Literature DB >> 12885231

Using motif-based methods in multiple genome analyses: a case study comparing orthologous mesophilic and thermophilic proteins.

David La1, Melanie Silver, Robert C Edgar, Dennis R Livesay.   

Abstract

Protein motifs represent highly conserved regions within protein families and are generally accepted to describe critical regions required for protein stability and/or function. In this comprehensive analysis, we present a robust, unique approach to identify and compare corresponding mesophilic and thermophilic sequence motifs between all orthologous proteins within 44 microbial genomes. Motif similarity is determined through global sequence alignment of mesophilic and thermophilic motif pairs, which are identified by a greedy algorithm. Our results reveal only modest correlation between motif and overall sequence similarity, highlighting the rationale of motif-based approaches in comprehensive multigenome comparisons. Conserved mutations reflect previously suggested physiochemical principles for conferring thermostability. Additionally, comparisons between corresponding mesophilic and thermophilic motif pairs provide key biochemical insights related to thermostability and can be used to test the evolutionary robustness of individual structural comparisons. We demonstrate the ability of our unique approach to provide key insights in two examples: the TATA-box binding protein and glutamate dehydrogenase families. In the latter example, conserved mutations hint at novel origins leading to structural stability differences within the hexamer structures. Additionally, we present amino acid composition data and average protein length comparisons for all 44 microbial genomes.

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Year:  2003        PMID: 12885231     DOI: 10.1021/bi027435e

Source DB:  PubMed          Journal:  Biochemistry        ISSN: 0006-2960            Impact factor:   3.162


  4 in total

1.  Metagenome analysis of an extreme microbial symbiosis reveals eurythermal adaptation and metabolic flexibility.

Authors:  Joseph J Grzymski; Alison E Murray; Barbara J Campbell; Mihailo Kaplarevic; Guang R Gao; Charles Lee; Roy Daniel; Amir Ghadiri; Robert A Feldman; Stephen C Cary
Journal:  Proc Natl Acad Sci U S A       Date:  2008-11-05       Impact factor: 11.205

2.  MINER: software for phylogenetic motif identification.

Authors:  David La; Dennis R Livesay
Journal:  Nucleic Acids Res       Date:  2005-07-01       Impact factor: 16.971

3.  Predicting functional sites with an automated algorithm suitable for heterogeneous datasets.

Authors:  David La; Dennis R Livesay
Journal:  BMC Bioinformatics       Date:  2005-05-13       Impact factor: 3.169

4.  Discriminative motif discovery in DNA and protein sequences using the DEME algorithm.

Authors:  Emma Redhead; Timothy L Bailey
Journal:  BMC Bioinformatics       Date:  2007-10-15       Impact factor: 3.169

  4 in total

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