Ecosystem-specific microbiota and microbiome databases in the era of big data

Area of Science:

• Microbiology
• Bioinformatics
• Ecology

Background:

• Advancements in sequencing technologies have expanded the scope of microbial and microbiome research.
• There's a shift from categorical studies to investigating microbial community functionality.
• Unequal genomic and environmental data coverage complicates identifying microbial relationships.

Purpose of the Study:

• To review ecosystem-specific databases (ES-DBs) as a tool for microbial community analysis.
• To compare ES-DBs with traditional microbial databases.
• To discuss the integration of ES-DBs with meta-omics platforms and their limitations.

Main Methods:

• Review of current literature on microbial databases and meta-omics.
• Analysis of the development and characteristics of ES-DBs.
• Comparison of data quality, heterogeneity, and standardization across database types.

Main Results:

• Generic databases offer broad data access but suffer from quality and heterogeneity issues.
• ES-DBs consolidate and standardize protocols for specific ecosystems, enabling comparable datasets.
• ES-DBs facilitate the contextualization of meta-omics data with habitat-specific standards.

Conclusions:

• ES-DBs represent an emerging tool for standardized microbial community analysis.
• Integration with meta-omics platforms shows promise but requires addressing inherent limitations.
• ES-DBs are crucial for advancing reproducible and comparable microbiome research.