Metagenomic HMM metabolic profiling

Knowledge graph centered on Metagenomic HMM metabolic profiling with 70 nodes and 155 connections. Top connected: Rocky Mountain Biological Laboratory, Gothic, Crested Butte, Bacteria, East River.

Method synopsis

Comprehensive Hidden Markov Model analysis of metagenomic sequences to identify and quantify metabolic functions across biogeochemical pathways. Uses both standardized TIGR-FAM and custom HMM databases with specific cutoff scores for gene identification.

Synthesized from method descriptions across 2 papers using this protocol.

Procedure from a recent peer-reviewed implementation

Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — Meanders as a scaling motif for understanding of floodplain soil microbiome and biogeochemical potential at the watershed scale (2021), Microbiome. Implementations in other papers (listed below) may differ.

1. Functional gene annotation using HMMs
   A set of Hidden Markov Models was used to annotate genes encoding individual protein subunits for key enzymes and complete or partial metabolic pathways. 32 functions comprised the final set of biogeochemical transformations under investigation, with criteria for presence that had to be met for a function to be encoded in a genome.
   Quantities: 32 biogeochemical functions analyzedDuration: Not specifiedConditions: Computational analysis
   Equipment: Hidden Markov Models (HMMs)

Typical Equipment

• TIGR-FAM database
• Custom HMM databases

Output Measurements

• metabolic gene abundance
• functional diversity
• biogeochemical pathway representation

Papers Using This Protocol (2)

Species Studied With This Protocol

Places Where Used