Genomic context of the two integrons of ST-111 Pseudomonas aeruginosa AG1: A VIM-2-carrying old-acquaintance and a novel IMP-18-carrying integron

Carbapenem-Resistant Pseudomonas aeruginosa's Resistome: Pan-Genomic Plasticity, the Impact of Transposable Elements and Jumping Genes

Pseudomonas aeruginosa, a Gram-negative, motile bacterium, may cause significant infections in both community and hospital settings, leading to substantial morbidity and mortality. This opportunistic pathogen can thrive in various environments, making it a public health concern worldwide. P. aeruginosa's genomic pool is highly dynamic and diverse, with a pan-genome size ranging from 5.5 to 7.76 Mbp. This versatility arises from its ability to acquire genes through horizontal gene transfer (HGT) via different genetic elements (GEs), such as mobile genetic elements (MGEs). These MGEs, collectively known as the mobilome, facilitate the spread of genes encoding resistance to antimicrobials (ARGs), resistance to heavy metals (HMRGs), virulence (VGs), and metabolic functions (MGs). Of particular concern are the acquired carbapenemase genes (ACGs) and other β-lactamase genes, such as classes A, B [metallo-β-lactamases (MBLs)], and D carbapenemases, which can lead to increased antimicrobial resistance. This review emphasizes the importance of the mobilome in understanding antimicrobial resistance in P. aeruginosa.

Genomic Epidemiology of Pseudomonas aeruginosa Sequence Type 111

PURPOSE

Pseudomonas aeruginosa ST111 is a global multidrug resistant (MDR) high-risk clone and comprehensive data about its molecular epidemiology is limited in Canada. Comprehensive data about the evolution of ST111 clades is limited. We characterized a Canadian collection of ST111 causing bloodstream infections and investigated the genomic relationship between Canadian and global ST111.

MATERIAL AND METHODS

We used long and short read WGS to characterize Canadian ST111 (n = 10 from 2010-18). We performed phylogenetic analysis on a global collection of ST111 (n = 969) and investigated the evolutionary history of clades using BEAST.

RESULTS

ST111 belonged to 3 clades (A, B, C) and two subclades (C1, C2). ST111-A was the ancestral clade while clades B, C1 and C2 emerged during the 1700s and 1800s. ST111-C2 dominated the global ST111 population. Serotype switching from O4 to O12 and the acquisition of Tn21, gyrA_T83I, parC_S87L, In59 with blaVIM-2 and aacA29 over time, were important in the evolution of ST111-C2. The Calgary ST111 strains consisted of a diverse collection that belonged to ST111-A (O4), ST111-C1 (O4) and ST111-C2 (O12) with different transposon structures.

CONCLUSIONS

We provided details on the emergence and evolution of different ST111 clades over time and highlighted the roles of serotype switching and the acquisition of certain AMR determinants and transposon structures in the evolution of ST111-C2.

High-risk Pseudomonas aeruginosa clones harboring β-lactamases: 2024 update

Carbapenem-resistant Pseudomonas aeruginosa is defined by the World Health Organization as a "high priority" in developing new antimicrobials. Indeed, the emergence and spread of multidrug-resistant (MDR) or extensively drug-resistant (XDR) bacteria increase the morbidity and mortality risk of infected patients. Genomic variants of P. aeruginosa that display phenotypes of MDR/XDR have been defined as high-risk global clones. In this mini-review, we describe some international high-risk clones that carry β-lactamase genes that can produce chronic colonization and increase infected patients' morbidity and mortality rates.

VIM-type metallo-β-lactamase (MBL)-encoding genomic islands in Pseudomonas spp. in Poland: predominance of clc-like integrative and conjugative elements (ICEs)

OBJECTIVES

To characterize VIM-type metallo-β-lactamase (MBL)-encoding genomic islands (GIs) in Pseudomonas aeruginosa and P. putida group isolates from Polish hospitals from 2001-2015/16.

METHODS

Twelve P. aeruginosa and 20 P. putida group isolates producing VIM-like MBLs were selected from a large collection of these based on epidemiological and typing data. The organisms represented all major epidemic genotypes of these species spread in Poland with chromosomally located blaVIM gene-carrying integrons. The previously determined short-read sequences were complemented by long-read sequencing in this study. The comparative structural analysis of the GIs used a variety of bioinformatic tools.

RESULTS

Thirty different GIs with blaVIM integrons were identified in the 32 isolates, of which 24 GIs from 26 isolates were integrative and conjugative elements (ICEs) of the clc family. These in turn were dominated by 21 variants of the GI2/ICE6441 subfamily with a total of 19 VIM integrons, each inserted in the same position within the ICE's Tn21-like transposon Tn4380. The three other ICEs formed a novel ICE6705 subfamily, lacking Tn4380 and having different VIM integrons located in another site of the elements. The remaining six non-ICE GIs represented miscellaneous structures. The presence of various integrons in the same ICE sublineage, and of the same integron in different GIs, indicated circulation and recombination of the integron-carrying genetic platforms across Pseudomonas species/genotypes.

CONCLUSIONS

Despite the general diversity of the blaVIM-carrying GIs in Pseudomonas spp. in Poland, a clear predominance of broadly spread and rapidly evolving clc-type ICEs was documented, confirming their significant role in antimicrobial resistance epidemiology.

phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things)

Phylogenetic comparative methods comprise the general endeavor of using an estimated phylogenetic tree (or set of trees) to make secondary inferences: about trait evolution, diversification dynamics, biogeography, community ecology, and a wide range of other phenomena or processes. Over the past ten years or so, the phytools R package has grown to become an important research tool for phylogenetic comparative analysis. phytools is a diverse contributed R library now consisting of hundreds of different functions covering a variety of methods and purposes in phylogenetic biology. As of the time of writing, phytools included functionality for fitting models of trait evolution, for reconstructing ancestral states, for studying diversification on trees, and for visualizing phylogenies, comparative data, and fitted models, as well numerous other tasks related to phylogenetic biology. Here, I describe some significant features of and recent updates to phytools, while also illustrating several popular workflows of the phytools computational software.

Differentially Expressed Genes of Pseudomonas aeruginosa Isolates from Eyes with Keratitis and Healthy Conjunctival Sacs

Background

Pseudomonas aeruginosa (P. aeruginosa) is the second-most common commensal bacterium in healthy conjunctival sacs. When the corneal epithelial barrier is damaged, P. aeruginosa in a healthy conjunctival sac can cause infectious keratitis, which can result in the loss of vision. This study was designed to investigate the differentially expressed genes (DEGs) of P. aeruginosa isolates from eyes with keratitis and from healthy conjunctival sacs to predict their functions and pathways through Illumina high-throughput RNA sequencing (RNA-seq).

Methods

P. aeruginosa isolates from keratitis and healthy conjunctival sacs were obtained. The transcriptome profile of P. aeruginosa was characterized by a high throughput RNA-seq strategy using the Illumina HiSeq 2500 platform. The DEGs were analyzed with DESeq and validated through quantitative real-time polymerase chain reaction (PCR) and with experimental mice. GO enrichment and the KEGG pathway were also analyzed.

Results

In genome-wide transcriptional analysis, 557 genes (332 upregulated and 225 downregulated) were found to be differentially expressed (fold change ≥ 2, p ≤ 0.05) in the strains from keratitis. GO enrichment analysis suggested that DEGs tended to be associated with cellular and metabolic processes. KEGG pathway analysis revealed the DEGs were typically associated with the pathways of the bacterial secretion system and pyoverdine metabolism. Eleven DEGs were validated using quantitative reverse-transcription PCR and verified with experimental mice. The results were consistent with those obtained in RNA-seq.

Conclusion

The DEGs related to pilin, T2SS, T3SS, and pyoverdine metabolisms were significantly altered in the strains from keratitis. The findings may be helpful for further investigations on genes or pathways related to the pathogenesis of and therapeutic targets for P. aeruginosa keratitis.

Pseudomonas putida group species as reservoirs of mobilizable Tn402-like class 1 integrons carrying blaVIM-2 metallo-β-lactamase genes

The Pseudomonas putida group (P. putida G) is composed of at least 21 species associated with a wide range of environments, including the clinical setting. Here, we characterized 13 carbapenem-resistant P. putida G clinical isolates bearing class 1 integrons/transposons (class 1 In/Tn) carrying bla_VIM-2 metallo-β-lactamase gene cassettes obtained from hospitals of Argentina. Multilocus sequencing (MLSA) and phylogenetic analyses based on 16S rDNA, gyrB and rpoD sequences distinguished 7 species among them. bla_VIM-2 was found in three different cassette arrays: In41 (bla_VIM-2-aacA4), In899 (only bla_VIM-2), and In528 (dfrB1-aacA4-bla_VIM-2). In41 and In899 were associated with complete tniABQC transposition modules and IRi/IRt boundaries characteristic of the Tn5053/Tn402 transposons, which were designated Tn6335 and Tn6336, respectively. The class 1 In/Tn element carrying In528, however, exhibited a defective tni module bearing only the tniC (transposase) gene, associated with a complete IS6100 bounded with two oppositely-oriented IRt end regions. In some P. putida G isolates including P. asiatica, P. juntendi, P. putida G/II, and P. putida G/V, Tn6335/Tn6336 were carried by pLD209-type conjugative plasmids capable of self-mobilization to P. aeruginosa or Escherichia coli. In other isolates of P. asiatica, P. putida G/II, and P. monteiliieilii, however, these bla_VIM-2-containing class 1 In/Tn elements were found inserted into the res regions preceding the tnpR (resolvase) gene of particular Tn21 subgroup members of Tn3 transposons. The overall results reinforce the notion of P. putida G members as bla_VIM-2 reservoirs, and shed light on the mechanisms of dissemination of carbapenem resistance genes to other pathogenic bacteria in the clinical setting.

Molecular Determinants of Antibiotic Resistance in the Costa Rican Pseudomonas aeruginosa AG1 by a Multi-omics Approach: A Review of 10 Years of Study

Pseudomonas aeruginosa AG1 (PaeAG1) is a Costa Rican strain that was isolated in 2010 in a major Hospital. This strain has resistance to multiple antibiotics such as β-lactams (including carbapenems), aminoglycosides, and fluoroquinolones. PaeAG1 is considered critical (Priority 1) due to its resistance to carbapenems, and it was the first report of a P. aeruginosa isolate carrying both VIM-2 and IMP-18 genes encoding for metallo-β-lactamases (MBL) enzymes (both with carbapenemase activity). Owing to these traits, we have studied this model for 10 years using diverse approaches including multi-omics. In this review, we summarize the main points of the different steps that we have studied in PaeAG1: preliminary analyses of this strain at the genomic and phenomic levels revealed that this microorganism has particular features of antibiotic resistance. In the multi-omics approach, the genome assembly was the initial step to identify the genomic determinants of this strain, including virulence factors, antibiotic resistance genes, as well as a complex accessory genome. Second, a comparative genomic approach was implemented to define and update the phylogenetic relationship among complete P. aeruginosa genomes, the genomic island content in other strains, and the architecture of the two MBL-carrying integrons. Third, the proteomic profile of PaeAG1 was studied after exposure to antibiotics using 2-dimensional gel electrophoresis (2D-GE). Fourth, to study the central response to multiple perturbations in P. aeruginosa, i.e., the core perturbome, a machine learning approach was used. The analysis revealed biological functions and determinants that are shared by different disturbances. Finally, to evaluate the effects of ciprofloxacin (CIP) on PaeAG1, a growth curve comparison, differential expression analysis (RNA-Seq), and network analysis were performed. Using the results of the core perturbome (pathways that also were found in this perturbation with CIP), it was possible to identify the “exclusive” response and determinants of PaeAG1 after exposure to CIP. Altogether, after a decade of study using a multi-omics approach (at genomics, comparative genomics, perturbomics, transcriptomics, proteomics, and phenomics levels), we have provided new insights about the genomic and transcriptomic determinants associated with antibiotic resistance in PaeAG1. These results not only partially explain the high-risk condition of this strain that enables it to conquer nosocomial environments and its multi-resistance profile, but also this information may eventually be used as part of the strategies to fight this pathogen.