MetAnnotate: function-specific taxonomic profiling and comparison of metagenomes

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Metagenomes offer insights into microbial community composition and function.
• Identifying specific taxa responsible for particular functions within metagenomes is challenging.
• Existing methods often struggle to pinpoint organisms linked to specific metabolic pathways.

Purpose of the Study:

• To introduce MetAnnotate, a novel tool for identifying organisms performing specific functions in metagenomic data.
• To enable researchers to answer: "Which organisms perform my function of interest within my metagenome(s) of interest?"

Main Methods:

• MetAnnotate utilizes profile hidden Markov models to analyze shotgun metagenomes.
• It identifies genes and pathways of interest.
• Sequence classification is achieved via phylogenetic placement or a best hit approach, allowing for inter-metagenome comparisons.

Main Results:

• MetAnnotate demonstrates high taxonomic classification accuracy for diverse genes on simulated datasets.
• The tool effectively identifies markers of community abundance and specific biological pathways.
• Analysis of cobalamin synthesis genes in aquatic metagenomes was significantly faster than using the Basic Local Alignment Search Tool (BLAST) top hit approach.

Conclusions:

• MetAnnotate is a versatile, multi-threaded tool available as a local web application or command-line utility for Linux.
• It provides a robust framework for both general and function-specific taxonomic profiling and comparative metagenomic analysis.