Genetic Evolution Analysis of Actinobacillus pleuropneumoniae

Yu LIANG Yanfei LIU Jiande YANG

Abstract In order to explore the genetic evolution of Actinobacillus pleuropneumoniae （App） in different countries and clarify the relationships among different App in each region， the 16S rRNA gene of App in the NCBI nucleotide database was analyzed and compared by the bioinformatics method. The phylogenetic tree was constructed after tailoring alignment. The results showed that a stable genetic phenomenon was indicated in the evolutionary process of App. The isolates derived from China were clustered and showed a high degree of conservation. They had a certain genetic relationship with the British and American strains， but had far relationship with the strains from Japan which was a neighboring country of China. The isolates from different countries in the Eurasian continent shared high homology. The isolates of the two regions originated from common ancestors.

Key words Actinobacillus pleuropneumoniae; Genetic evolution; Phylogenetic tree; Homology comparison; Origin; Relationship

Actinobacillus pleuropneumoniae （App） belongs to Haemophilus of Pasteurellaceae， which can cause porcine contagious pleuropneumonia， mainly manifested as lung hemorrhage， necrotizing bronchopneumonia and fibrinous pleuritis， with higher lethality[1]. At present， as many as 15 App serotypes have been identified， and the serotypes prevailing in different countries and regions are inconsistent， with the virulence not the same therebetween. In China， serotype 1， serotype 3， serotype 5 and serotype 7 are the main epidemic serotypes， and serotypes 13 and 14 were distributed in Europe and the United States[2]. Chinaюs current control of porcine contagious pleuropneumonia relies mainly on drugs or vaccines. Due to the lack of crossprotection of different serotype strains， the immunization effect of inactivated vaccines is not ideal. App infection is easy to secondary to other bacterial diseases or viral diseases， making the prevention of diseases more difficult[3].

Bacterial rRNA is highly conserved in terms of nucleotide sequence， structure and function， and is called "fossil". The conservativeness can reflect the genetic relationship between bacteria and provide clues for phylogenetic reconstruction. The 16S rRNA gene is about 1.5 kb in size and has a moderate sequence length. It has both conserved and mutated regions and is a good biomarker[4-5]. The genetic evolution distances between bacterial genera and strains can be calculated through analysis of their variable or fulllength sequences and homology comparisons. In recent years， with the development of sequencing technology， especially the maturity of the second generation of highthroughput sequencing technology， the 16S rRNA gene database has been greatly enriched[6]. In this study， 16S rRNAs of various App were screened and sorted， and their genetic phylogenetic tree was constructed by homologous sequence alignment analysis to explore the evolution and evolutionary relationships of App in different regions， so as to reveal the evolutionary laws of App in disease occurrence. This study provides reference for crossregional spread of the disease.

Materials

All App sequence information came from the NCBI （The National Center for Biotechnology Information） website. After entering the NCBI home page （http：//www.ncbi.nlm.nih.gov）， the required sequences were selected and downloaded. The BioEdit software was downloaded from http：//www. mbio.ncsu.edu， and the MEGA 7.0 software was downloaded from http：//www. megasoftware. net.

Methods

Gene discrimination and screening

The App′s 16S rRNA gene sequence （GenBank accession number： E05331.1） was used as the search code for BLAST search， and the target gene App 16S rRNA was input into the nucleotide search column of the NCBI homepage to perform sequence alignment analysis using the online BLAST comparison tool. In order to explore the evolutionary relationships between App in various regions in the genetic evolution process， the experiment excluded the sequence of Haemophilus parasuis isolate found in the sequence search， but chose strains of the same genus with higher similarity to the known App species. Based on the BLAST alignment results， gene sequences with higher homology similarity and sequence identity above 95% were found[7]. These sequences were downloaded， and sequence information was viewed and reduced， during which genes that are not App 16S rRNA genes or have very short sequences were excluded.

Construction of gene sequence evolutionary tree

The BioEdit software was used to integrate and compare the obtained gene sequences， and all the compared sequences were analyzed using the MEGA 7.0 software， to delete the gene segments with larger differences， cut off the parts with no similarity at both ends and reserve the comparative parts. A phylogenetic tree was constructed with the tailored gene sequences of approximately 1 364 bp in length using the MEGA 7.0 software. Specifically， according to the original tree construction parameters of the software， the evolutionary tree was constructed by the neighborjoining method， and more specifically， the maximum composite likelihood algorithm in MEGA 7.0 was used to generate the neighborjoining tree from the aligned and tailored sequences. And it was estimated that it can guide and support 100 000 times of repeated detections[8-9]. The Bootstrap 1 000 was used to test the confidence of each branch of the molecular phylogenetic tree. To ensure the diversity of nucleotides in the gene sequences， an online confidence limit calculator was used to estimate the 95% confidence limit[10]. The geographical data that had been prepared before were input into the phylogenetic tree generated by the MEGA 7.0 software to complete the construction of the phylogenetic tree.

Results and Analysis

Identification and screening of genes

The 16S rRNA gene sequences of App were obtained by searching in NCBI， and the App 16S rRNA gene sequence （GenBank accession number： E05331.1） with the highest conformity was selected as the target gene. By using the BLAST option in NCBI， 100 similar gene sequences were obtained. After further screening， 19 App 16S rRNA gene sequences with clear source， moderate gene length and high homology were obtained， as shown in Table 1.

Construction of gene sequence evolutionary tree

Multiple sequence alignment was performed on the sequences in Table 1 using MEGA 7.0 software， and the parts that gave ragged sequences after alignment due to that the sequencing primers were not the same， were eliminated. The molecular evolutionary tree was constructed by the neighborjoining method， as shown in Fig. 1.

It could be seen from Fig. 1 that there were multiple evolutionary branches in the App strain， and for the compared App 16S rRNA gene sequences， the lengths of the evolutionary branches were different according to genetic relationship. These gene sequences were clustered together at a far or near distance， and the various types of clustering branches showed very obvious regional characteristics[7-8]. The homology of the strains in the same region was extremely high， indicating that the App 16S rRNA genes had similar characteristics in some aspect of different geographical sources.

The App strains in the same region were the closest in genetic evolution， and the genetic relationships from other members of other countries were father. It confirmed that App was less likely to spread across regions， and the App strains from the same region formed an evolutionary branch with relatively obvious regional characteristics in the phylogenetic tree. It could be found from the comparison of strains from different regions that the members of the family evolved at a faster rate， and the same strain had genotypes with very low homology in multiple countries. The reasons for the rapid changes in the genome need to be further studied， and it is speculated that this might be an important reason for the rapid evolution of App into highly pathogenic strains[7-8].

Yu LIANG et al. Genetic Evolution Analysis of Actinobacillus pleuropneumoniae

In the phylogenetic tree， an obvious cluster of Chinese strains can be found. Such four strains as TJ12 （GenBank accession number： KC834743.1）， JXAU2 （GenBank accession number： KR071801.1）， JX2014 （GenBank accession number： KP271101.1） and HB13 （GenBank accession number： KC834744.1） constituted a Chinese genotype relatively closer in evolution， presenting a separate evolutionary branch， indicating that App had a unique bacterial type in China， which was highly conserved， but still had some differences. These findings suggested the existence of the Chinese pathogen branch. It could also be seen from the figure that both the US bacterial type and the Swiss bacterial type were clustered into one strain， respectively. The 16S rRNA （GenBank accession number： E05331.1） and Hopee 4074 （GenBank accession number： NR_115546.2） from the United States shared homology as high as 98%， while another isolate from the United States， MCCM 00189 （GenBank accession number： AF224283.1） was far from the two strains. MCCM 00189 had a different node， and was clustered on another branch together with another British isolate serovar 8 （GenBank accession number： LN908249.1）. The two shared very low homology， but had a common node， indicating that they might be evolved from the same strain long ago， and come from the same source. The two Swiss strains， N273 （GenBank accession number： AF302255.1） and HS143 （GenBank accession number： AY017472.1） shared 94% homology， and were genetically clustered together with Japanese strain QAS106 （GenBank accession number： AB635380.1） into one branch， suggesting that the bacterial type had crossevolution between the Asian continent and the European continent. Among these strains sharing higher homology， strains from different regions also existed. For instance， serovar7 str.AP76 from Germany （GenBank accession number： CP001091.1） and serovar3str.JL03 from China （GenBank accession number： CP000687.1） showed homology up to 95%. It is speculated that in Eurasia， the App might have evolved from an old original strain to different intercontinental types. The serotypes of the two strains are serotype 3 and serotype 7， respectively， and it is speculated that the two might be correlated in the evolution of some genes. In addition， the structure of the phylogenetic tree was complex and independent， with many branches， indicating that App has multiple variants in the subsequent evolution process， and these strains have gradually stabilized in the subsequent development process， forming strains with distinct geographical differences[7，11].

Among the branches with distant genetic relationships， the genetic relationships between various regions could not be visually seen， and the strains were in scattered distribution， which might be related to the high contact infection of App. For instance， the Nordic strain 634 （GenBank accession number： AF033058.1） was geographically distant from NCTC 8529 （GenBank accession number： NR_118760.1） and Germany ATCC 27088 （GenBank accession number： M75074.1）， but they were still clustered together， indicating that there were certain relationships[11-12].

Discussion

The App strains in the same region were the closest in genetic evolution， indicating that the strain had no strain variation caused by extensive spread worldwide， and the strain was still highly conserved in the same region[7，13]. It could be seen from the phylogenetic tree that the branch nodes of Asian countries appeared at front positions， indicating that App might be originated from the Asian continent. In the phylogenetic tree， four Chinese genotype strains were clustered into one branch， and every two of them were clustered into one small branch. It could be speculated that a certain area in China was the origin of App long ago. This indicates that the study of App strains in China can further reveal the evolution of App genes. The App genotypes from the United States had a certain relationship with the strains from Denmark and England， which are far away from the United States. This is related to the fact that the United States is a major immigrant and trade country， causing longdistance communication. Furthermore， the relationships were not very far， which showed that in hundreds of years of genetic evolution， the evolution rate of App in this place is not particularly fast， and the changes in genes are not very obvious[7，13].

It could also be found in the phylogenetic tree that some strains were geographically distant and differed in serotype， but they were clustered on the same branch， which might be due to some special factors such as migratory bird migration and artificial breeding. In addition， the strains showed high homology between Asia and Europe， and it was speculated that Appюs possible transmission pathway exists on land. In the branches of the phylogenetic tree， there were no common border areas between most countries， and it was further speculated that the evolution of bacteria might be also related to the air. Therefore， port or custom quarantine should be strengthened to prevent the spread of App in different regions[12-13].

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