EzBioCloud: a genome-driven database and platform for microbiome identification and discovery

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• DNA sequencing technologies are increasingly vital for classifying Bacteria and Archaea.
• Accurate taxonomic information is crucial, with species definition relying heavily on genome comparisons.
• The EzBioCloud platform provides quality-controlled 16S rRNA gene and genome sequences for microbial taxonomy.

Purpose of the Study:

• To present an updated version of the EzBioCloud database with refined and expanded capabilities.
• To incorporate advanced strategies for classifying underrepresented microbial lineages.
• To enhance the accuracy and comprehensiveness of microbial taxonomic identification.

Main Methods:

• Whole-genome assemblies from NCBI undergo stringent quality control to remove low-quality data.
• An enhanced bioinformatics pipeline performs 16S rRNA gene similarity searches and Average Nucleotide Identity (ANI) calculations.
• A core gene ANI (cgANI) method is applied for taxonomic placement of genomes lacking 16S rRNA sequences or closely related genomic representatives.

Main Results:

• The updated EzBioCloud database now contains 109,835 species, including 21,964 validly published names.
• 47,896 candidate species were identified via 16S rRNA similarity (phylotypes) or whole genome ANI (genomospecies).
• An additional 39,975 species clusters were positioned using the cgANI method.

Conclusions:

• The enhanced EzBioCloud database provides a more comprehensive and accurate resource for microbial taxonomy.
• The integration of cgANI broadens the scope of taxonomic placement, especially for understudied organisms.
• EzBioCloud remains a valuable, accessible tool for microbial identification and classification based on genomic data.