Comparative genomics of a drug-resistant Pseudomonas aeruginosa panel and the challenges of antimicrobial resistance prediction from genomes

Variation in the response to antibiotics and life-history across the major Pseudomonas aeruginosa clone type (mPact) panel

Pseudomonas aeruginosa is a ubiquitous, opportunistic human pathogen. Since it often expresses multidrug resistance, new treatment options are urgently required. Such new treatments are usually assessed with one of the canonical laboratory strains, PAO1 or PA14. However, these two strains are unlikely representative of the strains infecting patients, because they have adapted to laboratory conditions and do not capture the enormous genomic diversity of the species. Here, we characterized the major P. aeruginosa clone type (mPact) panel. This panel consists of 20 strains, which reflect the species' genomic diversity, cover all major clone types, and have both patient and environmental origins. We found significant strain variation in distinct responses toward antibiotics and general growth characteristics. Only few of the measured traits are related, suggesting independent trait optimization across strains. High resistance levels were only identified for clinical mPact isolates and could be linked to known antimicrobial resistance (AMR) genes. One strain, H01, produced highly unstable AMR combined with reduced growth under drug-free conditions, indicating an evolutionary cost to resistance. The expression of microcolonies was common among strains, especially for strain H15, which also showed reduced growth, possibly indicating another type of evolutionary trade-off. By linking isolation source, growth, and virulence to life history traits, we further identified specific adaptive strategies for individual mPact strains toward either host processes or degradation pathways. Overall, the mPact panel provides a reasonably sized set of distinct strains, enabling in-depth analysis of new treatment designs or evolutionary dynamics in consideration of the species' genomic diversity.

IMPORTANCE

New treatment strategies are urgently needed for high-risk pathogens such as the opportunistic and often multidrug-resistant pathogen Pseudomonas aeruginosa. Here, we characterize the major P. aeruginosa clone type (mPact) panel. It consists of 20 strains with different origins that cover the major clone types of the species as well as its genomic diversity. This mPact panel shows significant variation in (i) resistance against distinct antibiotics, including several last resort antibiotics; (ii) related traits associated with the response to antibiotics; and (iii) general growth characteristics. We further developed a novel approach that integrates information on resistance, growth, virulence, and life-history characteristics, allowing us to demonstrate the presence of distinct adaptive strategies of the strains that focus either on host interaction or resource processing. In conclusion, the mPact panel provides a manageable number of representative strains for this important pathogen for further in-depth analyses of treatment options and evolutionary dynamics.

Comparative genomic analysis of Pseudomonas aeruginosa strains susceptible and resistant to carbapenems and aztreonam isolated from patients with healthcare-associated infections in a Mexican hospital

Pseudomonas aeruginosa (PA) is an important opportunistic pathogen that causes different infections on immunocompromised patients. Within PA accessory genome, differences in virulence, antibiotic resistance and biofilm formation have been described between strains, leading to the emergence of multidrug-resistant strains. The genome sequences of 17 strains isolated from patients with healthcare-associated infections in a Mexican hospital were genomically and phylogenetically analyzed and antibiotic resistance genes, virulence genes, and biofilm formation genes were detected. Fifteen of the 17 strains were resistant to at least two of the carbapenems meropenem, imipenem, and the monobactam aztreonam. The antibiotic resistance (mexA, mexB, and oprM) and the biofilm formation (pslA and pslD) genes were detected in all strains. Differences were found between strains in accessory genome size. The strains had different sequence types, and seven strains had sequence types associated with global high risk epidemic PA clones. All strains were represented in two groups among PA global strains. In the 17 strains, horizontally acquired resistance genes to aminoglycosides and beta-lactams were found, mainly, and between 230 and 240 genes that encode virulence factors. The strains under study were variable in terms of their accessory genome, antibiotic resistance, and virulence genes. With these characteristics, we provide information about the genomic diversity of clinically relevant PA strains.

A comprehensive review of genomics, transcriptomics, proteomics, and metabolomic insights into the differentiation of Pseudomonas aeruginosa from the planktonic to biofilm state: A multi-omics approach

Biofilm formation by Pseudomonas aeruginosa is primarily responsible for chronic wound and lung infections in humans. These infections are persistent owing to the biofilm's high tolerance to antimicrobials and constantly changing environmental factors. Understanding the mechanism governing biofilm formation can help to develop therapeutics explicitly directed against the molecular markers responsible for this process. After numerous years of research, many genes responsible for both in vitro and in vivo biofilm development remain unidentified. However, there is no "all in one" complete in vivo or in vitro biofilm model. Recent findings imply that the shift from planktonic bacteria to biofilms is a complicated and interrelated differentiation process. Research on the applications of omics technologies in P. aeruginosa biofilm development is ongoing, and these approaches hold great promise for expanding our knowledge of the mechanisms of biofilm formation. This review discusses the different factors that affect biofilm formation and compares P. aeruginosa biofilm formation using the omics approaches targeting essential biological macromolecules, such as DNA, RNA, Protein, and metabolome. Furthermore, we have outlined the application of currently available omics tools, such as genomics, proteomics, metabolomics, transcriptomics, and integrated multi-omics methodologies, to understand the differential gene expression (biofilm vs. planktonic bacteria) of P. aeruginosa biofilms.

Nonlethal Molecular Nanomachines Potentiate Antibiotic Activity Against Gram-Negative Bacteria by Increasing Cell Permeability and Attenuating Efflux

Antibiotic resistance is a pressing public health threat. Despite rising resistance, antibiotic development, especially for Gram-negative bacteria, has stagnated. As the traditional antibiotic research and development pipeline struggles to address this growing concern, alternative solutions become imperative. Synthetic molecular nanomachines (MNMs) are molecular structures that rotate unidirectionally in a controlled manner in response to a stimulus, such as light, resulting in a mechanical action that can propel molecules to drill into cell membranes, causing rapid cell death. Due to their broad destructive capabilities, clinical translation of MNMs remains challenging. Hence, here, we explore the ability of nonlethal visible-light-activated MNMs to potentiate conventional antibiotics against Gram-negative bacteria. Nonlethal MNMs enhanced the antibacterial activity of various classes of conventional antibiotics against Gram-negative bacteria, including those typically effective only against Gram-positive strains, reducing the antibiotic concentration required for bactericidal action. Our study also revealed that MNMs bind to the negatively charged phospholipids of the bacterial inner membrane, leading to permeabilization of the cell envelope and impairment of efflux pump activity following light activation of MNMs. The combined effects of MNMs on membrane permeability and efflux pumps resulted in increased antibiotic accumulation inside the cell, reversing antibiotic resistance and attenuating its development. These results identify nonlethal MNMs as pleiotropic antibiotic enhancers or adjuvants. The combination of MNMs with traditional antibiotics is a promising strategy against multidrug-resistant Gram-negative infections. This approach can reduce the amount of antibiotics needed and slow down antibiotic resistance development, thereby preserving the effectiveness of our current antibiotics.

Biofilm antimicrobial susceptibility testing: where are we and where could we be going?

Our knowledge about the fundamental aspects of biofilm biology, including the mechanisms behind the reduced antimicrobial susceptibility of biofilms, has increased drastically over the last decades. However, this knowledge has so far not been translated into major changes in clinical practice. While the biofilm concept is increasingly on the radar of clinical microbiologists, physicians, and healthcare professionals in general, the standardized tools to study biofilms in the clinical microbiology laboratory are still lacking; one area in which this is particularly obvious is that of antimicrobial susceptibility testing (AST). It is generally accepted that the biofilm lifestyle has a tremendous impact on antibiotic susceptibility, yet AST is typically still carried out with planktonic cells. On top of that, the microenvironment at the site of infection is an important driver for microbial physiology and hence susceptibility; but this is poorly reflected in current AST methods. The goal of this review is to provide an overview of the state of the art concerning biofilm AST and highlight the knowledge gaps in this area. Subsequently, potential ways to improve biofilm-based AST will be discussed. Finally, bottlenecks currently preventing the use of biofilm AST in clinical practice, as well as the steps needed to get past these bottlenecks, will be discussed.

Mutation Analysis in Regulator DNA-Binding Regions for Antimicrobial Efflux Pumps in 17,000 Pseudomonas aeruginosa Genomes

Mutations leading to upregulation of efflux pumps can produce multiple drug resistance in the pathogen Pseudomonas aeruginosa. Changes in their DNA binding regions, i.e., palindromic operators, can compromise pump depression and subsequently enhance resistance against several antibacterials and biocides. Here, we have identified (pseudo)palindromic repeats close to promoters of genes encoding 13 core drug-efflux pumps of P. aeruginosa. This framework was applied to detect mutations in these repeats in 17,292 genomes. Eighty-nine percent of isolates carried at least one mutation. Eight binary genetic properties potentially related to expression were calculated for mutations. These included palindromicity reduction, mutation type, positioning within the repeat and DNA-bending shift. High-risk ST298, ST308 and ST357 clones commonly carried four conserved mutations while ST175 and the cystic fibrosis-linked ST649 clones showed none. Remarkably, a T-to-C transition in the fourth position of the upstream repeat for mexEF-oprN was nearly exclusive of the high-risk ST111 clone. Other mutations were associated with high-risk sublineages using sample geotemporal metadata. Moreover, 1.5% of isolates carried five or more mutations suggesting they undergo an alternative program for regulation of their effluxome. Overall, P. aeruginosa shows a wide range of operator mutations with a potential effect on efflux pump expression and antibiotic resistance.

Comparing antimicrobial resistant genes and phenotypes across multiple sequencing platforms and assays for Enterobacterales clinical isolates

INTRODUCTION

Whole genome sequencing (WGS) of bacterial isolates can be used to identify antimicrobial resistance (AMR) genes. Previous studies have shown that genotype-based AMR has variable accuracy for predicting carbapenem resistance in carbapenem-resistant Enterobacterales (CRE); however, the majority of these studies used short-read platforms (e.g. Illumina) to generate sequence data. In this study, our objective was to determine whether Oxford Nanopore Technologies (ONT) long-read WGS would improve detection of carbapenem AMR genes with respect to short-read only WGS for nine clinical CRE samples. We measured the minimum inhibitory breakpoint (MIC) using two phenotype assays (MicroScan and ETEST) for six antibiotics, including two carbapenems (meropenem and ertapenem) and four non-carbapenems (gentamicin, ciprofloxacin, cefepime, and trimethoprim/sulfamethoxazole). We generated short-read data using the Illumina NextSeq and long-read data using the ONT MinION. Four assembly methods were compared: ONT-only assembly; ONT-only assembly plus short-read polish; ONT + short-read hybrid assembly plus short-read polish; short-read only assembly.

RESULTS

Consistent with previous studies, our results suggest that the hybrid assembly produced the highest quality results as measured by gene completeness and contig circularization. However, ONT-only methods had minimal impact on the detection of AMR genes and plasmids compared to short-read methods, although, notably, differences in gene copy number differed between methods. All four assembly methods showed identical presence/absence of the blaKPC-2 carbapenemase gene for all samples. The two phenotype assays showed 100% concordant results for the non-carbapenems, but only 65% concordance for the two carbapenems. The presence/absence of AMR genes was 100% concordant with AMR phenotypes for all four non-carbapenem drugs, although only 22%-50% sensitivity for the carbapenems.

CONCLUSIONS

Overall, these findings suggest that the lack of complete correspondence between CRE AMR genotype and phenotype for carbapenems, while concerning, is independent of sequencing platform/assembly method.

Molecular epidemiology of antimicrobial-resistant Pseudomonas aeruginosa in a veterinary teaching hospital environment

This study aimed to investigate sites for colonization and molecular epidemiology of antimicrobial-resistant Pseudomonas aeruginosa in a veterinary teaching hospital. Bacterial specimens from surface and liquid samples (n = 165) located in five rooms were collected three times every 2 months, and antimicrobial susceptibility was subsequently determined by minimum inhibitory concentrations. The genomes of resistant strains were further analyzed using whole-genome sequencing. Among 19 P. aeruginosa isolates (11.5%, 19/165), sinks were the most frequent colonization site (53.3%), followed by rubber tubes (44.4%), and anesthesia-breathing circuit (33.3%). The highest resistance to gentamicin (47.4%), followed by piperacillin/tazobactam (36.8%), levofloxacin (36.8%), and ciprofloxacin (36.8%), was observed from 19 P. aeruginosa isolates, of which 10 were resistant strains. Of these 10 antimicrobial-resistant isolates, five were multidrug-resistant isolates, including carbapenem. From the multilocus sequence typing (MLST) analysis, five sequence types (STs), including a high-risk clone of human ST235 (n = 3), and ST244 (n = 3), ST606 (n = 2), ST485 (n = 1), and ST3405 (n = 1) were identified in resistant strains. Multiresistant genes were identified consistent with STs, except ST235. The MLST approach and single nucleotide polymorphism analysis revealed a link between resistant strains from ward rooms and those from examination, wound care, and operating rooms. The improvement of routine cleaning, especially of sink environments, and the continued monitoring of antimicrobial resistance of P. aeruginosa in veterinary hospitals are necessary to prevent the spread of resistant clones and ensure infection control.

Phenotypic and genotypic profile of ceftolozane/tazobactam-non-susceptible, carbapenem-resistant Pseudomonas aeruginosa

OBJECTIVES

To evaluate the genotypic and ceftazidime/avibactam-susceptibility profiles amongst ceftolozane/tazobactam-non-susceptible (NS), MBL-negative Pseudomonas aeruginosa in a global surveillance programme.

METHODS

Isolates were collected as part of the ERACE-PA Global Surveillance programme. Carbapenem-resistant P. aeruginosa deemed clinically relevant by the submitting laboratories were included. Broth microdilution MICs were conducted per CLSI standards to ceftolozane/tazobactam, ceftazidime/avibactam, ceftazidime and cefepime. Genotypic carbapenemases were detected using CarbaR and CarbaR NxG (research use only). Isolates negative for carbapenemases by PCR were assessed via WGS. Isolates were included in the analysis if they were ceftolozane/tazobactam-NS and lacked detection of known MBLs.

RESULTS

Of the 807 isolates collected in the ERACE-PA programme, 126 (16%) were ceftolozane/tazobactam-NS and lacked MBLs. Cross-resistance to ceftazidime and cefepime was common, with only 5% and 16% testing susceptible, respectively. Ceftazidime/avibactam retained in vitro activity, with 65% of isolates testing susceptible. GES was the most common enzymology, detected in 57 (45%) isolates, and 89% remained susceptible to ceftazidime/avibactam. Seven isolates harboured KPC and all tested susceptible to ceftazidime/avibactam. In the remaining 62 isolates, WGS revealed various ESBLs or OXA β-lactamases. While 39% remained susceptible to ceftazidime/avibactam, marked variability was observed among the diverse resistance mechanisms.

CONCLUSIONS

Ceftazidime/avibactam remained active in vitro against the majority of ceftolozane/tazobactam-NS, MBL-negative P. aeruginosa. Ceftazidime/avibactam was highly active against isolates harbouring GES and KPC β-lactamases. These data highlight the potential clinical utility of genotypic profiling as well as the need to test multiple novel agents when carbapenem-resistant P. aeruginosa are encountered.

Generation of a recombinant antibody for sensitive detection of Pseudomonas aeruginosa

Pseudomonas aeruginosa (P. aeruginosa) is a major pathogen that causes nosocomial infections and often exhibits antibiotic resistance. Therefore, the development of an accurate method for detecting P. aeruginosa is required to control P. aeruginosa-related outbreaks. In this study, we established an enzyme-linked immunosorbent assay method for the sensitive detection of three P. aeruginosa strains, UCBPP PA14, ATCC 27853, and multidrug-resistant ATCC BAA-2108. We produced a recombinant antibody (rAb) against P. aeruginosa V‐antigen (PcrV), which is a needle tip protein of the type III secretion system of P. aeruginosa using mammalian cells with high yield and purity, and confirmed its P. aeruginosa binding efficiency. The rAb was paired with commercial anti-P. aeruginosa Ab for a sandwich ELISA, resulting in an antigen-concentration-dependent response with a limit of detection value of 230 CFU/mL. These results suggest that the rAb produced herein can be used for the sensitive detection of P. aeruginosa with a wide range of applications in clinical diagnosis and point-of-care testing.

Identification of Promoter Region Markers Associated With Altered Expression of Resistance-Nodulation-Division Antibiotic Efflux Pumps in Acinetobacter baumannii

Genetic alterations leading to the constitutive upregulation of specific efflux pumps contribute to antibacterial resistance in multidrug resistant bacteria. The identification of such resistance markers remains one of the most challenging tasks of genome-level resistance predictors. In this study, 487 non-redundant genetic events were identified in upstream zones of three operons coding for resistance-nodulation-division (RND) efflux pumps of 4,130 Acinetobacter baumannii isolates. These events included insertion sequences, small indels, and single nucleotide polymorphisms. In some cases, alterations explicitly modified the expression motifs described for these operons, such as the promoter boxes, operators, and Shine-Dalgarno sequences. In addition, changes in DNA curvature and mRNA secondary structures, which are structural elements that regulate expression, were also calculated. According to their influence on RND upregulation, the catalog of upstream modifications were associated with “experimentally verified,” “presumed,” and “probably irrelevant” degrees of certainty. For experimental verification, DNA of upstream sequences independently carrying selected markers, three for each RND operon, were fused to a luciferase reporter plasmid system. Five out of the nine selected markers tested showed significant increases in expression with respect to the wild-type sequence control. In particular, a 25-fold expression increase was observed with the ISAba1 insertion sequence upstream the adeABC pump. Next, overexpression of each of the three multi-specific RND pumps was linked to their respective antibacterial substrates by a deep A. baumannii literature screen. Consequently, a data flow framework was then developed to link genomic upregulatory RND determinants to potential antibiotic resistance. Assignment of potential increases in minimal inhibitory concentrations at the “experimentally verified” level was permitted for 42 isolates to 7–8 unrelated antibacterial agents including tigecycline, which is overlooked by conventional resistome predictors. Thus, our protocol may represent a time-saving filter step prior to laborious confirmation experiments for efflux-driven resistance. Altogether, a computational-experimental pipeline containing all components required for identifying the upstream regulatory resistome is proposed. This schema may provide the foundational stone for the elaboration of tools approaching antibiotic efflux that complement routine resistome predictors for preventing antimicrobial therapy failure against difficult-to-threat bacteria.

Enhancing predictions of antimicrobial resistance of pathogens by expanding the potential resistance gene repertoire using a pan-genome-based feature selection approach

Background

Predicting which pathogens might exhibit antimicrobial resistance (AMR) based on genomics data is one of the promising ways to swiftly and precisely identify AMR pathogens. Currently, the most widely used genomics approach is through identifying known AMR genes from genomic information in order to predict whether a pathogen might be resistant to certain antibiotic drugs. The list of known AMR genes, however, is still far from comprehensive and may result in inaccurate AMR pathogen predictions. We thus felt the need to expand the AMR gene set and proposed a pan-genome-based feature selection method to identify potential gene sets for AMR prediction purposes.

Results

By building pan-genome datasets and extracting gene presence/absence patterns from four bacterial species, each with more than 2000 strains, we showed that machine learning models built from pan-genome data can be very promising for predicting AMR pathogens. The gene set selected by the eXtreme Gradient Boosting (XGBoost) feature selection approach further improved prediction outcomes, and an incremental approach selecting subsets of XGBoost-selected features brought the machine learning model performance to the next level. Investigating selected gene sets revealed that on average about 50% of genes had no known function and very few of them were known AMR genes, indicating the potential of the selected gene sets to expand resistance gene repertoires.

Conclusions

We demonstrated that a pan-genome-based feature selection approach is suitable for building machine learning models for predicting AMR pathogens. The extracted gene sets may provide future clues to expand our knowledge of known AMR genes and provide novel hypotheses for inferring bacterial AMR mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04666-2.

The core and accessory Hfq interactomes across Pseudomonas aeruginosa lineages

The major RNA-binding protein Hfq interacts with mRNAs, either alone or together with regulatory small noncoding RNAs (sRNAs), affecting mRNA translation and degradation in bacteria. However, studies tend to focus on single reference strains and assume that the findings may apply to the entire species, despite the important intra-species genetic diversity known to exist. Here, we use RIP-seq to identify Hfq-interacting RNAs in three strains representing the major phylogenetic lineages of Pseudomonas aeruginosa. We find that most interactions are in fact not conserved among the different strains. We identify growth phase-specific and strain-specific Hfq targets, including previously undescribed sRNAs. Strain-specific interactions are due to different accessory gene sets, RNA abundances, or potential context- or sequence- dependent regulatory mechanisms. The accessory Hfq interactome includes most mRNAs encoding Type III Secretion System (T3SS) components and secreted toxins in two strains, as well as a cluster of CRISPR guide RNAs in one strain. Conserved Hfq targets include the global virulence regulator Vfr and metabolic pathways involved in the transition from fast to slow growth. Furthermore, we use rGRIL-seq to show that RhlS, a quorum sensing sRNA, activates Vfr translation, thus revealing a link between quorum sensing and virulence regulation. Overall, our work highlights the important intra-species diversity in post-transcriptional regulatory networks in Pseudomonas aeruginosa.

Strengths and caveats of identifying resistance genes from whole genome sequencing data

INTRODUCTION

Antimicrobial resistance (AMR) continues to present major challenges to modern healthcare. Recent advances in whole-genome sequencing (WGS) have made the rapid molecular characterization of AMR a realistic possibility for diagnostic laboratories; yet major barriers to clinical implementation exist.

AREAS COVERED

We describe and compare short- and long-read sequencing platforms, typical components of bioinformatics pipelines, tools for AMR gene detection and the relative merits of read- or assembly-based approaches. The challenges of characterizing mobile genetic elements from genomic data are outlined, as well as the complexities inherent to the prediction of phenotypic resistance from WGS. Practical obstacles to implementation in diagnostic laboratories, the critical role of quality control and external quality assurance, as well as standardized reporting standards are also discussed. Future directions, such as the application of machine-learning and artificial intelligence algorithms, linked to clinically meaningful outcomes, may offer a new paradigm for the clinical application of AMR prediction.

EXPERT OPINION

AMR prediction from WGS data presents an exciting opportunity to advance our capacity to comprehensively characterize infectious pathogens in a rapid manner, ultimately aiming to improve patient outcomes. Collaborative efforts between clinicians, scientists, regulatory bodies and healthcare administrators will be critical to achieve the full promise of this approach.

Label-free quantitative proteomics identifies unique proteomes of clinical isolates of the Liverpool Epidemic Strain of Pseudomonas aeruginosa and laboratory strain PAO1

PURPOSE

Comparative genomics and phenotypic assays have shown that antibiotic resistance profiles differ among clinical isolates of Pseudomonas aeruginosa and that genotype-phenotype associations are difficult to establish for resistance phenotypes based on these comparisons alone.

EXPERIMENTAL DESIGN

Here, we used label-free quantitative proteomics to compare two isolates of the Liverpool Epidemic Strain (LES) of P. aeruginosa, LESlike1 and LESB58, and the common laboratory strain P. aeruginosa PAO1 to more accurately predict functional differences between strains.

RESULTS

Our results show that the proteomes of the LES isolates are more similar to each other than to PAO1; however, a number of differences were observed in the abundance of proteins involved in quorum sensing, virulence, and antibiotic resistance, including in the comparison of LESlike1 and LESB58. Additionally, the proteomic data revealed a higher abundance of proteins involved in polymyxin and aminoglycoside resistance in LESlike1. Minimum inhibitory concentration assays showed that LESlike1 had up to 128-fold higher resistance to antibiotics from these classes.

CONCLUSIONS

These findings provide an example of the ability of proteomic data to complement genotypic and phenotypic studies to understand resistance in clinical isolates.

CLINICAL RELEVANCE

P. aeruginosa is a predominant pathogen in chronic lung infections in individuals with cystic fibrosis (CF). LES isolates are capable of transferring between CF patients and have been associated with increased hospital visits and antibiotic treatments.

Role of RND Efflux Pumps in Drug Resistance of Cystic Fibrosis Pathogens

Drug resistance represents a great concern among people with cystic fibrosis (CF), due to the recurrent and prolonged antibiotic therapy they should often undergo. Among Multi Drug Resistance (MDR) determinants, Resistance-Nodulation-cell Division (RND) efflux pumps have been reported as the main contributors, due to their ability to extrude a wide variety of molecules out of the bacterial cell. In this review, we summarize the principal RND efflux pump families described in CF pathogens, focusing on the main Gram-negative bacterial species (Pseudomonas aeruginosa, Burkholderia cenocepacia, Achromobacter xylosoxidans, Stenotrophomonas maltophilia) for which a predominant role of RND pumps has been associated to MDR phenotypes.

Gene-Gene Interactions Dictate Ciprofloxacin Resistance in Pseudomonas aeruginosa and Facilitate Prediction of Resistance Phenotype from Genome Sequence Data

Ciprofloxacin is one of the most widely used antibiotics for treating Pseudomonas aeruginosa infections. However, P. aeruginosa acquires mutations that confer ciprofloxacin resistance, making treatment more difficult. Resistance is multifactorial, with mutations in multiple genes influencing the resistance phenotype. However, the contributions of individual mutations and mutation combinations to the amounts of ciprofloxacin that P. aeruginosa can tolerate are not well understood. Engineering P. aeruginosa strain PAO1 to contain mutations in any one of the resistance-associated genes gyrA, nfxB, rnfC, parC, and parE showed that only gyrA mutations increased the MIC for ciprofloxacin. Mutations in parC and parE increased the MIC of a gyrA mutant, making the bacteria ciprofloxacin resistant. Mutations in nfxB and rnfC increased the MIC, conferring resistance, only if both were mutated in a gyrA background. Mutations in all of gyrA, nfxB, rnfC, and parC/E further increased the MIC. These findings reveal an epistatic network of gene-gene interactions in ciprofloxacin resistance. We used this information to predict ciprofloxacin resistance/susceptibility for 274 isolates of P. aeruginosa from their genome sequences. Antibiotic susceptibility profiles were predicted correctly for 84% of the isolates. The majority of isolates for which prediction was unsuccessful were ciprofloxacin resistant, demonstrating the involvement of additional as yet unidentified genes and mutations in resistance. Our data show that gene-gene interactions can play an important role in antibiotic resistance and can be successfully incorporated into models predicting resistance phenotype.

Predicting Pseudomonas aeruginosa susceptibility phenotypes from whole genome sequence resistome analysis

OBJECTIVES

The aim was to develop and validate a Pseudomonas aeruginosa genotypic resistance score, based on analysis of the whole genome sequence resistome, to predict antimicrobial susceptibility phenotypes.

METHODS

A scoring system based on the analysis of mutation-driven resistance in 40 chromosomal genes and horizontally acquired resistance (Resfinder) was developed for ceftazidime, ceftolozane/tazobactam, meropenem, ciprofloxacin and tobramycin. Resistance genes/mutations were scored from 0 (no effect) to 1 (EUCAST clinical resistance). One hundred wild-type strains obtained from 51 different hospitals during a 2017 multicentre study were fully sequenced and analysed in order to define a catalogue of natural polymorphisms in the 40 chromosomal resistance genes. The capacity of genotypic score to predict the susceptibility phenotype was tested in 204 isolates randomly selected from the 51 hospitals (four from each hospital).

RESULTS

The analysis of the 100 wild-type isolates yielded a catalogue of 455 natural polymorphisms in the 40 genes involved in mutational resistance. However, resistance mutations and high-risk clones (such as ST235) were also documented among a few wild-type isolates. Overall, the capacity of the genotypic score (<0.5) for predicting phenotypic susceptibility (S + I in the case of meropenem) was very high (95-100%). In contrast, the capacity of the genotypic score to predict resistance (≥1) was far more variable depending on the agent. Prediction of meropenem clinical resistance was particularly low (18/39, 46.1%), whereas it classified clinical ceftolozane/tazobactam resistance in 100% (7/7) of cases.

DISCUSSION

Although a margin for improvement was evidenced in this proof of concept study, an overall good correlation between the genotypic resistance score and the susceptibility profile was documented. Further refining of the scoring system, automatization and testing of large international cohorts should follow.

The Pseudomonas aeruginosa substrate-binding protein Ttg2D functions as a general glycerophospholipid transporter across the periplasm

In Pseudomonas aeruginosa, Ttg2D is the soluble periplasmic phospholipid-binding component of an ABC transport system thought to be involved in maintaining the asymmetry of the outer membrane. Here we use the crystallographic structure of Ttg2D at 2.5 Å resolution to reveal that this protein can accommodate four acyl chains. Analysis of the available structures of Ttg2D orthologs shows that they conform a new substrate-binding-protein structural cluster. Native and denaturing mass spectrometry experiments confirm that Ttg2D, produced both heterologously and homologously and isolated from the periplasm, can carry two diacyl glycerophospholipids as well as one cardiolipin. Binding is notably promiscuous, allowing the transport of various molecular species. In vitro binding assays coupled to native mass spectrometry show that binding of cardiolipin is spontaneous. Gene knockout experiments in P. aeruginosa multidrug-resistant strains reveal that the Ttg2 system is involved in low-level intrinsic resistance against certain antibiotics that use a lipid-mediated pathway to permeate through membranes.

Yero et al. elucidate the function of Ttg2D, a Pseudomonas aeruginosa periplasmic protein, in maintaining phospholipid asymmetry between the outer and inner membrane. Gram negative bacteria have inner and outer membranes that differ in phospholipd composition. Using X-ray crystallography and mass spectrometry, the authors show that Ttg2D can carry two diacyl glycerophospholipids or a cardiolipin. The authors also identify a role for Ttg2D in resistance against antibiotics that use a lipid-mediated pathway into the cell.

Multidrug Resistance (MDR) and Collateral Sensitivity in Bacteria, with Special Attention to Genetic and Evolutionary Aspects and to the Perspectives of Antimicrobial Peptides-A Review

Antibiotic poly-resistance (multidrug-, extreme-, and pan-drug resistance) is controlled by adaptive evolution. Darwinian and Lamarckian interpretations of resistance evolution are discussed. Arguments for, and against, pessimistic forecasts on a fatal “post-antibiotic era” are evaluated. In commensal niches, the appearance of a new antibiotic resistance often reduces fitness, but compensatory mutations may counteract this tendency. The appearance of new antibiotic resistance is frequently accompanied by a collateral sensitivity to other resistances. Organisms with an expanding open pan-genome, such as Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae, can withstand an increased number of resistances by exploiting their evolutionary plasticity and disseminating clonally or poly-clonally. Multidrug-resistant pathogen clones can become predominant under antibiotic stress conditions but, under the influence of negative frequency-dependent selection, are prevented from rising to dominance in a population in a commensal niche. Antimicrobial peptides have a great potential to combat multidrug resistance, since antibiotic-resistant bacteria have shown a high frequency of collateral sensitivity to antimicrobial peptides. In addition, the mobility patterns of antibiotic resistance, and antimicrobial peptide resistance, genes are completely different. The integron trade in commensal niches is fortunately limited by the species-specificity of resistance genes. Hence, we theorize that the suggested post-antibiotic era has not yet come, and indeed might never come.

Combining Whole-Genome Sequencing and Multimodel Phenotyping To Identify Genetic Predictors of Salmonella Virulence

Salmonella comprises more than 2,600 serovars. Very few environmental and uncommon serovars have been characterized for their potential role in virulence and human infections. A complementary in vitro and in vivo systematic high-throughput analysis of virulence was used to elucidate the association between genetic and phenotypic variations across Salmonella isolates. The goal was to develop a strategy for the classification of isolates as a benchmark and predict virulence levels of isolates. Thirty-five phylogenetically distant strains of unknown virulence were selected from the Salmonella Foodborne Syst-OMICS (SalFoS) collection, representing 34 different serovars isolated from various sources. Isolates were evaluated for virulence in 4 complementary models of infection to compare virulence traits with the genomics data, including interactions with human intestinal epithelial cells, human macrophages, and amoeba. In vivo testing was conducted using the mouse model of Salmonella systemic infection. Significant correlations were identified between the different models. We identified a collection of novel hypothetical and conserved proteins associated with isolates that generate a high burden. We also showed that blind prediction of virulence of 33 additional strains based on the pan-genome was high in the mouse model of systemic infection (82% agreement) and in the human epithelial cell model (74% agreement). These complementary approaches enabled us to define virulence potential in different isolates and present a novel strategy for risk assessment of specific strains and for better monitoring and source tracking during outbreaks.IMPORTANCE Salmonella species are bacteria that are a major source of foodborne disease through contamination of a diversity of foods, including meat, eggs, fruits, nuts, and vegetables. More than 2,600 different Salmonella enterica serovars have been identified, and only a few of them are associated with illness in humans. Despite the fact that they are genetically closely related, there is enormous variation in the virulence of different isolates of Salmonella enterica Identification of foodborne pathogens is a lengthy process based on microbiological, biochemical, and immunological methods. Here, we worked toward new ways of integrating whole-genome sequencing (WGS) approaches into food safety practices. We used WGS to build associations between virulence and genetic diversity within 83 Salmonella isolates representing 77 different Salmonella serovars. Our work demonstrates the potential of combining a genomics approach and virulence tests to improve the diagnostics and assess risk of human illness associated with specific Salmonella isolates.

Current Affairs of Microbial Genome-Wide Association Studies: Approaches, Bottlenecks and Analytical Pitfalls

Microbial genome-wide association studies (mGWAS) are a new and exciting research field that is adapting human GWAS methods to understand how variations in microbial genomes affect host or pathogen phenotypes, such as drug resistance, virulence, host specificity and prognosis. Several computational tools and methods have been developed or adapted from human GWAS to facilitate the discovery of novel mutations and structural variations that are associated with the phenotypes of interest. However, no comprehensive, end-to-end, user-friendly tool is currently available. The development of a broadly applicable pipeline presents a real opportunity among computational biologists. Here, (i) we review the prominent and promising tools, (ii) discuss analytical pitfalls and bottlenecks in mGWAS, (iii) provide insights into the selection of appropriate tools, (iv) highlight the gaps that still need to be filled and how users and developers can work together to overcome these bottlenecks. Use of mGWAS research can inform drug repositioning decisions as well as accelerate the discovery and development of more effective vaccines and antimicrobials for pressing infectious diseases of global health significance, such as HIV, TB, influenza, and malaria.

Antibiotic resistance in Vibrio cholerae El Tor strains isolated during cholera complications in Siberia and the Far East of Russia

Currently, the spread of antimicrobial resistance (AMR) is a global trend and poses a severe threat to public health. The causative agent of cholera, a severe infectious disease with pandemic expansion, becomes more and more resistant to a wider range of drugs with every coming year. The Vibrio cholerae genome is highly flexible and adaptive; the acquisition of the SXT mobile element with a cluster of antibiotic resistance genes on it has marked a new stage in the adaptive evolution of the pathogen. The territory of Siberia and the Russian Far East is free of cholera; however, in the 1970s and 1990s a number of infection importation cases and acute outbreaks associated with the cholera importation were reported. The aim of this study was to describe the phenotypic characteristics and genetic determinants of AMR in V. cholerae strains isolated during epidemic complications in Siberia and the Far East of Russia, as well as to clarify the origin of the strains. The present research comprises analysis of nine V. cholerae El Tor strains isolated from patients and water sources during epidemic complications in Siberia and the Russian Far East in the 1990s. Here, we compared the phenotypic manifestations of antibiotic resistance among strains, harbored the resistance patterns in genomes; we also determined the structure, the type of SXT elements, and the mobilome profile based on the accepted classification. We identified that strains that caused outbreaks in Vladivostok and Yuzhno-Sakhalinsk in 1999 had ICEVchCHN4210 type SXT element with deletion of some loci. The research shows that the integration of the genome, SNP and the mobilome, associated with antibiotic resistance, analyses is necessary to understand the cholera epidemiology, it also helps to establish the origin of strains. The study of resistance determinants features allowed to make a conclusion about the heterogeneity of V. cholerae strains that were isolated during outbreaks in Vladivostok and Yuzhno-Sakhalinsk in 1999.

Genomic characterisation of an international Pseudomonas aeruginosa reference panel indicates that the two major groups draw upon distinct mobile gene pools

Pseudomonas aeruginosa is an important opportunistic pathogen, especially in the context of infections of cystic fibrosis (CF). In order to facilitate coordinated study of this pathogen, an international reference panel of P. aeruginosa isolates was assembled. Here we report the genome sequencing and analysis of 33 of these isolates and 7 reference genomes to further characterise this panel. Core genome single nucleotide variant phylogeny demonstrated that the panel strains are widely distributed amongst the P. aeruginosa population. Common loss-of-function mutations reported as adaptive during CF (such as in mucA and mexA) were identified amongst isolates from chronic respiratory infections. From the 40 strains analysed, 37 unique resistomes were predicted, based on the Resistance Gene Identifier method using the Comprehensive Antibiotic Resistance Database. Notably, hierarchical clustering and phylogenetic reconstructions based on the presence/absence of genomic islands (GIs), prophages and other regions of genome plasticity (RGPs) supported the subdivision of P. aeruginosa into two main groups. This is the largest, most diverse analysis of GIs and associated RGPs to date, and the results suggest that, at least at the largest clade grouping level (group 1 vs group 2), each group may be drawing upon distinct mobile gene pools.

Diversification of Pseudomonas aeruginosa within the cystic fibrosis lung and its effects on antibiotic resistance

The evolution and diversification of bacterial pathogens within human hosts represent potential barriers to the diagnosis and treatment of life-threatening infections. Tremendous genetic and phenotypic diversity is characteristic of host adaptation in strains of Pseudomonas aeruginosa that infect the airways of individuals with chronic lung diseases and prove to be extremely difficult to eradicate. In this MiniReview, we examine recent advances in understanding within-host diversity and antimicrobial resistance in P. aeruginosa populations from the lower airways of individuals with the fatal genetic disease cystic fibrosis and the potential impacts that this diversity may have on detecting and interpreting antimicrobial susceptibility within these populations.

Effects of Dairy Manure-Based Amendments and Soil Texture on Lettuce- and Radish-Associated Microbiota and Resistomes

Dairy cattle are routinely treated with antibiotics, and the resulting manure or composted manure is commonly used as a soil amendment for crop production, raising questions regarding the potential for antibiotic resistance to propagate from "farm to fork." The objective of this study was to compare the microbiota and "resistomes" (i.e., carriage of antibiotic resistance genes [ARGs]) associated with lettuce leaf and radish taproot surfaces grown in different soils amended with dairy manure, compost, or chemical fertilizer only (control). Manure was collected from antibiotic-free dairy cattle (DC) or antibiotic-treated dairy cattle (DA), with a portion composted for parallel comparison. Amendments were applied to loamy sand or silty clay loam, and lettuce and radishes were cultivated to maturity in a greenhouse. Metagenomes were profiled via shotgun Illumina sequencing. Radishes carried a distinct ARG composition compared to that of lettuce, with greater relative abundance of total ARGs. Taxonomic species richness was also greater for radishes by 1.5-fold. The resistomes of lettuce grown with DC compost were distinct from those grown with DA compost, DC manure, or fertilizer only. Further, compost applied to loamy sand resulted in twofold-greater relative abundance of total ARGs on lettuce than when applied to silty clay loam. The resistomes of radishes grown with biological amendments were distinct from the corresponding fertilizer controls, but effects of composting or antibiotic use were not measureable. Cultivation in loamy sand resulted in higher species richness for both lettuce and radishes than when grown in silty clay loam by 2.2-fold and 1.2-fold, respectively, when amended with compost.IMPORTANCE A controlled, integrated, and replicated greenhouse study, along with comprehensive metagenomic analysis, revealed that multiple preharvest factors, including antibiotic use during manure collection, composting, biological soil amendment, and soil type, influence vegetable-borne resistomes. Here, radishes, a root vegetable, carried a greater load of ARGs and species richness than lettuce, a leafy vegetable. However, the lettuce resistome was more noticeably influenced by upstream antibiotic use and composting. Network analysis indicated that cooccurring ARGs and mobile genetic elements were almost exclusively associated with conditions receiving raw manure amendments, suggesting that composting could alleviate the mobility of manure-derived resistance traits. Effects of preharvest factors on associated microbiota and resistomes of vegetables eaten raw are worthy of further examination in terms of potential influence on human microbiomes and spread of antibiotic resistance. This research takes a step toward identifying on-farm management practices that can help mitigate the spread of agricultural sources of antibiotic resistance.

Major Release of 161 Whole-Genome Sequences from the International Pseudomonas Consortium Database

Pseudomonas aeruginosa is an environmental bacterium and opportunistic pathogen. Here, we present draft genome sequences for 161 isolates from diverse clinical and environmental sources. This set of genome sequences complements other major public data releases from the International Pseudomonas Consortium Database.

Comparative genomics of clinical strains of Pseudomonas aeruginosa strains isolated from different geographic sites

The large and complex genome of Pseudomonas aeruginosa, which consists of significant portions (up to 20%) of transferable genetic elements contributes to the rapid development of antibiotic resistance. The whole genome sequences of 22 strains isolated from eye and cystic fibrosis patients in Australia and India between 1992 and 2007 were used to compare genomic divergence and phylogenetic relationships as well as genes for antibiotic resistance and virulence factors. Analysis of the pangenome indicated a large variation in the size of accessory genome amongst 22 stains and the size of the accessory genome correlated with number of genomic islands, insertion sequences and prophages. The strains were diverse in terms of sequence type and dissimilar to that of global epidemic P. aeruginosa clones. Of the eye isolates, 62% clustered together within a single lineage. Indian eye isolates possessed genes associated with resistance to aminoglycoside, beta-lactams, sulphonamide, quaternary ammonium compounds, tetracycline, trimethoprims and chloramphenicols. These genes were, however, absent in Australian isolates regardless of source. Overall, our results provide valuable information for understanding the genomic diversity of P. aeruginosa isolated from two different infection types and countries.