especially different from what is already sequenced. The second, the microbiome attention score (MAS), allows identification of microbiomes that have many close neighbors, implying that considerable scientific attention is devoted to their study. By computing a microbiome focus index based on the MNS and MAS, we objectively track and compare the novelty and attention scores of individual microbiome samples and projects over time and predict future trends in the field; i.e., we work toward yielding fundamentally new microbiomes rather than filling in the details. Therefore, MNS, MAS, and MFI can serve as "alt-metrics" for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.

Highlights

With the expansion of microbiome sequencing globally, a key challenge is to relate new microbiome samples to the existing space of microbiome samples
Its microbiome novelty score (MNS) was derived by searching its sequence against those of all samples produced by past studies
DISCUSSION an enormous volume of large- and small-scale microbiome data sets from various habitats and produced by different studies have been deposited into public data repositories (e.g., HMP [5], EMP [7], and AGP [8]), there are currently few approaches that scale to process and integrate all the microbiome data so that a global view of microbiomes can be generated in real time (9)

Summary

Introduction

With the expansion of microbiome sequencing globally, a key challenge is to relate new microbiome samples to the existing space of microbiome samples. By computing a microbiome focus index based on the MNS and MAS, we objectively track and compare the novelty and attention scores of individual microbiome samples and projects over time and predict future trends in the field; i.e., we work toward yielding fundamentally new microbiomes rather than filling in the details. Tracking the microbiome novelty score (MNS), a metric defined based on searching samples against the entire reference database, we detected weak correlation between novelty and alpha-diversity (Spearman r Ͻ 0.4) Using this metric, we showed that the structural novelty of the human microbiome is approaching saturation and likely bounded, whereas novelty in environmental habitats remains substantially higher. The microbiome focus index (MFI), derived from the MNS and a microbiome attention score (MAS), can objectively track and compare the structural novelty and received attention scores of individual microbiomes or projects and predict trends in the field. Marine and indoor environments and mother-baby interactions could be considered “sleeping beauties” soon to be awakened

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Results

Conclusion