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This review summarizes the most important reports about Pseudomonas aeruginosa pangenome. Pan-genomics has tackled some fundamental concerns in pathogenic bacteria. PATRIC and other databases, store more than 9000 P. aeruginosa genomes. This data mining is an opportunity to develop discoveries related to antibiotic resistance, virulence, pathogenicity, fitness, and evolution, among others. Observing the different pangenomes of P. aeruginosa, it is concluded that this species has an open pangenome, and its accessory genome is larger than the central genome. HGT is one important source for P. aeruginosa genome. In recent years various authors developed P. aeruginosa pangenomes, from works with five genomes to more than 1300 genomes. This last work analyzed 54,272 genes, and they found a short and tiny core genome (only 665 genes). Other research with lesser strains or genomes identified a core genome bigger, almost 20% of the pangenome. Nevertheless, the total work proves that the accessory plus unique genome is larger than the core genome in P. aeruginosa.
GEBIOMIC Group, FCEN, University of Antioquia, Medellín, Colombia
Juan David Patiño-Salazar
GEBIOMIC Group, FCEN, University of Antioquia, Medellín, Colombia
Diana Carolina Castaño
GEBIOMIC Group, FCEN, University of Antioquia, Medellín, Colombia
Amalia Muñoz-Gómez
GEBIOMIC Group, FCEN, University of Antioquia, Medellín, Colombia
*Address all correspondence to: mauricio.corredor@udea.edu.co
1. Introduction
Pan-genomics/pangenomics is an innovative tool to explain pan-genome/pangenome construction throughout the species, which is resolved with comparative genomics, among others. Pangenome is divided into two main classes: the core and accessory genomes. Thousands of unknown bacteria and microorganisms are exposed to natural and manufactured antibiotics, toxins, and harmful compounds, to the highest and lowest temperatures, extreme pHs, and other species competitors. Pangenomics is too a powerful approach to identifying those thousands of involved genes. Virulent genes, phenotypes, and environmental expressed genes from horizontal transference (HGT) derive from the core or accessory genome. These latest concepts are a challenge as a new point of view to face Pseudomonas aeruginosa: a new pathosystem, multidrug-resistant, and old human pathogen. To delve more specifically into pangenomics and pangenome, there have been published two remarked books recently [1, 2].
Different authors and web-published pangenomes’ P. aeruginosa [3, 4, 5, 6, 7] https://pangenome.org/Pseudomonas_aeruginosa): However, other valuable databases stocked P. aeruginosa genomes (https://www.pseudomonas.com/ or https://patricbrc.org/search/?and(keyword(Pseudomonas),keyword(aeruginosa)) with complete and draft 9954 genomes). These authors published different pangenomes using varying amounts of P. aeruginosa genomes: Sharma et al. [3] used 5 genomes, Fischer et al. [5] used 100 genomes, Ding et al. [7] used 153 genomes on the web page, Mosquera-Rendón et al. [4] used 181 genomes, and Freschi et al. [6] used 1311 genomes. We will see in the following subtitles, which will be the best amount of genomes to reach one open and close pangenome.
In the pangenome, the core or central genome is the total of genes common to all the examined and analyzed genomes from a genome pool of a given species. Likewise, this represents the genes present in the overall strains from one species. On the other hand, accessory, variable or flexible genome (for some authors, dispensable genome) represents the genes that do not present in all strains of one species [8], http://www.metagenomics.wiki/pdf/definition/pan-genomeb [9, 10]. Those terms are the key in pangenomics to reach a significant pangenome into some species. Moreover, the next sections will see the robustness degree or gene orthology analysis to have a core and accessory genome.
Concomitantly, multiple pangenomic tools were developed and tested over the last ten years. Of course, we can start from genomics annotation if we do not want to use the available databases since classical pangenomics use only annotated genes and orthology analysis. We will mention some of them because it is sure the high amount of pangenomics tools available today. Furthermore, now database strategy, currently developed to perform via a personal server [11], there are now online resources that allow to quickly build own pangenome analysis see Table 1.
List of some pangenomics tools. After publication, some addresses were inactivated. To obtain unavailable tools, please to contact the corresponding author from the references. More than 40 pangenomic tools are now available in online platforms or for local applications [12].
The pangenomic technique requires at least two or multiple genomes of bacteria, archaea, fungi, or any eukaryote. This tool can provide the broadest resolution of genetic variation, among them: pathogenicity islands, virulence genes, mobile elements, transposons, horizontal gene transfer, pathogenicity islands, orthologous shared and syntheny, plasticity, evolution, and others. The development of pangenomics has promoted advances in many fields, like bioinformatics and computational biology, comparative genomics, molecular medicine, molecular epidemiology, agronomy and foods, and many more [18]. In the beginning, one advantage of pangenomics was that experimental data have shown for some species that new genes are being discovered even after sequencing several strain genomes [19]. Given that, the number of unique genes is vast, the pangenome of a bacterial species might be orders of magnitude larger than any single genome, as predicted by [20], more than 14 years ago.
The connection between the core and accessory genome put together the close and open pangenome inside the species. Open pangenome increases when new genomes are added, contrary to a close when a new genome added does not increase the size of the pangenome [10]. Table 2 summarizes the terms applied to pangenome and pangenomics. It is worth mentioning that the term coined “unique genome”, is related to solitary genes not shared among strains.
Terminology
Description
Pangenome or Pan-genome
It is the gene collection from a genomes group of species or strain group. Also, the complete gene set of all strains of a species, including genes present in all strains (core genome) plus genes present only in some strains of a species (variable or accessory genome).
Core or Central genome
It is the maximum of genes common to all the examined genomes of a given species. Likewise, represent the genes present in the overall strains from one species.
Accessory or Variable genome
The variable or accessory genome (flexible, dispensable genome) refers to genes not available in all strains of a species. These include genes present in two or more strains, or even unique genes from a single strain (for some authors). For example, genes for specific strain adaptation such as antibiotic resistance. Not uniques, but not in the core genome.
Unique genome
A set of genes present in only one strain, that is never shared with other strains. Singleton is the name assigned to this kind of gene. Some authors classify singletons as accessory genomes others prefer to differentiate them.
Open pangenome
It is known as the pangenome increasing when a new genome is added to the pangenome. The number of genes of the pangenome increases with the number of additionally sequenced strains.
Closed pangenome
Finished pangenome is when there is no change when new genomes are added, after some sequenced strains, additional strains do not provide new genes to the species pangenome.
The term pan-genome, currently written today as pangenome was first used by Sigaux [21] in cancer research to describe a public database containing an assessment of genome and transcriptome alterations in types of tumors, tissues and experimental models. Later, Tettelin et al. [22], using bacterial genomes, defined a microbial pangenome as the combination of a core genome, carrying genes present in overall strains. And a dispensable genome (also described as a flexible or accessory genome) is composed of genes absent from one or more strains [23]. A generalization of such representation could contain not only the genes (transposons, promotors, other mobile elements such as HGT, microRNAs, etc., but also other variations present in the collection of genomes.
The study of bacterial pangenome has many applications in clinical microbiology, also to study resistant genes or HGTs, virulence, and pathogenicity, and finally to classify species and to know its evolutions and clonal dispersion inside de environments see Figure 1. The pangenomics offer a wealth of information about human-associated bacterial species (12).
Figure 1.
Pangenomics tool, in the worldwide context. Pangenomics is useful for the treatment of patients in evolutionary studies. The HGT and virulent genes are investigated today with pangenomics to solve the MDR problem of P. aeruginosa.
In his excellent chapter of Bobay [24], about the prokaryotic species concept, supported by the pangenome study, takes into account the approaches from Dobzhansky [25] and Mayr [26]. Speciation mechanism is involved in microorganisms, directly or indirectly, since the sustained interruption of gene flow between populations does not engage in sexual reproduction stricto sensu, escaping to the classic concept of species. Bobay [24] says that the definition of species has direct consequences regarding the definition of pangenome, and it is clear that 16S rRNA is not entirely cohesive, concluding and affirming: “studies focusing on the evolution of bacterial pangenomes should be based on rigorous species delimitation since the misclassification of a single genome can lead to dramatic overestimates or underestimates of the size of a species’ pangenome”.
Pangenomics is a fundamental tool for studying the entire repertoire of gene families in the genomes of pathogenic bacterial clades such as P. aeruginosa. This does not only provide the whole set of genes shared by this species, but also can be applied in interspecies differentiation analysis to mine species-specific genes to use a wealth of genome data [27]. Wang et al. [28] aimed at mining novel specific target gene sequences of P. aeruginosa based on the pangenome analysis and established high-specificity and high-sensitivity PCR and quantitative real-time PCR (qPCR) methods based on these targets. They used pangenome analysis to analyze the whole genomic sequences of 1,000 P. aeruginosa strains compared with other Pseudomonas species. A remarkable problem is the deficiency and mutations of some virulence factors in P. aeruginosa strains, which can result in false positives since existing pathogenic factors, may cause a potential threat of food poisoning (Baloyi et al. [29] cited by Wang et al. [28]).
The application of pangenomics in P. aeruginosa species with an open pangenome allows realizing that this species accepts external genes constantly and continuously from other strains and species, giving genetic richness and fitness to P. aeruginosa. Mutations over the genes and methylations in DNA and RNA gave a broad diversity to P. aeruginosa, expanding the variety and allowing success in diverse environments. Hilker et al. [30] compare some clonal genomes and indicate that the differential genetic repertoire of clones maintains a habitat-independent gradient of virulence in the P. aeruginosa population.
P. aeruginosa is excellently characterized in NCBI/taxonomy (https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=287; [31, 32]. However, genomics and classical taxonomic definition (Pseudo, false), (monas, unit) are on different approaches; although the first is based on sequencing, the second is based on metabolism and 16S rRNA, it is significant to remember that 16S must be sequenced. Also, to define species is necessary a certain number of strains. Likely, classical taxonomy and pangenome have similarities: it needs a certain number of strains, when better, a large number of those ones. In summary, pangenome comes to put together genomics and classical taxonomy. The contribution of P. aeruginosa is remarkable because new tools must complement the information and research and never disperse the consensus. When Carl Wose and colleagues redefined [33, 34, 35] taxonomic classification based on 16S rRNA, the initial reluctance to classify was constant. Today the regular is classified with 16S rRNA. But when looking at certain strains and their metabolism was found that 16S rRNA also falls short of classification [36]. Precisely the pangenomics comes in response to the new inconsistencies of 16S rRNA [37, 38].
As previously mentioned, different P. aeruginosa pangenomes were developed by Sharma et al. [3], Fisher et al. [5], Ding et al. [7], Mosquera-Rendón et al. [4], Freschi et al., [6], with a different number of 5, 100, 153, 181, 1311 genomes, respectively. However, the works ranging from 100 to 181 genomes almost agreed on the size of core and accessory genomes. Mosquera-Rendón et al. [4] found approximately 15 % was the core genome (2503/16,820 genes) of the pangenome, while Ding et al. [7] in their web page for P. aeruginosa, 16,327 genes selected from 18,780 total genes are accessory genome, and 2453 genes are the core genome. Freschi et al.’s [6] pangenome of P. aeruginosa consists of 54,272 genes: 665 are core genes, 26,420 are accessory genes, and 27,187 are unique genes. This work has a robust cutoff bioinformatic to discriminate homologous genes, eliminating potential orthologous (Figure 2).
Figure 2.
The P. aeruginosa pangenome from Ding et al. [7] in the interactive database https://pangenome.org/Pseudomonas_aeruginosa. This web developed with the panX tool allows comparing the pangenomes data of different pathogens and displays rapid results of pangenomics analysis.
It will most likely be necessary to adjust the core and accessory genome measurements for P. aeruginosa, given the differences mentioned before. One facility to improve this is that P. aeruginosa has become an influential species in many scenes, not just clinical or environmental. Therefore, the large number of strains coupled with improved bioinformatics tools, such as improving the complete sequencing of a large number of strains, will enhance the calculations between core and accessory genomes. Genomics and pangenomics are still focused on coding information, leaving aside epigenomic information such as microRNAs, and methylations, among others.
As we defined in Table 2, an open pangenome increases when a new genome is added to the pangenome. In other words, the open pangenome is contrary to the closed pangenome, so there are changes when new genomes are added, and new strains provide new genes to the species pangenome. P. aeruginosa was defined as an opened pangenome [39]. Likely, we will found continuously new strains with new genes. As mentioned by Rouli et al. [8]: the sympatric species, present in a community, have large genomes and, thereby, an open pangenome, a high rate of HGT genes transfer, and several ribosomal operons, citing to Georgiades and Raoult [40], and Diene et al. [41]. The open pangenome of P. aeruginosa has a large accessory genome highly mobile with a short core genome conserved, interchanging duplication and translocations, where HGTs enter (insertions) and go out (deletions). The evolution mechanisms as selection and genetic drift, play a central role inside the genome of the strain population (see Figure 3).
Figure 3.
Open pagenome of P. aeruginosa. The bacterial genome of P. aeruginosa has a large circular chromosome. The pangenome in total strains is divided by two regions in each chromosome, one conserved in overall strains (core genome) and the other not shared by the overall strains (accessory genome). This open pangenome among those strains has a large accessory genome highly mobile with a short core genome conserved. In the pangenome inside the species, different strains interchange HGTs, which enter (insertions) and go out (deletions). Both the core and accessory genomes undergo duplications and translocations. The evolution mechanisms such as selection, genetic drift, and others play a central role inside the genome of the strain population.
The P. aeruginosa genome has G + C content, ranging from 65 to 67%, with a size of 5.5–7 Mbp. It has a single circular chromosome and a variable number of plasmids [42]. The genome encodes a considerable repertoire of transporters, transcriptional regulators, and two-component regulatory systems, which reflects its metabolic diversity to utilize a broad range of nutrients. Additional works agree that P. aeruginosa has an open pangenome [39, 43]. Mosquera-Rendon et al. [4] identified distinctive positive selection in a variety of outer membrane proteins, with the data supporting the concept of genetic variation in P. aeruginosa proteins likely recognized as antigens. Hilker et al. [30], comparing single nucleotide polymorphism synteny indicated unrestricted gene flow between clonal complexes by recombination. Also, comparing the genomes point out that the differential genetic repertoire of clones maintains a habitat-independent gradient of virulence in the P. aeruginosa population.
There is a large variability in the size of the P. aeruginosa genome. For example, the RW109 strain has 7.049.347 bp and 6829 genes, and the PAO reference strain has 6.264.404 bp and 5697 genes. More than 700.000 bp and 1100 genes of difference between both strains, in other words, the core genome between both strains could be lower than 5697 genes, and the accessory genome could probably exceed more than 1100 genes, ignoring the repeated genes and excluding plasmids or other mobile elements. This simple exercise without robustness, and data processing without software, is less wise than Sharma et al. [3], using only five genomes, which shows the requirement to improve the level of comparison between two strains to reach the data support and confident results in pangenomics. It is the same exercise when we compare two phenotypes in metabolism or antibiotic resistance. We look by a cylinder at the wide world of the genome and its interactions, looking at a pair of genes or products, sometimes ignoring that two strains can reach the same product in two different ways. Nevertheless, Hilker et al. [30] identified 5892-7187 open reading frames (with a median of 6381 ORFs) in the P. aeruginosa pangenome of representative 20 strains, ranging from 6.4 to 7.4 Mbp large genomes with a core genome with approximately 4000 genes. Of course, 20 genomes is a small study for a pangenome, but there are 15 most frequent clonal complexes of the P. aeruginosa population.
Now, thinking about again the reported pangenomes: Sharma et al. [3] 5 genomes, Fischer et al. [5] 100 genomes, Ding et al. [7] 153 genomes, Mosquera-Rendón et al. [4] 181 genomes, and Freschi et al. [6] used 1311 genomes. It is clear that Freschi et al.’s study has the maximum number of samples and likely the best pangenome results for the P. aeruginosa species. However, pangenomics are not one study with the highest catalogs or number of samples. Those essential five studies have interesting matches: the accessory genome in P. aeruginosa is bigger than core genomes, and, thereby, the P. aeruginosa genome is an open pangenome, as we continue to emphasize.
Taking together the data extracted from Ding et al. [7], shown in Figure 2 for P. aeruginosa, performing the same analysis for other pangenomes species, such as Clostridium botulinum, Escherichia coli, Yersinia pestis, and Mycobacterium tuberculosis. And taken other data from the Mycoplasma genitalum from Corredor & Muñoz-Gómez [10], we can compare the pangenomes of these species with each other. It is observed that P. aeruginosa has a smaller core genome than Y. pestis, M. tuberculosis, and M. genitalum, although greater than E. coli and C. botulinum see Figure 4.
Figure 4.
Comparing the size of P. aeruginosa with other bacterial pathogens species. The comparison of P. aeruginosa pangenome (navy blue and red) with Clostridium botulinum, Escherichia coli, Yersinia pestis, Mycobacterium tuberculosis and Mycoplasma genitalum (turquoise blue and rose). Data obtained from PanX web.
From 2006 multidrug-resistant (MDR) P. aeruginosa was listed, also pandrug-resistant (PDR) [44]. The term PDR was inappropriately used in all five studies that used it and within a variety of genotypic and phenotypic characteristics. The terms MDR and PDR of P. aeruginosa likely cause confusion to researchers and clinicians. Falagas et al. [44] believe that at least an extended and accepted definition for the Acinetobacter baumannii and P. aeruginosa PDR should be uniformly used worldwide. Today, it is clear that MDR is a perfect term for P. aeruginosa antibiotic multiresistant, and probably PDR (resistance to all antibiotics) was an inconsistent term. However, the PDR acronym coins directly with pangenome, in the sense that MDR P. aeruginosa could be studied from pangenomics to solve the MDR problem.
The growth of MDR P. aeruginosa results from the extraordinary capacity of this bacterium for developing resistance through chromosomal mutations (probably in the core genome). In this species, there are increasing prevalence of transferable resistance elements as HGT genes (on the accessory and unique genome), particularly genes encoding carbapenemases or extended-spectrum β-lactamases (ESBLs) resistance. Given that P. aeruginosa has a nonclonal epidemic population structure and also has so much quantity of rare and unrelated genotypes that are recombining at high frequency [45].
As was mentioned previously, Freschi et al. [6], who developed the biggest pangenome of P. aeruginosa, initially predicted antimicrobial resistant gene profiles for 389 P. aeruginosa strains using the resistance gene identifier (RGI), and they found 334 unique profiles. Analysis of 1311 strains confirmed that there is, therefore, an immense variation in P. aeruginosa antimicrobial resistance (AMR) gene profiles, with the most frequent profile found in only 6% of the strains.
The antibiotic resistome of some organisms is the set of antibiotic-resistant genes used to resist the high concentration of some antibiotics [46]. Perhaps, the P. aeruginosa resistome has longtime studied [47], and now even more so with the development of next generations sequencing, databases, and the increase of pangenomics. Postgenomics data has the objective of developing the decryption of antibiotic resistome. Mercy to the other chemical techniques, today, we distinguish if the antibiotic concentration is increasing in the environment. This will have one effect on both the diversity and the abundance of resistome genes in the P. aeruginosa MDR. Selection for cells that carry resistance determines the addition of their relative abundance, and thus increases the more additional genes that confer resistance [48]. Fortunately, there are still susceptible strains to antibiotics, which will allow comparing those with resistant strains.
The opened pangenome of P. aeruginosa shows wide diversity of genes, plasmids, and mobile elements, which establish the resistome. For example, in the three reference strains, PAO1, LESB58, and PA14 are treated with seven resistant drugs exhibit phenotypic variability in their response to 27% of the antibiotics tested. For instance, the resistome annotation of 672 P. aeruginosa strains identified 147 loci associated with antibiotic resistance. These loci are composed mainly of acquired genomic elements and intrinsic genes [49].
In pangenomes of Freschi et al. [6] they study the role of HGTs in the evolution of the P. aeruginosa genome. They observed the flexible genes (accessory and unique genomes) and determined the proportion of these genes that were found in a single group of isolates, as well as the balance of flexible genes shared between multiple groups. Freschi et al. [6] found peculiar results because 10,515 genes (40%) of the 26,420 flexible genes were present in one group only and, on the contrary, 83 genes found in 3 groups of isolates were present in more than 90% of the isolates of a single group and, were not found in the other groups. The maximum of flexible genes was, thus, 15,905 or 60% present in isolates belonging to multiple groups; one result provides a higher estimate of the number of genes that could potentially be related to HGT episodes. They estimated the prevalence of phages because phages are often in connection with HGT events.
11. The future of pangenomics for P. aeruginosa
In conclusion and perspective, we can state that pangenomics had been an excellent and useful tool to decipher the P. aeruginosa pangenome. The open pangenome of P. aeruginosa displays an important diversity of HGT, mobile elements, and transposons in plasmids and phages, as a part of the accessory and unique genomes. Core genome in P. aeruginosa is lowest 20% of pangenome. Pangenomics is today a strategic instrument for studying the diversity in P. aeruginosa, useful to clarify the scene of MDR inside the specie without exception this species.
Acknowledgments
We thank the University of Antioquia for their financial support to the project CODI 2017-15753.
Conflicts of interest
The authors declare that they have no conflicts of interest regarding the publication of this paper
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Written By
Mauricio Corredor, Juan David Patiño-Salazar, Diana Carolina Castaño and Amalia Muñoz-Gómez
Submitted: 18 August 2022Reviewed: 20 September 2022Published: 13 March 2023
Open access peer-reviewed chapter - ONLINE FIRST
