Big Data for a Small World: A Review on Databases and Resources for Studying Microbiomes

Analysis of microbial dynamics in the soybean root-associated environments from community to single-cell levels

Plant root-associated environments such as the rhizosphere, rhizoplane, and endosphere, are notably different from non-root-associated soil environments. However, the microbial dynamics in these spatially divided compartments remain unexplored. In this study, we propose a combinational analysis of single-cell genomics with 16S rRNA gene sequencing. This method enabled us to understand the entire soil microbiome and individual root-associated microorganisms. We applied this method to soybean microbiomes and revealed that their composition was different between the rhizoplane and rhizosphere in the early growth stages, but became more similar as growth progressed. In addition, a total of 610 medium- to high-quality single-amplified genomes (SAGs) were acquired, including plant growth-promoting rhizobacteria (PGPR) candidates while genomes with high GC content tended to be missed by SAGs. The whole-genome analyses of the SAGs suggested that rhizoplane-enriched Flavobacterium solubilizes organophosphate actively and Bacillus colonizes roots more efficiently. Single-cell genomics, together with 16S rRNA gene sequencing, enabled us to connect microbial taxonomy and function, and assess microorganisms at a strain resolution even in the complex soil microbiome.

Twnbiome: a public database of the healthy Taiwanese gut microbiome

With new advances in next generation sequencing (NGS) technology at reduced costs, research on bacterial genomes in the environment has become affordable. Compared to traditional methods, NGS provides high-throughput sequencing reads and the ability to identify many species in the microbiome that were previously unknown. Numerous bioinformatics tools and algorithms have been developed to conduct such analyses. However, in order to obtain biologically meaningful results, the researcher must select the proper tools and combine them to construct an efficient pipeline. This complex procedure may include tens of tools, each of which require correct parameter settings. Furthermore, an NGS data analysis involves multiple series of command-line tools and requires extensive computational resources, which imposes a high barrier for biologists and clinicians to conduct NGS analysis and even interpret their own data. Therefore, we established a public gut microbiome database, which we call Twnbiome, created using healthy subjects from Taiwan, with the goal of enabling microbiota research for the Taiwanese population. Twnbiome provides users with a baseline gut microbiome panel from a healthy Taiwanese cohort, which can be utilized as a reference for conducting case-control studies for a variety of diseases. It is an interactive, informative, and user-friendly database. Twnbiome additionally offers an analysis pipeline, where users can upload their data and download analyzed results. Twnbiome offers an online database which non-bioinformatics users such as clinicians and doctors can not only utilize to access a control set of data, but also analyze raw data with a few easy clicks. All results are customizable with ready-made plots and easily downloadable tables. Database URL: http://twnbiome.cgm.ntu.edu.tw/ .