Affiliations: G.N. Ramachandran Knowledge Centre for Genome
Informatics, Institute of Genomics and Integrative Biology, Mall Road, Delhi
110007, India | School of Biotechnology, GGS Indraprastha University,
Delhi 110006, India | Department of Biotechnology, JayPee Institute of
Information Technology, Noida (UP) 201307, India
Abstract: In silico proteomics complements computational genomics in
characterizing genome evolution. Here we examine cluster patterns in archaeal
and bacterial proteomes using compositional properties of protein sequences in
contrast to the traditionally used sequence alignment procedures. Application
of standard Principal Component Analysis to the multi-dimensional data
identified cluster patterns. Two types of cluster patterns exist in bacterial
proteomes. Proteomes of type I have one major cluster with few isolated points
in space revealing an underlying largely homogeneous compositional structure.
In type II proteomes two clusters of protein distribution were discernible. The
two clusters differ in size and were separated from each other although the
boundary was somewhat fuzzy. Proteins falling in the major cluster were labeled
as 'typical' and proteins of the minor cluster were called 'atypical'. The
atypical proteins were mapped to Cluster of Orthologous Groups. Species
distribution in COGs maps with respect to atypical proteins illuminated the
biological relationships of extreme diversity among the archaeal members and of
diversity among bacteria in relation to their niche. Amino acids that were
over-represented in the atypical proteins had higher biosynthetic cost compared
to 'typical' ribosomal proteins. However, archaea and bacteria economize by
preferring the less costly amino acid to others closely related in chemical
structure. Further, over-representation of serine in atypical proteins of
archaeal members suggests re-examining these proteomes for the presence of
Serine/Threonine phosphatases and kinases in Archaea. Our computational
procedure can serve as a useful addition to the existing tools for carrying out
in silico proteomics.
