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Microbiological and molecular studies on a multidrug-resistant Pseudomonas aeruginosa from a liver transplant patient with urinary tract infection in Egypt

BMC Microbiology volume 24, Article number: 184 (2024) Cite this article

Abstract

Background

Pseudomonas aeruginosa is an opportunistic pathogen responsible for complicated UTIs and exhibits high antibiotic resistance, leading to increased mortality rates, especially in cases of multidrug-resistant strains. This study aimed to investigate the antibiotic susceptibility patterns and genomic characterization of XDR strains identified in end-stage liver disease patients who underwent liver transplants.

Methods

In this study, a number of 30 individuals who underwent liver transplants were registered. Ninety urine and 60 wound site swab samples were collected and processed for culturing, identification, and antimicrobial sensitivity. Extensively drug-resistant strain EMARA01 was confirmed through Sanger sequencing and was then processed for whole genome sequencing to characterize the genomic pattern. Sequencing data were processed for de novo assembly using various tools and databases, including genome annotation, serotype identification, virulence factor genes, and antimicrobial resistance gene. Pangenome analysis of randomly selected 147 reference strains and EMAR01 sequenced strain was performed using the Bacterial Pan Genome Analysis (BPGA) software.

Results

Of these total examined samples, nosocomial infection due to P. aeruginosa was detected in twelve patients’ samples. AST analysis showed that P. aeruginosa strains exhibit resistance to tobramycin, erythromycin, and gentamicin, followed by piperacillin and ofloxacin, and no strains exhibit resistance to meropenem and imipenem. The CARD database identified 59 AMR genes similar to the EMAR01 strain genome and mostly belong to the family involved in the resistance-nodulation-cell division (RND) antibiotic efflux pump. Five genes; nalC, nalD, MexR, MexA, and MexB, exhibit resistance to 14 classes of antibiotics, while two AMR; CpxR, and OprM, exhibit resistance to 15 classes of drugs. Pangenome analysis revealed that the pan-genome remained open, suggesting the potential for acquiring accessory and unique genes. Notably, the genes predominantly involved in amino acid transport metabolism were identified using the KEGG database.

Conclusions

This study provides valuable insights into the antimicrobial resistance profile, genetic features, and genomic evolution of P. aeruginosa strains causing UTIs in liver transplant patients. The findings emphasize the significance of comprehending AMR mechanisms and genetic diversity in P. aeruginosa for developing effective treatment strategies and infection control measures.

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Background

Liver transplantation surgery is a life-extending procedure for individuals suffering from end-stage liver disorder (ESLD). Opportunistic microbial infections are common during the initial year following liver transplantation surgery, primarily because the immune systems of individuals are suppressed by regular medications such as corticosteroids, which aid in the acceptance of the transplanted organ [1,2,3]. Among Liver transplant patients, bacterial infections reign as the predominant type, accounting for 70% of all infections observed, followed by fungal and viral infections. The risk of infection fluctuates depending on the postoperative timeframe, this temporal aspect plays a significant role in determining the susceptibility to the microbial infections [4]. Urinary tract infections (UTIs), bacteraemia, and pneumonia stand out as the most prevalent infections in the postoperative patients [5].

Pseudomonas aeruginosa is a formidable opportunistic human pathogen that can cause severe acute and chronic infections, particularly in immune-compromised patients, and is also responsible for the leading cause of complicated urinary tract infections (UTIs) [6, 7]. Such complicated UTIs due to P. aeruginosa strains often follow a progressive course because of their adaptability to various stress conditions and multifactorial resistance [8]. The high intrinsic antibiotic resistance mechanism of P. aeruginosa and its flexibility to develop new resistance during antibiotic treatment enables it to overcome many antibiotics [9]. Non-resistant strains are responsible for high mortality rates of up to 23% in UTI patients, while the mortality rate increases substantially to approximately 67% in cases of infection caused by multi-drug resistant (MDR) strains [10]. P. aeruginosa can harbour and accrue numerous resistance determinants resulting in frequent MDR [11]. P. aeruginosa isolated from organ transplant recipients exhibits significantly elevated rates of carbapenem resistance compared to those isolated from non-transplant recipients [12]. This finding highlights the tendency of P. aeruginosa to develop resistance mechanisms in individuals who have undergone organ transplantation. Reports in liver transplant recipients are often in the setting of single centre outbreaks or high local prevalence [13]. Rates of P. aeruginosa bloodstream infections in liver transplant range from 6.5 to 10%, with over 50% of isolates demonstrating multiple drug resistance [14]. Although recommended by many experts, routine combination therapy’s role in treating P. aeruginosa infections remains controversial [15].

Recently, the emergence of MDR and extensively drug-resistant (XDR) bacterial strains as a result of the evolution of many resistance genes such as lactamases, 16 S rRNA methylases, and carbapenems has resulted in incurable microbial infections with serious global threats to human health, underscoring the need for novel treatment approaches. The most prevalent form of P. aeruginosa-acquired resistance is the development of carbapenems, which impart resistance to most commercially available B-lactams [16]. The main defence mechanisms employed by P. aeruginosa against antibiotic assault may generally be divided into intrinsic, acquired, and adaptive resistance [17]. The low permeability of the outer membrane, the development of efflux pumps that expel drugs from the cell, and the creation of antibiotic-inactivating enzymes are all characteristics of P. aeruginosa intrinsic resistance [18].

The advancements in DNA sequencing technology has enabled the utilization of whole genome sequencing (WGS) in identifying, examining the evolutionary patterns of P. aeruginosa and investigating its epidemiology within healthcare facilities [19]. WGS has emerged as a cutting-edge approach to studying resistance mechanisms in bacteria, providing comprehensive insights into the genetic makeup of the pathogens. Moreover, this technique enables the simultaneous processing of vast amounts of DNA sequences in a high-throughput manner, reducing both time and resource requirements [20].

Herby, we systematically screened the presence of P. aeruginosa in both urine and stool specimens obtained from the liver transplant patients, both prior to and following the surgery. Additionally, we identified the antimicrobial resistance (AMR) genes in Liver transplant patient with UTI by sequencing the whole genome of the P. aeruginosa EMARA01 strain that exhibits resistance to various antibiotics from the liver transplant patient with urinary tract infection. This strain demonstrated heightened resistance to a broader spectrum of antibiotics compared to other P. aeruginosa isolates in this study. Genome sequencing analysis revealed 59 AMR genes involved in resistance against various drug classes, and with various resistance mechanisms. Pangenome analysis of EMARA01 with 147 randomly selected reference P. aeruginosa genomes of clinical isolates was performed to analyse both its genomic evolution and genetic diversity. To the best of our knowledge, this is the first study for the comparative genome analysis of P. aeruginosa strains obtained from liver transplant patient in Egypt, and as compared with other Arabian countries, and diverse geographical regions.

Materials and methods

Sample Collection and ethical approval

A cohort of 30 end-stage liver disease patients who had undergone liver transplants between March 2021 to December 2021 at the Gastroenterology Surgical Center (GEC), Mansoura University Hospital, Egypt, was included in the current study. The study was conducted according to the principles of the Declaration of Helsinki. Approval code MDP.23.08.129 was acquired from the Ethical Committee from the Faculty of Medicine, Mansoura University, Egypt. Following the acquisition of written informed consent from all of the participants in this study, urine samples were collected from each registered patient according to the specified criteria: one week before the liver transplant, one week after the transplant, and two weeks post-transplant, while swab samples at the surgical wound sites were obtained after one week and two weeks of postoperation. All samples were transported to the clinical microbiology laboratory within two hours to ensure timely analysis. Samples were analyzed for the identification of nosocomial infection due to P. aeruginosa.

Bacterial isolation, identification, and Antibiotic Susceptibility Test (AST)

All samples were initially processed for Gram staining and followed by culturing. The Gram-positive bacteria were inoculated using differential growth medium Blood Agar [21], while the Gram-negative bacteria were cultured in the cystine lactose electrolyte deficient agar (CLED) and MacConkey agar [22, 23] The inoculated plates were incubated aerobically at 37 °C for 24 h, and the isolated colonies were evaluated for colony morphology and then were examined for identification based on biochemical and molecular evaluation. For biochemical identification, the isolated colonies were examined for catalase [24], oxidase [25], triple sugar iron [26], indole [27], H2S production, and motility. Furthermore, it was further confirmed using an analytical profile index (API) [28]. Additionally, the bacterial DNA was isolated for molecular identification using DNeasy® Blood & Tissue Kit [29, 30]. The quality of extracted DNA was evaluated by Agarose gel electrophoresis [31], and the concentration was estimated by nanodrop. The targeted region (16 S DNA) was amplified by using two sets of universal primers; [785-For Primer GGATTAGATACCCTGGTA; & 907-Rev Primer: CCGTCAATTCMTTTRAGTTT] and [27-For Primer: AGAGTTTGATCMTGGCTCAG & 1492-Rev Primer: TACGGYTACCTTGTTACGACTT] [32, 33] The amplified products were confirmed by 2% Agarose gel electrophoresis. Amplified samples with intact bands were processed using GeneJET™ PCR purification kit (Thermo Scientific, USA) followed by chain termination reaction/Sanger sequencing using BigDye Terminator v.3.1 cycle sequencing kit as per manual instruction. Both strands were examined for chain termination reaction/Sanger sequencing to obtain the consensus sequences. The sequencing product was purified by ethanol precipitation and sequencing using an ABI Genetic analyser. The obtained consensus sequences and the sequencing data were analysed using BioEdit v 7.0 software [18]. The consensus sequences were processed for BLAST analysis to confirm the species with maximum resemblance.

The isolated colonies from the different culture media were examined for an antimicrobial sensitivity test (AST) using the Kirby Bauer technique [34] as per the guidelines of the Clinical and Laboratory Standards Institute (CLSI) [35]. For AST analysis, we examined the following antibiotics, including ciprofloxacin (CIP 5 µg), norfloxacin (NOR 10 µg), ofloxacin (OFX 5 µg), imipenem (IPM 10 µg), meropenem (MEM 10 µg), piperacillin (PRL 100 µg), ceftazidime (CAZ 10 µg), gentamicin (CN 10 µg), amikacin (AK 30 µg), tobramycin (TOB 10 µg) and erythromycin (E 15 µg) were examined for AST. Finally, the genomic characterization was performed for the most antibiotic-resistant P. aeruginosa EMARA01 strain, isolated from the patient’s urine sample.

Whole Genome Sequencing and Annotation

Whole genome sequencing of MDR P. aeruginosa EMARA01 strain was performed using 2*151 bp flow cell chemistry on the NovaSeq Illumina. The quality of short-sequenced raw reads was evaluated by the FASQC tool [36]. Adapter sequences and the poor-quality data were trimmed using Trimmomatic [37] software with default parameter settings. The quality cut-off value was Phred33. P. aeruginosa genome assembly was performed using BWA MEM package [38] and the percentage of the covered draft genome was determined by samtools [39]. The quality of the EMARA01 strain sequenced data aligned against the PA01 reference genome strain was evaluated by Qualimap v 2.3 [40].

The sequenced data was processed for de novo assembly using Unicycler [41], and the accuracy of assembled genome was improved by Pilon [42]. The quality of the assembled draft genome was assessed by QUAST [43]. The annotation of the sequenced EMARA01 strain was performed by NCBI Prokaryotic Genome Annotation Pipeline (PGAP), as well as PATRIC v 3.6.12, and rapid annotation using Subsystem Technology 2.0 (RAST) online tools [44]. The genomic visualization of the bacterial genome was performed by the Proksee tool [44].

The Pseudomonas aeruginosa serotyper (PAst) 1.0 tool (https://cge.food.dtu.dk/services/PAst) was employed for serotyping and serogrouping analysis, while the PathogenFinder tool [45] was used to determine the strain’s pathogenicity. To predict the antimicrobial resistance (AMR) genes in the EMARA01 strain, an in-silico method was employed using various databases, including the Comprehensive Antibiotic Resistance Database (CARD) [46], ResFinder 4.1 [47] (https://cge.cbs.dtu.dk/services/ResFinder). The BacAnt (http://bacant.net/BacAnt/) was also searched to identify resistance genes, introns, and transposable elements with 90% identity and 60% coverage [48]. The presence of plasmids was investigated using the plasmid database (PLSDB) [49], and virulence genes were identified using the virulence factor database (http://www.mgc.ac.cn/VFs). The antiSMASH v7.0.0 tool was utilized for secondary metabolites identification [50], and BAGEL4 was used to search genes coding bacteriocin [51].

Pangenome Analysis

The pan-genome and core genome statistics of the 148 P. aeruginosa strains were assessed using BPGA [52]. This analysis aimed to identify strain-specific genomic features and to analyse the genomic diversity among the selected strains. The study utilized genome sequences of 147 P. aeruginosa strains obtained from 30 countries belonging to various geographic regions, mostly from Egypt, Lebanon, India, China, Saudi Arabia, USA, Switzerland, and Turkey, sourced from the NCBI database along with one in-house sequenced strain (EMARA01).

Gene clustering into families was performed by the USEARCH clustering algorithm, and the sequence identity was selected as 70%. The pan-core plot was constructed with 30 combinations, and the coding sequences were aligned by MUSCLE. Core and pangenome phylogeny were plotted by the Neighbour-Joining method, and the phylogenetic visualization was done using web- based iTOL (https://itol.embl.de/).

Biological function and Pathways Identification

The BPGA’s pan-genome functional analysis module was utilized to assign cluster of Orthologous Genes (COG) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) classifications to the core, accessory, and unique gene families. The KEGG is a collection of databases dealing with genomes, gene function, biological pathways, diseases, drugs, and metabolism. Genes involved in the function pathways were also identified using the RASTtk annotation tool.

Results and discussion

Bacterial isolation, Identification and AST

The consent of thirty liver transplant patients in this study was taken. In this study, urine specimens were collected from patients at various time points before and after liver transplant surgery, along with wound site samples obtained at the corresponding intervals post-transplantation. Following analysis, P. aeruginosa was identified in a subset of patient samples, as it was detected in four urine samples and eight wound site samples collected from one week of the surgery. Gram staining result showed Gram-negative rods. The isolated bacterial colonies were tested positive for oxidase, citrate and negative for urease, indole, and H2S. Further, the colonies were identified as P. aeruginosa based on API. API results indicate that the EMARA01 strain showed a positive reaction with ADH (decarboxylation of the amino acid arginine by arginine dihydrolase), citrate, hydrolysing the gelatine (indicating the presence of gelatinase), and nitrate reduction (Supplementary Fig. 1).

Of the twelve P. aeruginosa strains, four isolated from urine samples and eight identified from wound site swab samples were tested for drug sensitivity and resistance. The tested result indicated that all twelve strains exhibit resistance to tobramycin, erythromycin, and gentamicin, followed by piperacillin, and ofloxacin, and no strains exhibit resistance to meropenem and imipenem. Despite the historical prominence of aminoglycoside antibiotics such as tobramycin and gentamicin in the treatment of P. aeruginosa infections, it is surprising that all isolates in this study were resistant to these drugs. It is conceivable that prolonged historical usage of these antibiotics has facilitated the development of resistance in P. aeruginosa. This resistance may arise through diverse mechanisms, such as the production of enzymes that deactivate the antibiotics or through efflux pumps. Therefore, the exploration of combination therapy or the pursuit of novel therapeutic approaches is strongly encouraged to address this challenge. The details of all tested 11 antibiotics tested among all P. aeruginosa strains isolated from urine samples and wound site swab isolated from liver transplant patient is shown in (Table 1).

Table 1 Antibiotic sensitivity test by using disk diffusion method according to CLSI 2018
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P. aeruginosa is recognized as a prominent contributor to nosocomial infections. A comprehensive study of isolates’ susceptibility to antimicrobial drugs is necessary to reduce the spread of this antimicrobial-resistant microorganism and to implement effective infection control strategies [53]. The analysis of antimicrobial susceptibility testing (AST) in the study disclosed that all strains were responsive to meropenem and imipenem, yet resistant to tobramycin, erythromycin, and gentamicin antibiotics. The four scrutinized antibiotics including amikacin, ciprofloxacin, meropenem, and imipenem, were identified as crucial components of anti-pseudomonal agents, exhibiting diverse levels of susceptibility among the isolates. All isolates were susceptible to meropenem, and imipenem, 92% were sensitive to amikacin, and 66% showed susceptibility to ciprofloxacin. Exploring the fluoroquinolone family, ofloxacin revealed a spectrum of responses: one isolate was susceptible, seven displayed intermediate resistance, and five exhibited full resistance among the twelve isolates. Turning attention to the quinolone family, norfloxacin demonstrated six isolates with susceptibility, five with intermediate resistance, and two with resistance (Table 1). In this study, more than 70% of the P. aeruginosa isolates exhibited resistance to ceftazidime (77%), piperacillin (75%), tobramycin (100.0%), and gentamicin (100.0%). These results were in line with previous reports from Iran [54], Egypt [55], USA [56], Kingdom of Saudi Arabia [57, 58], Malaysia [59]. It is noted that there was low resistance rates for ceftazidime was noted in Iran [60]. The variation could be attributed to distinctions in population characteristics, including type and race, as well as variations in isolate sources.

The phenotypic characterization of the antimicrobial resistance patterns of the P. aeruginosa EMARA01 identified in the urine sample collected before one week of the liver transplant exhibit resistance to numerous clinically available important antibiotics except for amikacin and two β-lactam antibiotics; meropenem and imipenem. This MDR EMARA01 strain was confirmed at the molecular level through 16 S rRNA (Supplementary Fig. 2). The gel image confirmed the amplified products, which were then processed for Sanger sequencing using both targeted regions. The consensus sequences were processed for BLAST analysis, and it is noted that the EMARA01 strain exhibits high nucleotide similarity to P. aeruginosa species. The sequenced data with read length 1356 nucleotides of 16 S rRNA gene (accession no. OQ976904) exhibit the closest similarity to P. aeruginosa various strains such as WS02, UASR_4, P2, SJC-03, and P4. Hence, the confirmed MDR P. aeruginosa EMARA01 was selected for complete genome sequencing.

Genome annotation of P. Aeruginosa EMARA01

The paired-end sequencing data obtained from the sequencing platform comprised 18,470,938 short reads in fastq format. After FASTQC analysis, all reads underwent pre-processing using the trimmomatic package with default parameters. This process involved removing adapter sequences, low-quality regions (especially towards the ends of the reads), and bases with a Phred score of less than 33. Out of the total filtered reads, 17,627,341 short-sequenced reads were aligned against the reference strain PA01 comprised of 6,264,404 nucleotide bases. Of the total mapped reads, 8,841,139 were first in pair and 8,786,202 s in pair, while 107,081 reads singleton in pair. The mean mapping quality of the EMARA01 strain against the reference genome was 59.37 and the sequence read depth was 411.2. The coverage of each base against the reference genome PAO1 strain is shown in (Supplementary Fig. 3).

The filter-sequenced reads were further processed for de novo assembly using Unicycler. The quality of the assembly was improved by Pilon, resulting in a final assembly of the P. aeruginosa EMARA01 genome with 66 contigs, each having a length greater than 300 bases. The assembled genome of P. aeruginosa EMARA01 (accession No. JARQZF000000000.1) was composed of 6,438,302 nucleotides distributed among the 66 contigs, with a GC content of 66.38%. The largest contig had a length of 1,044,180 bases, while the contig with the N50 value had a length of 394,570 nucleotides. The contig L50 value was 5, indicating the number of contigs needed to reach half of the genome length. Functional annotation of EMARA01 using PGAP identified 5,928 coding sequences (CDSs) and 65 RNA sequences. Among the 5,928 CDSs, 5,893 encoded proteins, while 35 were pseudogenes that did not code for any proteins. Of the 65 total RNA sequences, 58 were tRNA, and three were rRNA (two complete rRNA, including one 16 S, one 23 S, and one partial 5 S rRNA). The protein features included 5,416 previously characterized proteins and 477 hypothetical proteins. The non-ribosomal peptide synthase/polyketide synthase had the highest number of amino acids (n = 4,989), while the pyrroloquinoline quinone precursor peptide PqqA consisted of only 23 amino acids in the sequenced genome. The circular representation of the assembled P. aeruginosa EMARA01 genome visualized by Proksee is shown in (Fig. 1).

Fig. 1
figure 1

Circular genomic organization and characterization of P. aeruginosa EMARA01 strain. In A first three circle exhibit CDSs in forward strand, a contigs layer, three CDSs in reverse strand, two layers of GC skew and last circle representing GC content. B representing the position of AMR identified by using CARD database

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PathogenFinder analysis showed that the sequenced EMARA01 strain predicted as pathogenic with a probability of being a human pathogen was 0.75 out of 1. The P. aeruginosa serotyper (PAst) is utilized for in silico serotyping of P. aeruginosa isolates into 1 of 11 serogroups (covering the 20 serotypes). The PAst is highly efficient in silico serotyping tool that predicts serogroup based on the sequence of the O-specific antigen (OSA) gene cluster. Here, PAst v1.0 identified that the EMARA01 strain belongs to the O7 serogroup.

Antimicrobial Resistance Profiling

The functional annotation of the EMARA01 strain using the CARD databases revealed the presence of numerous genes that confer resistance to various antibiotics. Based on the CARD database analysis, 59 AMR genes were identified by resistance gene identifier, only selecting perfect and strict criteria (Fig. 1B). Due to its poor outer membrane permeability and aggressive antibiotic efflux, P. aeruginosa is renowned for its inherent resistance to numerous front-line medicines [61,62,63]. Out of 59 AMR genes, 44 genes belong to a family that is involved in resistance-nodulation-cell division (RND) antibiotic efflux pump, five genes; basS, cprR, cprS, arnA, and basR, belong to pmr phosphoethanolamine transferase gene family while the remaining ten belongs to each a single AMR gene family. Based on the protein homology model, four AMR genes, including nalC, nalD, MexR, MexA, and MexB exhibit resistance to 14 class of antibiotics namely macrolide antibiotic, fluoroquinolone antibiotic, monobactam, carbapenem, cephalosporin, cephamycin, tetracycline antibiotic, peptide antibiotic, aminocoumarin antibiotic, diaminopyrimidine antibiotic, sulfonamide antibiotic, phenicol antibiotic, penems. Two AMR genes, Pseudomonas aeruginosa CpxR, and OprM, resist these antibiotics besides cephamycin.

AMR gene profile suggests that the presence of resistome (ARGs) and associated resistance mechanisms in P. aeruginosa EMARA01, along with beta-lactam genes and efflux pump systems, may contribute to this bacterium’s extensive resistance to nearly all antibiotics used for treatment purposes and may even be the reason for its emergence as a pan drug-resistant bacterium in Egypt. Due to its numerous intrinsic defence mechanisms against antibiotics, P. aeruginosa EMARA01 is a particularly dangerous bacterium. According to a preliminary analysis of the distribution of a few genes involved in antibiotic resistance (oprM, ampC, ampD, and PIB-1) and functionally annotated using the Pseudomonas Genome Database, these genetic entities are identified in the in-house sequenced P. aeruginosa EMARA01 strain.

These findings are consistent with those of the P. aeruginosa Pa1242 strain, where it was shown that all four b-lactamase classes coexisted, were inherited chromosomally, and acquired a variety of resistance determinants, are the leading efflux pump systems conferring resistance to P. aeruginosa EMARA01. The resistance of this bacteria can be further increased by its ease of acquiring genetically encoded resistance determinants from other diseases. Through these efflux pump systems, clinically important P. aeruginosa strains demonstrate resistance to various medicines, including fluoroquinolone, rifamycin, cephalosporin, glycylcycline, tetracycline and glycopeptide antibiotic. MexAB-OprM, MexCD-OprJ, MexEFOprN, and MexXY/OprM are examples of tripartite efflux systems that are among the inherent and acquired resistance mechanisms [61] causing the extrusion of xenobiotics and antimicrobials from the inside of the cell. MexA contributes significantly to P. aeruginosa inherent resistance to numerous antibiotics including macrolide, fluoroquinolone, monobactam, carbapenem, cephalosporin, cephamycin, tetracycline, diaminopyrimidine antibiotic, sulfonamide antibiotic, phenicol antibiotic other structurally unrelated antimicrobial compounds, and various structurally unrelated antibacterial substances (Supplementary Table 1). MexEF-OprN can extrude quinolones [64], and MexXY-OprM may eject aminoglycosides and cephalosporins from inside bacterial cells [65]. However, no plasmid sequence was identified using PLSDB in the EMARA01 strain.

Genome annotation using antiSMASH v7.0, used to detect and characterize biosynthetic clusters, predicted the gene clusters, including especially NRP, and Polyketide for several antimicrobial compounds, including azetidomonamide A/azetidomonamide, pyoluteorin, pseudopaline, L-2-amino-4-methoxy-trans-3-butenoic acid, pyochelin, and others. BEAGAL analysis identified two areas of interest; 15.9.AOI_01 for class Bottromycin and 1.15.AOI_01 for class 91.3; Pyocin-S1. Based on nucleotide similarity, BacAnt analysis of EMARA01 strains identified 21 AMR, 15 transposons, and two integrons.

Pan and Core Genome statistics

The versatility of the studied strains is evaluated by assessing the open or closed nature of the pan-genome. The expected gene number in both the pan-genome and core-genome was calculated using curve fitting based on Heaps’ law. The equation Ypan = Apan * x^Bpan + Cpan represents the pan-genome, where Y is the pan-genome size, x is the number of genomes, and Apan, Bpan, and Cpan are fitting parameters. Similarly, the core-genome is represented by the exponential equation Ycore = Acore * e^(-Bcore * x) + Ccore. In this equation, Bpan determines whether the pan-genome is closed (Bpan < 0 or Bpan > 1) or open (0 < Bpan < 1).

A total of 148 strains were analysed, and the genomic data of 81 strains with complete genomes and 67 strains with contigs and scaffolds were obtained from NCBI. The genome size of all strains was observed to be 6.85 ± 0.289 MB, with a GC content of 66.024 ± 0.27. Additionally, the average protein sequences consisted of 6205.4 ± 289.385.

Protein sequences counted 953,346 from the 148 P. aeruginosa strains were examined for pangenome statistics. Figure 2 illustrates the distribution of coding DNA sequences concerning the genome size in all analysed sequenced strains with respect to countries. Among these, core CDSs were 4138, the 0.434% of the total CDSs in the 148 analysed Pseudomonas strains. Gene families (pangenome) and shared gene families (core genome) are plotted for all genomes added sequentially. Using power-fit curve equation: f(x) = 5222.14·x0.27 and exponential curve equation: f1(x) = 4999.31 e-0. 00.x, the parameter ‘b’ value was noted b = 0.272219, indicating that the pan-genome is still opened and the number of accessory and unique genes might be added to the genome (Fig. 3).

Fig. 2
figure 2

Distribution of coding sequences in the studied strains with respect to the genome size

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Fig. 3
figure 3

The pan and core genome plot of studied 148 P. aeruginosa genomes. Total gene families are shown by blue colour while pink colour represents core gene families

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It was previously believed that bacteria, including the genus Pseudomonas, should have a permanently open pan-genome due to natural evolution and horizontal gene transfer. The strain 34Pae36 (accession ID: CP095770) reported from Colombia comprised the highest number of proteins containing CDSs (6994) comprising 2630 accessory genes and 226 unique genes, while strain MCF363 contained the least number of protein-coding sequences (n = 5648) comprising 1479 accessory genes and 31 unique genes. A total number of 5742 unique genes were identified in all strains. Of these, the greatest number of genes (n = 298) were noted in ZBX-P21 (accession ID: JACWGQ01), and the maximum number of genes (n = 96) were exclusively absent in CMC-115 (acc ID. CP046602) that is reported from the USA. In an in-house sequenced P. aeruginosa Emara01 strain, out of 5754 protein-coding sequences, 1601 genes were accessory, 15 were unique and, seven were missing. None of the genes were exclusively absent in 85 strains, the singleton gene was absent in 19 strains, and more than ten genes were missed in 15 strains (Table 2).

Table 2 Pangenome statistics of inhouse sequenced EMARA01 strain and 147 other reference strains
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The phylogenetic relationships between P. aeruginosa EMARA01 and a total of 147 additional P. aeruginosa reference strains were examined to identify the genomic epidemiological features of P. aeruginosa EMARA01 in the context of the world. P. aeruginosa has a dynamic genetic makeup that enables it to colonize a wide range of environments, including humans, where it can cause opportunistic infections [66].

The genomic characteristics of P. aeruginosa EMARA01 are supported by the randomly selected reference strains reported from other regions [67, 68]. Compared to one of the most popular reference strains, P. aeruginosa PAO1, the P. aeruginosa EMARA01 exhibits 99.51% average nucleotide identity. EMARA01 strain genome exhibits a close evolutionary relationship with many other P. aeruginosa strains isolated from various clinical samples from countries like Mexico, Sweden, Egypt, Senegal, Brazil, and Saudi Arabia (Fig. 4). The phylogenetic analysis revealed that EMARA01 exhibits the closest relationship with the CCBH28525 strain isolated from the tracheal secretion of patients admitted to the hospital in Bahia state Brazil [69, 70].

Fig. 4
figure 4

Core genome MLST phylogenetic analysis of the 148 P. aeruginosa strains

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Biological function and Pathways Identification

The COG analysis of the pan-genome revealed that the highest number of genes in the core genome belongs to the prediction of general function, followed by amino acid transport metabolism and transcription (Fig. 5). Similar findings from earlier research have been found for P. aeruginosa core and accessory genomes, with the core genome being enriched in central metabolism functions and important cellular processes like replication, transcription, and translation as well as other related biosynthetic pathways [71, 72].

Fig. 5
figure 5

Cluster of orthologous groups distribution of the genes making up core, accessory and unique portion of the studied genomes

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RAST-based annotation identified 393 subsystems for functional genes and metabolic pathway connections in the EMARA01 strain. Most of the genes were involved in amino acid metabolism (501 genes), followed by genes involved in carbohydrates (n = 288), protein metabolism (n = 220 genes), the synthesis of cofactors, vitamins, prosthetic groups, and pigments (n = 200), several genes were involved in membrane transport, fatty acids, lipids, and isoprenoids, aromatic compounds, response to stress and respiration. According to the subsystem analysis, 62 genes are associated with disease, virulence, and defence. Of these, were responsible for toxic and antibiotic resistance, 17 were involved in invasion and intracellular resistance, and six were associated with the antibacterial peptides. We confirmed multiple earlier investigations by identifying distinct genes and proteins from the whole genome of P. aeruginosa EMARA01 that are attributed to various subsystem metabolic activities [73, 74]. Our study presents a significant increase in metabolic functional genes and the pathways crucial to the emergence of P. aeruginosa infection.

Conclusions

This study provides valuable information on P. aeruginosa isolates obtained from liver transplant patients and their antibiotic resistance profiles. The genomic characterization and pan-genome analysis contribute to our understanding of the genetic diversity and functional aspects of P. aeruginosa genes. These findings may have implications for infection control measures and the development of targeted therapies in the context of liver transplant patients. Future research and surveillance efforts should focus on monitoring the prevalence and dissemination of extensively drug-resistant P. aeruginosa strains, and novel therapeutic approaches targeting the identified AMR genes and pathways should be explored. Ultimately, this knowledge will contribute to improved patient outcomes and the prevention of infections in this vulnerable population.

Data availability

Sequencing data are available at the Sequence Read Archive (NCBI) the 16 S rRNA sequence is deposited under accession number OQ976904 and the assembled genome of P. aeruginosa EMARA01 is uploaded under the accession identifier JARQZF000000000.1.

Abbreviations

AMR:

Antimicrobial Resistance

AST:

Antibiotic susceptibility testing

BPGA:

Bacterial Pan Genome Analysis

COG:

Cluster of Orthologous Genes

CLED:

Cystine lactose electrolyte deficient agar

CLSI:

Clinical and Laboratory Standards Institute

ESLD:

End-stage liver disorder

GEC:

Gastroenterology Surgical Center

KEGG:

Kyoto Encyclopaedia of Genes and Genomes

MDR:

Multi-drug resistant

PGAP:

Prokaryotic Genome Annotation Pipeline

UTIs:

Urinary tract infections

WGS:

Whole genome sequencing

XDR:

Extensively drug-resistant

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Acknowledgements

We want to acknowledge Gastroenterology Surgical Centre, Mansoura University, Egypt for their advice towards collecting the samples, and experimental work.

Funding

The authors declare that they did not receive any fund to conduct this study.

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

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Authors and Affiliations

  1. Department of Botany and Microbiology, Faculty of Science, Menoufia University, Shebin El- Kom, Egypt

    Mohamed T. Shaaban, Muhammad Zayed & Mahmoud A. Emara

  2. Gastroenterology Surgical Centre, Mansoura University, Mansoura, Egypt

    Mohamed Abdel-Raouf

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Contributions

Mohamed T. Shaaban: Experiments design and interpretation of data. Mohamed Abdel-Raouf: Experimental design and collecting sample. Muhammad Zayed: Conceptualization, formal analysis, and writing. Mahmoud A. Emara: Experimental work and writing manuscript.

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Correspondence to Muhammad Zayed.

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The study was conducted according to the principles of the Declaration of Helsinki. An informed consent to participate was obtained from the participants in the study. Approval code MDP.23.08.129 was acquired from the Ethical Committee in the Faculty of Medicine, Mansoura University, Egypt.

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Shaaban, M.T., Abdel-Raouf, M., Zayed, M. et al. Microbiological and molecular studies on a multidrug-resistant Pseudomonas aeruginosa from a liver transplant patient with urinary tract infection in Egypt. BMC Microbiol 24, 184 (2024). https://doi.org/10.1186/s12866-024-03318-0

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BMC Microbiology

ISSN: 1471-2180

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