Long-term application of Swedish sewage sludge on farmland does not cause clear changes in the soil bacterial resistome

The widespread practice of applying sewage sludge to arable land makes use of nutrients indispensable for crops and reduces the need for inorganic fertilizer, however this application also provides a potential route for human exposure to chemical contaminants and microbial pathogens in the sludge. A recent concern is that such practice could promote environmental selection and dissemination of antibiotic resistant bacteria or resistance genes. Understanding the risks of sludge amendment in relation to antibiotic resistance development is important for sustainable agriculture, waste treatment and infectious disease management. To assess such risks, we took advantage of an agricultural field trial in southern Sweden, where land used for growing different crops has been amended with sludge every four years since 1981. We sampled raw, semi-digested and digested and stored sludge together with soils from the experimental plots before and two weeks after the most recent amendment in 2017. Levels of selected antimicrobials and bioavailable metals were determined and microbial effects were evaluated using both culture-independent metagenome sequencing and conventional culturing. Antimicrobials or bioavailable metals (Cu and Zn) did not accumulate to levels of concern for environmental selection of antibiotic resistance, and no coherent signs, neither on short or long time scales, of enrichment of antibiotic-resistant bacteria or resistance genes were found in soils amended with digested and stored sewage sludge in doses up to 12 metric tons per hectare. Likewise, only very few and slight differences in microbial community composition were observed after sludge amendment. Taken together, the current study does not indicate risks of sludge amendment related to antibiotic resistance development under the given conditions. Extrapolations should however be done with care as sludge quality and application practices vary between regions. Hence, the antibiotic concentrations and resistance load of the sludge are likely to be higher in regions with larger antibiotic consumption and resistance burden than Sweden.

Discovery of Species-unique Peptide Biomarkers of Bacterial Pathogens by Tandem Mass Spectrometry-based Proteotyping

Mass spectrometry (MS) and proteomics offer comprehensive characterization and identification of microorganisms and discovery of protein biomarkers that are applicable for diagnostics of infectious diseases. The use of biomarkers for diagnostics is widely applied in the clinic and the use of peptide biomarkers is increasingly being investigated for applications in the clinical laboratory. Respiratory-tract infections are a predominant cause for medical treatment, although, clinical assessments and standard clinical laboratory protocols are time-consuming and often inadequate for reliable diagnoses. Novel methods, preferably applied directly to clinical samples, excluding cultivation steps, are needed to improve diagnostics of infectious diseases, provide adequate treatment and reduce the use of antibiotics and associated development of antibiotic resistance. This study applied nano-liquid chromatography (LC) coupled with tandem MS, with a bioinformatics pipeline and an in-house database of curated high-quality reference genome sequences to identify species-unique peptides as potential biomarkers for four bacterial pathogens commonly found in respiratory tract infections (RTIs): Staphylococcus aureus; Moraxella catarrhalis; Haemophilus influenzae and Streptococcus pneumoniae The species-unique peptides were initially identified in pure cultures of bacterial reference strains, reflecting the genomic variation in the four species and, furthermore, in clinical respiratory tract samples, without prior cultivation, elucidating proteins expressed in clinical conditions of infection. For each of the four bacterial pathogens, the peptide biomarker candidates most predominantly found in clinical samples, are presented. Data are available via ProteomeXchange with identifier PXD014522. As proof-of-principle, the most promising species-unique peptides were applied in targeted tandem MS-analyses of clinical samples and their relevance for identifications of the pathogens, i.e. proteotyping, was validated, thus demonstrating their potential as peptide biomarker candidates for diagnostics of infectious diseases.

Sewage from Airplanes Exhibits High Abundance and Diversity of Antibiotic Resistance Genes

Airplane sanitary facilities are shared by an international audience. We hypothesized the corresponding sewage to be an extraordinary source of antibiotic-resistant bacteria (ARB) and resistance genes (ARG) in terms of diversity and quantity. Accordingly, we analyzed ARG and ARB in airplane-borne sewage using complementary approaches: metagenomics, quantitative polymerase chain reaction (qPCR), and cultivation. For the purpose of comparison, we also quantified ARG and ARB in the inlets of municipal treatment plants with and without connection to airports. As expected, airplane sewage contained an extraordinarily rich set of mobile ARG, and the relative abundances of genes were mostly increased compared to typical raw sewage of municipal origin. Moreover, combined resistance against third-generation cephalosporins, fluorochinolones, and aminoglycosides was unusually common (28.9%) among Escherichia coli isolated from airplane sewage. This percentage exceeds the one reported for German clinical isolates by a factor of 8. Our findings suggest that airplane-borne sewage can effectively contribute to the fast and global spread of antibiotic resistance.

The mobile FOX AmpC beta-lactamases originated in Aeromonas allosaccharophila

OBJECTIVE

It is important to understand the origins of antibiotic resistance genes so that risks associated with the emergence of novel resistance genes can be assessed and managed. The chromosomal ampC gene (CAV-1) of Aeromonas caviae (A. caviae) has been reported as the origin of mobile FOX cephalosporinases. The recent identification of A. caviae as the origin of MOX-2 cephalosporinases and the comparably great sequence divergence between FOX and MOX genes makes it unlikely that both genes arose from the same species. Therefore, this study investigated the origin of FOX cephalosporinases using large-scale genomics.

METHODS

Publicly available genomes and plasmids were searched for FOX-like genes. Synteny and nucleotide identities of the identified FOX-like genes and their genetic environments were compared and a phylogenetic tree was generated.

RESULTS

FOX-like genes were identified in > 230 Aeromonas genomes and in 46 Enterobacteriaceae isolates. Analysis of the genomic context of CAV-1 revealed a truncated insertion sequence directly upstream of the ampC gene. The chromosomal ampCs of A. caviae (n = 31) were 75-78% identical to CAV-1. In contrast, CAV-1, mobile FOX genes and their context were 95-98% similar to the chromosomal ampC-locus of Aeromonas allosaccharophila (A. allosaccharophila) (n = 6). The A. allosaccharophila ampCs formed a monophyletic branch with mobile FOX genes, whereas the A. caviae ampCs clustered with mobile MOX genes.

CONCLUSIONS

These findings show that FOX cephalosporinases originate not in A. caviae, as previously reported, but in A. allosaccharophila, which is a fish pathogen. This finding agrees with the hypothesis that antibiotic use in aquaculture could have contributed to the emergence of FOX genes in human pathogens.

ECOdrug: a database connecting drugs and conservation of their targets across species

Pharmaceuticals are designed to interact with specific molecular targets in humans and these targets generally have orthologs in other species. This provides opportunities for the drug discovery community to use alternative model species for drug development. It also means, however, there is potential for mode of action related effects in non-target wildlife species as many pharmaceuticals reach the environment through patient use and manufacturing wastes. Acquiring insight in drug target ortholog predictions across species and taxonomic groups has proven difficult because of the lack of an optimal strategy and because necessary information is spread across multiple and diverse sources and platforms. We introduce a new research platform tool, ECOdrug, that reliably connects drugs to their protein targets across divergent species. It harmonizes ortholog predictions from multiple sources via a simple user interface underpinning critical applications for a wide range of studies in pharmacology, ecotoxicology and comparative evolutionary biology. ECOdrug can be used to identify species with drug targets and identify drugs that interact with those targets. As such, it can be applied to support intelligent targeted drug safety testing by ensuring appropriate and relevant species are selected in ecological risk assessments. ECOdrug is freely accessible and available at: http://www.ecodrug.org.

Pharmacology beyond the patient - The environmental risks of human drugs

BACKGROUND

The presence of pharmaceuticals in the environment is a growing global concern and although environmental risk assessment is required for approval of new drugs in Europe and the USA, the adequacy of the current triggers and the effects-based assessments has been questioned.

OBJECTIVE

To provide a comprehensive analysis of all regulatory compliant aquatic ecotoxicity data and evaluate the current triggers and effects-based environmental assessments to facilitate the development of more efficient approaches for pharmaceuticals toxicity testing.

METHODS

Publicly-available regulatory compliant ecotoxicity data for drugs targeting human proteins was compiled together with pharmacological information including drug targets, Cmax and lipophilicity. Possible links between these factors and the ecotoxicity data for effects on, growth, mortality and/or reproduction, were evaluated. The environmental risks were then assessed based on a combined analysis of drug toxicity and predicted environmental concentrations based on European patient consumption data.

RESULTS

For most (88%) of the of 975 approved small molecule drugs targeting human proteins a complete set of regulatory compliant ecotoxicity data in the public domain was lacking, highlighting the need for both intelligent approaches to prioritize legacy human drugs for a tailored environmental risk assessment and a transparent database that captures environmental data. We show that presence/absence of drug-target orthologues are predictive of susceptible species for the more potent drugs. Drugs that target the endocrine system represent the highest potency and greatest risk. However, for most drugs (>80%) with a full set of ecotoxicity data, risk quotients assuming worst-case exposure assessments were below one in all European countries indicating low environmental risks for the endpoints assessed.

CONCLUSION

We believe that the presented analysis can guide improvements to current testing procedures, and provide valuable approaches for prioritising legacy drugs (i.e. those registered before 2006) for further ecotoxicity testing. For drugs where effects of possible concern (e.g. behaviour) are not captured in regulatory tests, additional mechanistic testing may be required to provide the highest confidence for avoiding environmental impacts.

Sewage effluent from an Indian hospital harbors novel carbapenemases and integron-borne antibiotic resistance genes

BACKGROUND

Hospital wastewaters contain fecal material from a large number of individuals, of which many are undergoing antibiotic therapy. It is, thus, plausible that hospital wastewaters could provide opportunities to find novel carbapenemases and other resistance genes not yet described in clinical strains. Our aim was therefore to investigate the microbiota and antibiotic resistome of hospital effluent collected from the city of Mumbai, India, with a special focus on identifying novel carbapenemases.

RESULTS

Shotgun metagenomics revealed a total of 112 different mobile antibiotic resistance gene types, conferring resistance against almost all classes of antibiotics. Beta-lactamase genes, including encoding clinically important carbapenemases, such as NDM, VIM, IMP, KPC, and OXA-48, were abundant. NDM (0.9% relative abundance to 16S rRNA genes) was the most common carbapenemase gene, followed by OXA-58 (0.84% relative abundance to 16S rRNA genes). Among the investigated mobile genetic elements, class 1 integrons (11% relative abundance to 16S rRNA genes) were the most abundant. The genus Acinetobacter accounted for as many as 30% of the total 16S rRNA reads, with A. baumannii accounting for an estimated 2.5%. High throughput sequencing of amplified integron gene cassettes identified a novel functional variant of an IMP-type (proposed IMP-81) carbapenemase gene (eight aa substitutions) along with recently described novel resistance genes like sul4 and bla_RSA1. Using a computational hidden Markov model, we detected 27 unique metallo-beta-lactamase (MBL) genes in the shotgun data, of which nine were novel subclass B1 genes, one novel subclass B2, and 10 novel subclass B3 genes. Six of the seven novel MBL genes were functional when expressed in Escherichia coli.

CONCLUSION

By exploring hospital wastewater from India, our understanding of the diversity of carbapenemases has been extended. The study also demonstrates that the microbiota of hospital wastewater can serve as a reservoir of novel resistance genes, including previously uncharacterized carbapenemases with the potential to spread further.

177Lu-octreotate therapy for neuroendocrine tumours is enhanced by Hsp90 inhibition

177Lu-octreotate is an FDA-approved radionuclide therapy for patients with gastroenteropancreatic neuroendocrine tumours (NETs) expressing somatostatin receptors. The 177Lu-octreotate therapy has shown promising results in clinical trials by prolonging progression-free survival, but complete responses are still uncommon. The aim of this study was to improve the 177Lu-octreotate therapy by means of combination therapy. To identify radiosensitising inhibitors, two cell lines, GOT1 and P-STS, derived from small intestinal neuroendocrine tumours (SINETs), were screened with 1,224 inhibitors alone or in combination with external radiation. The screening revealed that inhibitors of Hsp90 can potentiate the tumour cell-killing effect of radiation in a synergistic fashion (GOT1; false discovery rate <3.2×10-11). The potential for Hsp90 inhibitor ganetespib to enhance the anti-tumour effect of 177Lu-octreotate in an in vivo setting was studied in the somatostatin receptor-expressing GOT1 xenograft model. The combination led to a larger decrease in tumour volume relative to monotherapies and the tumour-reducing effect was shown to be synergistic. Using patient-derived tumour cells from eight metastatic SINETs, we could show that ganetespib enhanced the effect of 177Lu-octreotate therapy for all investigated patient tumours. Levels of Hsp90 protein expression were evaluated in 767 SINETs from 379 patients. We found that Hsp90 expression was upregulated in tumour cells relative to tumour stroma in the vast majority of SINETs. We conclude that Hsp90 inhibitors enhance the tumour-killing effect of 177Lu-octreotate therapy synergistically in SINET tumour models and suggest that this potentially promising combination should be further evaluated.

Identification and reconstruction of novel antibiotic resistance genes from metagenomes

BACKGROUND

Environmental and commensal bacteria maintain a diverse and largely unknown collection of antibiotic resistance genes (ARGs) that, over time, may be mobilized and transferred to pathogens. Metagenomics enables cultivation-independent characterization of bacterial communities but the resulting data is noisy and highly fragmented, severely hampering the identification of previously undescribed ARGs. We have therefore developed fARGene, a method for identification and reconstruction of ARGs directly from shotgun metagenomic data.

RESULTS

fARGene uses optimized gene models and can therefore with high accuracy identify previously uncharacterized resistance genes, even if their sequence similarity to known ARGs is low. By performing the analysis directly on the metagenomic fragments, fARGene also circumvents the need for a high-quality assembly. To demonstrate the applicability of fARGene, we reconstructed β-lactamases from five billion metagenomic reads, resulting in 221 ARGs, of which 58 were previously not reported. Based on 38 ARGs reconstructed by fARGene, experimental verification showed that 81% provided a resistance phenotype in Escherichia coli. Compared to other methods for detecting ARGs in metagenomic data, fARGene has superior sensitivity and the ability to reconstruct previously unknown genes directly from the sequence reads.

CONCLUSIONS

We conclude that fARGene provides an efficient and reliable way to explore the unknown resistome in bacterial communities. The method is applicable to any type of ARGs and is freely available via GitHub under the MIT license.

Modelling of zero-inflation improves inference of metagenomic gene count data

Metagenomics enables the study of gene abundances in complex mixtures of microorganisms and has become a standard methodology for the analysis of the human microbiome. However, gene abundance data is inherently noisy and contains high levels of biological and technical variability as well as an excess of zeros due to non-detected genes. This makes the statistical analysis challenging. In this study, we present a new hierarchical Bayesian model for inference of metagenomic gene abundance data. The model uses a zero-inflated overdispersed Poisson distribution which is able to simultaneously capture the high gene-specific variability as well as zero observations in the data. By analysis of three comprehensive datasets, we show that zero-inflation is common in metagenomic data from the human gut and, if not correctly modelled, it can lead to substantial reductions in statistical power. We also show, by using resampled metagenomic data, that our model has, compared to other methods, a higher and more stable performance for detecting differentially abundant genes. We conclude that proper modelling of the gene-specific variability, including the excess of zeros, is necessary to accurately describe gene abundances in metagenomic data. The proposed model will thus pave the way for new biological insights into the structure of microbial communities.

The resistomes of six carbapenem-resistant pathogens - a critical genotype-phenotype analysis

Carbapenem resistance is a rapidly growing threat to our ability to treat refractory bacterial infections. To understand how carbapenem resistance is mobilized and spread between pathogens, it is important to study the genetic context of the underlying resistance mechanisms. In this study, the resistomes of six clinical carbapenem-resistant isolates of five different species – Acinetobacter baumannii, Escherichia coli, two Klebsiella pneumoniae, Proteus mirabilis and Pseudomonas aeruginosa – were characterized using whole genome sequencing. All Enterobacteriaceae isolates and the A. baumannii isolate had acquired a large number of antimicrobial resistance genes (7–18 different genes per isolate), including the following encoding carbapenemases: bla_KPC-2, bla_OXA-48, bla_OXA-72, bla_NDM-1, bla_NDM-7 and bla_VIM-1. In addition, a novel version of bla_SHV was discovered. Four new resistance plasmids were identified and their fully assembled sequences were verified using optical DNA mapping. Most of the resistance genes were co-localized on these and other plasmids, suggesting a risk for co-selection. In contrast, five out of six carbapenemase genes were present on plasmids with no or few other resistance genes. The expected level of resistance – based on acquired resistance determinants – was concordant with measured levels in most cases. There were, however, several important discrepancies for four of the six isolates concerning multiple classes of antibiotics. In conclusion, our results further elucidate the diversity of carbapenemases, their mechanisms of horizontal transfer and possible patterns of co-selection. The study also emphasizes the difficulty of using whole genome sequencing for antimicrobial susceptibility testing of pathogens with complex genotypes.

PER extended-spectrum β-lactamases originate from Pararheinheimera spp

To investigate the origin of PER extended-spectrum β-lactamases, publicly available sequence databases were searched for bla_PER-like genes. Three genomes from Pararheinheimera, a genus associated with water and soil environments, were found to carry bla_PER-like genes but lacked the ISCR1/ISPa12/ISPa13 insertion sequences commonly associated with bla_PER in clinical isolates. Sequence analysis revealed 78-96% nucleotide identity and conserved synteny between the clinical mobile genetic elements (MGEs) encoding bla_PER-1 and the bla_PER locus in the Pararheinheimera genomes. Notably, bla_PER genes were only identified in 3 of 21 Pararheinheimera and Rheinheimera genomes, whereas the genetic environment of bla_PER genes as found in clinical MGEs was conserved in all Pararheinheimera and Rheinheimera genomes. These findings indicate that bla_PER genes were likely acquired by a branch of the Pararheinheimera genus long before the antibiotic era. Later, bla_PER genes were mobilised, likely through the involvement of insertion sequences, from one or several Pararheinheimera species, allowing their dissemination into human pathogens.

Introducing ribosomal tandem repeat barcoding for fungi

Sequence comparison and analysis of the various ribosomal genetic markers are the dominant molecular methods for identification and description of fungi. However, new environmental fungal lineages known only from DNA data reveal significant gaps in our sampling of the fungal kingdom in terms of both taxonomy and marker coverage in the reference sequence databases. To facilitate the integration of reference data from all of the ribosomal markers, we present three sets of general primers that allow for amplification of the complete ribosomal operon from the ribosomal tandem repeats. The primers cover all ribosomal markers: ETS, SSU, ITS1, 5.8S, ITS2, LSU and IGS. We coupled these primers successfully with third-generation sequencing (PacBio and Nanopore sequencing) to showcase our approach on authentic fungal herbarium specimens (Basidiomycota), aquatic chytrids (Chytridiomycota) and a poorly understood lineage of early diverging fungi (Nephridiophagidae). In particular, we were able to generate high-quality reference data with Nanopore sequencing in a high-throughput manner, showing that the generation of reference data can be achieved on a regular desktop computer without the involvement of any large-scale sequencing facility. The quality of the Nanopore generated sequences was 99.85%, which is comparable with the 99.78% accuracy described for Sanger sequencing. With this work, we hope to stimulate the generation of a new comprehensive standard of ribosomal reference data with the ultimate aim to close the huge gaps in our reference datasets.

miRNA profiling of small intestinal neuroendocrine tumors defines novel molecular subtypes and identifies miR-375 as a biomarker of patient survival

The aim of this study was to define the miRNA profile of small intestinal neuroendocrine tumors and to search for novel molecular subgroups and prognostic biomarkers. miRNA profiling was conducted on 42 tumors from 37 patients who underwent surgery for small intestinal neuroendocrine tumors. Unsupervised hierarchical clustering analysis of miRNA profiles identified two groups of tumor metastases, denoted cluster M1 and M2. The smaller cluster M1 was associated with shorter overall survival and contained tumors with higher grade (WHO grade G2/3) and multiple chromosomal gains including gain of chromosome 14. Tumors of cluster M1 had elevated expression of miR-1246 and miR-663a, and reduced levels of miR-488-3p. Pathway analysis predicted Wnt signaling to be the most significantly altered signaling pathway between clusters M1 and M2. Analysis of miRNA expression in relation to tumor proliferation rate showed significant alterations including downregulation of miR-137 and miR-204-5p in tumors with Ki67 index above 3%. Similarly, tumor progression was associated with significant alterations in miRNA expression, e.g. higher expression of miR-95 and miR-210, and lower expression of miR-378a-3p in metastases. Pathway analysis predicted Wnt signaling to be altered during tumor progression, which was supported by decreased nuclear translocation of β-catenin in metastases. Survival analysis revealed that downregulation of miR-375 was associated with shorter overall survival. We performed in situ hybridization on biopsies from an independent cohort of small intestinal neuroendocrine tumors using tissue microarrays. Expression of miR-375 was found in 578/635 (91%) biopsies and survival analysis confirmed that there was a correlation between downregulation of miR-375 in tumor metastases and shorter patient survival. We conclude that miRNA profiling defines novel molecular subgroups of metastatic small intestinal neuroendocrine tumors and identifies miRNAs associated with tumor proliferation rate and progression. miR-375 is highly expressed in small intestinal neuroendocrine tumors and may be used as a prognostic biomarker.

Selective concentration for ciprofloxacin resistance in Escherichia coli grown in complex aquatic bacterial biofilms

There is concern that antibiotics in the environment can select for and enrich bacteria carrying acquired antibiotic resistance genes, thus increasing the potential of those genes to emerge in a clinical context. A critical question for understanding and managing such risks is what levels of antibiotics are needed to select for resistance in complex bacterial communities. Here, we address this question by examining the phenotypic and genotypic profiles of aquatic communities exposed to ciprofloxacin, also evaluating the within-species selection of resistant E. coli in complex communities. The taxonomic composition was significantly altered at ciprofloxacin exposure concentrations down to 1 μg/L. Shotgun metagenomic analysis indicated that mobile quinolone resistance determinants (qnrD, qnrS and qnrB) were enriched as a direct consequence of ciprofloxacin exposure from 1 μg/L or higher. Only at 5-10 μg/L resistant E.coli increased relative to their sensitive counterparts. These resistant E. coli predominantly harbored non-transferrable, chromosomal triple mutations (gyrA S83 L, D87N and parC S80I), which confer high-level resistance. In a controlled experimental setup such as this, we interpret effects on taxonomic composition and enrichment of mobile quinolone resistance genes as relevant indicators of risk. Hence, the lowest observed effect concentration for resistance selection in complex communities by ciprofloxacin was 1 μg/L and the corresponding no observed effect concentration 0.1 μg/L. These findings can be used to define and implement discharge or surface water limits to reduce risks for selection of antibiotic resistance in the environment.

Using metagenomics to investigate human and environmental resistomes

Antibiotic resistance is a global health concern declared by the WHO as one of the largest threats to modern healthcare. In recent years, metagenomic DNA sequencing has started to be applied as a tool to study antibiotic resistance in different environments, including the human microbiota. However, a multitude of methods exist for metagenomic data analysis, and not all methods are suitable for the investigation of resistance genes, particularly if the desired outcome is an assessment of risks to human health. In this review, we outline the current state of methods for sequence handling, mapping to databases of resistance genes, statistical analysis and metagenomic assembly. In addition, we provide an overview of important considerations related to the analysis of resistance genes, and recommend some of the currently used tools and methods that are best equipped to inform research and clinical practice related to antibiotic resistance.

Comparison of normalization methods for the analysis of metagenomic gene abundance data

Background

In shotgun metagenomics, microbial communities are studied through direct sequencing of DNA without any prior cultivation. By comparing gene abundances estimated from the generated sequencing reads, functional differences between the communities can be identified. However, gene abundance data is affected by high levels of systematic variability, which can greatly reduce the statistical power and introduce false positives. Normalization, which is the process where systematic variability is identified and removed, is therefore a vital part of the data analysis. A wide range of normalization methods for high-dimensional count data has been proposed but their performance on the analysis of shotgun metagenomic data has not been evaluated.

Results

Here, we present a systematic evaluation of nine normalization methods for gene abundance data. The methods were evaluated through resampling of three comprehensive datasets, creating a realistic setting that preserved the unique characteristics of metagenomic data. Performance was measured in terms of the methods ability to identify differentially abundant genes (DAGs), correctly calculate unbiased p-values and control the false discovery rate (FDR). Our results showed that the choice of normalization method has a large impact on the end results. When the DAGs were asymmetrically present between the experimental conditions, many normalization methods had a reduced true positive rate (TPR) and a high false positive rate (FPR). The methods trimmed mean of M-values (TMM) and relative log expression (RLE) had the overall highest performance and are therefore recommended for the analysis of gene abundance data. For larger sample sizes, CSS also showed satisfactory performance.

Conclusions

This study emphasizes the importance of selecting a suitable normalization methods in the analysis of data from shotgun metagenomics. Our results also demonstrate that improper methods may result in unacceptably high levels of false positives, which in turn may lead to incorrect or obfuscated biological interpretation.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4637-6) contains supplementary material, which is available to authorized users.

The neuroendocrine phenotype, genomic profile and therapeutic sensitivity of GEPNET cell lines

Experimental models of neuroendocrine tumour disease are scarce, and no comprehensive characterisation of existing gastroenteropancreatic neuroendocrine tumour (GEPNET) cell lines has been reported. In this study, we aimed to define the molecular characteristics and therapeutic sensitivity of these cell lines. We therefore performed immunophenotyping, copy number profiling, whole-exome sequencing and a large-scale inhibitor screening of seven GEPNET cell lines. Four cell lines, GOT1, P-STS, BON-1 and QGP-1, displayed a neuroendocrine phenotype while three others, KRJ-I, L-STS and H-STS, did not. Instead, these three cell lines were identified as lymphoblastoid. Characterisation of remaining authentic GEPNET cell lines by copy number profiling showed that GOT1, among other chromosomal alterations, harboured losses on chromosome 18 encompassing the SMAD4 gene, while P-STS had a loss on 11q. BON-1 had a homozygous loss of CDKN2A and CDKN2B, and QGP-1 harboured amplifications of MDM2 and HMGA2 Whole-exome sequencing revealed both disease-characteristic mutations (e.g. ATRX mutation in QGP-1) and, for patient tumours, rare genetic events (e.g. TP53 mutation in P-STS, BON-1 and QGP-1). A large-scale inhibitor screening showed that cell lines from pancreatic NETs to a greater extent, when compared to small intestinal NETs, were sensitive to inhibitors of MEK. Similarly, neuroendocrine NET cells originating from the small intestine were considerably more sensitive to a group of HDAC inhibitors. Taken together, our results provide a comprehensive characterisation of GEPNET cell lines, demonstrate their relevance as neuroendocrine tumour models and explore their therapeutic sensitivity to a broad range of inhibitors.

Functional metagenomics reveals a novel carbapenem-hydrolyzing mobile beta-lactamase from Indian river sediments contaminated with antibiotic production waste

Evolution has provided environmental bacteria with a plethora of genes that give resistance to antibiotic compounds. Under anthropogenic selection pressures, some of these genes are believed to be recruited over time into pathogens by horizontal gene transfer. River sediment polluted with fluoroquinolones and other drugs discharged from bulk drug production in India constitute an environment with unprecedented, long-term antibiotic selection pressures. It is therefore plausible that previously unknown resistance genes have evolved and/or are promoted here. In order to search for novel resistance genes, we therefore analyzed such river sediments by a functional metagenomics approach. DNA fragments providing resistance to different antibiotics in E. coli were sequenced using Sanger and PacBio RSII platforms. We recaptured the majority of known antibiotic resistance genes previously identified by open shot-gun metagenomics sequencing of the same samples. In addition, seven novel resistance gene candidates (six beta-lactamases and one amikacin resistance gene) were identified. Two class A beta-lactamases, bla_RSA1 and bla_RSA2, were phylogenetically close to clinically important ESBLs like bla_GES, bla_BEL and bla_L2, and were further characterized for their substrate spectra. The blaRSA1 protein, encoded as an integron gene cassette, efficiently hydrolysed penicillins, first generation cephalosporins and cefotaxime, while blaRSA2 was an inducible class A beta-lactamase, capable of hydrolyzing carbapenems albeit with limited efficiency, similar to the L2 beta-lactamase from Stenotrophomonas maltophilia. All detected novel genes were associated with plasmid mobilization proteins, integrons, and/or other resistance genes, suggesting a potential for mobility. This study provides insight into a resistome shaped by an exceptionally strong and long-term antibiotic selection pressure. An improved knowledge of mobilized resistance factors in the external environment may make us better prepared for the resistance challenges that we may face in clinics in the future.

Environmental factors influencing the development and spread of antibiotic resistance

Antibiotic resistance and its wider implications present us with a growing healthcare crisis. Recent research points to the environment as an important component for the transmission of resistant bacteria and in the emergence of resistant pathogens. However, a deeper understanding of the evolutionary and ecological processes that lead to clinical appearance of resistance genes is still lacking, as is knowledge of environmental dispersal barriers. This calls for better models of how resistance genes evolve, are mobilized, transferred and disseminated in the environment. Here, we attempt to define the ecological and evolutionary environmental factors that contribute to resistance development and transmission. Although mobilization of resistance genes likely occurs continuously, the great majority of such genetic events do not lead to the establishment of novel resistance factors in bacterial populations, unless there is a selection pressure for maintaining them or their fitness costs are negligible. To enable preventative measures it is therefore critical to investigate under what conditions and to what extent environmental selection for resistance takes place. In addition, understanding dispersal barriers is not only key to evaluate risks, but also to prevent resistant pathogens, as well as novel resistance genes, from reaching humans.

Discovery of the fourth mobile sulfonamide resistance gene

BACKGROUND

Over the past 75 years, human pathogens have acquired antibiotic resistance genes (ARGs), often from environmental bacteria. Integrons play a major role in the acquisition of antibiotic resistance genes. We therefore hypothesized that focused exploration of integron gene cassettes from microbial communities could be an efficient way to find novel mobile resistance genes. DNA from polluted Indian river sediments were amplified using three sets of primers targeting class 1 integrons and sequenced by long- and short-read technologies to maintain both accuracy and context.

RESULTS

Up to 89% of identified open reading frames encode known resistance genes, or variations thereof (> 1000). We identified putative novel ARGs to aminoglycosides, beta-lactams, trimethoprim, rifampicin, and chloramphenicol, including several novel OXA variants, providing reduced susceptibility to carbapenems. One dihydropteroate synthase gene, with less than 34% amino acid identity to the three known mobile sulfonamide resistance genes (sul1-3), provided complete resistance when expressed in Escherichia coli. The mobilized gene, here named sul4, is the first mobile sulfonamide resistance gene discovered since 2003. Analyses of adjacent DNA suggest that sul4 has been decontextualized from a set of chromosomal genes involved in folate synthesis in its original host, likely within the phylum Chloroflexi. The presence of an insertion sequence common region element could provide mobility to the entire integron. Screening of 6489 metagenomic datasets revealed that sul4 is already widespread in seven countries across Asia and Europe.

CONCLUSIONS

Our findings show that exploring integrons from environmental communities with a history of antibiotic exposure can provide an efficient way to find novel, mobile resistance genes. The mobilization of a fourth sulfonamide resistance gene is likely to provide expanded opportunities for sulfonamide resistance to spread, with potential impacts on both human and animal health.

Untreated urban waste contaminates Indian river sediments with resistance genes to last resort antibiotics

Efficient sewage treatment is critical for limiting environmental transmission of antibiotic-resistant bacteria. In many low and middle income countries, however, large proportions of sewage are still released untreated into receiving water bodies. In-depth knowledge of how such discharges of untreated urban waste influences the environmental resistome is largely lacking. Here, we highlight the impact of uncontrolled discharge of partially treated and/or untreated wastewater on the structure of bacterial communities and resistome of sediments collected from Mutha river flowing through Pune city in India. Using shotgun metagenomics, we found a wide array (n = 175) of horizontally transferable antibiotic resistance genes (ARGs) including carbapenemases such as NDM, VIM, KPC, OXA-48 and IMP types. The relative abundance of total ARGs was 30-fold higher in river sediments within the city compared to upstream sites. Forty four ARGs, including the tet(X) gene conferring resistance to tigecycline, OXA-58 and GES type carbapenemases, were significantly more abundant in city sediments, while two ARGs were more common at upstream sites. The recently identified mobile colistin resistance gene mcr-1 was detected only in one of the upstream samples, but not in city samples. In addition to ARGs, higher abundances of various mobile genetic elements were found in city samples, including integron-associated integrases and ISCR transposases, as well as some biocide/metal resistance genes. Virulence toxin genes as well as bacterial genera comprising many pathogens were more abundant here; the genus Acinetobacter, which is often associated with multidrug resistance and nosocomial infections, comprised up to 29% of the 16S rRNA reads, which to our best knowledge is unmatched in any other deeply sequenced metagenome. There was a strong correlation between the abundance of Acinetobacter and the OXA-58 carbapenemase gene. Our study shows that uncontrolled discharge of untreated urban waste can contribute to an overall increase of the abundance and diversity of ARGs in the environment, including those conferring resistance to last-resort antibiotics.