Enzyme-specific profiles for genome annotation: PRIAM

Clotilde Claudel‐Renard

Nucleic Acids Research · 2003 · 383 citations · 35 references

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TL;DR

The advent of fully sequenced genomes enables reconstruction of metabolic pathways by identifying enzyme‑coding genes. The study introduces PRIAM, a method for automated enzyme detection in fully sequenced genomes based on ENZYME database classification. PRIAM employs enzyme‑specific position‑specific scoring matrix profiles and automatically generated logical rules to infer enzyme presence, and was applied to the Sinorhizobium meliloti genome to identify potential metabolic pathways. PRIAM’s predictions were compared to the original annotation, visualized on KEGG graphs, and helped highlight potentially missing enzymes in metabolic pathways.

Abstract

The advent of fully sequenced genomes opens the ground for the reconstruction of metabolic pathways on the basis of the identification of enzyme-coding genes. Here we describe PRIAM, a method for automated enzyme detection in a fully sequenced genome, based on the classification of enzymes in the ENZYME database. PRIAM relies on sets of position-specific scoring matrices ('profiles') automatically tailored for each ENZYME entry. Automatically generated logical rules define which of these profiles is required in order to infer the presence of the corresponding enzyme in an organism. As an example, PRIAM was applied to identify potential metabolic pathways from the complete genome of the nitrogen-fixing bacterium Sinorhizobium meliloti. The results of this automated method were compared with the original genome annotation and visualised on KEGG graphs in order to facilitate the interpretation of metabolic pathways and to highlight potentially missing enzymes.

References

35