SSTAR, a Stand-Alone Easy-To-Use Antimicrobial Resistance Gene Predictor

First report of a bla NDM-producing extensively drug resistant Klebsiella pneumoniae ST437 in Italy

Carbapenemase-producing Klebsiella pneumoniae strains (CP-Kps) have recently been observed to spread rapidly worldwide. New Delhi metallo-β-lactamase (NDM) producing clones of Klebsiella pneumoniae (K. pneumoniae) cause a significant healthcare burden, particularly in Indian sub-continent, where this clone is circulating widely. However, in Italy, data on the incidence of these new clones is limited, and an ST437 NDM-producing K. pneumoniae strain has not been reported to date. A sacral ulcer infection caused by a K. pneumoniae strain was identified in an 85-year-old Italian male patient with several comorbidities. Antimicrobial susceptibility testing revealed an extensive resistance to a wide range of antimicrobials, including novel agents such as cefiderocol and ceftazidime/avibactam. Genomic analysis identified the pathogen as an ST437 K. pneumoniae strain harboring bla NDM-5, bla OXA-232 and bla CTX-M-15 genes. Following the identification of this first case, several infection control measures were implemented in healthcare settings, including direct precautions and reinforcement of standard cross-transmission control measures. The emergence of pathogenic microbial clones carrying new genetic determinants, particularly in a little city, requires prompt diagnosis and therapeutic protocols. An effective infection control system for the early detection and/or control of the transmission of NDM-producing Enterobacteriaceae is also needed. Further investigations are required to better understand the potential transmission routes and evolution of these clones.

The Pseudomonas aeruginosa Resistome: Permanent and Transient Antibiotic Resistance, an Overview

One of the most concerning characteristics of Pseudomonas aeruginosa is its low susceptibility to several antibiotics of common use in clinics, as well as its facility to acquire increased resistance levels. Consequently, the study of the antibiotic resistance mechanisms of this bacterium is of relevance for human health. For such a study, different types of resistance should be distinguished. The intrinsic resistome is composed of a set of genes, present in the core genome of P. aeruginosa, which contributes to its characteristic, species-specific, phenotype of susceptibility to antibiotics. Acquired resistance refers to those genetic events, such as the acquisition of mutations or antibiotic resistance genes that reduce antibiotic susceptibility. Finally, antibiotic resistance can be transiently acquired in the presence of specific compounds or under some growing conditions. The current article provides information on methods currently used to analyze intrinsic, mutation-driven, and transient antibiotic resistance in P. aeruginosa.

A Comprehensive Bioinformatics Resource Guide for Genome-Based Antimicrobial Resistance Studies

The use of high-throughput sequencing technologies and bioinformatic tools has greatly transformed microbial genome research. With the help of sophisticated computational tools, it has become easier to perform whole genome assembly, identify and compare different species based on their genomes, and predict the presence of genes responsible for proteins, antimicrobial resistance, and toxins. These bioinformatics resources are likely to continuously improve in quality, become more user-friendly to analyze the multiple genomic data, efficient in generating information and translating it into meaningful knowledge, and enhance our understanding of the genetic mechanism of AMR. In this manuscript, we provide an essential guide for selecting the popular resources for microbial research, such as genome assembly and annotation, antibiotic resistance gene profiling, identification of virulence factors, and drug interaction studies. In addition, we discuss the best practices in computer-oriented microbial genome research, emerging trends in microbial genomic data analysis, integration of multi-omics data, the appropriate use of machine-learning algorithms, and open-source bioinformatics resources for genome data analytics.

The challenges of the genome-based identification of antifungal resistance in the clinical routine

The increasing number of chronic and life-threatening infections caused by antimicrobial resistant fungal isolates is of critical concern. Low DNA sequencing cost may facilitate the identification of the genomic profile leading to resistance, the resistome, to rationally optimize the design of antifungal therapies. However, compared to bacteria, initiatives for resistome detection in eukaryotic pathogens are underdeveloped. Firstly, reported mutations in antifungal targets leading to reduced susceptibility must be extensively collected from the literature to generate comprehensive databases. This information should be complemented with specific laboratory screenings to detect the highest number possible of relevant genetic changes in primary targets and associations between resistance and other genomic markers. Strikingly, some drug resistant strains experience high-level genetic changes such as ploidy variation as much as duplications and reorganizations of specific chromosomes. Such variations involve allelic dominance, gene dosage increments and target expression regime effects that should be explicitly parameterized in antifungal resistome prediction algorithms. Clinical data indicate that predictors need to consider the precise pathogen species and drug levels of detail, instead of just genus and drug class. The concomitant needs for mutation accuracy and assembly quality assurance suggest hybrid sequencing approaches involving third-generation methods will be utilized. Moreover, fatal fast infections, like fungemia and meningitis, will further require both sequencing and analysis facilities are available in-house. Altogether, the complex nature of antifungal resistance demands extensive sequencing, data acquisition and processing, bioinformatic analysis pipelines, and standard protocols to be accomplished prior to genome-based protocols are applied in the clinical setting.

Detection of Acquired Antibiotic Resistance Genes in Domestic Pig (Sus scrofa) and Common Carp (Cyprinus carpio) Intestinal Samples by Metagenomics Analyses in Hungary

The aim of this study was metagenomics analyses of acquired antibiotic-resistance genes (ARGs) in the intestinal microbiome of two important food-animal species in Hungary from a One Health perspective. Intestinal content samples were collected from 12 domestic pigs (Sus scrofa) and from a common carp (Cyprinus carpio). Shotgun metagenomic sequencing of DNA purified from the intestinal samples was performed on the Illumina platform. The ResFinder database was applied for detecting acquired ARGs in the assembled metagenomic contigs. Altogether, 59 acquired ARG types were identified, 51 genes from domestic pig and 12 genes from the carp intestinal microbiome. ARG types belonged to the antibiotic classes aminoglycosides (27.1%), tetracyclines (25.4%), β-lactams (16.9%), and others. Of the identified ARGs, tet(E), a bla_OXA-_48-like β-lactamase gene, as well as cphA4, ampS, aadA2, qnrS2, and sul1, were identified only in carp but not in swine samples. Several of the detected acquired ARGs have not yet been described from food animals in Hungary. The tet(Q), tet(W), tet(O), and mef(A) genes detected in the intestinal microbiome of domestic pigs had also been identified from free-living wild boars in Hungary, suggesting a possible relationship between the occurrence of acquired ARGs in domestic and wild animal populations.

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

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

Review and Comparison of Antimicrobial Resistance Gene Databases

As the prevalence of antimicrobial resistance genes is increasing in microbes, we are facing the return of the pre-antibiotic era. Consecutively, the number of studies concerning antibiotic resistance and its spread in the environment is rapidly growing. Next generation sequencing technologies are widespread used in many areas of biological research and antibiotic resistance is no exception. For the rapid annotation of whole genome sequencing and metagenomic results considering antibiotic resistance, several tools and data resources were developed. These databases, however, can differ fundamentally in the number and type of genes and resistance determinants they comprise. Furthermore, the annotation structure and metadata stored in these resources can also contribute to their differences. Several previous reviews were published on the tools and databases of resistance gene annotation; however, to our knowledge, no previous review focused solely and in depth on the differences in the databases. In this review, we compare the most well-known and widely used antibiotic resistance gene databases based on their structure and content. We believe that this knowledge is fundamental for selecting the most appropriate database for a research question and for the development of new tools and resources of resistance gene annotation.

GAMMA: a tool for the rapid identification, classification and annotation of translated gene matches from sequencing data

MOTIVATION

Tools used to identify genes in microbial sequences using a reference database generally report matches as a percent identity, which can be difficult to interpret in cases with <100% sequence identity, as changes to specific amino acids can have dramatic effects on protein function, such as when they occur in substrate binding regions or enzyme active sites, which in turn can have dramatic effects on phenotypes like antimicrobial resistance or virulence.

RESULTS

Here, we present GAMMA, an open-source tool for Gene Allele Mutation Microbial Assessment, which uses protein coding-level identity to make gene calls from any gene database and generates a classification (e.g. mutant, truncation) and translated annotation (e.g. Y190S mutation, truncation at residue 110) for these calls. GAMMA accurately called antimicrobial resistance genes from a large set of genomes faster than three other tools. It can also be used with any gene database, as we demonstrated by identifying virulence genes in the same genome set. Because of its speed and flexibility, GAMMA can be used to rapidly find and annotate any gene matches of interest in microbial sequencing data.

AVAILABILITY AND IMPLEMENTATION

GAMMA is freely available as a Bioconda package (https://bioconda.github.io/recipes/gamma/README.html) and as a command line script (https://github.com/rastanton/GAMMA).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.

Multispecies Outbreak of Verona Integron-Encoded Metallo-ß-Lactamase-Producing Multidrug Resistant Bacteria Driven by a Promiscuous Incompatibility Group A/C2 Plasmid

BACKGROUND

Antibiotic resistance is often spread through bacterial populations via conjugative plasmids. However, plasmid transfer is not well recognized in clinical settings because of technical limitations, and health care-associated infections are usually caused by clonal transmission of a single pathogen. In 2015, multiple species of carbapenem-resistant Enterobacteriaceae (CRE), all producing a rare carbapenemase, were identified among patients in an intensive care unit. This observation suggested a large, previously unrecognized plasmid transmission chain and prompted our investigation.

METHODS

Electronic medical record reviews, infection control observations, and environmental sampling completed the epidemiologic outbreak investigation. A laboratory analysis, conducted on patient and environmental isolates, included long-read whole-genome sequencing to fully elucidate plasmid DNA structures. Bioinformatics analyses were applied to infer plasmid transmission chains and results were subsequently confirmed using plasmid conjugation experiments.

RESULTS

We identified 14 Verona integron-encoded metallo-ß-lactamase (VIM)-producing CRE in 12 patients, and 1 additional isolate was obtained from a patient room sink drain. Whole-genome sequencing identified the horizontal transfer of blaVIM-1, a rare carbapenem resistance mechanism in the United States, via a promiscuous incompatibility group A/C2 plasmid that spread among 5 bacterial species isolated from patients and the environment.

CONCLUSIONS

This investigation represents the largest known outbreak of VIM-producing CRE in the United States to date, which comprises numerous bacterial species and strains. We present evidence of in-hospital plasmid transmission, as well as environmental contamination. Our findings demonstrate the potential for 2 types of hospital-acquired infection outbreaks: those due to clonal expansion and those due to the spread of conjugative plasmids encoding antibiotic resistance across species.

Antibiotic resistance: Global health crisis and metagenomics

Antibiotic resistance is a global problem which affects human health. The imprudent use of antibiotics (medicine, agriculture, aquaculture, and food industry) has resulted in the broader dissemination of resistance. Urban wastewater & sewage treatment plants act as the hotspot for the widespread of antimicrobial resistance. Natural environment also plays an important role in the dissemination of resistance. Mapping of antibiotic resistance genes (ARGS) in environment is essential for mitigating antimicrobial resistance (AMR) widespread. Therefore, the review article emphasizes on the application of metagenomics for the surveillance of antimicrobial resistance. Metagenomics is the next generation tool which is being used for cataloging the resistome of diverse environments. We summarize the different metagenomic tools that can be used for mining of ARGs and acquired AMR present in the metagenomic data. Also, we recommend application of targeted sequencing/ capture platform for mapping of resistome with higher specificity and selectivity.

Evaluating the emergence of nonsusceptibility among Pseudomonas aeruginosa respiratory isolates from a phase-3 clinical trial for treatment of nosocomial pneumonia (ASPECT-NP)

OBJECTIVES

The emergence of nonsusceptibility to ceftolozane/tazobactam and meropenem was evaluated among Pseudomonas aeruginosa (P. aeruginosa) lower respiratory tract isolates obtained from participants in the ASPECT-NP clinical trial.

METHODS

ASPECT-NP was a phase-3, randomised, double-blind, multicentre trial that demonstrated noninferiority of 3 g ceftolozane/tazobactam q8h versus 1 g meropenem q8h for treatment of ventilated hospital-acquired/ventilator-associated bacterial pneumonia. Molecular resistance mechanisms among postbaseline nonsusceptible P. aeruginosa isolates and clinical outcomes associated with participants with emergence of nonsusceptibility were examined. Baseline susceptible and postbaseline nonsusceptible P. aeruginosa isolate pairs from the same participant underwent molecular typing.

RESULTS

Emergence of nonsusceptibility was not observed among the 59 participants with baseline susceptible P. aeruginosa isolates in the ceftolozane/tazobactam arm. Among 58 participants with baseline susceptible P. aeruginosa isolates in the meropenem arm, emergence of nonsusceptibility was observed in 13 (22.4%). Among participants who received ceftolozane/tazobactam and meropenem, 5.1% and 3.4% had a new infection with a nonsusceptible strain, respectively. None of the isolates with emergence of nonsusceptibility to meropenem developed co-resistance to ceftolozane/tazobactam. The molecular mechanisms associated with emergence of nonsusceptibility to meropenem were decreased expression or loss of OprD and overexpression of MexXY.

CONCLUSIONS

Among participants with emergence of nonsusceptibility to meropenem, clinical outcomes were similar to overall clinical outcomes in the ASPECT-NP meropenem arm. Ceftolozane/tazobactam was more stable to emergence of nonsusceptibility versus meropenem; emergence of nonsusceptibility was not observed in any participants with baseline susceptible P. aeruginosa who received ceftolozane/tazobactam in ASPECT-NP.

Current Trends in Experimental and Computational Approaches to Combat Antimicrobial Resistance

A multitude of factors, such as drug misuse, lack of strong regulatory measures, improper sewage disposal, and low-quality medicine and medications, have been attributed to the emergence of drug resistant microbes. The emergence and outbreaks of multidrug resistance to last-line antibiotics has become quite common. This is further fueled by the slow rate of drug development and the lack of effective resistome surveillance systems. In this review, we provide insights into the recent advances made in computational approaches for the surveillance of antibiotic resistomes, as well as experimental formulation of combinatorial drugs. We explore the multiple roles of antibiotics in nature and the current status of combinatorial and adjuvant-based antibiotic treatments with nanoparticles, phytochemical, and other non-antibiotics based on synergetic effects. Furthermore, advancements in machine learning algorithms could also be applied to combat the spread of antibiotic resistance. Development of resistance to new antibiotics is quite rapid. Hence, we review the recent literature on discoveries of novel antibiotic resistant genes though shotgun and expression-based metagenomics. To decelerate the spread of antibiotic resistant genes, surveillance of the resistome is of utmost importance. Therefore, we discuss integrative applications of whole-genome sequencing and metagenomics together with machine learning models as a means for state-of-the-art surveillance of the antibiotic resistome. We further explore the interactions and negative effects between antibiotics and microbiomes upon drug administration.

The Clinical and Molecular Epidemiology of Noncarbapenemase-Producing Carbapenem-Resistant Enterobacteriaceae: A Case-Case-Control Matched Analysis

Background

Risk factors and outcomes associated with carbapenem-resistant Enterobacteriaceae (CRE) acquisitions are derived primarily from cohorts consisting of carbapenemase-producing (CP) strains. Worldwide epidemiology of non-CP-CRE is evolving, but controlled epidemiological analyses are lacking.

Methods

A matched case-case-control investigation was conducted at Shamir (Assaf Harofeh) Medical Center, Israel, on November 2014–December 2016. Noncarbapenemase-producing CRE (as defined by the US Clinical and Laboratory Standards Institute Standards) carriers were matched to patients with non-CRE Enterobacterales and to uninfected controls (1:1:1 ratio). Matched and nonmatched multivariable regression models were constructed to analyze predictors for acquisition and the independent impact of carriage on multiple outcomes, respectively. Representative isolates were whole genome sequenced and analyzed for resistome and phylogeny.

Results

Noncarbapenemase-producing CRE carriers (n = 109) were matched to the 2 comparative groups (overall n = 327). Recent exposure to antibiotics (but not specifically to carbapenems), prior intensive care unit admission, and chronic skin ulcers were all independent predictors for non-CP-CRE acquisition. Acquisitions were almost exclusively associated with asymptomatic carriage (n = 104), and despite strong associations per univariable analyses, none were independently associated with worse outcomes. Genomic analyses of 13 representative isolates revealed polyclonality, confirmed the absence of carbapenemases, but confirmed the coexistence of multiple other genes contributing to carbapenem-resistance phenotype (multiple beta-lactamases and efflux pumps).

Conclusions

Noncarbapenemase-producing CRE acquisitions are primarily associated with asymptomatic carriage, specifically among prone populations with extensive recent exposures to antibiotics. The prevalent mode of acquisition is “emergence of resistance” (not “patient-to-patient transmission”), and therefore the role of stewardship interventions in reducing the spread of these therapeutically challenging pathogens should be further explored.

PARGT: a software tool for predicting antimicrobial resistance in bacteria

With the ever-increasing availability of whole-genome sequences, machine-learning approaches can be used as an alternative to traditional alignment-based methods for identifying new antimicrobial-resistance genes. Such approaches are especially helpful when pathogens cannot be cultured in the lab. In previous work, we proposed a game-theory-based feature evaluation algorithm. When using the protein characteristics identified by this algorithm, called ‘features’ in machine learning, our model accurately identified antimicrobial resistance (AMR) genes in Gram-negative bacteria. Here we extend our study to Gram-positive bacteria showing that coupling game-theory-identified features with machine learning achieved classification accuracies between 87% and 90% for genes encoding resistance to the antibiotics bacitracin and vancomycin. Importantly, we present a standalone software tool that implements the game-theory algorithm and machine-learning model used in these studies.

Platforms for elucidating antibiotic resistance in single genomes and complex metagenomes

Antibiotic or antimicrobial resistance (AR) facilitated by the vertical and/or horizontal transfer of antibiotic resistance genes (ARGs), is a serious global health challenge. While traditionally associated with pathogens in clinical environments, it is becoming increasingly clear that non-clinical environments may also be reservoirs of ARGs. The recent improvements in rapid and affordable next generation sequencing technologies along with sophisticated bioinformatics platforms has the potential to revolutionize diagnostic microbiology and microbial surveillance. Through the study and characterization of ARGs in bacterial genomes and complex metagenomes, we are now able to reveal the genetic scope of AR in single bacteria and complex communities, and obtain important insights into AR dynamics at species, population and community levels, providing novel epidemiological and ecological perspectives. A suite of bioinformatics pipelines and ARG databases are currently available for genomic and metagenomic data analyses. However, different platforms may significantly vary and therefore, it is crucial to choose the tools that are most suitable for the specific analysis being conducted. This review provides a detailed account of available bioinformatics platforms for identification and characterization of ARGs and associated genetic elements within single bacterial isolates and complex environmental samples. It focuses primarily on currently available ARG databases, employing a comprehensive benchmarking pipeline to identify ARGs in four bacterial genomes (Aeromonas salmonicida, Bacillus cereus, Burkholderia sp. and Escherichia coli) and three shotgun metagenomes (human gut, poultry litter and soil) providing insight into which databases should be used for different analytical scenarios.

Rapid inference of antibiotic resistance and susceptibility by genomic neighbour typing

Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective empirical antibiotic therapy. However, traditional molecular epidemiology does not typically occur on a timescale that could affect patient treatment and outcomes. Here, we present a method called 'genomic neighbour typing' for inferring the phenotype of a bacterial sample by identifying its closest relatives in a database of genomes with metadata. We show that this technique can infer antibiotic susceptibility and resistance for both Streptococcus pneumoniae and Neisseria gonorrhoeae. We implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION data, can run in real time. This resulted in the determination of resistance within 10 min (91% sensitivity and 100% specificity for S. pneumoniae and 81% sensitivity and 100% specificity for N. gonorrhoeae from isolates with a representative database) of starting sequencing, and within 4 h of sample collection (75% sensitivity and 100% specificity for S. pneumoniae) for clinical metagenomic sputum samples. This flexible approach has wide application for pathogen surveillance and may be used to greatly accelerate appropriate empirical antibiotic treatment.

sraX: A Novel Comprehensive Resistome Analysis Tool

The accurate identification of the assortment of antibiotic resistance genes within a collection of genomes enables the discernment of intricate antimicrobial resistance (AMR) patterns while depicting the diversity of resistome profiles of the analyzed samples. The availability of large amount of sequence data, owing to the advancement of novel sequencing technologies, have conceded exciting possibilities for developing suitable AMR exploration tools. However, the level of complexity of bioinformatic analyses has raised as well, since the achievement of desired results involves executing several challenging steps. Here, sraX is proposed as a fully automated analytical pipeline for performing a precise resistome analysis. Our nominated tool is capable of scrutinizing hundreds of bacterial genomes in-parallel for detecting and annotating putative resistant determinants. Particularly, sraX presents unique features: genomic context analysis, validation of known mutations conferring resistance, illustration of drug classes and type of mutated loci proportions and integration of results into a single hyperlinked navigable HTML-formatted file. Furthermore, sraX also exhibits relevant operational features since the complete analysis is accomplished by executing a single-command step. The capacity and efficacy of sraX was demonstrated by re-analyzing 197 strains belonging to Enterococcus spp., from which we confirmed 99.15% of all detection events that were reported in the original study. sraX can be downloaded from https://github.com/lgpdevtools/srax.

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study

Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories.

Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe

Two billion people are infected with Mycobacterium tuberculosis, leading to 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, Mykrobe predictor, which provided offline species identification and drug resistance predictions for M. tuberculosis from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations.  Here we present a new tool, Mykrobe, which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. Mykrobe is released under MIT license at https://github.com/mykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 M. tuberculosis Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 M. tuberculosis isolates. Using culture based DST as the reference, we estimate Mykrobe to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rifampicin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) samples, and also show that Mykrobe gives concordant results with nanopore data.  We measure the ability of Mykrobe-based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools.

Multiple importations and transmission of colistin-resistant Klebsiella pneumoniae in a hospital in northern India

OBJECTIVE

Resistance to colistin, a last resort antibiotic, has emerged in India. We investigated colistin-resistant Klebsiella pneumoniae(ColR-KP) in a hospital in India to describe infections, characterize resistance of isolates, compare concordance of detection methods, and identify transmission events.

DESIGN

Retrospective observational study.

METHODS

Case-patients were defined as individuals from whom ColR-KP was isolated from a clinical specimen between January 2016 and October 2017. Isolates resistant to colistin by Vitek 2 were confirmed by broth microdilution (BMD). Isolates underwent colistin susceptibility testing by disk diffusion and whole-genome sequencing. Medical records were reviewed.

RESULTS

Of 846 K. pneumoniae isolates, 34 (4%) were colistin resistant. In total, 22 case-patients were identified. Most (90%) were male; their median age was 33 years. Half were transferred from another hospital; 45% died. Case-patients were admitted for a median of 14 days before detection of ColR-KP. Also, 7 case-patients (32%) received colistin before detection of ColR-KP. All isolates were resistant to carbapenems and susceptible to tigecycline. Isolates resistant to colistin by Vitek 2 were also resistant by BMD; 2 ColR-KP isolates were resistant by disk diffusion. Moreover, 8 multilocus sequence types were identified. Isolates were negative for mobile colistin resistance (mcr) genes. Based on sequencing analysis, in-hospital transmission may have occurred with 8 case-patients (38%).

CONCLUSIONS

Multiple infections caused by highly resistant, mcr-negative ColR-KP with substantial mortality were identified. Disk diffusion correlated poorly with Vitek 2 and BMD for detection of ColR-KP. Sequencing indicated multiple importation and in-hospital transmission events. Enhanced detection for ColR-KP may be warranted in India.

Using Genomics to Track Global Antimicrobial Resistance

The recent advancements in rapid and affordable DNA sequencing technologies have revolutionized diagnostic microbiology and microbial surveillance. The availability of bioinformatics tools and online accessible databases has been a prerequisite for this. We conducted a scientific literature review and here we present a description of examples of available tools and databases for antimicrobial resistance (AMR) detection and provide future perspectives and recommendations. At least 47 freely accessible bioinformatics resources for detection of AMR determinants in DNA or amino acid sequence data have been developed to date. These include, among others but not limited to, ARG-ANNOT, CARD, SRST2, MEGARes, Genefinder, ARIBA, KmerResistance, AMRFinder, and ResFinder. Bioinformatics resources differ for several parameters including type of accepted input data, presence/absence of software for search within a database of AMR determinants that can be specific to a tool or cloned from other resources, and for the search approach employed, which can be based on mapping or on alignment. As a consequence, each tool has strengths and limitations in sensitivity and specificity of detection of AMR determinants and in application, which for some of the tools have been highlighted in benchmarking exercises and scientific articles. The identified tools are either available at public genome data centers, from GitHub or can be run locally. NCBI and European Nucleotide Archive (ENA) provide possibilities for online submission of both sequencing and accompanying phenotypic antimicrobial susceptibility data, allowing for other researchers to further analyze data, and develop and test new tools. The advancement in whole genome sequencing and the application of online tools for real-time detection of AMR determinants are essential to identify control and prevention strategies to combat the increasing threat of AMR. Accessible tools and DNA sequence data are expanding, which will allow establishing global pathogen surveillance and AMR tracking based on genomics. There is however, a need for standardization of pipelines and databases as well as phenotypic predictions based on the data.

Evaluation of the Synergy of Ceftazidime-Avibactam in Combination with Meropenem, Amikacin, Aztreonam, Colistin, or Fosfomycin against Well-Characterized Multidrug-Resistant Klebsiella pneumoniae and Pseudomonas aeruginosa

Multidrug-resistant (MDR) Gram-negative organisms are a major health concern due to lack of effective therapy. Emergence of resistance to newer agents like ceftazidime-avibactam (CZA) further magnifies the problem. In this context, combination therapy of CZA with other antimicrobials may have potential in treating these pathogens. Unfortunately, there are limited data regarding these combinations. Therefore, the objective of this study was to evaluate CZA in combination with amikacin (AMK), aztreonam (AZT), colistin (COL), fosfomycin (FOS), and meropenem (MEM) against 21 carbapenem-resistant Klebsiella pneumoniae and 21 MDR Pseudomonas aeruginosa strains. The potential for synergy was evaluated via MIC combination evaluation and time-kill assays. All strains were further characterized by whole-genome sequencing, quantitative real-time PCR, and SDS-PAGE analysis to determine potential mechanisms of resistance. Compared to CZA alone, we observed a 4-fold decrease in CZA MICs for a majority of K. pneumoniae strains and at least a 2-fold decrease for most P. aeruginosa isolates in the majority of combinations tested. In both P. aeruginosa and K. pneumoniae strains, CZA in combination with AMK or AZT was synergistic (≥2.15-log10 CFU/ml decrease). CZA-MEM was effective against P. aeruginosa and CZA-FOS was effective against K. pneumoniae Time-kill analysis also revealed that the synergy of CZA with MEM or AZT may be due to the previously reported restoration of MEM or AZT activity against these organisms. Our findings show that CZA in combination with these antibiotics has potential for therapeutic options in difficult to treat pathogens. Further evaluation of these combinations is warranted.

Comparative Activities of Ceftazidime-Avibactam and Ceftolozane-Tazobactam against Enterobacteriaceae Isolates Producing Extended-Spectrum β-Lactamases from U.S. Hospitals

The activities of ceftazidime-avibactam, ceftolozane-tazobactam, and comparators were evaluated for 733 isolates displaying resistance to broad-spectrum cephalosporins and carrying extended-spectrum β-lactamase (ESBL) genes detected by whole-genome sequencing analysis. Isolates were collected during 2017 in U.S. hospitals. The ESBL producers were 486 Escherichia coli, 190 Klebsiella pneumoniae, and 42 Enterobacter cloacae isolates and isolates from 3 other species. The most common groups of ESBL-encoding genes were bla _CTX-M-15-like (n = 491 isolates) and bla _CTX-M-15 alone (n = 168) or plus bla _OXA-1 (n = 260), followed by bla _CTX-M-14-like (n = 162), which included bla _CTX-M-27 and bla _CTX-M-14 (104 and 51 isolates, respectively), and bla _SHV-12 and bla _SHV-7 (48 and 22 isolates, respectively). ESBL producers carried other β-lactamases, including 1 E. cloacae harboring bla _KPC-3 All ESBL-producing isolates were susceptible to ceftazidime-avibactam, and 90.2/83.9% (CLSI/EUCAST breakpoints) were susceptible to ceftolozane-tazobactam. Tigecycline (98.1/95.8% susceptible) and colistin (99.2%) were comparators that displayed the greatest activity against these isolates. Ceftolozane-tazobactam inhibited 91.4/83.9% of isolates carrying bla _CTX-M-15-like and 97.5/95.1% of isolates carrying bla _CTX-M-14-like, and its activity was more limited against the 91 isolates carrying bla _SHV (66.7/61.1% susceptible). Ceftolozane-tazobactam inhibited 95.5% of the E. coli isolates but only 83.0%, 64.3%, and 80.0% of K. pneumoniae, E. cloacae, and other species harboring ESBL-encoding genes (CLSI breakpoints), respectively. Outer membrane protein sequences for ceftolozane-tazobactam-nonsusceptible isolates did not exhibit significant differences compared to those in genetically related ceftolozane-tazobactam-susceptible isolates. Ceftazidime-avibactam was more active than other agents tested, including ceftolozane-tazobactam, and the activity of this combination was stable regardless of species or ESBL gene carried.

Sequencing-based methods and resources to study antimicrobial resistance

Antimicrobial resistance extracts high morbidity, mortality and economic costs yearly by rendering bacteria immune to antibiotics. Identifying and understanding antimicrobial resistance are imperative for clinical practice to treat resistant infections and for public health efforts to limit the spread of resistance. Technologies such as next-generation sequencing are expanding our abilities to detect and study antimicrobial resistance. This Review provides a detailed overview of antimicrobial resistance identification and characterization methods, from traditional antimicrobial susceptibility testing to recent deep-learning methods. We focus on sequencing-based resistance discovery and discuss tools and databases used in antimicrobial resistance studies.

Automated annotation of mobile antibiotic resistance in Gram-negative bacteria: the Multiple Antibiotic Resistance Annotator (MARA) and database

Background

Multiresistance in Gram-negative bacteria is often due to acquisition of several different antibiotic resistance genes, each associated with a different mobile genetic element, that tend to cluster together in complex conglomerations. Accurate, consistent annotation of resistance genes, the boundaries and fragments of mobile elements, and signatures of insertion, such as DR, facilitates comparative analysis of complex multiresistance regions and plasmids to better understand their evolution and how resistance genes spread.

Objectives

To extend the Repository of Antibiotic resistance Cassettes (RAC) web site, which includes a database of 'features', and the Attacca automatic DNA annotation system, to encompass additional resistance genes and all types of associated mobile elements.

Methods

Antibiotic resistance genes and mobile elements were added to RAC, from existing registries where possible. Attacca grammars were extended to accommodate the expanded database, to allow overlapping features to be annotated and to identify and annotate features such as composite transposons and DR.

Results

The Multiple Antibiotic Resistance Annotator (MARA) database includes antibiotic resistance genes and selected mobile elements from Gram-negative bacteria, distinguishing important variants. Sequences can be submitted to the MARA web site for annotation. A list of positions and orientations of annotated features, indicating those that are truncated, DR and potential composite transposons is provided for each sequence, as well as a diagram showing annotated features approximately to scale.

Conclusions

The MARA web site (http://mara.spokade.com) provides a comprehensive database for mobile antibiotic resistance in Gram-negative bacteria and accurately annotates resistance genes and associated mobile elements in submitted sequences to facilitate comparative analysis.

Whole Genome Sequencing of Extended Spectrum β-lactamase (ESBL)-producing Klebsiella pneumoniae Isolated from Hospitalized Patients in KwaZulu-Natal, South Africa

Extended spectrum β-lactamase (ESBL)-producing Klebsiella pneumoniae remain a critical clinical concern worldwide. The aim of this study was to characterize ESBL-producing K. pneumoniae detected within and between two hospitals in uMgungundlovu district, South Africa, using whole genome sequencing (WGS). An observational period prevalence study on antibiotic-resistant ESKAPE (i.e. Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp.) bacteria was carried out in hospitalized patients during a two-month period in 2017. Rectal swabs and clinical specimens were collected from patients hospitalized and were screened for ESBL-producing, Gram-negative ESKAPE bacteria using cefotaxime-containing MacConkey agar and ESBL combination disk tests. Nine confirmed ESBL-K. pneumoniae isolated from six patients and two hospitals were whole genome sequenced using an Illumina MiSeq platform. Genome sequences were screened for presence of integrons, insertion sequences, plasmid replicons, CRISPR regions, resistance genes and virulence genes using different software tools. Of the 159 resistant Gram-negative isolates collected, 31 (19.50%) were ESBL-producers, of which, nine (29.03%) were ESBL-K. pneumoniae. The nine K. pneumoniae isolates harboured several β-lactamase genes, including bla_CTX-M-15, bla_TEM-1b, bla_SHV-1, bla_OXA-1 concomitantly with many other resistance genes e.g. acc(6')-lb-cr, aadAI6, oqxA and oqxB that confer resistance to aminoglycosides and/or fluoroquinolones, respectively. Three replicon plasmid types were detected in both clinical and carriage isolates, namely ColRNAI, IncFIB(K), IncF(II). Sequence type ST152 was confirmed in two patients (one carriage isolate detected on admission and one isolate implicated in infection) in one hospital. In contrast, ST983 was confirmed in a clinical and a carriage isolate of two patients in two different hospitals. Our data indicate introduction of ESBL-producing K. pneumoniae isolates into hospitals from the community. We also found evidence of nosocomial transmission within a hospital and transmission between different hospitals. The Clustered Regularly Interspaced Palindromic Repeats (CRISPR)-associated cas3 genes were further detected in two of the nine ESBL-KP isolates. This study showed that both district and tertiary hospital in uMgungundlovu District were reservoirs for several resistance determinants and highlighted the necessity to efficiently and routinely screen patients, particularly those receiving extensive antibiotic treatment and long-term hospitalization stay. It also reinforced the importance of infection, prevention and control measures to reduce the dissemination of antibiotic resistance within the hospital referral system in this district.

How to discover new antibiotic resistance genes?

INTRODUCTION

Antibiotic resistance (AR) is a worldwide concern and the description of AR have been discovered mainly because of their implications in human medicine. Since the recent burden of whole-genome sequencing of microorganisms, the number of new AR genes (ARGs) have dramatically increased over the last decade. Areas covered: In this review, we will describe the different methods that could be used to characterize new ARGs using classic or innovative methods. First, we will focus on the biochemical methods, then we will develop on molecular methods, next-generation sequencing and bioinformatics approaches. The use of various methods, including cloning, mutagenesis, transposon mutagenesis, functional genomics, whole genome sequencing, metagenomic and functional metagenomics will be reviewed here, outlining the advantages and drawbacks of each method. Bioinformatics softwares used for resistome analysis and protein modeling will be also described. Expert opinion: Biological experiments and bioinformatics analysis are complementary. Nowadays, the ARGs described only account for the tip of the iceberg of all existing resistance mechanisms. The multiplication of the ecosystems studied allows us to find a large reservoir of AR mechanisms. Furthermore, the adaptation ability of bacteria facing new antibiotics promises a constant discovery of new AR mechanisms.

Application of Next-Generation Sequencing for Characterization of Surveillance and Clinical Trial Isolates: Analysis of the Distribution of β-lactamase Resistance Genes and Lineage Background in the United States

Background

Sequencing technologies and techniques have seen remarkable transformation and innovation that have significantly affected sequencing capability. Data analyses have replaced sequencing as the main challenge. This paper provides an overview on applying next-generation sequencing (NGS) and analysis and discusses the benefits and challenges. In addition, this document shows results from using NGS and bioinformatics tools to screen for β-lactamase genes and assess the epidemiological structure of Escherichia coli– and Klebsiella pneumoniae–causing bloodstream (BSIs) and urinary tract (UTIs) infections in patients hospitalized in the United States during the SENTRY Antimicrobial Surveillance Program for 2016.

Methods

A total of 3525 isolates (2751 E. coli and 774 K. pneumoniae) causing BSIs (n = 892) and UTIs (n = 2633) in hospitalized patients in the United States were included. Isolates were tested for susceptibility by broth microdilution, and those that met a minimum inhibitory concentration (MIC)–based screening criteria had their genomes sequenced and analyzed.

Results

A total of 11.6% and 16.1% of E. coli–causing UTIs and BSIs, respectively, met the MIC-based criteria, whereas 11.0% and 13.7% of K. pneumoniae isolates causing UTIs and BSIs, respectively, met the criteria. Among E. coli, bla_CTX-M variants (87.6% overall) prevailed (60.5% of CTX-M group 1 and 26.9% of group 9). A total of 60.3% of K. pneumoniae isolates carried bla_CTX-M variants (52.7% and 7.6% of groups 1 and 9, respectively). Two E. coli (0.6%) and 13 K. pneumoniae (12.9%) isolates harbored bla_KPC. Among KPC-producing K. pneumoniae (2 from BSIs and 11 from UTIs), 84.6% (11/13) were ST258 (CC258). Seventeen and 38 unique clonal complexes (CCs) were noted in E. coli that caused BSIs and UTIs, respectively, and CC131 (or ST131) was the most common CC among BSI (53.6%) and UTI (58.2%) isolates. Twenty-three and 26 CCs were noted among K. pneumoniae–causing BSIs and UTIs, respectively. CC258 (28.3%) prevailed in UTI pathogens, whereas CC307 (15.0%) was the most common CC among BSI isolates.

Conclusions

This study provides a benchmark for the distribution of β-lactamase genes and the population structure information for the most common Enterobacteriaceae species responsible for BSIs and UTIs in US medical centers during the 2016 SENTRY Program.

Genome-Based Prediction of Bacterial Antibiotic Resistance

Clinical microbiology has long relied on growing bacteria in culture to determine antimicrobial susceptibility profiles, but the use of whole-genome sequencing for antibiotic susceptibility testing (WGS-AST) is now a powerful alternative. This review discusses the technologies that made this possible and presents results from recent studies to predict resistance based on genome sequences. We examine differences between calling antibiotic resistance profiles by the simple presence or absence of previously known genes and single-nucleotide polymorphisms (SNPs) against approaches that deploy machine learning and statistical models. Often, the limitations to genome-based prediction arise from limitations of accuracy of culture-based AST in addition to an incomplete knowledge of the genetic basis of resistance. However, we need to maintain phenotypic testing even as genome-based prediction becomes more widespread to ensure that the results do not diverge over time. We argue that standardization of WGS-AST by challenge with consistently phenotyped strain sets of defined genetic diversity is necessary to compare the efficacy of methods of prediction of antibiotic resistance based on genome sequences.

Emergence of Colistin Resistance Gene mcr-8 and Its Variant in Raoultella ornithinolytica

Recently, a novel mobile colistin resistance gene, mcr-8, was identified in Klebsiella pneumoniae. Here, we report the identification of mcr-8 and its variant, mcr-8.4, in Raoultella ornithinolytica isolates which also belong to Enterobacteriaceae family. The mcr-8 gene was located on transferrable plasmids with difference sizes. Notably, the transferability of mcr-8-carrying plasmids was enhanced once they entered into Escherichia coli hosts and multiple β-lactamase genes could co-transfer with mcr-8. These findings expand our knowledge of mcr-8-carrying bacterial species.

Phenotypic and Genotypic Characterization of Enterobacteriaceae Producing Oxacillinase-48-Like Carbapenemases, United States

Oxacillinase (OXA)-48-like carbapenemases remain relatively uncommon in the United States. We performed phenotypic and genotypic characterization of 30 Enterobacteriaceae producing OXA-48-like carbapenemases that were recovered from patients during 2010-2014. Isolates were collected from 12 states and not associated with outbreaks, although we could not exclude limited local transmission. The alleles β-lactamase OXA-181 (bla_OXA-181) (43%), bla_OXA-232 (33%), and bla_OXA-48 (23%) were found. All isolates were resistant to ertapenem and showed positive results for the ertapenem and meropenem modified Hodge test and the modified carbapenem inactivation method; 73% showed a positive result for the Carba Nordmann-Poirel test. Whole-genome sequencing identified extended-spectrum β-lactamase genes in 93% of isolates. In all bla_OXA-232 isolates, the gene was on a ColKP3 plasmid. A total of 12 of 13 isolates harboring bla_OXA-181 contained the insertion sequence ΔISEcp1. In all isolates with bla_OXA-48, the gene was located on a TN1999 transposon; these isolates also carried IncL/M plasmids.

Exploring bacterial resistome and resistance dessemination: an approach of whole genome sequencing

For several decades antibiotics are used to combat against pathogenic bacteria, but their misuse and overuse have caused the emergence of resistant bacteria. The scarcities of effective antibiotics along with unavailability of alternative solutions have exacerbated bacterial infections and mortality rate. This review provides the concept of bacterial resistome and mechanisms of resistance. It has also described the utility of whole genome sequencing in identifying resistance and its dissemination in association with available bioinformatics tools and databases. Moreover, the whole genome sequencing methodology described in this review will help to select effective antibiotics, maintain unparalleled surveillance of resistance and provide early diagnosis during resistance outbreaks. The provided information could be used to control infection caused by resistant microorganisms.

Exploring Foodborne Pathogen Ecology and Antimicrobial Resistance in the Light of Shotgun Metagenomics

In this chapter, applications of shotgun metagenomics for taxonomic profiling and functional investigation of food microbial communities with a focus on antimicrobial resistance (AMR) were overviewed in the light of last data in the field. Potentialities of metagenomic approach, along with the challenges encountered for a wider and routinely use in food safety was discussed.

From Theory to Practice: Translating Whole-Genome Sequencing (WGS) into the Clinic

Hospitals worldwide are facing an increasing incidence of hard-to-treat infections. Limiting infections and providing patients with optimal drug regimens require timely strain identification as well as virulence and drug-resistance profiling. Additionally, prophylactic interventions based on the identification of environmental sources of recurrent infections (e.g., contaminated sinks) and reconstruction of transmission chains (i.e., who infected whom) could help to reduce the incidence of nosocomial infections. WGS could hold the key to solving these issues. However, uptake in the clinic has been slow. Some major scientific and logistical challenges need to be solved before WGS fulfils its potential in clinical microbial diagnostics. In this review we identify major bottlenecks that need to be resolved for WGS to routinely inform clinical intervention and discuss possible solutions.

Comprehensive antibiotic-linked mutation assessment by resistance mutation sequencing (RM-seq)

Mutation acquisition is a major mechanism of bacterial antibiotic resistance that remains insufficiently characterised. Here we present RM-seq, a new amplicon-based deep sequencing workflow based on a molecular barcoding technique adapted from Low Error Amplicon sequencing (LEA-seq). RM-seq allows detection and functional assessment of mutational resistance at high throughput from mixed bacterial populations. The sensitive detection of very low-frequency resistant sub-populations permits characterisation of antibiotic-linked mutational repertoires in vitro and detection of rare resistant populations during infections. Accurate quantification of resistance mutations enables phenotypic screening of mutations conferring pleiotropic phenotypes such as in vivo persistence, collateral sensitivity or cross-resistance. RM-seq will facilitate comprehensive detection, characterisation and surveillance of resistant bacterial populations ( https://github.com/rguerillot/RM-seq ).

Emergence of the colistin resistance gene mcr-1 and its variant in several uncommon species of Enterobacteriaceae from commercial poultry farm surrounding environments

The colistin resistance gene mcr-1 has been detected in multiple members of Enterobacteriaceae family. Here, we report the emergence of mcr-1 in Providencia alcalifaciens and a mcr-1 variant, named mcr-1.3, in Raoultella planticola. Both of the mcr-1-carrying plasmids in these two isolates belong to IncI2 type of plasmids, but they are different in sizes and genetic characteristics. We also detected the mcr-1 gene in one Enterobacter cloacae isolate, however, the mcr-1-carrying plasmid is distinct from the previous reports. Conjugation assay showed that mcr-1-carrying plasmids in P. alcalifaciens and E. cloacae were successfully transferred into recipient E. coli strains. It is worth noting that the transferability of mcr-1-carrying plasmid from E. cloacae was enhanced once it entered into E. coli hosts, which might further accelerate the dissemination of mcr-1 among Enterobacteriaceae. These findings further expand our knowledge of the mcr-1-carrying species in Enterobacteriaceae.

Genomic Analysis of a Pan-Resistant Isolate of Klebsiella pneumoniae, United States 2016

Antimicrobial resistance is a threat to public health globally and leads to an estimated 23,000 deaths annually in the United States alone. Here, we report the genomic characterization of an unusual Klebsiella pneumoniae, nonsusceptible to all 26 antibiotics tested, that was isolated from a U.S. patient. The isolate harbored four known beta-lactamase genes, including plasmid-mediated bla_NDM-1 and bla_CMY-6, as well as chromosomal bla_CTX-M-15 and bla_SHV-28, which accounted for resistance to all beta-lactams tested. In addition, sequence analysis identified mechanisms that could explain all other reported nonsusceptibility results, including nonsusceptibility to colistin, tigecycline, and chloramphenicol. Two plasmids, IncA/C2 and IncFIB, were closely related to mobile elements described previously and isolated from Gram-negative bacteria from China, Nepal, India, the United States, and Kenya, suggesting possible origins of the isolate and plasmids. This is one of the first K. pneumoniae isolates in the United States to have been reported to the Centers for Disease Control and Prevention (CDC) as nonsusceptible to all drugs tested, including all beta-lactams, colistin, and tigecycline.

Antimicrobial resistance is a major public health threat worldwide. Bacteria that are nonsusceptible or resistant to all antimicrobials available are of major concern to patients and the public because of lack of treatment options and potential for spread. A Klebsiella pneumoniae strain that was nonsusceptible to all tested antibiotics was isolated from a U.S. patient. Mechanisms that could explain all observed phenotypic antimicrobial resistance phenotypes, including resistance to colistin and beta-lactams, were identified through whole-genome sequencing. The large variety of resistance determinants identified demonstrates the usefulness of whole-genome sequencing for detecting these genes in an outbreak response. Sequencing of isolates with rare and unusual phenotypes can provide information on how these extremely resistant isolates develop, including whether resistance is acquired on mobile elements or accumulated through chromosomal mutations. Moreover, this provides further insight into not only detecting these highly resistant organisms but also preventing their spread.

Antibiotic resistant pathogen outbreak investigation: an interdisciplinary module to teach fundamentals of evolutionary biology

The evolution of resistance to antibiotics provides a timely and relevant topic for teaching undergraduate students evolutionary biology. Here, we present a module incorporating modified sequencing data from eight antibiotic resistant pathogen outbreaks in hospital settings with bioinformatics and phylogenetic analyses. This module uses whole genome sequencing data from hospital outbreaks investigated by the Centers for Disease Control and Prevention to provide examples of antibiotic resistance spread. Students work in groups to analyze outbreak data to identify the bacterial species and antibiotic resistance genes, to infer a phylogenetic tree examining relatedness among isolates, and to determine a possible source of the outbreak. Students then compile their results in individual reports and provide recommendations for preventing the further spread of antibiotic resistant organisms. In addition to providing genomic outbreak data, we include a teaching concepts guide discussing three integral components of the module: how evolutionary biology concepts of natural selection and competition impact antibiotic resistance; outbreak investigation information to aid in phylogenetic analysis and creation of recommendations; and instructions for the bioinformatics protocol. Completion of this module provides students an opportunity to think critically about the evolution of resistance, practice bioinformatics techniques, and relate evolutionary biology to current events.

ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads

Antimicrobial resistance (AMR) is one of the major threats to human and animal health worldwide, yet few high-throughput tools exist to analyse and predict the resistance of a bacterial isolate from sequencing data. Here we present a new tool, ARIBA, that identifies AMR-associated genes and single nucleotide polymorphisms directly from short reads, and generates detailed and customizable output. The accuracy and advantages of ARIBA over other tools are demonstrated on three datasets from Gram-positive and Gram-negative bacteria, with ARIBA outperforming existing methods.

Whole-Genome Sequences of Two Carbapenem-Resistant Klebsiella quasipneumoniae Strains Isolated from a Tertiary Hospital in Johor, Malaysia

We report the whole-genome sequences of two carbapenem-resistant clinical isolates of Klebsiella quasipneumoniae subsp. similipneumoniae obtained from two different patients. Both strains contained three different extended-spectrum β-lactamase genes and showed strikingly high pairwise average nucleotide identity of 99.99% despite being isolated 3 years apart from the same hospital.

Multicenter Performance Assessment of Carba NP Test

Eighty Gram-negative bacilli (54 Enterobacteriaceae and 26 nonfermenting Gram-negative bacilli) obtained from multiple institutions in the United States were distributed in a blinded manner to seven testing laboratories to compare their performance of a test for detection of carbapenemase production, the Carba NP test. The Carba NP test was performed by all laboratories, following the Clinical and Laboratory Standards Institute (CLSI) procedure. Site-versus-site comparisons demonstrated a high level of consistency for the Carba NP assay, with just 3/21 site comparisons yielding a difference in sensitivity (P < 0.05). Previously described limitations with bla_OXA-48-like carbapenemases and bla_OXA carbapenemases associated with Acinetobacter baumannii were noted. Based on these data, we demonstrate that the Carba NP test, when implemented with the standardized CLSI methodology, provides reproducible results across multiple sites for detection of carbapenemases.

Modified Carbapenem Inactivation Method for Phenotypic Detection of Carbapenemase Production among Enterobacteriaceae

The ability of clinical microbiology laboratories to reliably detect carbapenemase-producing carbapenem-resistant Enterobacteriaceae (CP-CRE) is an important element of the effort to prevent and contain the spread of these pathogens and an integral part of antimicrobial stewardship. All existing methods have limitations. A new, straightforward, inexpensive, and specific phenotypic method for the detection of carbapenemase production, the carbapenem inactivation method (CIM), was recently described. Here we describe a two-stage evaluation of a modified carbapenem inactivation method (mCIM), in which tryptic soy broth was substituted for water during the inactivation step and the length of this incubation was extended. A validation study was performed in a single clinical laboratory to determine the accuracy of the mCIM, followed by a nine-laboratory study to verify the reproducibility of these results and define the zone size cutoff that best discriminated between CP-CRE and members of the family Enterobacteriaceae that do not produce carbapenemases. Bacterial isolates previously characterized through whole-genome sequencing or targeted PCR as to the presence or absence of carbapenemase genes were tested for carbapenemase production using the mCIM; isolates with Ambler class A, B, and D carbapenemases, non-CP-CRE isolates, and carbapenem-susceptible isolates were included. The sensitivity of the mCIM observed in the validation study was 99% (95% confidence interval [95% CI], 93% to 100%), and the specificity was 100% (95% CI, 82% to 100%). In the second stage of the study, the range of sensitivities observed across nine laboratories was 93% to 100%, with a mean of 97%; the range of specificities was 97% to 100%, with a mean of 99%. The mCIM was easy to perform and interpret for Enterobacteriaceae, with results in less than 24 h and excellent reproducibility across laboratories.

Low Frequency of Ceftazidime-Avibactam Resistance among Enterobacteriaceae Isolates Carrying blaKPC Collected in U.S. Hospitals from 2012 to 2015

Klebsiella pneumoniae carbapenemase (KPC)-producing Enterobacteriaceae isolates have been increasingly reported worldwide, and therapeutic options to treat infections caused by these organisms are limited. We evaluated the activity of ceftazidime-avibactam and comparators against 456 Enterobacteriaceae isolates carrying bla_KPC collected from 79 U.S. hospitals during 2012 to 2015. Overall, ceftazidime-avibactam (MIC_50/90, 0.5/2 μg/ml; 99.3% susceptible) and tigecycline (MIC_50/90, 0.5/1 μg/ml; 98.9% susceptible at ≤2 μg/ml) were the most active agents. Only 80.5% and 59.0% of isolates were susceptible to colistin and amikacin, respectively. All three isolates (0.7%) displaying resistance to ceftazidime-avibactam (K. pneumoniae; MICs, ≥16 μg/ml) were evaluated using whole-genome sequencing analysis and relative quantification of expression levels of porins and efflux pump. Two isolates carried metallo-β-lactamase genes, bla_NDM-1 or bla_VIM-4, among other β-lactam resistance mechanisms, and one displayed a premature stop codon in ompK35 and decreased expression of ompK36 Ceftazidime-avibactam was active against 100.0 and 99.3% of isolates carrying bla_KPC-3 (n = 221) and bla_KPC-2 (n = 145), respectively. Isolates carrying bla_KPC were more commonly recovered from pneumonia (n = 155), urinary tract (n = 93), and skin/soft tissue (n = 74) infections. Ceftazidime-avibactam (97.8 to 100.0% susceptible) was consistently active against isolates from all infection sites. K. pneumoniae (83.3% of the collection) susceptibility rates were 99.2% for ceftazidime-avibactam, 98.9% for tigecycline, and 80.1% for colistin. Ceftazidime-avibactam susceptibility did not vary substantially when comparing isolates from intensive care unit (ICU) patients to those from non-ICU patients. Ceftazidime-avibactam was active against this large collection of isolates carrying bla_KPC and represents a valuable addition to the armamentarium currently available for the treatment of infections caused by KPC-producing Enterobacteriaceae.

A Novel Rapidly Growing Mycobacterium Species Causing an Abdominal Cerebrospinal Fluid Pseudocyst Infection

Nontuberculous mycobacteria (NTM) are a rare cause of ventriculoperitoneal shunt infections. We describe the isolation and identification of a novel, rapidly growing, nonpigmented NTM from an abdominal cerebrospinal fluid pseudocyst. The patient presented with fevers, nausea, and abdominal pain and clinically improved after shunt removal. NTM identification was performed by amplicon and whole-genome sequencing.

Draft Genome Sequence of Mycobacterium wolinskyi, a Rapid-Growing Species of Nontuberculous Mycobacteria

Mycobacterium wolinskyi is a nonpigmented, rapidly growing nontuberculous mycobacterium species that is associated with bacteremia, peritonitis, infections associated with implants/prostheses, and skin and soft tissue infections often following surgical procedures in humans. Here, we report the first functionally annotated draft genome sequence of M. wolinskyi CDC_01.