Kullback Leibler divergence in complete bacterial and phage genomes

Author:

Akhter Sajia1,Aziz Ramy K.23,Kashef Mona T.2,Ibrahim Eslam S.2,Bailey Barbara4,Edwards Robert A.1345

Affiliation:

1. Computational Science Research Center, San Diego State University, San Diego, CA, USA

2. Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Cairo, Egypt

3. Department of Computer Science, San Diego State University, San Diego, CA, United States of America

4. Department of Mathematics & Statistics, San Diego State University, San Diego, CA, USA

5. Department of Biology, San Diego State University, San Diego, CA, USA

Abstract

The amino acid content of the proteins encoded by a genome may predict the coding potential of that genome and may reflect lifestyle restrictions of the organism. Here, we calculated the Kullback–Leibler divergence from the mean amino acid content as a metric to compare the amino acid composition for a large set of bacterial and phage genome sequences. Using these data, we demonstrate that (i) there is a significant difference between amino acid utilization in different phylogenetic groups of bacteria and phages; (ii) many of the bacteria with the most skewed amino acid utilization profiles, or the bacteria that host phages with the most skewed profiles, are endosymbionts or parasites; (iii) the skews in the distribution are not restricted to certain metabolic processes but are common across all bacterial genomic subsystems; (iv) amino acid utilization profiles strongly correlate with GC content in bacterial genomes but very weakly correlate with the G+C percent in phage genomes. These findings might be exploited to distinguish coding from non-coding sequences in large data sets, such as metagenomic sequence libraries, to help in prioritizing subsequent analyses.

Funder

National Science Foundation (NSF) Division of Biological Infrastructure

Faculty of Pharmacy, Cairo University

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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