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Article

Genomic Features of Pseudomonas putida PCL1760: A Biocontrol Agent Acting via Competition for Nutrient and Niche

by
Daniel Mawuena Afordoanyi
1,2,*,
Roderic Gilles Claret Diabankana
1,3,
Aynur Kamilevich Miftakhov
1,
Evgenii Sergeyevich Kuchaev
1 and
Shamil Zavdatovich Validov
1,*
1
Laboratory of Molecular Genetics and Microbiology Methods, Kazan Scientific Center, Russian Academy of Sciences, 420111 Kazan, Russia
2
Kazan Institute of Biochemistry and Biophysics, Kazan Scientific Center, Russian Academy of Sciences, 420111 Kazan, Russia
3
Centre of Agroecological Research, Kazan State Agrarian University, 420015 Kazan, Russia
*
Authors to whom correspondence should be addressed.
Appl. Microbiol. 2022, 2(4), 749-765; https://doi.org/10.3390/applmicrobiol2040057
Submission received: 10 September 2022 / Revised: 26 September 2022 / Accepted: 28 September 2022 / Published: 2 October 2022

Abstract

:
Pseudomonasputida strain PCL1760 is a biocontrol agent protecting plants from pathogens via the mechanism of competition for nutrients and niches (CNN). To confirm this mechanism as well as to adapt the strain for biotechnological applications, full genome analysis was compared with the known biotechnological model, P. putida S12, and other related species, which were analyzed on different genomic databases. Moreover, the antibacterial activity of PCL1760 was tested against Staphylococcus aureus, Pseudomonas aeruginosa, and Pseudomonas syringae. No genetic systems involved in antibiosis were revealed among the secondary metabolite clusters of the strain of PCL1760. The only antagonistic effect was observed against P. syringae, which might be because of siderophore (yellow-greenish fluorescence), although less than 19% pyoverdin biosynthesis clusters were predicted using the AntiSMASH server. P. putida PCL1760 in comparison with the Pseudomonas simiae strain PCL1751, another biocontrol agent acting solely via CNN, which lost its ‘luxury’ genes necessary for antibiosis or parasitism/predation mechanisms, but carries genetic systems providing motility. Interestingly, immunity genes (CRISPR/Cas and prophages) showed PCL1760 to be robust in comparison with S12, while annotation on OrthoVenn2 showed PCL1760 to be amenable for genetic manipulations. It is tempting to state that rhizobacteria using the mechanism of CNN are distinguishable from biocontrol agents acting via antibiosis or parasitism/predation at the genomic level. This confirms the CNN of PCL1760 as the sole mechanism for biocontrol and we suggest the strain as a new model for genetic engineering.

1. Introduction

Biological control of plant disease has been considered the safest method for controlling plant diseases considering the harmful effects of chemical application such as fungicides and antibiotics on the ecology as a whole. The effectiveness of biocontrol agents varies (30–100%) in comparison with commercial fungicides, which is almost completely effective because of diverse environmental conditions, different strains of pathogens, and the inconsistency of biocontrol strains [1]. The mechanisms for biocontrol of plant pathogens to date include the production of antimicrobial compounds (antibiosis), the induction of plant resistance (induced systemic resistance (ISR), parasitism and predation based on the secretion of hydrolytic enzymes for the consumption of lysed cells of the pathogens, competition for plant nutrients and niches (CNN), and interference with pathogenicity factors of the pathogen [2]. The effective genera of rhizobacteria with these mechanisms mostly include Pseudomonas and Bacillus [3].
Pseudomonas putida is one of the ubiquitous species found in soils, plants, and waterbodies with a wide application in both the agricultural and industrial sectors. Their ability to control phytopathogens such as Fusarium oxysporum, Xanthomonas campestris, Rhizoctonia solani, Colletotrichum gloeosporioides, Athelia rolfsii, Gibberella moniliformis Magnaporthe oryzae, Ralstonia pseudosolanacearum, and plant parasitic nematode Radopholus similis has been well documented in several scientific works [4,5,6]. As a plant growth-promoting bacteria, P. putida strains have been known to produce the phytohormone, indoleacetic acid (IAA) [7], as well as solubilize phosphate [8] and fix nitrogen [9].
The use of P. putida as a cell factory in bio-industrial applications, through its genomic engineering amenability, its robustness to extreme conditions, and fast growth in minimal medium, has revolutionized the production of beneficial compounds [10]. Since its discovery, P. putida has also been adapted for the degradation of toxic compounds, which include aliphatic, aromatic, and heterocyclic compounds [11]. Other applications include the decolorization of dyes by peroxidases used in biosensors or immunodetection analysis [12] and, recently, P. putida was applied in the degradation of ceftriaxone through genetic engineering [13]. Another recent work is the treatment of diazinon in wastewater by the popular P. putida KT2440 [14].
P. putida strain PCL1760 was isolated from the rhizosphere of an avocado plant and has been proven to control Fusarium oxysporum f. sp. radicis-lycopersici ZUM2407 via the mechanism “competition for nutrients and niches” (CNN) [15]. Taking into account the diverse abilities of P. putida strains [16], strain PCL1760 may possess other mechanisms besides CNN to control plant diseases. To confirm this mechanism and the propensity of PCL1760 to be used as a model for genetic manipulations in biotechnological applications, the full genome needs to be analyzed and compared with other closely related species. We compared the full genetic sequence of P. putida PCL1760 to P. putida S12 as well as to other different species: P. simiae PCL1751, P. simiae WCS417, P. flourescens W-6, and P. flourescens Pt14. We further confirmed its antagonistic activity on bacterial pathogens to prove CNN the as sole mechanism of biological control for P. putida PCL1760.

2. Materials and Methods

Complete genomes used in this study were obtained from NCBI genomes (Table 1).
Table 1. Genomes used in this study.
Table 1. Genomes used in this study.
Microbial StrainsNCBI GenBankSource of IsolationReference
P. putida PCL1760CP099727.1From the rhizosphere of the avocado plant In this study
P. simiae PCL1751NZ_CP010896.1From the rhizosphere potato Kamilova et al. [17]
P. fluorescens Pt14CP017296.1From the rhizosphere of rice plants in acidic soil Rani et al. [18]
P. simiae WCS417NZ_CP007637.1From lesions of wheat roots growing in a take all disease-suppressive soilPieterse et al. [19]
P. putida S12CP009974.1From soil using styrene as a sole carbon sourceHartmans et al. [20]
P. fluorescens W-6CP058533.1From the Napahai plateau wetlandXiang et al. [21]

2.1. Genomic DNA Preparation

Chromosomal genomic DNA of P. putida PCL1760 was extracted using TRIzol reagent (Thermo Fisher, Waltham, MA, USA) according to the manufacturer’s protocol, from the pellet of overnight culture grown at 28 °C in King’s B (KB) medium (g/L: 10 g proteose peptone, 1.5 g K2HPO4, 15 g glycerol, 1.5 g MgSO4, pH 7.2).

2.2. Library Preparation, Genome Sequencing, and Annotation

The DNA library for bacterial genome sequencing was prepared from high-quality genomic DNA. The whole genome of P. putida PCL1760 was sequenced using paired-end (PE) 2  ×  125 bp on the MiSeq Illumina® platform at Evrogen (Moscow, Russia). The quality of raw sequence data was analyzed using FastQC (v. 0.11.2) [22]. To remove adapters and low-quality reads, the sequencing reads were trimmed using Trimmomatic v. 0. 36 [23]. The high-quality adapter-free reads were then de novo assembled using the Unicycler v. 0.5.0 [24], while contigs with size < 200 bp or coverage lower than 10× were cut from the genome assembly. Average nucleotide identity based on Blast (ANIb) was used to select the closely related reference strain by measuring nucleotide level similarity between the coding regions of the genomes with those of NCBI. Mauve Contig Mover [25] was then used to align and reorder contigs based on comparison with the complete reference genome. The quality of the assembled genomes was evaluated using QUAST [26]. Gaps within the scaffolds were filled and closed using GAPPadder, v. 1.10 [27]. The assembled genome sequence of PCL1760 was deposited in NCBI GenBank under the accession number CP099727.1.

2.3. Genome Annotation and Comparison

The genome annotation of P. putida PCL1760 was carried out using the Prokaryotic Genome Annotation Pipeline (PGAP) provided by NCBI [28]. The coding gene prediction of the genome was also performed with Prokka (rapid prokaryotic genome annotation) version 1.12 [29].
Pan-genome analysis based on Roary (which takes the GFF3 file of the annotated assemblies produced by Prokka) [30] with default parameters was used to compare the genomic relationships between PCL1760 and the selected genomes. Whereas more than 95% identical genes’ prevalence in all genomes (>99%) of the compared strain are classified as Core genes, Cloud genes refers to gene families present only in one genome and Shell genes refer to gene families present in two genomes. OrthoVenn2 was applied for whole genomic comparison and annotation of orthologous clusters [31]. We further used the BlastN search method to screen for the presence of genes involved in the production of functional flagella (FlgK, FlgL, FlgE, FlgD, FliC, and FliD) and biofilm formation (LapA and LapF). The web tool CRISPR Finder was used for the identification and comparative analysis of CRISPR/Cas systems between genomes [32]. AntiSMASH [33] was used for comparative analysis of secondary metabolite gene clusters. PHASTER server (PHAge Search Tool Enhanced Release) was used for the identification and comparative analysis of prophage among genomes. The Comprehensive Antibiotic Resistance Database (CARD) was used to identify and compare potential antibiotic resistance genes among genomes [34].

2.4. Cell Suspension and Cell-Free Suspension Preparation

The cell suspension was prepared from the bacterial culture of PCL1760 grown overnight in (KB) medium at 28 ± 1 °C. The culture was centrifuged at 4000 rpm for 15 min at 4 °C. The precipitate obtained was then washed with sterile phosphate-buffered saline (PBS) (140 mM NaCl, 5 mM KH2PO4, 1 mM NaHCO3, pH 7.4) and resuspended in the same solution to an optical density value of 0.5 at 595 nm. The cell-free suspension was obtained by centrifugation at 10,000 rpm for 10 min at 4 °C of PCL1760 culture grown in King’s B (KB) medium at 35 ± 1 °C for 5 days. The supernatant obtained was aseptically filtrated (through a 0.20 μm pore-size membrane filter).

2.5. Antagonistic Activities

The ability of P. putida PCL1760 to inhibit the growth of pathogenic bacteria (Table 2) was performed on KB agar medium using the dual culture and disc-diffusion method. For this purpose, 100 μL of an overnight culture of each phytopathogenic bacteria with an optical density (595 nm) value of 0.05 was plated on King’s B agar using a plate spreader, and then cell and cell-free suspension of PCL1760 were co-inoculated on the same plate using cotton wool discs (which were amended with 50 μL of the suspension). The plates were then incubated at 28 ± 1 °C for 3 days. The formation of a clear zone around the growing bacteria was considered as a positive antagonistic activity.
Table 2. Pathogenic bacterial strains used in this study for antagonistic activity.
Table 2. Pathogenic bacterial strains used in this study for antagonistic activity.
Pathogenic Bacterial StrainsReferences
Pseudomonas syringae pv. tomato DC3000Cuppels and Ainsworth [35]
Staphylococcus aureus RN6390Khusainov et al. [36]
Pseudomonas aeruginosa IR1.5Egamberdieva et al. [37]
In addition, to validate the functionality of the AMR gene found in the genome of PCL1760, the antibiotic susceptibility test was assayed using the disc-diffusion method. Antibiotics used for this purpose included ampicillin (Ap), Ceftriaxone (Cef), Chloramphenicol (Cm), Ciprofloxacin (Cf), Erythromycin (Em), Kanamycin (Km), Moxifloxacin (Mf), Spectinomycin (Sp), and Tetracycline (Tc). Each antibiotic was used in the range of 0.75–24 µg (0.75 µg, 1.5 µg, 3 µg, 6 µg, 12 µg, and 24 µg). The antibiogram of P. putida PCL1760 was then identified as susceptible (S), intermediate (I), and resistant (R) as recommended by the National Committee for Clinical Laboratory Standard Guidelines [38].

3. Results

3.1. The Genome Assembly, Annotation, and Comparison

Contig blasting revealed that PCL1760 is mapped to the assembled GenBank: CP009974.1 and GenBank: CP002290.1 (https://blast.ncbi.nlm.nih.gov/Blast.cgi, accessed on 25 May 2020) with alignment rates of 100% and 99.55%, respectively. Based on the obtained ANIb result, P. putida S12 was selected as a reference genome assembly.
The genomic features of P. putida PCL1760 are summarized in Table 3. Based on the annotation provided by the Prokaryotic Genome Annotation Pipeline (PGAP), the full genome of P. putida PCL1760 contained a single circular chromosome of 6,002,785 bp with 61.80% G + C. The whole genome of PCL1760 harbors 5215 gene-coding sequences covering 96.53% of the genome, as well as 72 tRNAs, 4 ncRNAs, and 88 pseudogenes. Plasmid genome was not predicted in PCL1760. The genomes of strain Pt14, W-6, S12, PCL1751, and WC417 harbor gene-coding sequences that cover 96.96%, 96.65%, 96.95%, 97.15, and 97.22% of their genomes, respectively, in comparison with PCL1760 (Table 3). Pseudogenes were more commonly predicted in P. putida S12. The percentage of pseudogenes for PCL1760, Pt14, W-6, S12, PCL1751, and WCS417 calculated in these genomes was 1.63, 1.32, 1.53, 1.64, 1.12, and 1.42%, respectively, in relation to their total genes. All of the selected genomes harbor identical ncRNAs and proximity identical G + C content (Table 3).
The comparative analysis of CRISPR/Cas revealed that P. putida PCL1760 harbors five CRISPR elements (Table 3 and Table S1), as compared with strains Pt14, W-6, S12, PCL1751, and WCS417, in which 11, 1, 3, 2, and 14 CRISPR elements were predicted, respectively (Table 3 and Tables S2–S6). All compared genomes had a Cas cluster containing different numbers of the same Cas3 Type I elements. Moreover, the Cas cluster found in the whole genome of the strain Pt14 and W-6 contained 16 Cas3 elements type I, whereby the Cas cluster present in the strain of S12, PCL1751, and WCS417 harbors 12, 14, and 14 Cas3 elements type I, respectively (Table 3).
Average nucleotide identity comparison of PCL1760 with the selected strains revealed that PCL1760 is closely related to P. putida S12, with an average nucleotide identity of 98.39% (based on BLAST) and 97.5% (based on the average aligned nucleotide). P. simiae strains (PCL1751 and WCS417) and P. fluorescens strains (W-6 and Pt14) have an average nucleotide similarity (based on BLAST) of less than 90% and 80%, respectively, based on the average aligned nucleotide with P. putida strains PCL1760 and S12 (Table 4).
Prophage analysis of PCL1760 using PHASTER revealed three prophages, of which one region is intact, one is incomplete, and one is questionable (Table S7). The intact prophage in the genome regions 3,796,726–387,790 nucleotides (nt) of PCL1760 was predicted to be similar to the most common phage Pseudo YMC11/02/R656 NC 028657, while the questionable prophage found in the genome regions 5,159,654–5,188,739 nt was predicted to be similar to the PHAGE Pseudo JBD44 NC 030929. The incomplete phage in the genome region 735,221–772,596 nt was identified as PHAGE Escher 500465 1 NC 049342.
In comparison with the strain of PCL1760, no intact and questionable prophages were predicted in P. putida S12 (Table S8). The presence of these three incomplete phage regions in P. putida S12 is similar to the most common phage PHAGE Escher 500465 1 NC 049342, PHAGE Pseudo JBD44 NC 030929, and PHAGE Bacill vB BtS BMBtp14 NC 048640 (Table 5). P. fluorescens Pt14, P. simiae WCS417, P. simiae PCL1751, and P. fluorescens W-6 carried four prophages (two intact and two incomplete); two prophages (two intact); four prophages (two intact, one questionable, and one incomplete); and two prophages (intact and incomplete), respectively (Tables S9–S12). Two identical prophages similar to the most common phage PHAGE Vibrio VP882 NC 009016 and PHAGE Pseudo YMC11/02/R656 NC 028657 were predicted in P. fluorescens Pt14, P. simiae WCS417, and P. simiae PCL1751. The presence of the intact phage PHAGE Pseudo YMC11/02/R656 NC 028657 was also predicted in P. fluorescens W-6 (Table 5).
The comparison of the AMR gene family is summarized in Table 6. As can be seen, the antibiotic resistance ontology (ARO) adeF and Pseudomonas aeruginosa soxR belong to the AMR gene family resistance-nodulation cell division (RND) antibiotic efflux pump, an ATP binding cassette (ABC) antibiotic efflux pump, and the major facilitator superfamily (MFS) antibiotic efflux pump, which confers resistance to fluoroquinolone antibiotic, tetracycline antibiotic cephalosporin, glycylcycline, penam, rifamycin antibiotic, phenicol antibiotic, disinfecting agents, and antiseptics. Additionally, an ARO term Acinetobacter baumannii AbaQ belonging to the major facilitator superfamily (MFS) antibiotic efflux pump, which confers resistance to the fluoroquinolone antibiotic predicted in strains of Pt14, W-6, PCL1751, and WCS417, was absent in P. putida PCL1760 and S12.
The comparison of gene clusters related to the biosynthesis of secondary metabolites using antiSMASH is presented in Table 7. Nine and eight gene clusters were found in the PCL1760 and S12 genomes, respectively, related to the biosynthesis of secondary metabolites (Figure S1A,B). The putative gene clusters in PCL1760 were two cluster types encoding NRPS (non-ribosomal peptide synthetase) with 14 and 19% similarity to the most known pyoverdin biosynthetic gene cluster, one redox-cofactor with 13% similarity to lankacidin C, two RIPPs-like (other unspecified ribosomally synthesized and post-translationally modified peptide product (RiPP) cluster) type, one T1PKS (type I polyketide synthetase) with 27% similarity to the most known O-antigen biosynthetic gene cluster, one RRE-containing (RRE-element containing cluster), one NAGGN (N-acetylglutaminylglutamine amide), and a ranphipeptides type cluster (Cys-rich peptides). The ranphipeptides type cluster had 7% similarity to the most known cluster for the synthesis of pyoverdin. The ranphipeptide-type gene cluster was absent from the genome of S12. Furthermore, four gene cluster types (NAGGN, RRE-containing, and two RIPPs-like) related to the biosynthesis of secondary metabolites in PCL1760 and S12 did not correspond to the most known cluster.
As compared with P. putida strains PCL1760 and S12, twelve gene cluster types were found to be associated with the biosynthesis of secondary metabolites in W-6, Pt14, PCL1751, and WCS417 (Figure S1C–F). The presence of siderophores, arylpolyene, hserlactone, terpene, and betalactone gene cluster types in these genomes was predicted. Each genome harbored three cluster types NRPS (non-ribosomal peptide synthetase) with less than 19% similarity to the most known pyoverdin biosynthetic gene cluster in comparison with PCL1760 and S12. The cluster type betalactone was predicted as a fengycin biosynthetic gene cluster with 13% similarity in all analyzed strains, except the two P. putida strains, PCL1760 and S12 (Table 7). The gene cluster type arylpolyene, absent in P. putida PCL1760 and S12, but present in P. fluorescens W-6, Pt14, P. simiae PCL1751, and WCS417, was found to be less than 50% similar to the APE-vf biosynthesis gene cluster. The cluster responsible for the synthesis of pseudomonine (with 100% similarity) with siderophoric activity and ambactin (with 25% similarity) was only predicted in P. fluorescens Pt14.
Coelibactin biosynthesis gene cluster was only predicted in P. simiae WCS417, PCL1751, and P. fluorescens W-6. The NRPS-like cluster type with 40% similarity to the most known L-2-amino-4-methoxytrans-3-butenioc acid biosynthesis cluster was only predicted in strains of P. fluorescens. Five types of clusters (terpene, RIPP-like, NAGGN, and hserlactone) present in P. simiae WCS417, P. fluorescens W-6, P. fluorescens Pt14, and P. simiae PCL1751 have no identified biosynthesis cluster (Figure S1).
The pangenome analysis using Roary identified a total of 14,548 genes. The core genome comprised 467 (3.22%) genes present in all selected bacterial strains. The accessory genome included 14,081 (96.78%) shell genes (15% ≤ strains < 95%). No cloud genes (0% ≤ strains < 15%) and soft-core gene (95% ≤ strains < 99%) were predicted among the compared bacterial strains (Figure 1).
Figure 1. Pangenome analysis of P. putida PCL1760 with related strains using Roary. The whole-genome alignment of the selected strains was clustered based on the presence (in blue color) and absence (in white color) of genes in each strain, which was visualized with Phandango [39]. A phylogeny (A) was generated based on genes shared by the strain of PCL1760 with Pt14, W-6, S12, PCL1751, and WCS417. Roary representation (B) of core genome (1) and accessory genome (2) among selected bacterial strains.
Figure 1. Pangenome analysis of P. putida PCL1760 with related strains using Roary. The whole-genome alignment of the selected strains was clustered based on the presence (in blue color) and absence (in white color) of genes in each strain, which was visualized with Phandango [39]. A phylogeny (A) was generated based on genes shared by the strain of PCL1760 with Pt14, W-6, S12, PCL1751, and WCS417. Roary representation (B) of core genome (1) and accessory genome (2) among selected bacterial strains.
Applmicrobiol 02 00057 g001
The analysis of orthologous gene clusters using OrthoVenn2 revealed that the species form 6905 clusters, 3788 (54.86%) orthologous clusters (at least contain two species), and 3117 single-copy gene clusters. PCL1760, Pt24, W-6, S12, PCL1751, and WCS417 harbored 4920, 4702, 4817, 4890, 5347, and 5375 clusters, respectively, and 278, 469, 613, 161, 172, and 192 proteins, respectively, that are unique to the strains (Table 8).
The genome of P. putida PCL1760 shares a core gene of 3208 orthologous gene clusters with genomes of P. putida S12, P. simiae, and P. fluorescens strains (Figure 2).
Strains PCL1760, Pt 24, W-6, S12, PCL1751, and WCS417 had 4, 10, 17, 5, 3, and 2 clusters of genes, respectively, which are not included in orthologous clusters (Figure 2B). These unique gene clusters found in PCL1760 were related to the oxidoreductase activity response, DNA-binding transcription factor activity, and the putrescine catabolic process (Figure S2). Those found in Pt24 were related to phosphorelay sensor kinase activity and transposition, as well as DNA-mediated signaling (Figure S3). The gene clusters found in the strain of W-6 were associated with the antigen biosynthetic process, hydrolase activity, protein secretion by the type II secretion system, nitrogen compound metabolic process, ion transport, carbohydrate metabolic process, and transmembrane transport (Figure S4).
In the strain of S12, these five clusters are responsible for transposition (putative transposase y4uL), ATP binding (putative insertion sequence ATP-binding protein y4pL), and response to chromate stress (Figure S5). The clusters found in PCL1751 are related to the DNA restriction-modification system (Figure S6). In the strain of WCS417, no function was associated with the two clusters (Figure S7).
The strain of PCL1760 and S12 shared 1143 orthologous gene clusters (Figure 1B). Among them are orthologous clusters involved in the butanediol metabolic process (Acetolactate synthase, catabolic), bacteriocin immunity (Colicin-E7 immunity protein), pilus assembly, cell adhesion (Fimbrial protein), capsule polysaccharide biosynthetic process (Gamma-glutamyl-CDP-amidate hydrolase), cellular response to nitric oxide, riboflavin biosynthetic process, purine nucleobase metabolic process, biotin biosynthetic process, biotin biosynthetic process, metal ion binding, antibiotic biosynthetic process (Mycosubtilin synthase subunit C), aromatic compound catabolic process (2,4-dinitrotoluene dioxygenase system, ferredoxin component), creatinase activity, protein secretion by the type II secretion system (type II secretion system protein I), and others (Figure S8).
The strains PCL1760 and S12 each share 11 orthologous clusters with Pt14, W-6, PCL1751, and WCS417 (Figure 2B). Among orthologous clusters shared by PCL1760 with Pt24, W-6, PCL1751, and WCS417, clusters responsible for the viral protein involved in tail assembly, virion attachment to host cell, glycine betaine transport, signal transduction, and others were present (Figure S9). In addition, some of the clusters shared by S12 with other strains, with the exception of PCL1760, include clusters responsible for transferase activity (transferring glycosyl groups), aromatic compound catabolic process (Figures S10 and S11), galactonate catabolic process, phosphorelay sensor kinase activities, response to cadmium ion, inositol catabolic process (Figure S12), basic amino acid transport, and other clusters.
Nine hundred and forty-five orthologous gene clusters are shared by Pt24, W-6, PCL1751, and WCS417 strains. Among the clusters found are those responsible for purine nucleoside transmembrane transporter activity, regulation of carbohydrate catabolic process, response to antibiotics, 3-phytase activity, fatty acid beta-oxidation, macromolecule deacylation, and other clusters (Figure S13). The BlastN search method revealed the presence of genes involved in the functional motility of the strains, flagella (FlgK, FlgL, FlgE, FlgD, FliC, and FliD), and biofilm formation (LapA and LapF).

3.2. Antagonistic Activity

Antagonistic activity tested on KB medium revealed the ability of cell suspension of P. putida PCL1760 to inhibit directly the growth of pathogenic bacteria P. syringae DC3000 (Figure 3B), but not S. aureus RN6390 and P. aeruginosa IR1.5 (Figure 3A,C), as Bacillus velezensis KS04AU did. This can be observed by the appearance of a yellow-greenish zone of inhibition around the colony of PCL1760 (Figure 3B).
However, a different result was obtained with the PCL1760 cell-free supernatant (Figure 4). No antagonistic activity against pathogenic bacteria tested was observed.
The antibiogram result of PCL1760 against nine antibiotics is represented in Table 9. The antibiotic susceptibility test of the nine antibiotics showed PCL1760 to be resistant to erythromycin, ampicillin, chloramphenicol, and spectinomycin, as well as an intermediate resistance to tetracycline when 24 μg of the antibiotic was applied. High susceptibility of PCL1760 against moxifloxacin was observed in all ranges of antibiotics per filter disc used in the experiment (Figure S16). A partial or intermediate susceptibility was observed against ciprofloxacin, kanamycin (≤3 μg), and Ceftriaxone (≤1.5 μg).

4. Discussion

The biocontrol ability of P. putida PCL1760 against tomato foot and root rot disease (Forl ZUM2407) through CNN and the absence of hydrolytic enzyme activity has been well documented [4]. As there is a shift to engineering bacteria cells rather for the catabolism of complex substrates, there is a tendency to search for new model systems. To investigate the absence of genes responsible for antibiosis and how suitable our strain is to be genetically manipulated for biotechnological applications, there was the need to annotate the full genome sequence of PCL1760 and confirm the antagonistic activity of the strain.
The antagonistic activity against the bacterial phytopathogen P. syringae also brought our attention to study the sequence of the full genome of PCL1760 to find the active compound inhibiting the pathogen [40]. Ye et al. [16] studied the antimicrobial activity of P. putida strain W15Oct28 on the phytopathogen P. syringae and other bacterial pathogens based on putisolvin biosynthesis. The authors observed antagonistic activity of P. putida on Staphylococcus aureus, P. aeruginosa, and P. syringae. In our case, P. putida PCL1760 was able to inhibit only P. syringae, which was profound on minimal media (Figure S15A), than KB agar (Figure S15B) suggesting the occurrence of inhibition being a siderophoric activity. This is observed by the fewer cell or halo zones with yellow-greenish fluorescence around the colonies of PCL1760. In addition, secondary metabolites of cell-free supernatant did not inhibit the pathogen, suggesting either effector genes are released by P. syringae to activate the production of siderophores as competition for nutrients, triggering the inhibition effect in dual culture experiments (Figure 4). The analysis of 16 rhizobacteria strains from the ginseng plant showed a weak antagonistic effect of siderophore of all P. putida strains in comparison with the strain P. putida KNUK9, being eminent in inhibiting the fungus Aspergillus niger [41]. The above discussion suggests that not all P. putida strains possess the antibiosis mechanism, and confirms the mechanism of CNN as being the sole biocontrol mechanism of PCL1760 against phytopathogens and its application in the greenhouse [4,15].
The advantages of P. putida strains in industrial biotechnology have been well reported by Weimer et al. [42]. In this mini-review article, the authors present beneficial applications of P. putida strains in several genome-scale metabolic models, as transcriptomic and proteomic models, in the production of polyhydroxyalkanoates (PHA), as a multi-omics integration agent and its use in bioremediation. The two most popular strains adapted in industrial and genetic biotechnological applications are P. putida KT2440 and P. putida S12, domesticated for their easy genetic manipulations and inducible promoter systems for high expression of proteins [42,43]. Recent work on these strains includes the efficient catalytic transformation of D-fructose to 2,5-Bis(hydroxymethyl)furan or improved bioproduction of PHA from styrene vapors by S12 [44,45] and the improved production of muconate from p-coumarate by KT2440 through the conversion of lignin-related aromatic compounds [46]. The authors explain how PobA, the native P. putida flavoprotein oxygenases, was replaced with PraI, a flavoprotein oxygenases of Paenibacillus sp. JJ-1b turned to alleviate the inhibition caused by the accumulation of 4-hydroxybenzoate, thereby increasing muconic synthesis. As P. putida has well been adapted for the above purposes, the variation in the genetic compositions in different strains helps in the search for new model strains, with a less robust genome to manipulate for its use in the biodegradation of different complex substrates. For this purpose, we decided to analyze the full genome of the well-published P. putida strain and confirm its applicability in comparison with the known model S12 as a novel model for genetic biotechnological applications.
One important characteristic of P. putida PCL1760 is the adaptative property to some xenobiotics, rendering it a resistant strain to be used in biotechnological applications in terms of viability to resist some antibiotics (Table 6). Although all of the different Pseudomonas species compared had more antibiotic-resistant genes present in their genome, the two P. putida strains (PCL1760 and S12) had antibiotic efflux pump adeF genes able to prevent the actions of DNA synthesis inhibitors, fluoroquinolone, and tetracycline antibiotics [47,48]. The antibiotic susceptibility test of fluoroquinolone and tetracycline antibiotics showed intermediate resistance to ciprofloxacin (≤3 μg), but not moxifloxacin. Tetracycline resistance was higher in comparison with the fluoroquinolone antibiotics, as observed in P. putida by Igbinosa et al. [49]. Interestingly, antibiogram tests of the nine antibiotics against PCL1760 also revealed resistance to macrolide, aminopenicillin, amphenicol, and aminocyclitol class of antibiotics, although the CARD server did not predict these genes. AntiSMASH results of the PCL1760 genome showed no secondary metabolite operon responsible for volatile antifungal compounds, which are not needed in terms of genetic reconstructions. Pyoverdin (NRP) siderophore was present in all of the compared strains, but with a low percentage similarity, 7–19% (Figure S1). In comparison with S12, both had secondary metabolites, which included lankacidin C (NRP + Polyketide) and O-antigen (Saccharide) and pyoverdin showing the only mechanism for their inhibition by the uptake of essential trace metal ions for microbial growth. Another interesting piece of information is the absence of core genes (AmbA, AmbB, AmbC, AmbD, AmbE) for the synthesis of L-2-amino-4-methoxy-trans-3-butenoic acid (AMB)—a toxin against prokaryotes and eukaryotes, in the clusters of P. simiae PCL1751, P. simiae WCS417, and P. fluorescens W-6 [50]. This suggests the possibility of the strains losing these ‘luxury’ genes, thereby controlling plant diseases by CNN, as confirmed in P. putida PCL1760.
Gene clusters on the genomic server, Orthovenn2, showed the presence of genes responsible for cadmium ions and mandelamide amidase or hydrolase (Pseudomonas mandelamide hydrolase) activity in all compared strains except for PCL1760 and W-6. As observed in these Pseudomonas strains analyzed, a study was reported on a different P. putida strain ATCC 12633 that harbors an operon responsible for the catabolic activity of mandelate that can be a sole carbon source for cell growth [51]. Another interesting finding is the presence of gene clusters responsible for aromatic compounds including inositol catabolic processes in all the tested strains. In contrast to S12, only one cluster gene was found in PCL1760 that was responsible for aromatic compounds catabolism and identical to S12, whilre S12 harbors the gene cluster also responsible for mandelamide amidase activity (Figure S14). The absence of these gene clusters shows P. putida PCL1760 as a suitable biotransformation host organism for easy cloning of operons responsible for the biocatalysts of complex aromatic compounds without the interference of other ‘autochthonous’ operons [52].
An important genetic characteristic in the genome for bacteria immunity against bacteriophages is the presence of CRISPR/Cas and Prophage genes, which can also be manipulated by anti-CRISPR genes of some phages to bypass the immune system of bacteria [53,54]. In this case, the greater the number of CRISPR genes present in the genome, the wider the resistance to other phages or the lower the chance of the strain encountering anti-CRISPR genes to manipulate their defense system. From the results obtained, in comparison with the two P. putida strains (KT2440 and S12) as robust laboratory ‘work horses’ [43], PCL1760 might have an advantage over S12 (5 to 3 CRISPR genes, respectively). Prophages exist in the genome of bacteria after lysogenic infection by bacteriophages as a ‘moron’ gene (enhancing the immunity of the host), as phage-encoding toxins (to increase virulence in pathogens), or as cryptic prophages (to help bacteria adapt to adverse conditions) [55,56,57]. In our study, PCL1760 and S12 had the same number of Prophages, but PCL1760 had an intact unique Pseudo YMCII in comparison with the incomplete Bacilli-v8-BIS-BMBtp14 of S12. Although prophages have been proposed to have a link with CRISPR spacers targeting protospacers or STS (self-targeting spacers) to promote auto-immunity, there is still an innate immunity in the acquisition of prophages [58,59]. Thus, the full genomic comparison of P. putida PCL1760 to the closely related strain S12 and the other species of Pseudomonas analyzed in this work confirms the CNN mechanism of PCL1760 and its genomic amenability for genetic engineering.

5. Conclusions

In summary, the full genome analysis helped to confirm the CNN mechanism of P. putida strain PCL1760 as a sole mechanism for protecting plants against microbial pathogens. This was based on the low percentage similarity of the predicted secondary metabolites biosynthesis gene and the absence of cluster genes responsible for antibiosis. The inhibition effect on P. syringae might be due to siderophores (pyoverdin) in the gene clusters of PCL1760, which chelate essential trace metal ions, which can be also considered as a CNN mechanism. The genomic comparison to the known model strain P. putida S12 thus suggests PCL1760 as a competitive strain in terms of immunity (CRISPR/Cas and Prophages), antibiotic resistance, and its flexibility as a cell factory for genetic manipulations or biosynthesis of desirable organic compounds. The strain has a high prospect not only in agriculture (plant protection and plant growth promoting), but also in biotechnology as a genetic model strain.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/applmicrobiol2040057/s1. Table S1: CRISPR/CAS elements present in P. putida PCL1760 using CRISPR Finder; Table S2: CRISPR/CAS elements present in P. putida S12 using CRISPR Finder; Table S3: CRISPR/CAS elements present in P. fluorescens Pt14 using CRISPR Finder; Table S4: CRISPR/CAS elements present in P. fluorescens W-6 using CRISPR Finder; Table S5. CRISPR/CAS elements present in P. simiae PCL1751 using CRISPR Finder; Table S6: CRISPR/CAS elements present in P. simiae WCS417 using CRISPR Finder; Figure S1: Analysis of secondary metabolites biosynthesis of P. putida PCL1760 (A), P. putida S12 (B), P. simiae PCL1751 (C), P. fluorescens Pt14 (D), P. simiae WCS417(E), and P. fluorescens W-6 (F) using antiSMASH; Table S7: Prophages predicted in P. putida PCL1760 using PHASTER; Table S8. Prophages predicted in P. putida S12 using PHASTER; Table S9: Prophages predicted in P. fluorescens Pt14 using PHASTER; Table S10: Prophages predicted in P. simiae WCS417 using PHASTER; Table S11: Prophages predicted in P. simiae PCL1751 using PHASTER; Table S12: Prophages predicted in P. fluorescens W-6 using PHASTER; Figure S2: Clusters present in the strain of P. putida PCL1760 that are not included in any orthologous clusters with other strains; Figure S3: The unique clusters present in the strain of P. fluorescens Pt14 that are not included in any orthologous clusters with other strains; Figure S4: The unique clusters present in the strain of P. fluorescens W-6 that are not included in any orthologous clusters with other strains; Figure S5: The unique clusters present in the strain of P. putida S12 that are not included in any orthologous clusters with other strains; Figure S6: The unique clusters present in the strain of P. simae PCL1751 that are not included in any orthologous clusters with other strains; Figure S7: The unique clusters present in the strain of P. simae WCS417 that are not included in any orthologous clusters with other strains; Figure S8: Orthologous gene clusters shared by PCL160 with the strain of S12; Figure S9: Clusters shared among strains of PCL1760, Pt14, W-6, PCL1751, and WCS417; Figure S10: Clusters shared among strains of Pt14, W-6, S12, PCL1751, and WCS417; Figure S11: Cluster GO:0019439; P:aromatic compound catabolic process; IEA:UniProtKB-KW shared by the strain of PCL1760 with Pt14, W-6, S12, PCL1751, and WCS417. Layout of the cluster (A); multiple sequence alignment (B), phylogenetic tree (C); Figure S12: Cluster GO:0019310; P:inositol catabolic process; IEA:UniProtKB-UniRule shared by the strain of PCL1760 with Pt14, W-6, S12, PCL1751, and WCS417. Layout of the cluster (A), multiple sequence alignment (B), and phylogenetic tree (C); Figure S13: Clusters shared among strains of Pt14, W-6, PCL1751, and WCS417 that are not included in any orthologous clusters with other strains; Figure S14: Cluster GO:0050537, F:mandelamide amidase activity; IDA:UniProtKB shared by the strain of Pt14, S12, PCL1751, and WCS417; Figure S15: Antagonistic activity of P. putida PCL1760 against P. syringae DC300 on M9 minimal (A) and LB (B) agar plates. Bacillus velezensis KS04AU and Bacillus aryabhattai NN2 were used as positive controls, respectively; Figure S16: The antibiotic susceptibility test of P. putida PCL1760 using the disk diffusion method performed on Multer–Hinter agar.

Author Contributions

Conceptualization, S.Z.V. and D.M.A.; methodology, R.G.C.D., E.S.K. and A.K.M.; software, R.G.C.D.; validation, D.M.A. and S.Z.V.; formal analysis, R.G.C.D. and D.M.A.; investigation, D.M.A., R.G.C.D., A.K.M., and E.S.K.; data curation, D.M.A.; writing—original draft preparation, D.M.A. and R.G.C.D.; writing—review and editing, S.Z.V., D.M.A. and R.G.C.D.; supervision, D.M.A. and S.Z.V.; project administration, S.Z.V. All authors have read and agreed to the published version of the manuscript.

Funding

The study was conducted with financial support provided by the Ministry of Education and Science of the Russian Federation, Grant No. 075-15-2022-254 17.06.2022 (13.2251.21.0126).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Figure 2. The analysis of orthologous gene clusters using OrthoVenn2. (A) Venn diagram presentation of orthologous clusters distributed among P. putida PCL1760 and related species. (B) Summary of protein harbored by each species. (C) Orthologous gene clusters’ distribution and proteins counted among P. putida PCL1760 and related strains of Pseudomonas genus. (D) Similarity matrix for paired genome comparisons showing a heat map between genomes.
Figure 2. The analysis of orthologous gene clusters using OrthoVenn2. (A) Venn diagram presentation of orthologous clusters distributed among P. putida PCL1760 and related species. (B) Summary of protein harbored by each species. (C) Orthologous gene clusters’ distribution and proteins counted among P. putida PCL1760 and related strains of Pseudomonas genus. (D) Similarity matrix for paired genome comparisons showing a heat map between genomes.
Applmicrobiol 02 00057 g002
Figure 3. Antagonistic activity of P. putida PCL1760 against S. aureus RN6390 (A), P. syringae DC3000 (B), and P. aeruginosa IR1.5 (C). Bacillus velezensis KS04AU and Bacillus aryabhattai NN2 were used as positive and negative controls, respectively.
Figure 3. Antagonistic activity of P. putida PCL1760 against S. aureus RN6390 (A), P. syringae DC3000 (B), and P. aeruginosa IR1.5 (C). Bacillus velezensis KS04AU and Bacillus aryabhattai NN2 were used as positive and negative controls, respectively.
Applmicrobiol 02 00057 g003
Figure 4. Antagonistic activity of cell-free supernatant obtained from P. putida PCL1760 against S. aureus RN6390 (A), P. syringae DC3000 (B), and P. aeruginosa IR1.5 (C). Rifampicin and sterile PBS were used as positive and negative controls, respectively.
Figure 4. Antagonistic activity of cell-free supernatant obtained from P. putida PCL1760 against S. aureus RN6390 (A), P. syringae DC3000 (B), and P. aeruginosa IR1.5 (C). Rifampicin and sterile PBS were used as positive and negative controls, respectively.
Applmicrobiol 02 00057 g004
Table 3. Comparative genomic features between P. putida PCL1760 and related strains.
Table 3. Comparative genomic features between P. putida PCL1760 and related strains.
FeaturesPCL1760Pt14W-6S12PCL1751WCS417
Genome size (bp)6,002,7855,841,7226,190,1906,382,4346,143,9506,169,071
G + C (%)61.8060.3062.7061.4460.4060.30
Genes (total)540253015674588856685692
CDSs (total)530352105571580555755615
Genes (coding)521551405484570855075534
Genes (RNA)9991103839377
tRNAs726876617064
ncRNAs445444
Pseudo genes (total)887087976881
Plasmid 000000
CRISPR-elements5111321
Cas3 elements type I101616121414
Table 4. Average nucleotide identity comparison of P. putida PLC1760 with related strains of Pseudomonas genera based on BLAST.
Table 4. Average nucleotide identity comparison of P. putida PLC1760 with related strains of Pseudomonas genera based on BLAST.
PCL1760S12Pt14W-6PCL1751WCS417
PCL176099.30
(94.29)
76.06
(51.55)
75.82
(52.16)
76.26
(52.29)
76.26
(52.27)
S1299.75
(94.84)
76.32
(51.84)
76.03
(52.22)
76.38
(52.58)
76.35
(52.68)
Pt1476.40
(50.52)
76.45
(50.53)
85.65
(75.31)
86.08
(77.14)
86.04
(77.26)
W-675.78
(50.40)
75.77
(50.22)
85.44
(72.36)
86.57
(77.32)
86.59
(77.25)
PCL175176.30
(50.29)
76.32
(50.11)
85.82
(74.17)
86.73
(76.41)
99.50
(95.70)
WCS41776.15
(49.73)
76.12
(49.60)
85.70
(73.71)
86.57
(76.28)
99.41
(95.25)
N.B. ANI (average nucleotides aligned)—data in italic; ANIb (average nucleotides aligned based on BLAST)—data in bold.
Table 5. Comparison of the prophage predicted in related bacterial strains.
Table 5. Comparison of the prophage predicted in related bacterial strains.
Predicted ProphagesThe Presence (+) or Absence (−) in Related Bacterial Strains
PCL1760S12Pt14W-6PCL1751WCS417
PHAGE Escher 500465 1 NC 049342++++
PHAGE Pseudo YMC11/02/R656 NC 028657+++++
PHAGE Pseudo JBD44 NC 030929++
PHAGE Bacill vB BtS BMBtp14 NC 048640+
PHAGE Vibrio VP882 NC 009016 +++
PHAGE Pseudo F10 NC 007805+
PHAGE Vibrio vB VpaM MAR NC 019722+
PHAGE Salmon SJ46 NC 031129+
Table 6. Antimicrobial resistance gene family between P. putida PCL1760 and related bacterial strains.
Table 6. Antimicrobial resistance gene family between P. putida PCL1760 and related bacterial strains.
ARO TermAMR Gene FamilyDrug ClassResistance MechanismThe Presence (+) or Absence (−) in Related Bacterial Strains
PCL1760S12Pt14W-6PCL1751WCS417
adeFResistance-nodulation-cell division (RND) antibiotic efflux pumpfluoroquinolone antibiotic, tetracycline antibioticantibiotic efflux++++++
Pseudomo-nas aeruginosa soxRATP-binding cassette (ABC) antibiotic efflux pump, major facilitator superfamily (MFS) antibiotic efflux pump, resistance-nodulation-cell division (RND) antibiotic efflux pumpfluoroquinolone antibiotic, cephalosporin, glycylcycline, penam, tetracycline antibiotic, rifamycin antibiotic, phenicol antibiotic, disinfecting agents and antisepticsantibiotic target alteration, antibiotic efflux++++
Acinetobacter baumannii AbaQmajor facilitator superfamily (MFS) antibiotic efflux pumpfluoroquinolone antibioticantibiotic efflux++++
Table 7. The comparison of gene clusters related to the biosynthesis of secondary metabolites between P. putida PCL1760 and related bacterial strains.
Table 7. The comparison of gene clusters related to the biosynthesis of secondary metabolites between P. putida PCL1760 and related bacterial strains.
Secondary Metabolites Related to the Most Known Biosynthesis Cluster GenesThe Presence (+) or Absence (−) in Related Bacterial Strains
PCL1760S12Pt14W-6PCL1751WCS417
O-antigen++++++
lankacidin C++++++
pyoverdin++++++
fengycin++++
APE-vf++++
Coelibactin+++
L-2-amin0-4-methoxy-trans-3-butenioc acid++
Pseudomonine+
Ambactin+
Table 8. Comparison of the number of proteins, orthologous clusters, and singletons predicted in the strain of PCL1760 and related bacterial strains assembly using OrthoVenn2.
Table 8. Comparison of the number of proteins, orthologous clusters, and singletons predicted in the strain of PCL1760 and related bacterial strains assembly using OrthoVenn2.
SpeciesClusterSingletons
P. putida PCL17604920278
P. simiae PCL17514702469
P. fluorescens Pt144817613
P. simiae WCS4174890161
P. putida S125345172
P. fluorescens W-65375192
Table 9. Antibiotic susceptibility test of Pseudomonas putida strain PCL1760.
Table 9. Antibiotic susceptibility test of Pseudomonas putida strain PCL1760.
AntibioticsMasses of Antibiotics and Susceptibility of P. putida PCL1760
0.75 µg1.5 µg3 µg6 µg12 µg24 µg
Erythromycin RRRRRR
CiprofloxacinRIISSS
MoxifloxacinSSSSSS
AmpicillinRRRRRR
ChloramphenicolRRRRRR
KanamycinIIISSS
CeftriaxoneIISSSS
SpectinomycinRRRRRR
TetracyclineRRRRRI
Legend: (S)–Susceptible, (I)– intermediate and (R)–resistant.
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Afordoanyi, D.M.; Diabankana, R.G.C.; Miftakhov, A.K.; Kuchaev, E.S.; Validov, S.Z. Genomic Features of Pseudomonas putida PCL1760: A Biocontrol Agent Acting via Competition for Nutrient and Niche. Appl. Microbiol. 2022, 2, 749-765. https://doi.org/10.3390/applmicrobiol2040057

AMA Style

Afordoanyi DM, Diabankana RGC, Miftakhov AK, Kuchaev ES, Validov SZ. Genomic Features of Pseudomonas putida PCL1760: A Biocontrol Agent Acting via Competition for Nutrient and Niche. Applied Microbiology. 2022; 2(4):749-765. https://doi.org/10.3390/applmicrobiol2040057

Chicago/Turabian Style

Afordoanyi, Daniel Mawuena, Roderic Gilles Claret Diabankana, Aynur Kamilevich Miftakhov, Evgenii Sergeyevich Kuchaev, and Shamil Zavdatovich Validov. 2022. "Genomic Features of Pseudomonas putida PCL1760: A Biocontrol Agent Acting via Competition for Nutrient and Niche" Applied Microbiology 2, no. 4: 749-765. https://doi.org/10.3390/applmicrobiol2040057

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