Fluoroquinolone resistance in the environment and the human gut – Analysis of bacterial DNA sequences to explore the underlying genetic mechanisms

Fluoroquinolones (FQs) are synthetic, broad-spectrum antibiotics that target type II topoisomerases. High-level resistance is often caused by mutations in the target genes of FQs, especially in gyrA and parC. In contrast, plasmid-mediated resistance genes, such as qnr, often confer moderate levels of resistance. Several sites near Patancheru, India, have been previously shown to be severely contaminated with FQs. To study how environmental bacteria adapt to this extreme environment, we first used whole-genome sequencing (454) of a highly multi-drug resistant strain of Ochrobactrum intermedium. The strain was isolated from a wastewater treatment plant (WWTP) in Patancheru that treats industrial effluent from pharmaceutical production. The strain was considerably more resistant to tetracyclines, sulphonamides, and FQs than to other O. intermedium strains, and it had, accordingly, acquired a tetracycline efflux pump, a sulphonamide resistance gene, and mutations in the target genes for FQs. In the second study, sequencing (Illumina) was used to characterise horizontally transferrable resistance plasmids captured from bacterial communities sampled from a lake with a history of FQ pollution, near Patancheru. All transconjugants had acquired qnr genes and this is, to the best of our knowledge, the first time qnrVC1 has been described on a conjugative plasmid. Furthermore, the bacteria from the lake sediments were significantly more resistant to FQs and sulphonamides compared to bacteria from Indian and Swedish reference lakes. In the third study, the Escherichia communities inhabiting a stream in Patancheru receiving WWTP effluent with high levels of FQs were tested for resistance mutations in gyrA and parC using amplicon sequencing (454). A stream receiving municipal WWTP effluent in Sk\uf6vde, Sweden, and a remote highland lake were included as references. To our surprise, all communities showed high abundances of FQ resistance mutations, suggesting that these mutations are not associated with a fitness cost in the studied environments. The same method was utilised in the fourth study, on faecal samples collected from Swedish students before and after travel to India. The abundance of the amino acid substitution S83L in GyrA increased significantly, and the number of observed genotypes decreased after travel. This finding shows that international travel contributes to the spread of bacteria carrying chromosomal resistance mutations. Taken together, the development and spread of antibiotic resistance from antibiotic-polluted environments is a concern for everyone

NLMEModeling: A Wolfram Mathematica Package for Nonlinear Mixed Effects Modeling of Dynamical Systems

Nonlinear mixed effects modeling is a powerful tool when analyzing data from several entities in an experiment. In this paper, we present NLMEModeling, a package for mixed effects modeling in Wolfram Mathematica. NLMEModeling supports mixed effects modeling of dynamical systems where the underlying dynamics are described by either ordinary or stochastic differential equations combined with a flexible observation error model. Moreover, NLMEModeling is a user-friendly package with functionality for model validation, visual predictive checks and simulation capabilities. The package is freely available and provides a flexible add-on to Wolfram Mathematica

Combining dense and sparse labeling in optical DNA mapping

Optical DNA mapping (ODM) is based on fluorescent labeling, stretching and imaging of single DNA molecules to obtain sequence-specific fluorescence profiles, DNA barcodes. These barcodes can be mapped to theoretical counterparts obtained from DNA reference sequences, which in turn allow for DNA identification in complex samples and for detecting structural changes in individual DNA molecules. There are several types of DNA labeling schemes for ODM and for each labeling type one or several types of match scoring methods are used. By combining the information from multiple labeling schemes one can potentially improve mapping confidence; however, combining match scores from different labeling assays has not been implemented yet. In this study, we introduce two theoretical methods for dealing with analysis of DNA molecules with multiple label types. In our first method, we convert the alignment scores, given as output from the different assays, into p-values using carefully crafted null models. We then combine the p-values for different label types using standard methods to obtain a combined match score and an associated combined p-value. In the second method, we use a block bootstrap approach to check for the uniqueness of a match to a database for all barcodes matching with a combined p-value below a predefined threshold. For obtaining experimental dual-labeled DNA barcodes, we introduce a novel assay where we cut plasmid DNA molecules from bacteria with restriction enzymes and the cut sites serve as sequence-specific markers, which together with barcodes obtained using the established competitive binding labeling method, form a dual-labeled barcode. All experimental data in this study originates from this assay, but we point out that our theoretical framework can be used to combine data from all kinds of available optical DNA mapping assays. We test our multiple labeling frameworks on barcodes from two different plasmids and synthetically generated barcodes (combined competitive-binding- and nick-labeling). It is demonstrated that by simultaneously using the information from all label types, we can substantially increase the significance when we match experimental barcodes to a database consisting of theoretical barcodes for all sequenced plasmids

Outbreak of OXA-48-producing Enterobacteriaceae in a neonatal intensive care unit in Western Sweden

In 2015, an outbreak caused by OXA-48-producing Enterobacteriaceae affected a neonatal intensive care unit at a Swedish University Hospital. The aim was to explore the transmission of OXA-48-producing strains between infants and the transfer of resistance plasmids between strains during the outbreak. Twenty-four outbreak isolates from ten suspected cases were whole-genome sequenced. A complete assembly was created for the index isolate (Enterobacter cloacae) and used as a mapping reference to detect its plasmids in the remaining isolates (17 Klebsiella pneumoniae, 4 Klebsiella aerogenes, and 2 Escherichia coli). Strain typing was performed using core genome MLST and SNP analysis. As judged from sequencing and clinical epidemiological data, the outbreak involved nine cases (two developed sepsis) and four OXA-48-producing strains: E. cloacae ST1584 (index case), K. pneumoniae ST25 (eight cases), K. aerogenes ST93 (two cases), and E. coli ST453 (2 cases). Two plasmids from the index strain, pEclA2 and pEclA4, carrying blaOXA48 and blaCMY-4, respectively, were traced to all K. pneumoniae ST25 isolates. Klebsiella aerogenes ST93 and E. coli ST453 harboured either only pEclA2, or both pEclA2 and pEclA4. One suspected case harbouring OXA-162-producing K. pneumoniae ST37 could be excluded from the outbreak. Once initiated by an E. cloacae strain, the outbreak was caused by the dissemination of a K. pneumoniae ST25 strain and involved inter-species horizontal transfer of two resistance plasmids, one of which carried blaOXA-48. To our knowledge, this is the first description of an outbreak of OXA-48-producing Enterobacteriaceae in a neonatal setting in northern Europe

Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes

BACKGROUND: Bacterial communities in humans, animals, and the external environment maintain a large collection of antibiotic resistance genes (ARGs). However, few of these ARGs are well-characterized and thus established in existing resistance gene databases. In contrast, the remaining latent ARGs are typically unknown and overlooked in most sequencing-based studies. Our view of the resistome and its diversity is therefore incomplete, which hampers our ability to assess risk for promotion and spread of yet undiscovered resistance determinants. RESULTS: A reference database consisting of both established and latent ARGs (ARGs not present in current resistance gene repositories) was created. By analyzing more than 10,000 metagenomic samples, we showed that latent ARGs were more abundant and diverse than established ARGs in all studied environments, including the human- and animal-associated microbiomes. The pan-resistomes, i.e., all ARGs present in an environment, were heavily dominated by latent ARGs. In comparison, the core-resistome, i.e., ARGs that were commonly encountered, comprised both latent and established ARGs. We identified several latent ARGs shared between environments and/or present in human pathogens. Context analysis of these genes showed that they were located on mobile genetic elements, including conjugative elements. We, furthermore, identified that wastewater microbiomes had a surprisingly large pan- and core-resistome, which makes it a potentially high-risk environment for the mobilization and promotion of latent ARGs. CONCLUSIONS: Our results show that latent ARGs are ubiquitously present in all environments and constitute a diverse reservoir from which new resistance determinants can be recruited to pathogens. Several latent ARGs already had high mobile potential and were present in human pathogens, suggesting that they may constitute emerging threats to human health. We conclude that the full resistome-including both latent and established ARGs-needs to be considered to properly assess the risks associated with antibiotic selection pressures. Video Abstract

Quinolone resistance mutations in the faecal microbiota of Swedish travellers to India

Background: International travel contributes to the spread of antibiotic resistant bacteria over the world. Most studies addressing travel-related changes in the faecal flora have focused on specific mobile resistance genes, or depended on culturing of individual bacterial isolates. Antibiotic resistance can, however, also spread via travellers colonized by bacteria carrying chromosomal antibiotic resistance mutations, but this has received little attention so far. Here we aimed at exploring the abundance of chromosomal quinolone resistance mutations in Escherichia communities residing in the gut of Swedish travellers, and to determine potential changes after visiting India. Sweden is a country with a comparably low degree of quinolone use and quinolone resistance, whereas the opposite is true for India. Methods: Massively parallel amplicon sequencing targeting the quinolone-resistance determining region of gyrA and parC was applied to total DNA extracted from faecal samples. Paired samples were collected from 12 Swedish medical students before and after a 4-15 week visit to India. Twelve Indian residents were included for additional comparisons. Methods known resistance mutations were common in Swedes before travel as well as in Indians, with a trend for all mutations to be more common in the Indian sub group. There was a significant increase in the abundance of the most common amino acid substitution in GyrA (S83L, from 44 to 72 %, p = 0.036) in the samples collected after return to Sweden. No other substitution, including others commonly associated with quinolone resistance (D87N in GyrA, S80I in ParC) changed significantly. The number of distinct genotypes encoded in each traveller was significantly reduced after their visit to India for both GyrA (p = 0.0020) and ParC (p = 0.0051), indicating a reduced genetic diversity, similar to that found in the Indians. Conclusions: International travel can alter the composition of the Escherichia communities in the faecal flora, favouring bacteria carrying certain resistance mutations, and, thereby, contributes to the global spread of antibiotic resistance. A high abundance of specific mutations in Swedish travellers before visiting India is consistent with the hypothesis that these mutation have no fitness cost even in the absence of an antibiotic selection pressure

Large-scale characterization of the macrolide resistome reveals high diversity and several new pathogen-associated genes

Macrolides are broad-spectrum antibiotics used to treat a range of infections. Resistance to macrolides is often conferred by mobile resistance genes encoding Erm methyltransferases or Mph phosphotransferases. New erm and mph genes keep being discovered in clinical settings but their origins remain unknown, as is the type of macrolide resistance genes that will appear in the future. In this study, we used optimized hidden Markov models to characterize the macrolide resistome. Over 16 terabases of genomic and metagenomic data, representing a large taxonomic diversity (11 030 species) and diverse environments (1944 metagenomic samples), were searched for the presence of erm and mph genes. From this data, we predicted 28 340 macrolide resistance genes encoding 2892 unique protein sequences, which were clustered into 663 gene families (<70 % amino acid identity), of which 619 (94 %) were previously uncharacterized. This included six new resistance gene families, which were located on mobile genetic elements in pathogens. The function of ten predicted new resistance genes were experimentally validated in Escherichia coli using a growth assay. Among the ten tested genes, seven conferred increased resistance to erythromycin, with five genes additionally conferring increased resistance to azithromycin, showing that our models can be used to predict new functional resistance genes. Our analysis also showed that macrolide resistance genes have diverse origins and have transferred horizontally over large phylogenetic distances into human pathogens. This study expands the known macrolide resistome more than ten-fold, provides insights into its evolution, and demonstrates how computational screening can identify new resistance genes before they become a significant clinical problem

Draft genome sequence of extended-spectrum-β-lactamase-producing Escherichia coli strain CCUG 62462, isolated from a urine sample

The draft genome sequence has been determined for an extended-spectrum-β-lactamase (ESBL)-producing (blaCTX-M-15) Escherichia coli strain (CCUG 62462), composed of 119 contigs and a total size of 5.27 Mb. This E. coli is serotype O25b and sequence type 131, a pandemic clonal group, causing worldwide antimicrobial-resistant infections

Comprehensive screening of genomic and metagenomic data reveals a large diversity of tetracycline resistance genes

Tetracyclines are broad-spectrum antibiotics used to prevent or treat a variety of bacterial infections. Resistance is often mediated through mobile resistance genes, which encode one of the three main mechanisms: active efflux, ribosomal target protection or enzymatic degradation. In the last few decades, a large number of new tetracycline-resistance genes have been discovered in clinical settings. These genes are hypothesized to originate from environmental and commensal bacteria, but the diversity of tetracycline-resistance determinants that have not yet been mobilized into pathogens is unknown. In this study, we aimed to characterize the potential tetracycline resistome by screening genomic and metagenomic data for novel resistance genes. By using probabilistic models, we predicted 1254 unique putative tetracycline resistance genes, representing 195 gene families (<70 % amino acid sequence identity), whereof 164 families had not been described previously. Out of 17 predicted genes selected for experimental verification, 7 induced a resistance phenotype in an Escherichia coli host. Several of the predicted genes were located on mobile genetic elements or in regions that indicated mobility, suggesting that they easily can be shared between bacteria. Furthermore, phylogenetic analysis indicated several events of horizontal gene transfer between bacterial phyla. Our results also suggested that acquired efflux pumps originate from proteobacterial species, while ribosomal protection genes have been mobilized from Firmicutes and Actinobacteria. This study significantly expands the knowledge of known and putatively novel tetracycline resistance genes, their mobility and evolutionary history. The study also provides insights into the unknown resistome and genes that may be encountered in clinical settings in the future

Parameter Estimation for Nonlinear Mixed Effects Models Implemented in Mathematica

In many applications within biology and medicine, measurements are gathered from several entities in the same experiment. This could for example be patients exposed to a treatment or cells measured after stimuli. To characterize the variability in response between entities, the nonlinear mixed effects (NLME) model is a suitable statistical model. An NLME model enables quantification of both within- and between subject variability. The parameter estimation in NLME models is not straightforward, due to the intractable expression of the likelihood function. In this work we present a Mathematica package for parameter estimation in NLME models where the longitudinal model is defined by differential equations. The parameter estimation problem is solved by the first-order conditional estimation (FOCE) method with exact gradients. The package is demonstrated using data from a simulated drug concentration model