The Translation And Mutation Mechanisms Involved In Shaping Amino Acid Compositions

Amino acid composition is an old and new topic at the same time.In this manuscript,we systematically investigated the correlation between amino acid compositions and mechanisms for translation and mutation.Although more and more entangled participants of translation process were realized,how they cooperate and co-determine the final translation efficiency still lacks details.Here,we reasoned that the basic translation components,tRNAs and amino acids should be consistent to maximize the efficiency and minimize the cost.We firstly revealed that 310 out of 410 investigated genomes of three domains had significant co-adaptions between the tRNA gene copy numbers and amino acid compositions,indicating that maximum efficiency constitutes ubiquitous selection pressure on protein translation.Furthermore,fast-growing and larger bacteria are found to have significantly better co-adaption and confirmed the effect of this pressure.Within organism,highly expressed proteins and those connected to acute responses have higher co-adaption intensity.Thus,the better co-adaption probably speeds up the growing of cells through accelerating the translation of special proteins.Experimentally,manipulating the tRNA gene copy number to optimize co-adaption between enhanced green fluorescent protein(EGFP)and tRNA gene set of Escherichia coli indeed lifted the translation rate(speed).Finally,as a newly confirmed translation rate regulating mechanism,the co-adaption reflecting translation rate not only deepens our understanding on translation process but also provides an easy and practicable method to improve protein translation rates and productivity.Inconsistent results on the association between evolutionary rates and amino acid composition of proteins have been reported in eukaryotes.However,there are few studies of how and why amino acid composition can influence evolutionary rates in bacteria.Thus,we constructed linear regression models between composition frequencies of amino acids and evolutionary rates for bacteria.On average,compositions of all amino acids can explain only 21.5%of the variation in evolutionary rates among 273 investigated bacterial organisms.In five model organisms,amino acid compositions contribute more to variation in evolutionary rates than protein abundance,and frequency of optimal codons.The contribution of individual amino acid composition to evolutionary rate vary among organisms.The closer the GC-content of genes are to its maximum or its minimum,the better the correlation between the amino acid content and the evolutionary rate of proteins could be.The types of amino acids that significantly contribute to evolutionary rates can be grouped into GC-rich and AT-rich amino acids.We further observed that the higher usage of rare amino acids homologous proteins have,and the lower the evolutionary rate they will have.Finally,amino acid composition significantly contributes to the rate of evolution in bacterial organisms and this in turn is impacted by GC-content.Understanding how proteins evolve is important.Those GC rich(AT rich)organisms tend to have proteins coded by more(fewer)GC rich codons.However,the GC content is not considered as a universal factor to affect the ongoing changes of amino acid frequencies.A generally accepted viewpoint suggested that some amino acids were incorporated into the genetic codes more recently than others and'recent'amino acids are becoming more common.However,this nearly neutral model was argued by a mutation-selection equilibrium.In this paper,we further compared the general effects of the GC content and the putative recruitment order on the trend for the loss and gain of amino acids.The essential genes are supposed to be more evolutionarily conserved than nonessential genes,which are supposed to exist both in the last universal common ancestor and the extant lives,thus we compared the amino acid compositions of essential proteins.To acquire the general tendency of amino acid compositions,the gain and loss of amino acids in homologous proteins,putatively existing in the last universal common ancestor,were compared through their amino acid compositions.They are found to be mostly influenced by the GC content.Statistic test showed that GC content have strong effects on the variation of amino acid composition than the recruitment order of amino acids.GC content is a non-negligible factor influencing the energy efficiency,causing the biased gain or loss of amino acids during evolution,and finally influencing the amino acid compositions.Our results support that GC contents have more effects on the gain and loss of amino acids than the recruitment order of amino acids during the evolution of homologous proteins.In summary,the thesis focuses on amino acid composition researches to investigate the underlying translation and mutation mechanisms with comparative and computation biology methods.Data of genome,transcriptome,proteome and others are combined with codon usage index,evolutionary rates,COG clusters and KEGG pathways.An index named TAAI which could be used to optimize the translation efficiency was designed after the validated co-adaption relationship theory and then was successfully applied on the expression of EGFP in E.coli.Next,the mutation and evolution processes were proved to be under strong effect of GC content after comparing multi amino acid related features.In a word,this thesis could help us further understand the translation and mutation mechanisms using comparative and evolutionary genomics.