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

Abstract

Microorganisms are ubiquitous in nature and form complex community networks to survive in various environments. This community structure depends on numerous factors like nutrient availability, abiotic factors like temperature and pH as well as microbial composition. Categorising accessible biomes according to their habitats would help in understanding the complexity of the environment-specific communities. Owing to the recent improvements in sequencing facilities, researchers have started to explore diverse microbiomes rapidly and attempts have been made to study microbial crosstalk. However, different metagenomics sampling, preprocessing, and annotation methods make it difficult to compare multiple studies and hinder the recycling of data. Huge datasets originating from these experiments demand systematic computational methods to extract biological information beyond microbial compositions. Further exploration of microbial co-occurring patterns across the biomes could help us in designing cross-biome experiments. In this review, we catalogue databases with system-specific microbiomes, discussing publicly available common databases as well as specialised databases for a range of microbiomes. If the new datasets generated in the future could maintain at least biome-specific annotation, then researchers could use those contemporary tools for relevant and bias-free analysis of complex metagenomics data.

Non-Targeted RNA Sequencing: Towards the Development of Universal Clinical Diagnosis Methods for Human and Veterinary Infectious Diseases

“…The fields of metagenomics and metatranscriptomics are rapidly growing beyond analytical software. The creation and ongoing improvements of specialized databases are abundant, and there is a need for uniformity and validation [113][114][115][116][117][118]. The FDA-ARGOS database [119], the SILVA ribosomal database (https://www.arb-silva.de/, accessed on 9 May 2024), and RDP (https://www.glbrc.org/data-and-tools/glbrc-data-sets/ribosomaldatabase-project, accessed on 9 May 2024) are important but there is a need to develop a consensus database that would have clinical acceptability.…”

Modeling plant-microbe interactions with species distribution models

“…While large-scale sampling campaigns to quantify plant-associated microbiota remain challenging, an alternative approach is to compile existing datasets to achieve a broad geographical and plant-host taxonomic coverage. An increasing number of datasets on plantmicrobial associations has been published over the past decades (Sengupta et al, 2023). These data are accessible through international nucleotide sequence database collaborations such as the European Nucleotide Archive and the U.S. National Center for Biotechnology Information.…”