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Distribution of MGEs across the ESKAPE pathogens. (A) Maximum likelihood tree representing the ESKAPE genomes. Tree nodes are coloured according to the ESKAPE pathogen. Three bar charts with aligned fields are shown outside the tree: the innermost bar chart shows the density of ICEs/IMEs, while the density of prophages and plasmids across the genomes are shown in the middle and outermost bar charts, respectively. (B) Total number of MGEs and of considered masked genomes per ESKAPE pathogen. Size of the circles is proportional to the number of identified elements. (C) Proportion of genomes carrying at least one plasmid, ICE/IME or prophage. (D) Total number of RGPs and ICEs/IMEs per ESKAPE. The size of the green bars is proportional to the total number of ICEs/IMEs identified per ESKAPE pathogen, and the relative number of ICEs/IMEs per RGPs is shown in percentage next to the green bars. Bars are sorted according to the relative number of ICEs/IMEs per RGPs. Ab, A. baumannii; Ef, E. faecium; En, Enterobacter sp.; Kp, K. pneumoniae; Pa, P. aeruginosa; Sa, S. aureus.
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Mobile genetic elements (MGEs) mediate the shuffling of genes among organisms. They contribute to the spread of virulence and antibiotic resistance (AMR) genes in human pathogens, such as the particularly problematic group of ESKAPE pathogens. Here, we performed the first systematic analysis of MGEs, including plasmids, prophages, and integrative a...
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... this parameter is only applied for species delineation, we also built a phylogenomic tree with Enterobacter sp. genomes and type strains belonging to the Enterobacteriaceae family (Supplementary Figure S1). Our curated dataset included 1746 complete genomes which belong to 451 different MLST profiles (Supplementary Table S2). ...
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... curated dataset included 1746 complete genomes which belong to 451 different MLST profiles (Supplementary Table S2). We found a total of 21 478 MGEs, including 16 153 prophages, 2685 ICEs/IMEs and 2640 plasmids ( Figure 1A and B). The density of these MGEs (i.e. the cumulative length of each MGE type per genome length) shows a patchy distribution across the ESKAPE phylogeny ( Figure 1A and Supplementary Figure S2). ...
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... found a total of 21 478 MGEs, including 16 153 prophages, 2685 ICEs/IMEs and 2640 plasmids ( Figure 1A and B). The density of these MGEs (i.e. the cumulative length of each MGE type per genome length) shows a patchy distribution across the ESKAPE phylogeny ( Figure 1A and Supplementary Figure S2). S. aureus genomes are densely populated by prophages, while ICEs/IMEs are prevalent in P. aeruginosa. ...
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... pneumoniae and Enterobacter are populated by plasmids and prophages. In fact, plasmids were prevalent in every ESKAPE except P. aeruginosa and S. aureus Figures 1A and C). The majority of plasmids carried a relaxase (62.5%, 1651/2640), and were classified as mobilizable (either self-conjugative or not) (64). ...
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... majority of plasmids carried a relaxase (62.5%, 1651/2640), and were classified as mobilizable (either self-conjugative or not) (64). Curiously, E. faecium genomes have high densities of both prophages, plasmids and ICEs/IMEs ( Figure 1A). ...
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... look for RGPs exclusively integrated in the chromosome, we used the 1746 chromosomal replicons to generate plasmid-free pangenomes for each ESKAPE taxon. We identified a total of 50482 plasmid-free RGPs in chromosomal replicons ( Figure 1D). Of these, 2685 were classified as ICEs/IMEs due to the presence of relaxase and integrase domains ( Figure 1B and D). ...
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... identified a total of 50482 plasmid-free RGPs in chromosomal replicons ( Figure 1D). Of these, 2685 were classified as ICEs/IMEs due to the presence of relaxase and integrase domains ( Figure 1B and D). At least one ICE/IME was detected in >50% of genomes for all ESKAPE pathogens and was abundant in E. faecium and P. aeruginosa (∼3 elements/genome) ( Figure 1B and C). ...
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... these, 2685 were classified as ICEs/IMEs due to the presence of relaxase and integrase domains ( Figure 1B and D). At least one ICE/IME was detected in >50% of genomes for all ESKAPE pathogens and was abundant in E. faecium and P. aeruginosa (∼3 elements/genome) ( Figure 1B and C). After masking the ICEs/IMEs identified in the ESKAPE chromosomes, we performed a search for prophages. ...
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... observed that AMR genes are broadly distributed in plasmids across the ESKAPE pathogens. Even though the total number of prophages far outnumber that of plasmids in our collection (Figure 1), the absolute count of AMR genes in plasmids is greater than that observed in prophages (6068 versus 1845, respectively) (Supplementary Figure S9). Interestingly, most AMR genes in plasmids and prophages are found in K. pneumoniae, whereas P. aeruginosa carries the majority of these genes within ICEs/IMEs (Supplementary Table S4). ...
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... most AMR genes in plasmids and prophages are found in K. pneumoniae, whereas P. aeruginosa carries the majority of these genes within ICEs/IMEs (Supplementary Table S4). All ESKAPE pathogens have a large proportion of AMR-carrying plasmids (>35% of plasmids across the different ESKAPE carry at least one AMR gene), while a high proportion of AMR-harbouring ICEs (>25%) was only observed for S. aureus and P. aeruginosa (Supplementary Figures S10A and B). As previously reported (72), we observed that AMR genes are rarely found in prophages (<12% of prophages across the different ES-KAPE carry at least one AMR gene) ( Supplementary Fig- ure S10C). ...
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... ESKAPE pathogens have a large proportion of AMR-carrying plasmids (>35% of plasmids across the different ESKAPE carry at least one AMR gene), while a high proportion of AMR-harbouring ICEs (>25%) was only observed for S. aureus and P. aeruginosa (Supplementary Figures S10A and B). As previously reported (72), we observed that AMR genes are rarely found in prophages (<12% of prophages across the different ES-KAPE carry at least one AMR gene) ( Supplementary Fig- ure S10C). As expected from the vast repertoire of MGEs present in K. pneumoniae ( Figure 1A), this species presented a wider selection of different AMR genes. ...
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... previously reported (72), we observed that AMR genes are rarely found in prophages (<12% of prophages across the different ES-KAPE carry at least one AMR gene) ( Supplementary Fig- ure S10C). As expected from the vast repertoire of MGEs present in K. pneumoniae ( Figure 1A), this species presented a wider selection of different AMR genes. Some AMR genes were restricted to specific ESKAPE pathogens, while others were more promiscuous. ...
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... next assessed the distribution of virulence genes. These genes are broadly distributed in prophages and ICEs/IMEs across the ESKAPE pathogens (Supplementary Figure S11 and Table S5). In fact, we identified no virulence genes in E. faecium plasmids, and only 0.6% of A. baumannii plasmids carry these genes. ...
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... fact, we identified no virulence genes in E. faecium plasmids, and only 0.6% of A. baumannii plasmids carry these genes. More than 25% ICEs/IMEs in S. aureus, K. pneumoniae, and E. faecium carried at least one virulence gene (Supplementary Figures S10C and D). P. aeruginosa is the ESKAPE pathogen carrying a wider variety of virulence genes in these MGEs, mostly on prophages. ...
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... pneumoniae and Enterobacter sp.). These virulence loci were mostly present in ICEs/IMEs, as previously reported (74), but we also found these genes on plasmids and prophages (Supplementary Figure S11 and Table S5). Interestingly, S. aureus was the ESKAPE pathogen with a higher proportion of both plasmids and ICEs/IMEs carrying at least one AMR or virulence genes (Supplementary Figure S10). ...
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... virulence loci were mostly present in ICEs/IMEs, as previously reported (74), but we also found these genes on plasmids and prophages (Supplementary Figure S11 and Table S5). Interestingly, S. aureus was the ESKAPE pathogen with a higher proportion of both plasmids and ICEs/IMEs carrying at least one AMR or virulence genes (Supplementary Figure S10). ...
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... the low prevalence of CRISPR-Cas systems in S. aureus, this species was also excluded, and we focused exclusively on P. aeruginosa, K. pneumoniae, and A. baumannii. Interestingly, some sequence types (ST) consisted entirely of either CRISPR-Cas positive or negative genomes (Supplementary Figure S12 and Table S2). For example, the most frequent MLST profile in A. baumannii from our dataset was ST2 (n = 101), which only included strains with no CRISPR-Cas systems. ...
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... contrast, ST233 and ST1971 (n = 8 for both) consisted exclusively of strains carrying the I-F CRISPR-Cas system on masked genomes (Supple- mentary Table S2). These findings suggest that the presence or absence of CRISPR-Cas systems across the ESKAPE pathogens is related to sequence type and thus most likely due to phylogenetic history of the strains (Supplementary Figure S12). ...
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... looking into the influence of GC content and sequence length in pairs of conspecific ESKAPE pathogens with and without CRISPR-Cas systems, we would expect to observe smaller and GC richer strains on those carrying these systems. Size expectations could only be met for P. aeruginosa, for which CRISPR-Cas positive genomes were significantly smaller than their counterparts (Supplementary Figure S13A, P-value 0.0028), as observed before (76-78). Surprisingly in K. pneumoniae, genomes with CRISPRCas systems were significantly larger than CRISPR-Cas negative genomes (Supplementary Figure S13A, P-value 0.0023). ...
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... expectations could only be met for P. aeruginosa, for which CRISPR-Cas positive genomes were significantly smaller than their counterparts (Supplementary Figure S13A, P-value 0.0028), as observed before (76-78). Surprisingly in K. pneumoniae, genomes with CRISPRCas systems were significantly larger than CRISPR-Cas negative genomes (Supplementary Figure S13A, P-value 0.0023). The non-significant differences observed for A. baumannii, Enterobacter sp. and S. aureus could in part be explained by the low sample size of CRISPR-Cas positive genomes ( Figure 6A). ...
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... the GC content, we observed significant differences in A. baumannii, K. pneumoniae, and P. aeruginosa. CRISPR-Cas positive genomes were GC richer in A. baumannii and P. aeruginosa (Supplementary Figure S13B, P-values 0.0013 and 0.046, respectively). Curiously, we noticed that CRISPR-Cas positive genomes in K. pneumoniae were GC poorer (Supplementary Figure S13B, P-value 5.7e−09). ...
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... positive genomes were GC richer in A. baumannii and P. aeruginosa (Supplementary Figure S13B, P-values 0.0013 and 0.046, respectively). Curiously, we noticed that CRISPR-Cas positive genomes in K. pneumoniae were GC poorer (Supplementary Figure S13B, P-value 5.7e−09). Given the known association between GC content and genome size (67), these GC differences in CRISPR-Cas positive and negative P. aeruginosa genomes may be a spurious correlation driven by small size of CRISPR-Cas positive genomes. ...
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... the known association between GC content and genome size (67), these GC differences in CRISPR-Cas positive and negative P. aeruginosa genomes may be a spurious correlation driven by small size of CRISPR-Cas positive genomes. So, we corrected the GC content for variation in genome size, and we observed that the association was maintained (Supplementary Figure S14A, P-value 0.0035), in accordance to a previous study (77). ...
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... virulence genes are overrepresented in the chromosome (Figure 5), we assessed the distribution of these genes in pairs of conspecific ESKAPE pathogens with and without CRISPR-Cas systems. Virulence genes were significantly less abundant in CRISPR-Cas positive genomes from P. aeruginosa and A. baumannii ( Supplementary Fig- ure S13C, P-values 4.1e−06 and 0.0016, respectively). Given that P. aeruginosa genomes positive for these systems are significantly smaller than their CRISPR-Cas negative counterparts (Supplementary Figure S13A), the lower prevalence of these genes in CRISPR-Cas positive P. aeruginosa genomes may again be driven by a spurious correlation. ...
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... genes were significantly less abundant in CRISPR-Cas positive genomes from P. aeruginosa and A. baumannii ( Supplementary Fig- ure S13C, P-values 4.1e−06 and 0.0016, respectively). Given that P. aeruginosa genomes positive for these systems are significantly smaller than their CRISPR-Cas negative counterparts (Supplementary Figure S13A), the lower prevalence of these genes in CRISPR-Cas positive P. aeruginosa genomes may again be driven by a spurious correlation. As so, we corrected the number of virulence genes for variation in genome size, and we observed that indeed the difference was no longer significant ( Supplementary Fig- ure S14B, P-value 0.74), confirming our prediction that the genome size was a confounding variable obscuring the effect of CRISPR-Cas systems on the prevalence of virulence genes in P. aeruginosa. ...
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... that P. aeruginosa genomes positive for these systems are significantly smaller than their CRISPR-Cas negative counterparts (Supplementary Figure S13A), the lower prevalence of these genes in CRISPR-Cas positive P. aeruginosa genomes may again be driven by a spurious correlation. As so, we corrected the number of virulence genes for variation in genome size, and we observed that indeed the difference was no longer significant ( Supplementary Fig- ure S14B, P-value 0.74), confirming our prediction that the genome size was a confounding variable obscuring the effect of CRISPR-Cas systems on the prevalence of virulence genes in P. aeruginosa. ...
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... this trend was only observed Nucleic Acids Research, 2023 11 in K. pneumoniae (Figure 7). The variation in the number of MGEs in genomes either with or without CRISPRCas systems still holds when correcting for genome size (Supplementary Figure S15). Finally, we focused on AMR and virulence genes carried exclusively by plasmids and ICEs/IMEs, as these were the most important vectors (Supplementary Figure S10). ...
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... variation in the number of MGEs in genomes either with or without CRISPRCas systems still holds when correcting for genome size (Supplementary Figure S15). Finally, we focused on AMR and virulence genes carried exclusively by plasmids and ICEs/IMEs, as these were the most important vectors (Supplementary Figure S10). For most MGE/ESKAPE pairs, we observed no significant difference between pairs of conspecific genomes with and without CRISPR-Cas systems. ...
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... most MGE/ESKAPE pairs, we observed no significant difference between pairs of conspecific genomes with and without CRISPR-Cas systems. When it comes to AMR genes, we only observed significant differences in MGEs from P. aeruginosa (Supplementary Figure S16A, P-values 0.037). Indeed, AMR genes were more prevalent on ICEs/IMEs from P. aeruginosa genomes with CRISPR-Cas systems (Supplementary Table S7). ...
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... the less prevalent I-C CRISPR-Cas subtype, which was exclusively identified in P. aeruginosa and mostly on ICEs/IMEs (Supplementary Table S6), was recently found to be positively correlated with certain AMR genes (76). Regarding virulence genes, we observed significant differences in MGEs from K. pneumoniae, where CRISPRCas-carrying elements were associated with more virulence genes than their CRISPR-Cas negative counterparts (Supplementary Figure S16B, P-values 0.0054). Taken together, we observed species-specific trends shaping the number of MGEs, AMR and virulence genes across pairs of conspecific ESKAPE genomes with and without CRISPR-Cas systems. ...
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... total of 1087 spacers was found across all MGEs (n = 554 on plasmids, n = 343 on ICEs/IMEs and n = 190 on prophages). Given the large number of MGEs and CRISPR-Cas-encoding plasmids in K. pneumoniae (Figures 1 and 6B), it was no surprise to observe that more than half of the spacers were found in this species (577/1087). The large majority of plasmid spacers were identified on mobilizable plasmids (99.4%, 551/554). ...
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... then corrected the total length of CRISPR spacers found on each MGE by the size of the corresponding MGE. Interestingly, we found that the density of CRISPR arrays is significantly higher across prophages than that of plasmids and ICEs/IMEs (P-value 3.7e−07, Supplementary Figure S17). ...
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... A. baumannii; En, Enterobacter sp.; Kp, K. pneumoniae; Pa, P. aeruginosa; Sa, S. aureus. of CRISPR-Cas systems in the E. faecium strains from our dataset, no spacers were identified in masked genomes from this species. The number of CRISPR spacers per genome varied considerably between the masked genomes of the ESKAPE pathogens (Supplementary Figure S18), reaching as high as 189 in A. baumannii. In fact, only strains from this species carried >100 spacers per masked genome. ...
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Mobile genetic elements (MGEs) or mobilomes promote the mobilization and dissemination of antimicrobial resistance genes (ARGs), serving as critical drivers for antimicrobial resistance (AMR) accumulation, interaction, and persistence. However, systematic and quantitative evaluations of the role of mobilome in spreading resistome in a bacterial pat...
Citations
... 5 The antimicrobial resistant ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter) are reported as the major cause of life-threatening nosocomial infections throughout the world. 6,7 In combination with improvements in antibiotic resistance measurement, the discovery of new treatment options to combat pathogens is urgently needed, especially for antibiotic-resistant bacteria. Identifying bioactive compounds from gut and environmental microbiomes that target antibiotic-resistant bacteria is an important new strategy. ...
Multidrug-resistant microorganisms have become a major public health concern around the world. The gut microbiome is a gold mine for bioactive compounds that protect the human body from pathogens. We used a multi-omics approach that integrated whole-genome sequencing (WGS) of 74 commensal gut microbiome isolates with metabolome analysis to discover their metabolic interaction with Salmonella and other antibiotic-resistant pathogens. We evaluated differences in the functional potential of these selected isolates based on WGS annotation profiles. Furthermore, the top altered metabolites in co-culture supernatants of selected commensal gut microbiome isolates were identified including a series of dipeptides and examined for their ability to prevent the growth of various antibiotic-resistant bacteria. Our results provide compelling evidence that the gut microbiome produces metabolites, including the compound class of dipeptides that can potentially be applied for anti-infection medication, especially against antibiotic-resistant pathogens. Our established pipeline for the discovery and validation of bioactive metabolites from the gut microbiome as novel candidates for multidrug-resistant infections represents a new avenue for the discovery of antimicrobial lead structures.
... We identified at least one putative antibiotic resistance or virulence hostrelated gene within the prophage regions of all species studied. In comparison, <12% of highly antibiotic resistant ESKAPE pathogens carry a prophage-encoded antibiotic resistance gene 32 . In addition, lysogens carrying antibiotic resistance genes have been shown to provide a fitness benefit for their host 31,33 . ...
Evidence from the International Space Station suggests microbial populations are rapidly adapting to the spacecraft environment; however, the mechanism of this adaptation is not understood. Bacteriophages are prolific mediators of bacterial adaptation on Earth. Here we survey 245 genomes sequenced from bacterial strains isolated on the International Space Station for dormant (lysogenic) bacteriophages. Our analysis indicates phage-associated genes are significantly different between spaceflight strains and their terrestrial counterparts. In addition, we identify 283 complete prophages, those that could initiate bacterial lysis and infect additional hosts, of which 21% are novel. These prophage regions encode functions that correlate with increased persistence in extreme environments, such as spaceflight, to include antimicrobial resistance and virulence, DNA damage repair, and dormancy. Our results correlate microbial adaptation in spaceflight to bacteriophage-encoded functions that may impact human health in spaceflight.
... Transposons commonly mediate gene acquisition and duplication in plasmids [5], but these elements appear to be counterselected in phages, suggesting that DNA translocation is the main HGT driver between plasmids and P-Ps whereas homologous recombination would promote gene exchange between P-Ps and phages. Since plasmids and phages tend to form distinctive clusters in a sequence similarity network [4,6], the frequency of recombination events between these MGE types is predicted to be low. Here, P-Ps potentially supply a platform for expanding the boundaries of HGT by enabling the gene flow between seemingly different MGEs via both DNA translocation and homologous recombination. ...
... ICEs and IMEs usually integrate into bacterial chromosomes, as prophages do, but encode conjugation machinery (or have the ability to hijack it from other MGEs) to transfer horizontally between cells as plasmids [10] the opposite of P-Ps. Interestingly, ICEs and IMEs tend to cluster with either plasmids or phages [6]. Hence, it would not be surprising if they could enable HGT between them, similarly to P-Ps. ...
... In a recent study, it was identified that anti-CRISPR proteins are up to 15 times overrepresented in the MGEs of ESKAPE pathogens when compared to the "nonmobile" genome. 216 Furthermore, loci that code for anti-CRISPR proteins have been detected in MGEs of various Gram-negative bacteria, 217 some of the clinical relevance. 218 Considering the high frequency of horizontal transfer events between bacteria and the selective pressure that CRISPR-based antimicrobials could impose, it is expected that the transfer of plasmids that confer resistance to cutting by Cas nucleases will pose a challenge for the use of this type of antimicrobial therapy alternatives. ...
The emergence of antibiotic-resistant bacterial strains is a source of public health concern across the globe. As the discovery of new conventional antibiotics has stalled significantly over the past decade, there is an urgency to develop novel approaches to address drug resistance in infectious diseases. The use of a CRISPR-Cas-based system for the precise elimination of targeted bacterial populations holds promise as an innovative approach for new antimicrobial agent design. The CRISPR-Cas targeting system is celebrated for its high versatility and specificity, offering an excellent opportunity to fight antibiotic resistance in pathogens by selectively inactivating genes involved in antibiotic resistance, biofilm formation, pathogenicity, virulence, or bacterial viability. The CRISPR-Cas strategy can enact antimicrobial effects by two approaches: inactivation of chromosomal genes or curing of plasmids encoding antibiotic resistance. In this Review, we provide an overview of the main CRISPR-Cas systems utilized for the creation of these antimicrobials, as well as highlighting promising studies in the field. We also offer a detailed discussion about the most commonly used mechanisms for CRISPR-Cas delivery: bacteriophages, nanoparticles, and conjugative plasmids. Lastly, we address possible mechanisms of interference that should be considered during the intelligent design of these novel approaches.
... We indeed found that genomes with CRISPR-Cas systems are significantly smaller than those without (Fig. 4A, p-values 8.3e-05 and 0.00025 for the phylogroup A and B comparisons, respectively), supporting the hypothesis that CRISPR-Cas systems may restrict horizontal gene transfer in P. aeruginosa. [48][49][50] While the number of CRISPR-Cas pos and CRISPR-Cas neg genomes in phylogroups A and C is evenly distributed, phylogroup B genomes without CRISPR-Cas (n = 279) were almost twice as abundant as those that carried these systems (n = 156, Table S2). Interestingly, the masked genome size of CRISPR-Cas pos and CRISPR-Cas neg phylogroup B isolates was no longer significantly different from one another (Fig. 4B). ...
... 12,51 The type I-C CRISPR-Cas subtype is typically encoded on ICEs and is also involved in competition dynamics between mobile elements. 49,52 Overall, our findings show that phylogroup B genomes are significantly larger and have a wider pool of accessory genes than those from the other two phylogroups, possibly driven by the lower prevalence of CRISPR-Cas systems in phylogroup B. ...
... Remarkably, genomes devoid of CRISPR-Cas systems in phylogroups A and B were generally significantly larger than those with these systems, a trend that was no longer observed when only considering the non-RGP ("masked") genomes. This observation is consistent with the hypothesis that CRISPR-Cas systems can restrict horizontal gene transfer in P. aeruginosa, [48][49][50]68 at least for genomes belonging to the larger phylogroups. ...
Background:
Pseudomonas aeruginosa is an opportunistic pathogen consisting of three phylogroups (hereafter named A, B, and C). Here, we assessed phylogroup-specific evolutionary dynamics across available and also new P. aeruginosa genomes.
Methods:
In this genomic analysis, we first generated new genome assemblies for 18 strains of the major P. aeruginosa clone type (mPact) panel, comprising a phylogenetically diverse collection of clinical and environmental isolates for this species. Thereafter, we combined these new genomes with 1991 publicly available P. aeruginosa genomes for a phylogenomic and comparative analysis. We specifically explored to what extent antimicrobial resistance (AMR) genes, defence systems, and virulence genes vary in their distribution across regions of genome plasticity (RGPs) and "masked" (RGP-free) genomes, and to what extent this variation differs among the phylogroups.
Findings:
We found that members of phylogroup B possess larger genomes, contribute a comparatively larger number of pangenome families, and show lower abundance of CRISPR-Cas systems. Furthermore, AMR and defence systems are pervasive in RGPs and integrative and conjugative/mobilizable elements (ICEs/IMEs) from phylogroups A and B, and the abundance of these cargo genes is often significantly correlated. Moreover, inter- and intra-phylogroup interactions occur at the accessory genome level, suggesting frequent recombination events. Finally, we provide here the mPact panel of diverse P. aeruginosa strains that may serve as a valuable reference for functional analyses.
Interpretation:
Altogether, our results highlight distinct pangenome characteristics of the P. aeruginosa phylogroups, which are possibly influenced by variation in the abundance of CRISPR-Cas systems and are shaped by the differential distribution of other defence systems and AMR genes.
Funding:
German Science Foundation, Max-Planck Society, Leibniz ScienceCampus Evolutionary Medicine of the Lung, BMBF program Medical Infection Genomics, Kiel Life Science Postdoc Award.
... Certain additional bacterial genes, such as aac(3)-IId-like, strA, strB, aac(3)-IIa-like, strA-like, strB and aac(6')Ib-cr, responsible for ESBL production and multi drug resistances were figured out [23]. The non-stoppable distribution of these bacterial genes is the absolute reason underlying the hurdles to handle the AMR cases globally [24]. ...
Antimicrobial resistance is the rising global health issue that should not be ignored. This problem needs to be addressed and professionally handled since it is starting to threaten global health, which eventually could lead to disaster. Extended spectrum beta lactamase (ESBL)-producing bacteria were found threatening lives, since most antibiotics were found to not be effective in treating patients with infections caused by those bacteria. ESBL-producing Escherichia coli and Klebsiella pneumoniae are the two most reported bacteria in causing the bacteremia and nosocomial infections worldwide. In this article, the prevalence of ESBL-producing E. coli and K. pneumoniae in causing blood stream and urinary tract infections in Indonesia were compared to the neighboring countries based on the global antimicrobial resistance surveillance system performed worldwide by World Health Organization (WHO). In this article, the prevalence of ESBL-producing E. coli and K. pneumoniae in Indonesia and its neighboring countries were assayed and compared in order to evaluate the antimicrobial resistances. By comparing the prevalence data to the neighboring countries, some insightful evidence and information was served to support improved health in Indonesia. Some hurdles and strategies in combating the antimicrobial resistances were further discussed. Eventually, an alternate solution to overcome the antimicrobial drug resistance should be well-provided, studied and implemented globally.
... We identi ed at least one antibiotic resistance or virulence host related gene within the prophage regions of all species studied. In comparison, terrestrial, less than 12% of highly antibiotic resistant ESKAPE pathogens carry a prophage-encoded antibiotic resistance gene (33). Additionally, lysogens carrying antibiotic resistance genes have been shown to provide a tness bene t for their host (32,34). ...
Evidence from the International Space Station suggests microbial populations are rapidly adapting to the spacecraft environment; however, the mechanism of this adaptation is not understood. Bacteriophages are prolific mediators of bacterial adaptation on Earth. We surveyed 245 genomes sequenced from bacterial strains isolated on the International Space Station for dormant (lysogenic) bacteriophages. Our analysis indicated phage-associated genes are significantly different between spaceflight strains and their terrestrial counterparts. Additionally, we identified 283 complete prophages, those that could initiate bacterial lysis and infect additional hosts, of which 46% are novel. These prophage regions encode functions that are correlated with increased persistence in extreme environments, such as spaceflight, to include antimicrobial resistance and virulence, DNA damage repair, and dormancy. Our results correlate microbial adaptation in spaceflight to bacteriophage-encoded functions that may impact human health in spaceflight.
... As demonstrated by earlier work, anti-phage defense systems can be shared among bacteria as they are often associated with MGEs [21,40]. In addition, it is common for MGEs to cross species barriers and disseminate in other bacterial species, which can, for example, result in the spread of antimicrobial resistance [41]. For example, plasmids have been shown to exchange DNA beyond the genus (and phylum) barrier [42]. ...
Bacteriophages, which specifically infect and kill bacteria, are currently used as additives to control pathogens such as Salmonella in human food (PhageGuard S®) or animal feed (SalmoF-REE®, Bafasal®). Indeed, salmonellosis is among the most important zoonotic foodborne illnesses. The presence of anti-phage defenses protecting bacteria against phage infection could impair phage applications aiming at reducing the burden of foodborne pathogens such as Salmonella enterica subsp. enterica serovar Typhimurium (S. Typhimurium) to the food industry. In this study, the landscape of S. Typhimurium anti-phage defenses was bioinformatically investigated in publicly available ge-nomes using the webserver PADLOC. The primary anti-phage systems identified in S. Typhi-murium use nucleic acid degradation and abortive infection mechanisms. Reference systems were identified on an integrative and conjugative element, a transposon, a putative integrative and mo-bilizable element, and prophages. Additionally, the mobile genetic elements (MGEs) containing a subset of anti-phage systems were found in the Salmonella enterica species. Lastly, the MGEs alone were also identified in the Enterobacteriaceae family. The presented diversity assessment of the anti-phage defenses and investigation of their dissemination through MGEs in S. Typhimurium constitute a first step towards the design of preventive measures against the spread of phage resistance that may hinder phage applications.
The Klebsiella pneumoniae (K. pneumoniae, Kp) populations carrying both resistance-encoding and virulence-encoding mobile genetic elements (MGEs) significantly threaten global health. In this study, we identified a new anti-CRISPR gene (acrIE10) on a conjugative plasmid with self-target sequence in K. pneumoniae with type I-E* CRISPR-Cas system. AcrIE10 interacts with the Cas7* subunit of K. pneumoniae I-E* CRISPR-Cas system. The crystal structure of the AcrIE10-KpCas7* complex suggests that AcrIE10 suppresses the I-E* CRISPR-Cas by binding directly to Cas7 to prevent its hexamerization, thereby preventing the surveillance complex assembly and crRNA loading. Bioinformatic and functional analyses revealed that AcrIE10 is functionally widespread across diverse species. Our study reports a novel anti-CRISPR and highlights its potential role in spreading resistance and virulence among pathogens.
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.
