Articles producció científica> Química Analítica i Química Orgànica

Use of a multi-way method to analyze the amino acid composition of a conserved group of orthologous proteins in prokaryotes

  • Identification data

    Identifier: imarina:5117688
    Authors:
    Pasamontes A, Garcia-Vallve S.
    Abstract:
    Background: Amino acids in proteins are not used equally. Some of the differences in the amino acid composition of proteins are between species ( mainly due to nucleotide composition and lifestyle) and some are between proteins from the same species ( related to protein function, expression or subcellular localization, for example). As several factors contribute to the different amino acid usage in proteins, it is difficult both to analyze these differences and to separate the contributions made by each factor. Results: Using a multi-way method called Tucker3, we have analyzed the amino composition of a set of 64 orthologous groups of proteins present in 62 archaea and bacteria. This dataset corresponds to essential proteins such as ribosomal proteins, tRNA synthetases and translational initiation or elongation factors, which are common to all the species analyzed. The Tucker3 model can be used to study the amino acid variability within and between species by taking into consideration the tridimensionality of the data set. We found that the main factor behind the amino acid composition of proteins is independent of the organism or protein function analyzed. This factor must be related to the biochemical characteristics of each amino acid. The difference between the non-ribosomal proteins and the ribosomal proteins ( which are rich in arginine and lysine) is the main factor behind the differences in amino acid composition within species, while G+C content and optimal growth temperature are the main factors behind the differences in amino acid usage between species. Conclusion: We show that a multi-way method is useful for comparing the amino acid composition of several groups of orthologous proteins from the same group of species. This kind of dataset is extremely useful
  • Others:

    Author, as appears in the article.: Pasamontes A, Garcia-Vallve S.
    Department: Química Analítica i Química Orgànica
    e-ISSN: 1471-2105
    URV's Author/s: Garcia Vallve, Santiago / PASAMONTES FUNEZ, ALBERTO
    Keywords: Rna Ribosomal-subunit Principal component analysis Optimal-growth temperature Genomic g+c content Dna-repair system Codon usage Bioinformatics Bacteria Archaea Adaptation
    Abstract: Background: Amino acids in proteins are not used equally. Some of the differences in the amino acid composition of proteins are between species ( mainly due to nucleotide composition and lifestyle) and some are between proteins from the same species ( related to protein function, expression or subcellular localization, for example). As several factors contribute to the different amino acid usage in proteins, it is difficult both to analyze these differences and to separate the contributions made by each factor. Results: Using a multi-way method called Tucker3, we have analyzed the amino composition of a set of 64 orthologous groups of proteins present in 62 archaea and bacteria. This dataset corresponds to essential proteins such as ribosomal proteins, tRNA synthetases and translational initiation or elongation factors, which are common to all the species analyzed. The Tucker3 model can be used to study the amino acid variability within and between species by taking into consideration the tridimensionality of the data set. We found that the main factor behind the amino acid composition of proteins is independent of the organism or protein function analyzed. This factor must be related to the biochemical characteristics of each amino acid. The difference between the non-ribosomal proteins and the ribosomal proteins ( which are rich in arginine and lysine) is the main factor behind the differences in amino acid composition within species, while G+C content and optimal growth temperature are the main factors behind the differences in amino acid usage between species. Conclusion: We show that a multi-way method is useful for comparing the amino acid composition of several groups of orthologous proteins from the same group of species. This kind of dataset is extremely useful for detecting differences between and within species.
    Thematic Areas: Structural biology Saúde coletiva Química Molecular biology Medicina veterinaria Medicina ii Medicina i Mathematical & computational biology Matemática / probabilidade e estatística Interdisciplinar Farmacia Engenharias iv Engenharias iii Computer science applications Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência da computação Biotecnología Biotechnology & applied microbiology Biodiversidade Biochemistry Biochemical research methods Applied mathematics
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: santi.garcia-vallve@urv.cat
    Author identifier: 0000-0002-0348-7497
    Record's date: 2023-02-18
    Journal volume: 7
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-7-257
    Papper original source: Bmc Bioinformatics. 7
    APA: Pasamontes A, Garcia-Vallve S. (2006). Use of a multi-way method to analyze the amino acid composition of a conserved group of orthologous proteins in prokaryotes. Bmc Bioinformatics, 7(), -. DOI: 10.1186/1471-2105-7-257
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1186/1471-2105-7-257
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2006
    Publication Type: Journal Publications
  • Keywords:

    Applied Mathematics,Biochemical Research Methods,Biochemistry,Biotechnology & Applied Microbiology,Computer Science Applications,Mathematical & Computational Biology,Molecular Biology,Structural Biology
    Rna
    Ribosomal-subunit
    Principal component analysis
    Optimal-growth temperature
    Genomic g+c content
    Dna-repair system
    Codon usage
    Bioinformatics
    Bacteria
    Archaea
    Adaptation
    Structural biology
    Saúde coletiva
    Química
    Molecular biology
    Medicina veterinaria
    Medicina ii
    Medicina i
    Mathematical & computational biology
    Matemática / probabilidade e estatística
    Interdisciplinar
    Farmacia
    Engenharias iv
    Engenharias iii
    Computer science applications
    Ciências sociais aplicadas i
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências agrárias i
    Ciência da computação
    Biotecnología
    Biotechnology & applied microbiology
    Biodiversidade
    Biochemistry
    Biochemical research methods
    Applied mathematics
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