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Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

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Published on: June 24, 2019

Codon and aminoacid usage patterns in mycobacteria.

C Scapoli¹, E Bartolomei, S De Lorenzi

¹Department of Biology and Evolution, University of Ferrara, Ferrara, Italy.

Journal of Molecular Microbiology and Biotechnology

|January 21, 2009

Summary

This summary is machine-generated.

Molecular evolution in Mycobacterium species reveals strong correlations in codon and amino acid usage. GC content significantly influences codon bias, suggesting mutational forces shape Mycobacterium genome evolution.

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Area of Science:

Microbiology
Molecular Biology
Evolutionary Biology

Background:

Advancements in gene sequencing enable molecular evolution studies in lower taxonomic ranks like genera and species.
The genus Mycobacterium presents a suitable model for investigating codon and amino acid usage patterns.

Purpose of the Study:

To analyze codon and amino acid usage across 13 Mycobacterium species and 12 subspecies.
To identify factors influencing synonymous codon usage and effective number of codons within the genus.
To compare phylogenies derived from molecular usage patterns with traditional evolutionary trees.

Main Methods:

Analysis of 8,836,513 codons from 26,755 sequences within the Mycobacterium genus.
Statistical examination of codon and amino acid frequencies, molecular weight, codon degeneracy, and GC content.
Construction of evolutionary trees based on codon and amino acid usage data.

Main Results:

Frequencies of codon and amino acid usage show significant correlations between Mycobacterium species and subspecies.
Amino acid molecular weight and codon degeneracy impact usage correlations.
Genomic GC content, particularly at the third codon position, is the primary determinant of effective codon number, indicating mutational bias dominance.
Evolutionary trees derived from usage patterns align with established Mycobacterium phylogenies.

Conclusions:

Synonymous codon usage in Mycobacterium is predominantly shaped by GC content and mutational bias.
Molecular evolution analyses based on codon and amino acid usage provide a robust framework for understanding Mycobacterium phylogeny.