Literature DB >> 22536428

Comparative genomics of Mycoplasma: analysis of conserved essential genes and diversity of the pan-genome.

Wei Liu1, Liurong Fang, Mao Li, Sha Li, Shaohua Guo, Rui Luo, Zhixin Feng, Bin Li, Zhemin Zhou, Guoqing Shao, Huanchun Chen, Shaobo Xiao.   

Abstract

Mycoplasma, the smallest self-replicating organism with a minimal metabolism and little genomic redundancy, is expected to be a close approximation to the minimal set of genes needed to sustain bacterial life. This study employs comparative evolutionary analysis of twenty Mycoplasma genomes to gain an improved understanding of essential genes. By analyzing the core genome of mycoplasmas, we finally revealed the conserved essential genes set for mycoplasma survival. Further analysis showed that the core genome set has many characteristics in common with experimentally identified essential genes. Several key genes, which are related to DNA replication and repair and can be disrupted in transposon mutagenesis studies, may be critical for bacteria survival especially over long period natural selection. Phylogenomic reconstructions based on 3,355 homologous groups allowed robust estimation of phylogenetic relatedness among mycoplasma strains. To obtain deeper insight into the relative roles of molecular evolution in pathogen adaptation to their hosts, we also analyzed the positive selection pressures on particular sites and lineages. There appears to be an approximate correlation between the divergence of species and the level of positive selection detected in corresponding lineages.

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Year:  2012        PMID: 22536428      PMCID: PMC3335003          DOI: 10.1371/journal.pone.0035698

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Mycoplasmas are widespread in nature as parasites of humans, mammals, reptiles, fish, arthropods, and plants [1]. As a conditional pathogenic organism, it associates with various diseases, including pneumonia, arthritis, meningitis and chronic urogenital tract disease [2]. Although they are the smallest self-replicating organisms, both commensal forms and pathogenic forms are diverse. With a minimal metabolism and little genomic redundancy, the genome of Mycoplasma is expected to be a close approximation to the minimal set of genes needed to sustain bacterial life [3]. An early projection proposed a minimal gene set composed of 206 genes based on the analysis of eight free-living and endosymbiotic bacterial genomes [4]. More recently, Glass et al. [5] performed a global transposon mutagenesis study and identified 100 putatively nonessential genes in M. genitalium. Logically, the remaining 387 genes presumably constitute the set of essential genes. However, these data greatly exceed theoretical projections of how many genes comprise a minimal genome, as proposed by Gil et al. [4]. Natural selection leads to the fixation of essential genes and can delete nonessential genes in a wide range of species [6], [7]. This process is similar, but more robust than manual mutagenesis studies. Through long term evolution form a more conventional progenitor in the Firmicutes taxon [8], Mycoplasmas have undergone a process of massive genome reduction [1]. These wall-less bacteria are obligate parasites that live in relatively unchanging niches requiring little adaptive capability. M. genitalium, a human urogenital pathogen, is the extreme manifestation of this genomic parsimony, having only 482 protein-coding genes and the smallest genome of any known free-living organism capable of being grown in axenic culture [9]. Thus, with little genomic redundancy and contingencies for different environmental conditions, Mycoplasmas are regarded as optimal microbes to perform genes essentiality studies [5]. Along with the burgeoning increase in Mycoplasma genome sequence data, this would appear to be the right time to explore gene essentiality from a comparative genomics perspective. An enormous genetic diversity exists in the mycoplasmas, yet how much diversity is functional, and what are the important adaptations that serve to partition species into different niches? M. hyopneumoniae and M. hyorhinis are the causal agents of swine mycoplasmosis. The former causes a mild, chronic pneumonia of swine and results in deactivation of mucociliary functions [10]. This agent is infective for a single host species, but the mechanisms of host specificity are unknown. The latter is responsible for respiratory tract and arthritis disease in swine [1]. M. hyorhinis is generally considered a swine pathogen, yet is most commonly infect laboratory cell lines, implying that it can thrive among different species of cell lines [11]. A strong link between M. hyorhinis and human cancer was reported recently by Huang et al. [12], who used a monoclonal antibody against the unique M. hyorhinis–specific protein p37 to detect mycoplasma in over 600 carcinoma tissues from a variety of organs. The study indicated that up to 56% of gastric carcinoma and 55% of colon carcinoma biopsies were positive for M. hyorhinis [12]. With a similar genome size, M. hyorhinis and M. hyopneumoniae exhibit high levels of functional diversity. Interest has therefore shifted to questions of why M. hyorhinis can thrive among different species of cell lines. This paper communicates the results of three major analyses. In the first analysis, we present the details of a comparative analysis of twenty Mycoplasma strains and investigate the conserved essential genes set for mycoplasma survival. For the second analysis, phylogenomic reconstructions based on 3,355 homologous groups allows robust estimation of phylogenetic relatedness among mycoplasma strains. The third analysis employs the branch-site method to assess positive selection pressures on particular sites and lineages. There appears to be an approximate correlation between the divergence of species and the level of positive selection detected in corresponding lineages.

Results

Diversity of Mycoplasmataceae family: core genome vs. flexible gene pool

The number of protein coding genes per genome within the various strains and species of mycoplasmas is relatively similar (ranging from 475 to 1,037; Table 1), but the gene composition of these genomes is much more variable. Based on the gene content table (obtained as described in Materials and Methods; Table S1), three M. hyopneumoniae strains share about 95% of their genes, and three different species of mycoplasmas share only around 71% of their genes (Figure 1). This latter result appears to be independent of the particular strains or species involved in the comparison. Even with the inclusion of 20 genomes, the pan-genome size of Mycoplasmas appears not to be determined, and we estimate that the size probably surpasses 8,000 genes. This huge pan-genome size may be a reflection of their different lifestyles in distinct ecological niches. Within species, the pan-genome size also remains uncertain, although our estimates suggest that the pan-genome size of M. hyopneumoniae is smaller.
Table 1

Bacterial Strains Used in This Study.

Mollicute strainsHostCDSGenome size (bp)AccessionCitation
U. urealyticum serovar 10 str. ATCC 33699 Human646874478CP001184-
U. parvum serovar 3 str. ATCC 700970 Human611751719AF222894 [45]
U. parvum serovar 3 str. ATCC 27815 Human609751679CP000942-
M. synoviae 53 Bird659799476NC_007294 [46]
M. pulmonis UAB CTIP Rodent-963879AL445566 [47]
M. pneumoniae M129 Human688816394U00089 [48]
M. penetrans HF-2 Human10371358633BA000026 [49]
M. mycoides subsp. mycoides SC str. PG1 Ruminant10161211703BX293980 [50]
M. mobile 163K Fish635777079AE017308 [51]
M. hyorhinis HUB-1 Swine658839615NC_014448 [52]
M. hyopneumoniae J Swine657897405NC_007295 [46]
M. hyopneumoniae 7448 Swine657920079NC_007332 [46]
M. hyopneumoniae 232 Swine691892758NC_006360 [53]
M. genitalium G37 Human475580076NC_000908 [5]
M. gallisepticum str. R(low) Bird7631012800AE015450 [54]
M. crocodyli MP145 Crocodile689934379CP001991-
M. conjunctivae HRC Sheep and goats696846214FM864216 [55]
M. capricolum subsp. ATCC 27343 Ruminant8121010023CP000123-
M. arthritidis 158L3-1 Rats and mice631820453NC_011025 [56]
M. agalactiae PG2 Sheep and goats759877438CU179680-
Figure 1

Venn diagram for two sets of three taxa.

Above are taxa of the same species and below are taxa of different species. The surfaces are approximately proportional to the number of genes.

Venn diagram for two sets of three taxa.

Above are taxa of the same species and below are taxa of different species. The surfaces are approximately proportional to the number of genes. The extent of the pan-genome is opposed to the core. Genes that are in common between the different species within the family Mycoplasmataceae comprised our core genome - the set of orthologous genes determined the common properties of this family. In this work, the tribeMCL program was used to cluster orthologous genes, and a total of 13,654 predicted proteins were grouped into 3,355 clusters, each cluster representing a group of putative orthologs. The 1,481 genes that are present in single genomes (Figure 2) represent lineage specific genes. In addition, the 196 genes shared by all the 20 strains comprised our core genome (Figure 3).
Figure 2

Frequency of genes within the 20 genomes included in this analysis.

Genes present in a single genome represent lineage specific genes, while at the opposite end of the scale, genes found in all 20 genomes represent the Mycoplasma core genome.

Figure 3

Viable core and pan genes distribution in the M. hyorhinis HUB-1 map.

The M. hyorhinis HUB-1 genome is shown at a scale of 100 kb per line. Colored arrows above the line indicate annotated genes. Genes are colored according to their functional category, as indicated in the key. rRNAs and tRNAs are denoted by red and purple rectangles, respectively. Red triangles above the line represent the core genes of Mycoplasmataceae. Blue triangles above the line represent the genes shared by all the species in clade III, but which are absent from other lineages. Black triangles below the line represent the disrupted genes documented in M. genitalium G37, mapped onto the M. hyorhinis HUB-1 genome [5].

Frequency of genes within the 20 genomes included in this analysis.

Genes present in a single genome represent lineage specific genes, while at the opposite end of the scale, genes found in all 20 genomes represent the Mycoplasma core genome.

Viable core and pan genes distribution in the M. hyorhinis HUB-1 map.

The M. hyorhinis HUB-1 genome is shown at a scale of 100 kb per line. Colored arrows above the line indicate annotated genes. Genes are colored according to their functional category, as indicated in the key. rRNAs and tRNAs are denoted by red and purple rectangles, respectively. Red triangles above the line represent the core genes of Mycoplasmataceae. Blue triangles above the line represent the genes shared by all the species in clade III, but which are absent from other lineages. Black triangles below the line represent the disrupted genes documented in M. genitalium G37, mapped onto the M. hyorhinis HUB-1 genome [5].

Functional Characterization of the Core Genome

The use of the core genome concept has led to important insights into the evolution of bacterial species and identification of potentially important novel genes [13]. In terms of functional assignments according to COGs, almost half (42.3%) of the proteins observed from the core genome are devoted to translation, ribosomal structure, and biogenesis (Figure S1). Our results support the analysis of Ouzounis and Kyrpides [14], who demonstrated that genetic processes such as translation are conserved and close to the original form. Strikingly, 10.6% of the observed core genes have resisted functional assignments according to COGs classification (Table S2), which highlights the need for better functional characterization of these genes. Furthermore, by comparing functional categories of the core genome with the categories of the genome of M. hyorhinis HUB-1, we noticed that a large array of proteins devoted to amino acid, carbohydrate transport and metabolism, as well as defense mechanisms, were sharply reduced. Our results support the analysis of Fraser et al. [9] and Himmelreich et al. [15], who demonstrated that both M. genitalium and M. pneumoniae lost all the genes involved in amino acid synthesis, and their survival is totally dependent on an exogenous supply of the complete spectrum of amino acids. Beyond this, the pronounced reduction of those functional categories observed in the core genome might be the further genetic evidence for gene loss in M. genitalium and M. pneumonia [9], [15].

Persistent Nonessential Genes vs. Essential Genes

Identification of the core genome has important implications for a broad range of microbiological applications, such as determining the essentiality of genes derived from the core genome and deriving traits that correspond to a common ancestor (orthology) [4]. In this work, we classified the core genome into two classes according to persistence and essentiality: persistent nonessential genes and conserved essential genes (Figure 3). Glass et al. [5] performed a global transposon mutagenesis study and identified 100 putatively nonessential genes in M. genitalium. We mapped those nonessential genes onto the M. hyorhinis HUB-1 genome and 24 of them were persistent among Mycoplasma genomes. Focusing on gene persistence, the essentiality of a gene is relative to a set of experimental conditions. It is quite different for a cell to survive in a laboratory setting, with plenty of supplied metabolites, compared to thriving in the wild, where it competes with other organisms for limited resources. Starvation or stresses are omnipresent, and the fitness effect of persistent genes may be essential for survival under transition from one environmental condition to another [16]. After transposon mutagenesis, disrupted genes may not be essential for growth in rich media, but their loss may lead to such a low fitness that its deletion will never be fixed in natural populations [16]. For example, Glass et al. [5] isolated six mutants involved in recombination and DNA repair: recA, recU, Holliday junction DNA helicases uvrA and uvrB, formamidopyrimidine-DNA glycosylase mutM, which excises oxidized urines from DNA, and a likely DNA damage inducible protein gene. Interestingly, we noticed that these six disrupted genes occur in the core genome set, which suggests that these disrupted persistent genes might be critical for growth in variable environments over long periods. The survival of these mutants is probably due to their tolerances of IS element within a relatively short period. According to Glass et al., these six mutants grew more poorly after repeated passage, which indicates that those genes are also critical for bacterial survival [5]. Our results in this regard generally agree with the analysis by Glass et al. This analysis prompted us to explore gene essentiality by combining both the experimental approaches and comparative genomics analysis.

Genome-Based Reconstruction of Mycoplasmataceae Phylogeny

We constructed robust phylogenies for the family Mycoplasmataceae based on whole genome analysis. The supertree contains five major, distinct clades (Figure 4). In clade I, three Ureaplasma strains with a common host are clustered on a single branch. In clade II, six mycoplasma species (M. pulmonis etc.) with various lifestyles formed the cluster. In clade III, the strain HRC appears adjacent to strain HUB-1 and three isolates of M. hyopneumoniae strains are clustered closely, indicative of a recent common ancestry. In clade IV, M. capricolum and M. mycoides are clustered closely on a single branch and both of them are the agents of ruminant mycoplasmosis. In clade V, M. genitalium and M. pneumoniae are closely related, together with M. penetrans and M. gallisepticum, forming the cluster.
Figure 4

Phylogenetic tree of Mycoplasmataceae.

The phylogenetic relationship was estimated and tested in one thousand bootstrap samples using TREE-PUZZLE version 5.2 with a BIONJ model (see Materials and Methods). This supertree shows five major distinct clades. The four lineages that were used as foreground in the branch-site model positive selection test are highlighted in red.

Phylogenetic tree of Mycoplasmataceae.

The phylogenetic relationship was estimated and tested in one thousand bootstrap samples using TREE-PUZZLE version 5.2 with a BIONJ model (see Materials and Methods). This supertree shows five major distinct clades. The four lineages that were used as foreground in the branch-site model positive selection test are highlighted in red. Although single gene trees have been used extensively to estimate the species tree, evidence has shown that single gene trees may have particular difficulty in representing prokaryotic species phylogeny, because lateral gene transfer (LGT) occurs among prokaryotic genomes, and LGT may obscure the phylogenetic signal [17]. In this work, the 16S rRNA-based phylogeny has also been reconstructed for the family Mycoplasmataceae (Figure 5), which shows almost the same topology as the supertree. However, these two trees differ in the placement of M. penetrans HF-2 and M. mobile 163.
Figure 5

16S rRNA tree of Mycoplasmataceae.

This consensus tree of 100 bootstrap replications was constructed based on 16S rRNA sequences using the Neighbor Joining (NJ) method implemented in MEGA 4.1. The bootstrap values are marked at the root of each branch.

16S rRNA tree of Mycoplasmataceae.

This consensus tree of 100 bootstrap replications was constructed based on 16S rRNA sequences using the Neighbor Joining (NJ) method implemented in MEGA 4.1. The bootstrap values are marked at the root of each branch. A recent study proposed that the “Tree of Life” may be resolved by concatenation of 31 orthologs occurring in 191 species [18], and an analogous approach has been applied to infer Mycoplasmas phylogeny by random concatenation of 91 protein sequences shared by 16 mollicutes [19]. The placement of M. penetrans in the concatenation-based phylogeny is consistent with the supertree (Figure 4).

Positive Selection Analysis

We employed the branch-site test of Yang and Nielsen [20], [21] implemented in the program HY-PHY (http://www.datam0nk3y.org/hyphy/doku.php) to assess positive selection [22], [23] at particular sites in particular lineages. This method compares synonymous and nonsynonymous substitution rates in protein coding genes and regards a nonsynonymous rate elevated above the synonymous rate as evidence for positive selection. For the Mycoplasma data set, both swine-infecting and human-infecting lineages were tested. The branches we tested are highlighted in red on Figure 4. In the four swine-infected lineages (HUB-1 lineage, MC lineage, MH lineage, and the common ancestor of clade III), 661 orthologous groups shared by all species in clade III were tested. A total of 23 genes were identified to be under positive selection (Table 2). These genes were assigned to functional categories according to the COG database. We found that a large fraction of the genes subject to positive selection were connected to DNA replication, recombination, and repair. Successful genome replication is essential for growth and survival of an organism, and polymerase complexes often fail to complete this task [24]. Also, replication is thought to contribute to proliferation and efficiency of the colonization of hostile environments [25]. Interestingly, we detected that positive selection occurs in the both of the dnaA and dnaN genes, which comprise the oriC region in M. hyorhinis, and in several copies of proteins connected to replication, recombination and repair in both MC lineage and the common ancestor of clade III. Selection pressure on these genes could reflect constraints on efficient genome replication during colonization and proliferation in the hostile environment of the host [25].
Table 2

Genes under Positive Selection in Swine-infecting Lineages.

LineageGenedN/dSa Sequence %COG(s)Product
MH Lineage mhp623543.87116.60%COG1744RABC transporter
mhp388306.0295.00%COG3037Sascorbate-specific PTS system enzyme IIC
mhp6034.420.00%COG0195Ktranscription elongation factor NusA
mhp3684.7739.70%COG0531Eputative membrane lipoprotein
mhp595515.57713.40%COG0266Lformamidopyrimidine-DNA glycosylase
mhp4801913.8215.20%-hypothetical protein
MC Lineage MCJ_005740525.9559.30%COG1196Dputative ABC transporter ATP-binding protein P
MCJ_003040547.0977.90%COG0013Jalanyl-tRNA synthetase
MCJ_007160227.3578.10%COG2176LDNA polymerase III PolC
MCJ_002410488.4087.20%COG4608Eoligopeptide ABC transporter ATP-binding protein
MCJ_000340316.7195.10%COG0556Lexcinuclease ABC subunit B
HUB-1 Lineage MHR_00012.1227.10%COG0593LChromosomal replication initiator protein dnaA
MHR_0002786.65425.60%COG0592LDNA polymerase III beta subunit
MHR_00098.1555.50%COG0525JValyl tRNA synthetase
MHR_0132306.6247.30%COG0060JIsoleucyl tRNA synthetase
MHR_0148732.20414.30%COG0006EXaa-pro aminopeptidase
MHR_02482.6373.60%COG0187LDNA gyrase subunit B
MHR_0318180.11516.40%-ABC transporter permease protein
MHR_03776.3459.70%COG0202KDNA-directed RNA polymerase subunit alpha
MHR_044333.3977.70%COG0178LExcinuclease ATPase subunit-like protein
MHR_060914.41616.70%COG0544OTrigger factor
Common Ancester b MHR_0128133.03823.40%COG0322LExcinuclease ABC subunit C
MHR_013133.67913.50%COG0188LTopoisomerase IV subunit A
MHR_0310754.51215.80%COG2274VABC transporter ATP-binding and permease protein
MHR_048658.16412.90%COG0587LDNA polymerase III alpha subunit
MHR_04893.66929.10%COG0532JTranslation initiation factor IF-2
MHR_06398298.4631.60%-Lipoprotein
MHR_03636343.5114.00%COG1164EOligoendopeptidase F
MHR_03566343.5114.00%COG1164EOligoendopeptidase F

Ratio of the nonsynonymous to the synonomous mutation rate (dN/dS) measures the strength of selection, where values >1 indicate positive selection, and larger values indicate stronger selection.

In the common ancestor lineage: a single gene of M. hyorhinis HUB-1 was used to represent each ortholog group (Table S1). Genes of M. conjunctivae HRC and three M. hyopneumoniae strains in the same ortholog group are also under positive selection.

Ratio of the nonsynonymous to the synonomous mutation rate (dN/dS) measures the strength of selection, where values >1 indicate positive selection, and larger values indicate stronger selection. In the common ancestor lineage: a single gene of M. hyorhinis HUB-1 was used to represent each ortholog group (Table S1). Genes of M. conjunctivae HRC and three M. hyopneumoniae strains in the same ortholog group are also under positive selection. In the case of human-infecting lineages, the lineage that stood out from the rest with regard to host specificity was M. gallisepticum, which is significantly associated with chronic respiratory disease in chickens [26]. Not surprisingly, this lineage was identified to be under the strongest selection pressure in clade V (Table S3). However, we failed to notice any selection pressure on the dnaA and dnaN genes in the MG lineage. A large number of genes related to DNA repair, RNA processing, Amino acid transport and metabolism were found under positive selection. Selection pressure on these genes may facilitate evolutionary flexibility in the MG lineage, hence its ability to adapt to new environments.

Discussion

Numerous global transposon mutagenesis studies of minimal genomes have been performed to identify essential genes [5], [27]. Long-term natural selection can also delete nonessential genes in a wide range of species [6], [7], which is similar to, but more robust than, manual mutagenesis studied. With a minimal metabolism and little genomic redundancy, mycoplasmas are regarded as optimal microbes for the identification of essential genes [1]. It is believed that the Mycoplasmas evolved from a more conventional progenitor in the Firmicutes taxon by a process of massive genome reduction [16]. We found that each of the species in Mycoplasmataceae has undergone a similar process. These species have undergone various natural selection pressures in different environments. Most of the core genes remaining for such a long time should be considered as the essential genes needed by all the species within this family. Generally speaking, our comparative analysis was highly consistent with the studies by Glass et al. (Figure 6); however, we identified more genes that may have been deleted due to natural selection. The six genes differing between the two studies are all key genes of DNA replication and DNA repair: recA, recU, Holliday junction DNA helicases uvrA and uvrB, mutM and a likely DNA damage inducible protein gene. Those genes are core genes, but were disrupted in transposon mutagenesis studies [5]. Interestingly, Glass et al. stated that these six mutants grew more poorly after repeated passage, probably due to an accumulation of cell damage over time. This indicates that these six disrupted core genes may be critical for bacterial survival, especially over long periods. Therefore, we classified these genes as truly essential genes.
Figure 6

Similarity relationship between core and essential genes.

Genes on x-axis represent the essential genes documented in M. genitalium G37, while genes on y-axis represent the core genome identified in this study. Both the genes on x-axis and y-axis are distributed in terms of genomic coordinates. On-diagonal, genes that are both essentials and core are indicated as a series of colored dots.

Similarity relationship between core and essential genes.

Genes on x-axis represent the essential genes documented in M. genitalium G37, while genes on y-axis represent the core genome identified in this study. Both the genes on x-axis and y-axis are distributed in terms of genomic coordinates. On-diagonal, genes that are both essentials and core are indicated as a series of colored dots. Although transposon mutagenesis has proven to be a useful method and has been used extensively to determine the essentiality of genes [27], this method is highly dependent on environmental conditions. For the most part, mutagenesis studies performed under nutrient-rich conditions provide a substantial underestimate of the number of genes that are essential under host environmental conditions [28]. In reality, it is quite different for a cell to survive in a laboratory setting and to thrive in the wild. Transposon mutagenesis might misclassify nonessential genes that slow growth without arresting it but can also miss essential genes that tolerate transposon insertions [4]. However, comparative genomics analysis has also limitations, since it is likely to underestimate the core genome because it takes into account only the genes that have remained similar enough during the course of evolution to be recognized as true orthologues. Therefore, it will not include genes with a high rate of evolution, which may not show their relationship in comparisons of distant taxons [4]. Taken together, both the experimental approaches and comparative genomics analysis should be taken into account when addressing questions of essentiality. Besides, the core genes set proposed in the current study are only essential for most species within this family. We failed to estimate the conserved genes needed for single species. Each member of a particular species was maintained in a distinct ecological niche, in which some of the genes that were not present in core genome may also be important for the mycoplasma survival. These genes may be termed “lineage specific” essential genes. As more genome sequence becomes available in the future, there will be an opportunity to explore more properties of species special core genes set using comparative genomic tools. To date, most mycoplasma phylogenies have been derived from single gene comparisons, or from concatenated alignments of a small number of genes. The increasing availability of mycoplasma genomes presents an opportunity to reconstruct evolutionary events using entire genomes [29], [30]. As a tool for future comparative phylogenetic studies, we used both supertrees and single gene alignments to infer relationships between 20 strains of the family Mycoplasmataceae. Our supertree and 16S rRNA phylogenies are consistent in most of their branches. However, there are conflicts regarding whether M. penetrans is clustered with the Ureaplasma lineage or with Clade V, as well as the placement of M. mobile 163. We also compared our trees with a recent study, in which the phylogeny of the Mycoplasmas was reconstructed by random concatenation of 91 protein sequences shared by 16 mollicutes [19]. The placement of M. penetrans in the concatenation-based phylogeny is consistent with the supertree, while the bootstrap value ( = 62) of the branch of M. penetrans and Ureaplasma in the 16S rRNA tree is low. Therefore, we placed M. penetrans into clade V. The location of M. mobile 163 is different among all three trees, which indicates a complicated phylogenic history for this strain, which may have involved recombination or other LGT events. Phylogenetic reconstruction based upon concatenation of multiple orthologous genes can generate a more accurate tree than that done with a single gene [31], [32]. The supertree is even better than the concatenation-based tree, because it is immune to long-branch attraction artifacts [33], [34]. Thus, a robust supertree was constructed in this study to present the phylogeny of the family Mycoplasmataceae. The supertree was then used as a foreground for further analysis. Based on the supertree of Mycoplasmataceae, we classified these twenty strains into five different clades, between which the host specificity varies. All three strains in Clade I and three of the four strains in Clade V (except M. gallisepticum) were identified to be agents of human infection; therefore, these two clades form the human-infecting lineage. Both of the two sequenced strains in clade IV are the agent of ruminant infection, and thus represent the ruminant-infecting lineage. Four of the five strains in Clade III (except M. conjunctivae) are associated with swine mycoplasmosis and form the swine-infecting lineage. Briefly, most species with the same host specificity clustered together, forming a separate clade. There appears to be an approximate correlation between the divergence of species and the level of positive selection detected in different lineages. We suspect that host specificity was determined after the emergence of Mycoplasma species. Subsequent host jumping events may have been caused by a series of natural selection events during evolution. To gain deeper insights into the molecular evolution events underlying natural selection, we employed the branch-site method to assess positive selection in swine-infecting and human-infect lineages. According to Petersen et al. [35], two categories of genes, immune-related and environmental adaptation related genes, are expected to show strong evidence for positive selection. Our analysis revealed that a number of genes related to DNA replication and repair (dnaA, dnaN, gyrB, uvrA, polC, uvrB, uvrC, parC, dnaE), show remarkably strong evidence for positive selection. These genes were unevenly distributed across HUB-1, the MC lineage and the common ancestor of clade III. Notably, both the dnaA and dnaN genes, which compose the oriC region, were identified to be under positive selection in the HUB-1 lineage. Previous studies have already demonstrated that replication may contribute to proliferation and efficiency of the colonization of hostile environments [25]. Therefore, we suspected that selection pressure on oriC may be one of the reasons why M. hyorhinis can thrive among different species of cell lines. This research provides a better insight into, and understanding of, persistent nonessential genes, and encourages exploration of essential genes by combining both the experimental approaches and comparative genomics analysis. This study also provides a comparative genomics method for addressing questions of essentiality. With the increasing number of genome sequences available for the same species in the future, this method will be useful for exploring species-specific essential genes.

Materials and Methods

Bacterial Strains and Genome Sequences

M. hyorhinis strain HUB-1 was isolated from the respiratory tract of swine in China and confirmed to be an M. hyorhinis strain by verifying the 16S rRNA region. The main characteristics of 20 Mycoplasmas strains with freely available genomes at the time of the study are presented in Table 1. These genomes were used for comparative analysis.

Assignment of Orthologs and Phylogenetic Analysis

We analyzed M. hyorhinis HUB-1 and 19 other Mycoplasmataceae genomes from the NCBI databases. To ensure consistency, the annotations of all genomes were verified based on the similarity with M. hyorhinis HUB-1, using the tBLASTn algorithm [36]. The sets of orthologous protein-coding genes were defined as mutual fully transitive reciprocal BLASTP [37] hits (with E-value<10−4) [38]. Co-ortholog groups were identified by the method similar to Inparanoid [39] and ortholog gene clusters were obtained using the tribeMCL program [40]. The nucleic acid sequence of each ortholog group was aligned using the CLUSTALW program version 1.83 [41]. For each data set, the phylogenetic relationship was estimated and tested in one thousand bootstrap samples using TREE-PUZZLE version 5.2 (general time reversible (GTR) +Γ4+I model of evolution with a BIONJ starting tree) [42]. The bi-partitions with at least 70% support from the bootstrap test in each data set were recorded as “0/1” status and used to reconstruct the consensus sequence. The phylogenetic relationship of the consensus sequence was built using the SplitsTREE 4 with the BioNJ model.

Positive selection analysis

We employed the branch-site test of Yang and Nielsen [20], implemented in the program HY-PHY, to assess positive selection at particular sites and lineages. Briefly, the likelihood of a model that does not allow positive selection is compared to one allowing positive selection on some specified lineages. The model allowing positive selection is tested using a likelihood ratio test (LRT) [43] that is compared to a χ2 statistic with two degrees of freedom. Likelihoods were estimated on the genes or species trees. For the Mycoplasma data set, both swine-infecting and human-infecting lineages were tested (Figure 4). To avoid the interference of recombination, only genes that support all four lineages in their gene trees (with >70% bootstrap support) were used. In total, 661 genes were tested. Finally, p values were corrected for multiple hypotheses testing using the Bonferroni method [44]. Comparison of COG Distribution in the Core Genome and in M. hyorhinis HUB-1. (TIF) Click here for additional data file. Gene Content Table: Composition of Each Gene Cluster per Genome. (XLS) Click here for additional data file. Characteristics of the Core Genome Identified in the Family Mycoplasmataceae. (XLS) Click here for additional data file. Genes under Positive Selection in the Human-infecting Lineage. (XLS) Click here for additional data file.
  56 in total

1.  The complete genome sequence of the murine respiratory pathogen Mycoplasma pulmonis.

Authors:  I Chambaud; R Heilig; S Ferris; V Barbe; D Samson; F Galisson; I Moszer; K Dybvig; H Wróblewski; A Viari; E P Rocha; A Blanchard
Journal:  Nucleic Acids Res       Date:  2001-05-15       Impact factor: 16.971

2.  A phylogenomic approach to bacterial phylogeny: evidence of a core of genes sharing a common history.

Authors:  Vincent Daubin; Manolo Gouy; Guy Perrière
Journal:  Genome Res       Date:  2002-07       Impact factor: 9.043

3.  Comparative analysis of the genome sequences of Bordetella pertussis, Bordetella parapertussis and Bordetella bronchiseptica.

Authors:  Julian Parkhill; Mohammed Sebaihia; Andrew Preston; Lee D Murphy; Nicholas Thomson; David E Harris; Matthew T G Holden; Carol M Churcher; Stephen D Bentley; Karen L Mungall; Ana M Cerdeño-Tárraga; Louise Temple; Keith James; Barbara Harris; Michael A Quail; Mark Achtman; Rebecca Atkin; Steven Baker; David Basham; Nathalie Bason; Inna Cherevach; Tracey Chillingworth; Matthew Collins; Anne Cronin; Paul Davis; Jonathan Doggett; Theresa Feltwell; Arlette Goble; Nancy Hamlin; Heidi Hauser; Simon Holroyd; Kay Jagels; Sampsa Leather; Sharon Moule; Halina Norberczak; Susan O'Neil; Doug Ormond; Claire Price; Ester Rabbinowitsch; Simon Rutter; Mandy Sanders; David Saunders; Katherine Seeger; Sarah Sharp; Mark Simmonds; Jason Skelton; Robert Squares; Steven Squares; Kim Stevens; Louise Unwin; Sally Whitehead; Bart G Barrell; Duncan J Maskell
Journal:  Nat Genet       Date:  2003-08-10       Impact factor: 38.330

4.  Global transposon mutagenesis and a minimal Mycoplasma genome.

Authors:  C A Hutchison; S N Peterson; S R Gill; R T Cline; O White; C M Fraser; H O Smith; J C Venter
Journal:  Science       Date:  1999-12-10       Impact factor: 47.728

5.  Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level.

Authors:  Jianzhi Zhang; Rasmus Nielsen; Ziheng Yang
Journal:  Mol Biol Evol       Date:  2005-08-17       Impact factor: 16.240

6.  Complete sequence analysis of the genome of the bacterium Mycoplasma pneumoniae.

Authors:  R Himmelreich; H Hilbert; H Plagens; E Pirkl; B C Li; R Herrmann
Journal:  Nucleic Acids Res       Date:  1996-11-15       Impact factor: 16.971

7.  The genome sequence of Mycoplasma mycoides subsp. mycoides SC type strain PG1T, the causative agent of contagious bovine pleuropneumonia (CBPP).

Authors:  Joakim Westberg; Anja Persson; Anders Holmberg; Alexander Goesmann; Joakim Lundeberg; Karl-Erik Johansson; Bertil Pettersson; Mathias Uhlén
Journal:  Genome Res       Date:  2004-02       Impact factor: 9.043

8.  Patterns of positive selection in six Mammalian genomes.

Authors:  Carolin Kosiol; Tomás Vinar; Rute R da Fonseca; Melissa J Hubisz; Carlos D Bustamante; Rasmus Nielsen; Adam Siepel
Journal:  PLoS Genet       Date:  2008-08-01       Impact factor: 5.917

9.  Complete genome sequence and comparative genome analysis of enteropathogenic Escherichia coli O127:H6 strain E2348/69.

Authors:  Atsushi Iguchi; Nicholas R Thomson; Yoshitoshi Ogura; David Saunders; Tadasuke Ooka; Ian R Henderson; David Harris; M Asadulghani; Ken Kurokawa; Paul Dean; Brendan Kenny; Michael A Quail; Scott Thurston; Gordon Dougan; Tetsuya Hayashi; Julian Parkhill; Gad Frankel
Journal:  J Bacteriol       Date:  2008-10-24       Impact factor: 3.490

10.  Comparing patterns of natural selection across species using selective signatures.

Authors:  B Jesse Shapiro; Eric J Alm
Journal:  PLoS Genet       Date:  2008-02       Impact factor: 5.917

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  27 in total

1.  Analysis of pan-genome to identify the core genes and essential genes of Brucella spp.

Authors:  Xiaowen Yang; Yajie Li; Juan Zang; Yexia Li; Pengfei Bie; Yanli Lu; Qingmin Wu
Journal:  Mol Genet Genomics       Date:  2016-01-02       Impact factor: 3.291

Review 2.  Minimal Cells-Real and Imagined.

Authors:  John I Glass; Chuck Merryman; Kim S Wise; Clyde A Hutchison; Hamilton O Smith
Journal:  Cold Spring Harb Perspect Biol       Date:  2017-12-01       Impact factor: 10.005

3.  An outbreak of Mycoplasma mycoides subspecies capri arthritis in young goats: a case study.

Authors:  Gayle C Johnson; William H Fales; Brian M Shoemake; Pamela R Adkins; John R Middleton; Fred Williams; Mike Zinn; W Jeff Mitchell; Michael J Calcutt
Journal:  J Vet Diagn Invest       Date:  2019-03-11       Impact factor: 1.279

Review 4.  Mycoplasmas as Host Pantropic and Specific Pathogens: Clinical Implications, Gene Transfer, Virulence Factors, and Future Perspectives.

Authors:  Ali Dawood; Samah Attia Algharib; Gang Zhao; Tingting Zhu; Mingpu Qi; Kong Delai; Zhiyu Hao; Marawan A Marawan; Ihsanullah Shirani; Aizhen Guo
Journal:  Front Cell Infect Microbiol       Date:  2022-05-13       Impact factor: 6.073

5.  Coevolution of the translational machinery optimizes initiation with unusual initiator tRNAs and initiation codons in mycoplasmas.

Authors:  Shreya Ahana Ayyub; Divya Dobriyal; Riyaz Ahmad Shah; Kuldeep Lahry; Madhumita Bhattacharyya; Souvik Bhattacharyya; Saikat Chakrabarti; Umesh Varshney
Journal:  RNA Biol       Date:  2017-09-29       Impact factor: 4.652

6.  Identification of the Treponema pallidum subsp. pallidum TP0092 (RpoE) regulon and its implications for pathogen persistence in the host and syphilis pathogenesis.

Authors:  Lorenzo Giacani; Oleg Denisenko; Martin Tompa; Arturo Centurion-Lara
Journal:  J Bacteriol       Date:  2012-12-14       Impact factor: 3.490

7.  Streamlining and core genome conservation among highly divergent members of the SAR11 clade.

Authors:  Jana Grote; J Cameron Thrash; Megan J Huggett; Zachary C Landry; Paul Carini; Stephen J Giovannoni; Michael S Rappé
Journal:  MBio       Date:  2012-09-18       Impact factor: 7.867

8.  Short and long-term genome stability analysis of prokaryotic genomes.

Authors:  Matteo Brilli; Pietro Liò; Vincent Lacroix; Marie-France Sagot
Journal:  BMC Genomics       Date:  2013-05-08       Impact factor: 3.969

9.  A pan-genome method to determine core regions of the Bacillus subtilis and Escherichia coli genomes.

Authors:  Granger Sutton; Gary B Fogel; Bradley Abramson; Lauren Brinkac; Todd Michael; Enoch S Liu; Sterling Thomas
Journal:  F1000Res       Date:  2021-04-13

10.  Development of New PCR Assay with SYBR Green I for Detection of Mycoplasma, Acholeplasma, and Ureaplasma sp. in Cell Cultures.

Authors:  Jolanta Krzysztoń-Russjan; Jakub Chudziak; Małgorzata Bednarek; Elżbieta Lidia Anuszewska
Journal:  Diagnostics (Basel)       Date:  2021-05-14
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