Evolution Analysis And Function Study Of Small Proteins On Streptococcus Suis

Streptococcus suis (S. suis) is a spherical Gram-positive anaerobic pathogen arranged in chains or pairs. S. suis is responsible for a variety of swine diseases and even acute death, which impact the swine husbandry worldwide. Furthermore, the pathogens infect human through wounds or respiratory systems and cause acute diseases with a serious clinic condition and high mortality. The issue of S. suis draws attention to agronomy and medicine. Early studies are from a clinical point of S. suis disease prevention and control. With the development of large-scale sequencing technology and bioinformatics,17strains have been sequenced and assembled and14of them have complete genome sequences. The genome data bring the genome-wide study of the evolution and function of the S. suis.A polypeptide containing no more than100amino acid residues are generally considered to be small protein (SP). Because of the constraints of computational biology methods, SPs were once thought to be trivial molecules and the study of SPs is an almost untapped virgin territory in biological research. Many of the earlier studies assumed that the length of a protein sequence is associated with its specific functions and that SPs probably have few notable functions compared to large proteins thus large proteins have the priority to be annotated. However, the identification of increasing numbers of important SPs has gradually attracted the attention of scientists and many studies have demonstrated that SPs are widespread and have important functionality in all three domains of life.This paper focuses on mining the special significance of SPs by using systematic comparison and analysis of the similarities and differences of all S. suis proteins and SPs in evolutionary and functional processes based on S. suis genome data. We search the continuous non-conserved region in genomes of S. suis standard strains05ZYH33, analyze the relationship of conservative degree, and protein length, and find protein clusters on one of the different zone89K. We also analyze evolution pattern of05ZYH33proteins and construct protein co-existence network. Furthermore, we find similarities and differences among phylogenetic trees using five different strategies based on SPs and all proteins.The homologous protein cluster results implicate the relationship between length of protein and conservative degrees and the association between protein functions and conservative degrees as well. Generally, most of the large proteins are all-conserved while SPs tend to be less-conserved, which are more enriched in the metabolic or control functions. It may have potential biological significance that the evolution of species tends to choose strain-specific SPs to maintain adjustable flexibility.We search the continuous non-conserved region in genomes of S. suis standard strains05ZYH33revealing that the largest contiguous non-conserved region is named89K pathogenic island. Although most of the SPs on the89K are function unknown proteins, we find two SPs whose functions are regulating their upstream large proteins involving the site-specific excision and transposition process. We also analyze the relationship of conservative degree and protein length and find protein clusters on one of the different zone of89K are essential factors in the type Ⅳ secretion system.Protein evolution analysis from standard strain to other genome indicates that SPs are more active than large proteins. Although they are less-conserved, SPs may not disappear in the evolution and we find homologs on genome sequences and more than half of the homologous proteins are located in the protein coding region. The protein co-existence pattern clusters is indicative that SPs accompany large proteins in the evolution of the prokaryotes, that is, if some large protein increasing or missing, some relative SPs do as well.By using five different strategies we construct phylogenetic trees, which indicate that JS14and SS12are close to type2S. suis, while D9, D12, ST1and ST3are clustered in a large branch. Protein gain and loss method constructs two trees with high degree of consistency based on SPs and all proteins respectively. However, we find some difference when constructing phylogenetic trees based on SPs and all proteins through association rules algorithm. Through other two methods, irredundant protein evolution spectrum and the concatenation alignments of equal length all conserved sequences, the trees are more clearly distinguish the different serotypes of strains using SPs data than the trees constructed using all proteins.