A comprehensive computer-based assessment of Deacetylnomilin as an inhibitor for antibiotic-resistant genes identified from the whole genome sequence of the multidrug-resistant Enterobacter cloacae isolate 1382. - Related Documents




#
Rank
Similarity
Title + Abs.
Year
PMID
012345
509601.0000A comprehensive computer-based assessment of Deacetylnomilin as an inhibitor for antibiotic-resistant genes identified from the whole genome sequence of the multidrug-resistant Enterobacter cloacae isolate 1382. The twenty-first century presents a serious threat to public health due to the growth in antibiotic resistance among opportunistic bacteria, particularly within the ESKAPE group, which includes Enterobacter species with high morbidity, mortality, virulence, and nosocomial dissemination rates. Enterobacter species, especially Enterobacter cloacae, bacteria have developed resistance to multiple antibiotics through mechanisms, such as continuous production of AmpC beta-lactamase. In this study, a comprehensive bioinformatics approach was employed to analyze the genome of Enterobacter cloacae, utilizing sequence data from GenBank (ID: OW968328.1). The AbritAMR and ResFinder tools were utilized to identify antibiotic-resistant genes, which included the presence of blaOXA-48, blaCMH, FosA, OqxA, and OqxB each conferring resistance to specific antibiotics such as β-lactams and fluoroquinolones. These proteins were analyzed using bioinformatics tools such as ProtParam, SOPMA, Robetta, I-TASSER, AlphaFold, and PROCHECK to investigate different structural models and their properties. The models from AlphaFold had the best quality in terms of structural accuracy, providing valuable insights into the 3D conformations of these resistant proteins. Based on the Molecular docking studies, these constructed targets were docked with 20 natural compounds known for their activity against Gram-negative bacteria. Among them, Deacetylnomilin showed the highest docking score and passed their ADMET properties. Molecular dynamic (MD) simulation was conducted for 100 ns for Deacetylnomilin with different resistant proteins. Deacetylnomilin exhibited more favorable binding free energies compared to the reference compounds across all five proteins, indicating higher stability and affinity. These results suggest that Deacetylnomilin could be an effective inhibitor against the resistant proteins of Enterobacter cloacae, making it a promising candidate for further drug development.202539702793
502310.9993Fosfomycin resistance mechanisms in Enterobacterales: an increasing threat. Antimicrobial resistance is well-known to be a global health and development threat. Due to the decrease of effective antimicrobials, re-evaluation in clinical practice of old antibiotics, as fosfomycin (FOS), have been necessary. FOS is a phosphonic acid derivate that regained interest in clinical practice for the treatment of complicated infection by multi-drug resistant (MDR) bacteria. Globally, FOS resistant Gram-negative pathogens are raising, affecting the public health, and compromising the use of the antibiotic. In particular, the increased prevalence of FOS resistance (FOS(R)) profiles among Enterobacterales family is concerning. Decrease in FOS effectiveness can be caused by i) alteration of FOS influx inside bacterial cell or ii) acquiring antimicrobial resistance genes. In this review, we investigate the main components implicated in FOS flow and report specific mutations that affect FOS influx inside bacterial cell and, thus, its effectiveness. FosA enzymes were identified in 1980 from Serratia marcescens but only in recent years the scientific community has started studying their spread. We summarize the global epidemiology of FosA/C2/L1-2 enzymes among Enterobacterales family. To date, 11 different variants of FosA have been reported globally. Among acquired mechanisms, FosA3 is the most spread variant in Enterobacterales, followed by FosA7 and FosA5. Based on recently published studies, we clarify and represent the molecular and genetic composition of fosA/C2 genes enviroment, analyzing the mechanisms by which such genes are slowly transmitting in emerging and high-risk clones, such as E. coli ST69 and ST131, and K. pneumoniae ST11. FOS is indicated as first line option against uncomplicated urinary tract infections and shows remarkable qualities in combination with other antibiotics. A rapid and accurate identification of FOS(R) type in Enterobacterales is difficult to achieve due to the lack of commercial phenotypic susceptibility tests and of rapid systems for MIC detection.202337469601
569120.9992Rapid and Accurate Antibiotic Susceptibility Determination of tet(X)-Positive E. coli Using RNA Biomarkers. The emergence and prevalence of novel plasmid-mediated tigecycline resistance genes, namely, tet(X) and their variants, pose a serious threat to public health worldwide. Rapid and accurate antibiotic susceptibility testing (AST) that can simultaneously detect the genotype and phenotype of tet(X)-positive bacteria may contribute to the deployment of an effective antibiotic arsenal, mortality reduction, and a decrease in the use of broad-spectrum antimicrobial agents. However, current bacterial growth-based AST methods, such as broth microdilution, are time consuming and delay the prompt treatment of infectious diseases. Here, we developed a rapid RNA-based AST (RBAST) assay to effectively distinguish tet(X)-positive and -negative strains. RBAST works by detecting specific mRNA expression signatures in bacteria after short-term tigecycline exposure. As a proof of concept, a panel of clinical isolates was characterized successfully by using the RBAST method, with a 3-h assay time and 87.9% accuracy (95% confidence interval [CI], 71.8% to 96.6%). Altogether, our findings suggest that RNA signatures upon antibiotic exposure are promising biomarkers for the development of rapid AST, which could inform early antibiotic choices. IMPORTANCE Infections caused by multidrug-resistant (MDR) Gram-negative pathogens are an increasing threat to global health. Tigecycline is one of the last-resort antibiotics for the treatment of these complicated infections; however, the emergence of plasmid-encoded tigecycline resistance genes, namely, tet(X), severely diminishes its clinical efficacy. Currently, there is a lack of rapid and accurate antibiotic susceptibility testing (AST) for the detection of tet(X)-positive bacteria. In this study, we developed a rapid and robust RNA-based antibiotic susceptibility determination (RBAST) assay to effectively distinguish tet(X)-negative and -positive strains using specific RNA biomarkers in bacteria after tigecycline exposure. Using this RBAST method, we successfully characterized a set of clinical strains in 3 h. Our data indicate that the RBAST assay is useful for identifying tet(X)-positive Escherichia coli.202134704829
569030.9992Rapid Detection of MCR-Mediated Colistin Resistance in Escherichia coli. Colistin is one of the last-resort antibiotics for infections caused by multidrug-resistant Gram-negative bacteria. However, the wide spread of novel plasmid-carrying colistin resistance genes mcr-1 and its variants substantially compromise colistin's therapeutic effectiveness and pose a severe danger to public health. To detect colistin-resistant microorganisms induced by mcr genes, rapid and reliable antibiotic susceptibility testing (AST) is imminently needed. In this study, we identified an RNA-based AST (RBAST) to discriminate between colistin-susceptible and mcr-1-mediated colistin-resistant bacteria. After short-time colistin treatment, RBAST can detect differentially expressed RNA biomarkers in bacteria. Those candidate mRNA biomarkers were successfully verified within colistin exposure temporal shifts, concentration shifts, and other mcr-1 variants. Furthermore, a group of clinical strains were effectively distinguished by using the RBAST approach during the 3-h test duration with over 93% accuracy. Taken together, our findings imply that certain mRNA transcripts produced in response to colistin treatment might be useful indicators for the development of fast AST for mcr-positive bacteria. IMPORTANCE The emergence and prevalence of mcr-1 and its variants in humans, animals, and the environment pose a global public health threat. There is a pressing urgency to develop rapid and accurate methods to identify MCR-positive colistin-resistant bacteria in the clinical samples, providing a basis for subsequent effective antibiotic treatment. Using the specific mRNA signatures, we develop an RNA-based antibiotic susceptibility testing (RBAST) for effectively distinguishing colistin-susceptible and mcr-1-mediated colistin-resistant strains. Meanwhile, the detection efficiency of these RNA biomarkers was evidenced in other mcr variants-carrying strains. By comparing with the traditional AST method, the RBAST method was verified to successfully characterize a set of clinical isolates during 3 h assay time with over 93% accuracy. Our study provides a feasible method for the rapid detection of colistin-resistant strains in clinical practice.202235616398
583940.9992Computer Program for Detection and Analyzing the Porin-Mediated Antibiotic Resistance of Bacteria. The aim of this work was to develop a new software tool for identifying gene mutations that determine the porin-mediated resistance to antibiotics in gram-negative bacteria and to demonstrate the functionality of this program by detecting porin-mediated resistance to carbapenems in clinical isolates of Pseudomonas aeruginosa. MATERIALS AND METHODS: The proposed algorithm is based on searching for a correspondence between the reference and the studied genes. When the sought nucleotide sequence is found in the analyzed genome, it is compared with the reference one and analyzed. The genomic analysis is then verified by comparing between the amino acid sequences encoded by the reference and studied genes. The genes of the susceptible P. aeruginosa ATCC 27853 strain were used as the reference nucleotide sequences encoding for porins (OprD, OpdD, and OpdP) involved in the transport of carbapenems into the bacterial cell. The complete genomes of clinical P. aeruginosa isolates from the PATRIC database 3.6.9 and our own collection were used to test the functionality of the proposed program. The analyzed isolates were phenotypically characterized according to the CLSI standard. The search for carbapenemase genes in the studied genomes of P. aeruginosa was carried out using the ResFinder 4.1. RESULTS: The developed program for detecting the genetic determinants of non-plasmid antibiotic resistance made it possible to identify mutations of various types and significance in the porin genes of P. aeruginosa clinical isolates. These mutations led to modifications of the peptide structure of porin proteins. Single amino acid substitutions prevailed in the OpdD and OpdP porins of carbapenem-susceptible and carbapenem-resistant isolates. In the carbapenem-resistant strains, the gene encoding for OprD porin was found heavily modified, including insertions and/or deletions, which led to premature termination of porin synthesis. In several isolates resistant to meropenem, no mutations were detected in the gene encoding for OprD, which might be associated with alternative mechanisms of resistance to carbapenems. CONCLUSION: The proposed software product can become an effective tool for deciphering the molecular genetic mechanisms of bacterial chromosomal resistance to antibiotics. Testing the program revealed differences between the occurrences of mutations significant for carbapenem resistance in the oprD, opdD, and opdP genes.202135265355
466950.9992Functional Metagenome Mining of Soil for a Novel Gentamicin Resistance Gene. Extensive use of antibiotics over recent decades has led to bacterial resistance against antibiotics, including gentamicin, one of the most effective aminoglycosides. The emergence of resistance is problematic for hospitals, since gentamicin is an important broad-spectrum antibiotic for the control of bacterial pathogens in the clinic. Previous study to identify gentamicin resistance genes from environmental samples have been conducted using culture-dependent screening methods. To overcome these limitations, we employed a metagenome-based culture-independent protocol to identify gentamicin resistance genes. Through functional screening of metagenome libraries derived from soil samples, a fosmid clone was selected as it conferred strong gentamicin resistance. To identify a specific functioning gene conferring gentamicin resistance from a selected fosmid clone (35-40 kb), a shot-gun library was constructed and four shot-gun clones (2-3 kb) were selected. Further characterization of these clones revealed that they contained sequences similar to that of the RNA ligase, T4 rnlA that is known as a toxin gene. The overexpression of the rnlA-like gene in Escherichia coli increased gentamicin resistance, indicating that this toxin gene modulates this trait. The results of our metagenome library analysis suggest that the rnlA-like gene may represent a new class of gentamicin resistance genes in pathogenic bacteria. In addition, we demonstrate that the soil metagenome can provide an important resource for the identification of antibiotic resistance genes, which are valuable molecular targets in efforts to overcome antibiotic resistance.201626699755
569360.9992Evaluation of an expanded microarray for detecting antibiotic resistance genes in a broad range of gram-negative bacterial pathogens. A microarray capable of detecting genes for resistance to 75 clinically relevant antibiotics encompassing 19 different antimicrobial classes was tested on 132 Gram-negative bacteria. Microarray-positive results correlated >91% with antimicrobial resistance phenotypes, assessed using British Society for Antimicrobial Chemotherapy clinical breakpoints; the overall test specificity was >83%. Microarray-positive results without a corresponding resistance phenotype matched 94% with PCR results, indicating accurate detection of genes present in the respective bacteria by microarray when expression was low or absent and, hence, undetectable by susceptibility testing. The low sensitivity and negative predictive values of the microarray results for identifying resistance to some antimicrobial resistance classes are likely due to the limited number of resistance genes present on the current microarray for those antimicrobial agents or to mutation-based resistance mechanisms. With regular updates, this microarray can be used for clinical diagnostics to help accurate therapeutic options to be taken following infection with multiple-antibiotic-resistant Gram-negative bacteria and prevent treatment failure.201323129055
493270.9992Comprehensive analysis of beta-lactamase genes in clinical strains of Escherichia coli and Klebsiella pneumoniae: molecular characterization, and in Silico predictions. The emergence of beta-lactamase producing multidrug-resistant (MDR) gram-negative bacteria presents a significant challenge to effective treatment of infections. This study focuses on the isolation, amplification, and molecular characterization of β-lactamase genes from clinical strains of Escherichia coli and Klebsiella pneumoniae. Seven new partial gene sequences, including novel variants of blaOXA and blaNDM, were identified after screening 108 clinical samples and submitted to NCBI GenBank. In silico analysis revealed considerable diversity and distribution of these resistance genes among different strains of bacteria. Gene structure predictions using GENSCAN showed that blaOXA genes typically contain single exons with moderate GC content, whereas blaNDM genes feature longer exons with higher GC content. Multiple sequence alignment showed that NDM and OXA β-lactamases were highly similar, with only slight differences in a few amino acids. The study also analyzed the physico-chemical properties, functional domains, and phosphorylation patterns of the β-lactamase proteins. Secondary structure prediction indicated a dominance of beta sheets, contributing to protein stability, while tertiary modeling provided insights into their 3D structure. Overall, these findings provide critical insights into the genetic diversity and potential mechanisms of β-lactamase-mediated resistance, offering valuable information for the development of novel therapeutic strategies and surveillance programs.202540898000
493080.9991Whole-genome sequencing based characterization of antimicrobial resistance in Enterococcus. Whole-genome sequencing (WGS) has transformed our understanding of antimicrobial resistance, yielding new insights into the genetics underlying resistance. To date, most studies using WGS to study antimicrobial resistance have focused on gram-negative bacteria in the family Enterobacteriaceae, such as Salmonella spp. and Escherichia coli, which have well-defined resistance mechanisms. In contrast, relatively few studies have been performed on gram-positive organisms. We sequenced 197 strains of Enterococcus from various animal and food sources, including 100 Enterococcus faecium and 97 E. faecalis. From analyzing acquired resistance genes and known resistance-associated mutations, we found that resistance genotypes correlated with resistance phenotypes in 96.5% of cases for the 11 drugs investigated. Some resistances, such as those to tigecycline and daptomycin, could not be investigated due to a lack of knowledge of mechanisms underlying these phenotypes. This study showed the utility of WGS for predicting antimicrobial resistance based on genotype alone.201829617860
493390.9991Distribution and Classification of Serine β-Lactamases in Brazilian Hospital Sewage and Other Environmental Metagenomes Deposited in Public Databases. β-lactam is the most used antibiotic class in the clinical area and it acts on blocking the bacteria cell wall synthesis, causing cell death. However, some bacteria have evolved resistance to these antibiotics mainly due the production of enzymes known as β-lactamases. Hospital sewage is an important source of dispersion of multidrug-resistant bacteria in rivers and oceans. In this work, we used next-generation DNA sequencing to explore the diversity and dissemination of serine β-lactamases in two hospital sewage from Rio de Janeiro, Brazil (South Zone, SZ and North Zone, NZ), presenting different profiles, and to compare them with public environmental data available. Also, we propose a Hidden-Markov-Model approach to screen potential serine β-lactamases genes (in public environments samples and generated hospital sewage data), exploring its evolutionary relationships. Due to the high variability in β-lactamases, we used a position-specific scoring matrix search method (RPS-BLAST) against conserved domain database profiles (CDD, Pfam, and COG) followed by visual inspection to detect conserved motifs, to increase the reliability of the results and remove possible false positives. We were able to identify novel β-lactamases from Brazilian hospital sewage and to estimate relative abundance of its types. The highest relative abundance found in SZ was the Class A (50%), while Class D is predominant in NZ (55%). CfxA (65%) and ACC (47%) types were the most abundant genes detected in SZ, while in NZ the most frequent were OXA-10 (32%), CfxA (28%), ACC (21%), CEPA (20%), and FOX (19%). Phylogenetic analysis revealed β-lactamases from Brazilian hospital sewage grouped in the same clade and close to sequences belonging to Firmicutes and Bacteroidetes groups, but distant from potential β-lactamases screened from public environmental data, that grouped closer to β-lactamases of Proteobacteria. Our results demonstrated that HMM-based approach identified homologs of serine β-lactamases, indicating the specificity and high sensitivity of this approach in large datasets, contributing for the identification and classification of a large number of homologous genes, comprising possible new ones. Phylogenetic analysis revealed the potential reservoir of β-lactam resistance genes in the environment, contributing to understanding the evolution and dissemination of these genes.201627895627
4946100.9991Escherichia coli B-Strains Are Intrinsically Resistant to Colistin and Not Suitable for Characterization and Identification of mcr Genes. Antimicrobial resistance is an increasing threat to human and animal health. Due to the rise of multi-, extensive, and pandrug resistance, last resort antibiotics, such as colistin, are extremely important in human medicine. While the distribution of colistin resistance genes can be tracked through sequencing methods, phenotypic characterization of putative antimicrobial resistance (AMR) genes is still important to confirm the phenotype conferred by different genes. While heterologous expression of AMR genes (e.g., in Escherichia coli) is a common approach, so far, no standard methods for heterologous expression and characterization of mcr genes exist. E. coli B-strains, designed for optimum protein expression, are frequently utilized. Here, we report that four E. coli B-strains are intrinsically resistant to colistin (MIC 8-16 μg/mL). The three tested B-strains that encode T7 RNA polymerase show growth defects when transformed with empty or mcr-expressing pET17b plasmids and grown in the presence of IPTG; K-12 or B-strains without T7 RNA polymerase do not show these growth defects. E. coli SHuffle T7 express carrying empty pET17b also skips wells in colistin MIC assays in the presence of IPTG. These phenotypes could explain why B-strains were erroneously reported as colistin susceptible. Analysis of existing genome data identified one nonsynonymous change in each pmrA and pmrB in all four E. coli B-strains; the E121K change in PmrB has previously been linked to intrinsic colistin resistance. We conclude that E. coli B-strains are not appropriate heterologous expression hosts for identification and characterization of mcr genes. IMPORTANCE Given the rise in multidrug, extensive drug, and pandrug resistance in bacteria and the increasing use of colistin to treat human infections, occurrence of mcr genes threatens human health, and characterization of these resistance genes becomes more important. We show that three commonly used heterologous expression strains are intrinsically resistant to colistin. This is important because these strains have previously been used to characterize and identify new mobile colistin resistance (mcr) genes. We also show that expression plasmids (i.e., pET17b) without inserts cause cell viability defects when carried by B-strains with T7 RNA polymerase and grown in the presence of IPTG. Our findings are important as they will facilitate improved selection of heterologous strains and plasmid combinations for characterizing AMR genes, which will be particularly important with a shift to Culture-independent diagnostic tests where bacterial isolates become increasingly less available for characterization.202337199645
4758110.9991Development of New Tools to Detect Colistin-Resistance among Enterobacteriaceae Strains. The recent discovery of the plasmid-mediated mcr-1 gene conferring resistance to colistin is of clinical concern. The worldwide screening of this resistance mechanism among samples of different origins has highlighted the urgent need to improve the detection of colistin-resistant isolates in clinical microbiology laboratories. Currently, phenotypic methods used to detect colistin resistance are not necessarily suitable as the main characteristic of the mcr genes is the low level of resistance that they confer, close to the clinical breakpoint recommended jointly by the CLSI and EUCAST expert systems (S ≤ 2 mg/L and R > 2 mg/L). In this context, susceptibility testing recommendations for polymyxins have evolved and are becoming difficult to implement in routine laboratory work. The large number of mechanisms and genes involved in colistin resistance limits the access to rapid detection by molecular biology. It is therefore necessary to implement well-defined protocols using specific tools to detect all colistin-resistant bacteria. This review aims to summarize the current clinical microbiology diagnosis techniques and their ability to detect all colistin resistance mechanisms and describe new tools specifically developed to assess plasmid-mediated colistin resistance. Phenotyping, susceptibility testing, and genotyping methods are presented, including an update on recent studies related to the development of specific techniques.201830631384
4849120.9991Active site loops of membrane-anchored metallo-β-lactamases from environmental bacteria determine cephalosporinase activity. Antimicrobial resistance is a significant global public health threat that limits treatment options for bacterial infections. This situation is aggravated by the environmental spread of β-lactamase genes. In particular, metallo-β-lactamases (MBLs) hydrolyze almost all available β-lactam antibiotics, including late-generation cephalosporins and carbapenems. Among MBLs, the New Delhi metallo-β-lactamase (NDM-1) of subclass B1 has shown the most ominous dissemination. NDM variants are the only MBLs of clinical importance that are membrane-anchored, a sub-cellular localization that endows them with high stability under conditions of metal limitation. However, antibiotic resistance predates modern antibiotic usage, and environmental bacteria serve as reservoirs for resistance genes. Here, we report the biochemical and structural characterization of two membrane-bound MBLs: CJO-1 and CIM-2, from Chryseobacterium joostei and Chryseobacterium indologenes, respectively. Both MBLs confer β-lactam resistance on producer bacterial strains and hydrolyze several antibiotics, although with impaired efficiency compared to NDM-1. Crystal structures reveal differences, compared to previously studied B1 MBLs, in the active site loops and their dynamic properties that impact activity. Specifically, a hindered access to the active site with the contribution of a Tyr residue in loop L10 and the presence of a positively charged Lys residue in loop L3 limit hydrolysis of cephalosporins with charged C3 substituents. Some of these novel features are preserved in other MBLs from Chryseobacterium spp. These findings suggest that Chryseobacterium spp. could act as reservoirs of MBL genes, while informing on the diversity of structure-function relationships and dynamic behaviors within the B1 subclass of these enzymes.202540548716
4670130.9991Novel Antibiotic Resistance Genes Identified by Functional Gene Library Screening in Stenotrophomonas maltophilia and Chryseobacterium spp. Bacteria of Soil Origin. As one of the most diverse habitats of microorganisms, soil has been recognised as a reservoir of both antibiotics and the antibiotic resistance genes (ARGs). Bacteria naturally inhabiting soil or water often possess innate ARGs to counteract the chemical compounds produced by competitors living in the same environment. When such bacteria are able to cause infections in immunocompromised patients, their strong innate antibiotic resistance mechanisms make treatment difficult. We generated functional gene libraries using antibiotic-resistant Stenotrophomonas maltophilia and Chryseobacterium spp. bacteria isolated from agricultural soils in Lithuania to select for the genetic determinants responsible for their resistance. We were able to find novel variants of aminoglycoside and β-lactam resistance genes, with β-lactamases isolated from the Chryseobacterium spp. functional gene library, one of which is a variant of IND-like metallo-β-lactamase (MBL) IND-17 and the other of which is a previously uncharacterised MBL we named CHM (Chryseobacterium metallo β-lactamase). Our results indicate that soil microorganisms possess a diversity of ARG variants, which could potentially be transferred to the clinical setting.202337047008
5694140.9991Multiplex characterization of human pathogens including species and antibiotic-resistance gene identification. The efficient medical treatment of infections requires detailed information about the pathogens involved and potential antibiotic-resistance mechanisms. The dramatically increasing incidence of multidrug-resistant bacteria especially highlights the importance of sophisticated diagnostic tests enabling a fast patient-customized therapy. However, the current molecular detection methods are limited to either the detection of species or only a few antibiotic-resistance genes.In this work, we present a human pathogen characterization assay using a rRNA gene microarray identifying 75 species comprising bacteria and fungi. A statistical classifier was developed to facilitate the automated species identification. Additionally, the clinically most important β-lactamases were identified simultaneously in a 100-plex reaction using padlock probes and the same microarray. The specificity and sensitivity of the combined assay was determined using clinical isolates. The detection limit was 10(5) c.f.u. ml(-1), recovering 89 % of the detectable β-lactamase-encoding genes specifically. The total assay time was less than 7 hand the modular character of the antibiotic-resistance detection allows the easy integration of further genetic targets. In summary, we present a fast, highly specific and sensitive multiplex pathogen characterization assay.201626489938
4940150.9991Predicting Phenotypic Polymyxin Resistance in Klebsiella pneumoniae through Machine Learning Analysis of Genomic Data. Polymyxins are used as treatments of last resort for Gram-negative bacterial infections. Their increased use has led to concerns about emerging polymyxin resistance (PR). Phenotypic polymyxin susceptibility testing is resource intensive and difficult to perform accurately. The complex polygenic nature of PR and our incomplete understanding of its genetic basis make it difficult to predict PR using detection of resistance determinants. We therefore applied machine learning (ML) to whole-genome sequencing data from >600 Klebsiella pneumoniae clonal group 258 (CG258) genomes to predict phenotypic PR. Using a reference-based representation of genomic data with ML outperformed a rule-based approach that detected variants in known PR genes (area under receiver-operator curve [AUROC], 0.894 versus 0.791, P = 0.006). We noted modest increases in performance by using a bacterial genome-wide association study to filter relevant genomic features and by integrating clinical data in the form of prior polymyxin exposure. Conversely, reference-free representation of genomic data as k-mers was associated with decreased performance (AUROC, 0.692 versus 0.894, P = 0.015). When ML models were interpreted to extract genomic features, six of seven known PR genes were correctly identified by models without prior programming and several genes involved in stress responses and maintenance of the cell membrane were identified as potential novel determinants of PR. These findings are a proof of concept that whole-genome sequencing data can accurately predict PR in K. pneumoniae CG258 and may be applicable to other forms of complex antimicrobial resistance.IMPORTANCE Polymyxins are last-resort antibiotics used to treat highly resistant Gram-negative bacteria. There are increasing reports of polymyxin resistance emerging, raising concerns of a postantibiotic era. Polymyxin resistance is therefore a significant public health threat, but current phenotypic methods for detection are difficult and time-consuming to perform. There have been increasing efforts to use whole-genome sequencing for detection of antibiotic resistance, but this has been difficult to apply to polymyxin resistance because of its complex polygenic nature. The significance of our research is that we successfully applied machine learning methods to predict polymyxin resistance in Klebsiella pneumoniae clonal group 258, a common health care-associated and multidrug-resistant pathogen. Our findings highlight that machine learning can be successfully applied even in complex forms of antibiotic resistance and represent a significant contribution to the literature that could be used to predict resistance in other bacteria and to other antibiotics.202032457240
5837160.9991The secondary resistome of multidrug-resistant Klebsiella pneumoniae. Klebsiella pneumoniae causes severe lung and bloodstream infections that are difficult to treat due to multidrug resistance. We hypothesized that antimicrobial resistance can be reversed by targeting chromosomal non-essential genes that are not responsible for acquired resistance but essential for resistant bacteria under therapeutic concentrations of antimicrobials. Conditional essentiality of individual genes to antimicrobial resistance was evaluated in an epidemic multidrug-resistant clone of K. pneumoniae (ST258). We constructed a high-density transposon mutant library of >430,000 unique Tn5 insertions and measured mutant depletion upon exposure to three clinically relevant antimicrobials (colistin, imipenem or ciprofloxacin) by Transposon Directed Insertion-site Sequencing (TraDIS). Using this high-throughput approach, we defined three sets of chromosomal non-essential genes essential for growth during exposure to colistin (n = 35), imipenem (n = 1) or ciprofloxacin (n = 1) in addition to known resistance determinants, collectively termed the "secondary resistome". As proof of principle, we demonstrated that inactivation of a non-essential gene not previously found linked to colistin resistance (dedA) restored colistin susceptibility by reducing the minimum inhibitory concentration from 8 to 0.5 μg/ml, 4-fold below the susceptibility breakpoint (S ≤ 2 μg/ml). This finding suggests that the secondary resistome is a potential target for developing antimicrobial "helper" drugs that restore the efficacy of existing antimicrobials.201728198411
5058170.9991Widespread Fosfomycin Resistance in Gram-Negative Bacteria Attributable to the Chromosomal fosA Gene. Fosfomycin is a decades-old antibiotic which is being revisited because of its perceived activity against many extensively drug-resistant Gram-negative pathogens. FosA proteins are Mn(2+) and K(+)-dependent glutathione S-transferases which confer fosfomycin resistance in Gram-negative bacteria by conjugation of glutathione to the antibiotic. Plasmid-borne fosA variants have been reported in fosfomycin-resistant Escherichia coli strains. However, the prevalence and distribution of fosA in other Gram-negative bacteria are not known. We systematically surveyed the presence of fosA in Gram-negative bacteria in over 18,000 published genomes from 18 Gram-negative species and investigated their contribution to fosfomycin resistance. We show that FosA homologues are present in the majority of genomes in some species (e.g., Klebsiella spp., Enterobacter spp., Serratia marcescens, and Pseudomonas aeruginosa), whereas they are largely absent in others (e.g., E. coli, Acinetobacter baumannii, and Burkholderia cepacia). FosA proteins in different bacterial pathogens are highly divergent, but key amino acid residues in the active site are conserved. Chromosomal fosA genes conferred high-level fosfomycin resistance when expressed in E. coli, and deletion of chromosomal fosA in S. marcescens eliminated fosfomycin resistance. Our results indicate that FosA is encoded by clinically relevant Gram-negative species and contributes to intrinsic fosfomycin resistance.IMPORTANCE There is a critical need to identify alternate approaches to treat infections caused by extensively drug-resistant (XDR) Gram-negative bacteria. Fosfomycin is an old antibiotic which is routinely used for the treatment of urinary tract infections, although there is substantial interest in expanding its use to systemic infections caused by XDR Gram-negative bacteria. In this study, we show that fosA genes, which encode dimeric Mn(2+)- and K(+)-dependent glutathione S-transferase, are widely distributed in the genomes of Gram-negative bacteria-particularly those belonging to the family Enterobacteriaceae-and confer fosfomycin resistance. This finding suggests that chromosomally located fosA genes represent a vast reservoir of fosfomycin resistance determinants that may be transferred to E. coli Furthermore, they suggest that inhibition of FosA activity may provide a viable strategy to potentiate the activity of fosfomycin against XDR Gram-negative bacteria.201728851843
4929180.9991Comparative genomics analysis of Acinetobacter baumannii multi-drug resistant and drug sensitive strains in China. The incidence of multidrug-resistant Acinetobacter baumannii has posed a major challenge for clinical treatment. There is still a significant gap in understanding the mechanism causing multi-drug resistance (MDR). In this study, the genomes of 10 drug sensitive and 10 multi-drug resistant A.baumannii strains isolated from a hospital in China were sequenced and compared. The antibiotic resistance genes, virulence factors were determined and CRIPSR-Cas system along with prophages were detected. The results showed that MDR strains are significantly different from the drug sensitive strains in the CARD entries, patterns of sequences matching up to plasmids, VFDB entries and CRISPR-Cas system. MDR strains contain unique CARD items related to antibiotic resistance which are absent in sensitive strains. Furthermore, sequences from genomes of MDR strains can match up with plasmids from more diversified bacteria genera compared to drug sensitive strains. MDR strains also contain a lower level of CRISPR genes and larger amount of prophages, along with higher levels of spacer sequences. These findings provide new experimental evidences for the study of the antibiotic resistance mechanism of A. baumannii.202235307599
5059190.9991Site-selective modifications by lipid A phosphoethanolamine transferases linked to colistin resistance and bacterial fitness. Genes encoding lipid A modifying phosphoethanolamine transferases (PETs) are genetically diverse and can confer resistance to colistin and antimicrobial peptides. To better understand the functional diversity of PETs, we characterized three canonical mobile colistin resistance (mcr) alleles (mcr-1, -3, -9), one intrinsic pet (eptA), and two mcr-like genes (petB, petC) in Escherichia coli. Using an isogenic expression system, we show that mcr-1 and mcr-3 confer similar phenotypes of decreased colistin susceptibility with low fitness costs. mcr-9, which is phylogenetically closely related to mcr-3, and eptA only provide fitness advantages in the presence of sub-inhibitory concentrations of colistin and significantly reduce fitness in media without colistin. PET-B and PET-C were phenotypically distinct from bonafide PETs; neither impacted colistin susceptibility nor caused considerable fitness cost. Strikingly, we found for the first time that different PETs selectively modify different phosphates of lipid A; MCR-1, MCR-3, and PET-C selectively modify the 4'-phosphate, whereas MCR-9 and EptA modify the 1-phosphate. However, 4'-phosphate modifications facilitated by MCR-1 and -3 are associated with lowered colistin susceptibility and low toxicity. Our results suggest that PETs have a wide phenotypic diversity and that increased colistin resistance is associated with specific lipid A modification patterns that have been largely unexplored thus far. IMPORTANCE: Rising levels of resistance to increasing numbers of antimicrobials have led to the revival of last resort antibiotic colistin. Unfortunately, resistance to colistin is also spreading in the form of mcr genes, making it essential to (i) improve the identification of resistant bacteria to allow clinicians to prescribe effective drug regimens and (ii) develop new combination therapies effective at targeting resistant bacteria. Our results demonstrate that PETs, including MCR variants, are site-selective in Escherichia coli and that site-selectivity correlates with the level of susceptibility and fitness costs conferred by certain PETs. Site selectivity associated with a given PET may not only help predict colistin resistance phenotypes but may also provide an avenue to (i) improve drug regimens and (ii) develop new combination therapies to better combat colistin-resistant bacteria.202439611852