Transformers enable accurate prediction of acute and chronic chemical toxicity in aquatic organisms

Environmental hazard assessments are reliant on toxicity data that cover multiple organism groups. Generating experimental toxicity data is, however, resource-intensive and time-consuming. Computational methods are fast and cost-efficient alternatives, but the low accuracy and narrow applicability domains have made their adaptation slow. Here, we present a AI-based model for predicting chemical toxicity. The model uses transformers to capture toxicity-specific features directly from the chemical structures and deep neural networks to predict effect concentrations. The model showed high predictive performance for all tested organism groups-algae, aquatic invertebrates and fish-and has, in comparison to commonly used QSAR methods, a larger applicability domain and a considerably lower error. When the model was trained on data with multiple effect concentrations (EC50/EC10), the performance was further improved. We conclude that deep learning and transformers have the potential to markedly advance computational prediction of chemical toxicity.

The UNITE database for molecular identification and taxonomic communication of fungi and other eukaryotes: sequences, taxa and classifications reconsidered

UNITE (https://unite.ut.ee) is a web-based database and sequence management environment for molecular identification of eukaryotes. It targets the nuclear ribosomal internal transcribed spacer (ITS) region and offers nearly 10 million such sequences for reference. These are clustered into ∼2.4M species hypotheses (SHs), each assigned a unique digital object identifier (DOI) to promote unambiguous referencing across studies. UNITE users have contributed over 600 000 third-party sequence annotations, which are shared with a range of databases and other community resources. Recent improvements facilitate the detection of cross-kingdom biological associations and the integration of undescribed groups of organisms into everyday biological pursuits. Serving as a digital twin for eukaryotic biodiversity and communities worldwide, the latest release of UNITE offers improved avenues for biodiversity discovery, precise taxonomic communication and integration of biological knowledge across platforms.

Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms

Empirical and in silico data on the aquatic ecotoxicology of 2697 organic chemicals were collected in order to compile a dataset for assessing the predictive power of current Quantitative Structure Activity Relationship (QSAR) models and software platforms. This document presents the dataset and the data pipeline for its creation. Empirical data were collected from the US EPA ECOTOX Knowledgebase (ECOTOX) and the EFSA (European Food Safety Authority) report "Completion of data entry of pesticide ecotoxicology Tier 1 study endpoints in a XML schema - database". Only data for OECD recommended algae, daphnia and fish species were retained. QSAR toxicity predictions were calculated for each chemical and each of six endpoints using ECOSAR, VEGA and the Toxicity Estimation Software Tool (T.E.S.T.) platforms. Finally, the dataset was amended with SMILES, InChIKey, pKa and logP collected from webchem and PubChem.

Extensive screening reveals previously undiscovered aminoglycoside resistance genes in human pathogens

Antibiotic resistance is a growing threat to human health, caused in part by pathogens accumulating antibiotic resistance genes (ARGs) through horizontal gene transfer. New ARGs are typically not recognized until they have become widely disseminated, which limits our ability to reduce their spread. In this study, we use large-scale computational screening of bacterial genomes to identify previously undiscovered mobile ARGs in pathogens. From ~1 million genomes, we predict 1,071,815 genes encoding 34,053 unique aminoglycoside-modifying enzymes (AMEs). These cluster into 7,612 families (<70% amino acid identity) of which 88 are previously described. Fifty new AME families are associated with mobile genetic elements and pathogenic hosts. From these, 24 of 28 experimentally tested AMEs confer resistance to aminoglycoside(s) in Escherichia coli, with 17 providing resistance above clinical breakpoints. This study greatly expands the range of clinically relevant aminoglycoside resistance determinants and demonstrates that computational methods enable early discovery of potentially emerging ARGs.

Phenotypic and transcriptomic acclimation of the green microalga Raphidocelis subcapitata to high environmental levels of the herbicide diflufenican

Herbicide pollution poses a worldwide threat to plants and freshwater ecosystems. However, the understanding of how organisms develop tolerance to these chemicals and the associated trade-off expenses are largely unknown. This study aims to investigate the physiological and transcriptional mechanisms underlying the acclimation of the green microalgal model species Raphidocelis subcapitata (Selenastraceae) towards the herbicide diflufenican, and the fitness costs associated with tolerance development. Algae were exposed for 12 weeks (corresponding to 100 generations) to diflufenican at the two environmental concentrations 10 and 310 ng/L. The monitoring of growth, pigment composition, and photosynthetic performance throughout the experiment revealed an initial dose-dependent stress phase (week 1) with an EC₅₀ of 397 ng/L, followed by a time-dependent recovery phase during weeks 2 to 4. After week 4, R. subcapitata was acclimated to diflufenican exposure with a similar growth rate, content of carotenoids, and photosynthetic performance as the unexposed control algae. This acclimation state of the algae was explored in terms of tolerance acquisition, changes in the fatty acids composition, diflufenican removal rate, cell size, and changes in mRNA gene expression profile, revealing potential fitness costs associated with acclimation, such as up-regulation of genes related to cell division, structure, morphology, and reduction of cell size. Overall, this study demonstrates that R. subcapitata can quickly acclimate to environmental but toxic levels of diflufenican; however, the acclimation is associated with trade-off expenses that result in smaller cell size.

Risk assessment of chemicals and their mixtures are hindered by scarcity and inconsistencies between different environmental exposure limits

In chemical risk assessment, measured or modelled environmental concentrations are compared to environmental exposure limits (EELs), such as Predicted No Effect Concentrations (PNECs) or hazardous concentrations for 5% of species (HC05s) derived from species sensitivity distributions (SSDs). However, for many chemicals the EELs include large uncertainties or, in the worst case, the necessary data for their estimation are completely missing. This makes the assessment of chemical risks and any subsequent implementation of management strategies challenging. In this study we analyzed the uncertainty of EELs and its impact on chemical risk assessment. First, we compared three individual EEL datasets, two primarily based on experimental data and one based on computational predictions. The comparison demonstrates large disagreements between EEL data sources, with experimentally derived EELs differing by more than seven orders of magnitude. In a case-study, based on the predicted emissions of 2005 chemicals, we showed that these uncertainties lead to significantly different risk assessment outcomes, including large differences in the magnitude of the total risk, risk driver identification, and the ranking of use categories as risk contributors. We also show that the large data-gaps in EEL datasets cannot be covered by commonly used computational approaches (QSARs). We conclude that an expanded framework for interpreting risk characterization outcomes is needed. We also argue that the large data-gaps present in ecotoxicological data need to be addressed in order to achieve the European zero pollution vision as the growing emphasis on ambient exposures will further increase the demand for accurate and well-established EELs.

How, not if, is the question mycologists should be asking about DNA-based typification

Fungal metabarcoding of substrates such as soil, wood, and water is uncovering an unprecedented number of fungal species that do not seem to produce tangible morphological structures and that defy our best attempts at cultivation, thus falling outside the scope of the International Code of Nomenclature for algae, fungi, and plants. The present study uses the new, ninth release of the species hypotheses of the UNITE database to show that species discovery through environmental sequencing vastly outpaces traditional, Sanger sequencing-based efforts in a strongly increasing trend over the last five years. Our findings challenge the present stance of some in the mycological community - that the current situation is satisfactory and that no change is needed to "the code" - and suggest that we should be discussing not whether to allow DNA-based descriptions (typifications) of species and by extension higher ranks of fungi, but what the precise requirements for such DNA-based typifications should be. We submit a tentative list of such criteria for further discussion. The present authors hope for a revitalized and deepened discussion on DNA-based typification, because to us it seems harmful and counter-productive to intentionally deny the overwhelming majority of extant fungi a formal standing under the International Code of Nomenclature for algae, fungi, and plants.

Evidence for wastewaters as environments where mobile antibiotic resistance genes emerge

The emergence and spread of mobile antibiotic resistance genes (ARGs) in pathogens have become a serious threat to global health. Still little is known about where ARGs gain mobility in the first place. Here, we aimed to collect evidence indicating where such initial mobilization events of clinically relevant ARGs may have occurred. We found that the majority of previously identified origin species did not carry the mobilizing elements that likely enabled intracellular mobility of the ARGs, suggesting a necessary interplay between different bacteria. Analyses of a broad range of metagenomes revealed that wastewaters and wastewater-impacted environments had by far the highest abundance of both origin species and corresponding mobilizing elements. Most origin species were only occasionally detected in other environments. Co-occurrence of origin species and corresponding mobilizing elements were rare in human microbiota. Our results identify wastewaters and wastewater-impacted environments as plausible arenas for the initial mobilization of resistance genes.

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.

Strain-level bacterial typing directly from patient samples using optical DNA mapping

BACKGROUND

Identification of pathogens is crucial to efficiently treat and prevent bacterial infections. However, existing diagnostic techniques are slow or have a too low resolution for well-informed clinical decisions.

METHODS

In this study, we have developed an optical DNA mapping-based method for strain-level bacterial typing and simultaneous plasmid characterisation. For the typing, different taxonomical resolutions were examined and cultivated pure Escherichia coli and Klebsiella pneumoniae samples were used for parameter optimization. Finally, the method was applied to mixed bacterial samples and uncultured urine samples from patients with urinary tract infections.

RESULTS

We demonstrate that optical DNA mapping of single DNA molecules can identify Escherichia coli and Klebsiella pneumoniae at the strain level directly from patient samples. At a taxonomic resolution corresponding to E. coli sequence type 131 and K. pneumoniae clonal complex 258 forming distinct groups, the average true positive prediction rates are 94% and 89%, respectively. The single-molecule aspect of the method enables us to identify multiple E. coli strains in polymicrobial samples. Furthermore, by targeting plasmid-borne antibiotic resistance genes with Cas9 restriction, we simultaneously identify the strain or subtype and characterize the corresponding plasmids.

CONCLUSION

The optical DNA mapping method is accurate and directly applicable to polymicrobial and clinical samples without cultivation. Hence, it has the potential to rapidly provide comprehensive diagnostics information, thereby optimizing early antibiotic treatment and opening up for future precision medicine management.

The curse of the uncultured fungus

The international DNA sequence databases abound in fungal sequences not annotated beyond the kingdom level, typically bearing names such as “uncultured fungus”. These sequences beget low-resolution mycological results and invite further deposition of similarly poorly annotated entries. What do these sequences represent? This study uses a 767,918-sequence corpus of public full-length fungal ITS sequences to estimate what proportion of the 95,055 “uncultured fungus” sequences that represent truly unidentifiable fungal taxa – and what proportion of them that would have been straightforward to annotate to some more meaningful taxonomic level at the time of sequence deposition. Our results suggest that more than 70% of these sequences would have been trivial to identify to at least the order/family level at the time of sequence deposition, hinting that factors other than poor availability of relevant reference sequences explain the low-resolution names. We speculate that researchers’ perceived lack of time and lack of insight into the ramifications of this problem are the main explanations for the low-resolution names. We were surprised to find that more than a fifth of these sequences seem to have been deposited by mycologists rather than researchers unfamiliar with the consequences of poorly annotated fungal sequences in molecular repositories. The proportion of these needlessly poorly annotated sequences does not decline over time, suggesting that this problem must not be left unchecked.

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.

Estimating the release of chemical substances from consumer products, textiles and pharmaceuticals to wastewater

Chemical emissions from households originate from a wide range of sources and results in highly diverse mixtures. This makes traditional monitoring based on analytical chemistry challenging, especially for compounds that appear in low concentrations. We therefore developed a method for predicting emissions of chemicals from households into wastewater, relying on consumption patterns from multiple data sources. The method was then used to predict the emissions of chemical preparations, chemicals leaching from textiles and prescription pharmaceuticals in Sweden. In total we predicted emissions of 2007 chemicals with a combined emission of 62,659 tonnes per year - or 18 g/person and day. Of the emitted chemicals, 2.0% (w/w) were either classified as hazardous to the environment or were both persistent and mobile. We also show that chemical emissions come from a wide range of uses and that the total emission of any individual chemical is determined primarily by its use pattern, not by the total amount used. This emphasizes the need for continuous updates and additional knowledge generation both on emission factors and excretion rates as well as a need for improved reporting on the intended use of individual chemicals. Finally, we scrutinize the model and its uncertainty and suggest areas that need improvement to increase the accuracy of future emission modelling. We conclude that emission modelling can help guide environmental monitoring and provide input into management strategies aimed at reducing the environmental effect caused by hazardous chemicals.

GEnView: a gene-centric, phylogeny-based comparative genomics pipeline for bacterial genomes and plasmids

SUMMARY

Comparing genomic loci of a given bacterial gene across strains and species can provide insights into their evolution, including information on e.g. acquired mobility, the degree of conservation between different taxa or indications of horizontal gene transfer events. While thousands of bacterial genomes are available to date, there is no software that facilitates comparisons of individual gene loci for a large number of genomes. GEnView (Genetic Environment View) is a Python-based pipeline for the comparative analysis of gene-loci in a large number of bacterial genomes, providing users with automated, taxon-selective access to the >800.000 genomes and plasmids currently available in the NCBI Assembly and RefSeq databases, and is able to process local genomes that are not deposited at NCBI, enabling searches for genomic sequences and to analyze their genetic environments through the interactive visualization and extensive metadata files created by GEnView.

AVAILABILITY AND IMPLEMENTATION

GEnView is implemented in Python 3. Instructions for download and usage can be found at https://github.com/EbmeyerSt/GEnView under GLP3.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Detection of structural variations in densely-labelled optical DNA barcodes: A hidden Markov model approach

Large-scale genomic alterations play an important role in disease, gene expression, and chromosome evolution. Optical DNA mapping (ODM), commonly categorized into sparsely-labelled ODM and densely-labelled ODM, provides sequence-specific continuous intensity profiles (DNA barcodes) along single DNA molecules and is a technique well-suited for detecting such alterations. For sparsely-labelled barcodes, the possibility to detect large genomic alterations has been investigated extensively, while densely-labelled barcodes have not received as much attention. In this work, we introduce HMMSV, a hidden Markov model (HMM) based algorithm for detecting structural variations (SVs) directly in densely-labelled barcodes without access to sequence information. We evaluate our approach using simulated data-sets with 5 different types of SVs, and combinations thereof, and demonstrate that the method reaches a true positive rate greater than 80% for randomly generated barcodes with single variations of size 25 kilobases (kb). Increasing the length of the SV further leads to larger true positive rates. For a real data-set with experimental barcodes on bacterial plasmids, we successfully detect matching barcode pairs and SVs without any particular assumption of the types of SVs present. Instead, our method effectively goes through all possible combinations of SVs. Since ODM works on length scales typically not reachable with other techniques, our methodology is a promising tool for identifying arbitrary combinations of genomic alterations.

Structural and biochemical characterization of the environmental MBLs MYO-1, ECV-1 and SHD-1

BACKGROUND

MBLs form a large and heterogeneous group of bacterial enzymes conferring resistance to β-lactam antibiotics, including carbapenems. A large environmental reservoir of MBLs has been identified, which can act as a source for transfer into human pathogens. Therefore, structural investigation of environmental and clinically rare MBLs can give new insights into structure-activity relationships to explore the role of catalytic and second shell residues, which are under selective pressure.

OBJECTIVES

To investigate the structure and activity of the environmental subclass B1 MBLs MYO-1, SHD-1 and ECV-1.

METHODS

The respective genes of these MBLs were cloned into vectors and expressed in Escherichia coli. Purified enzymes were characterized with respect to their catalytic efficiency (kcat/Km). The enzymatic activities and MICs were determined for a panel of different β-lactams, including penicillins, cephalosporins and carbapenems. Thermostability was measured and structures were solved using X-ray crystallography (MYO-1 and ECV-1) or generated by homology modelling (SHD-1).

RESULTS

Expression of the environmental MBLs in E. coli resulted in the characteristic MBL profile, not affecting aztreonam susceptibility and decreasing susceptibility to carbapenems, cephalosporins and penicillins. The purified enzymes showed variable catalytic activity in the order of <5% to ∼70% compared with the clinically widespread NDM-1. The thermostability of ECV-1 and SHD-1 was up to 8°C higher than that of MYO-1 and NDM-1. Using solved structures and molecular modelling, we identified differences in their second shell composition, possibly responsible for their relatively low hydrolytic activity.

CONCLUSIONS

These results show the importance of environmental species acting as reservoirs for MBL-encoding genes.

An updated phylogeny of the metallo-β-lactamases

BACKGROUND

Metallo-β-lactamases (MBLs) are enzymes that use zinc-dependent hydrolysis to confer resistance to almost all available β-lactam antibiotics. They are hypothesized to originate from commensal and environmental bacteria, from where some have mobilized and transferred horizontally to pathogens. The current phylogeny of MBLs, however, is biased as it is founded largely on genes encountered in pathogenic bacteria. This incompleteness is emphasized by recent findings of environmental MBLs with new forms of zinc binding sites and atypical functional profiles.

OBJECTIVES

To expand the phylogeny of MBLs to provide a more accurate view of their evolutionary history.

METHODS

We searched more than 16 terabases of genomic and metagenomic data for MBLs of the three subclasses B1, B2 and B3 using the validated fARGene method. Predicted genes, together with the previously known ones, were used to infer phylogenetic trees.

RESULTS

We identified 2290 unique MBL genes forming 817 gene families, of which 741 were previously uncharacterized. MBLs from subclasses B1 and B3 separated into distinct monophyletic groups, in agreement with their taxonomic and functional properties. We present evidence that clinically associated MBLs were mobilized from Proteobacteria. Additionally, we identified three new variants of the zinc binding sites, indicating that the functional repertoire is broader than previously reported.

CONCLUSIONS

Based on our results, we recommend that the nomenclature of MBLs is refined into the phylogenetic groups B1.1-B1.5 and B3.1-B3.4 that more accurately describe their molecular and functional characteristics. Our results will also facilitate the annotation of novel MBLs, reflecting their taxonomic organization and evolutionary origin.

CMY-1/MOX-family AmpC β-lactamases MOX-1, MOX-2 and MOX-9 were mobilized independently from three Aeromonas species

Objectives

To investigate the origin of CMY-1/MOX-family β-lactamases.

Methods

Publicly available genome assemblies were screened for CMY-1/MOX genes. The loci of CMY-1/MOX genes were compared with respect to synteny and nucleotide identity, and subjected to phylogenetic analysis.

Results

The chromosomal ampC genes of several Aeromonas species were highly similar to known mobile CMY-1/MOX variants. Annotation and sequence comparison revealed nucleotide identities >98% and conserved syntenies between MOX-1-, MOX-2- and MOX-9-associated mobile sequences and the chromosomal Aeromonas sanarellii, Aeromonas caviae and Aeromonas media ampC loci. Furthermore, the phylogenetic analysis showed that MOX-1, MOX-2 and MOX-9 formed three distinct monophyletic groups with the chromosomal ampC genes of A. sanarellii, A. caviae and A. media, respectively.

Conclusions

Our findings show that three CMY-1/MOX-family β-lactamases were mobilized independently from three Aeromonas species and hence shine new light on the evolution and emergence of mobile antibiotic resistance genes.

SMAD4 haploinsufficiency in small intestinal neuroendocrine tumors

BACKGROUND

Patients with small intestinal neuroendocrine tumors (SINETs) frequently present with lymph node and liver metastases at the time of diagnosis, but the molecular changes that lead to the progression of these tumors are largely unknown. Sequencing studies have only identified recurrent point mutations at low frequencies with CDKN1B being the most common harboring heterozygous mutations in less than 10% of all tumors. Although SINETs are genetically stable tumors with a low frequency of point mutations and indels, they often harbor recurrent hemizygous copy number alterations (CNAs) yet the functional implications of these CNA are unclear.

METHODS

Utilizing comparative genomic hybridization (CGH) arrays we analyzed the CNA profile of 131 SINETs from 117 patients. Two tumor suppressor genes and corresponding proteins i.e. SMAD4, and CDKN1B, were further characterized using a tissue microarray (TMA) with 846 SINETs. Immunohistochemistry (IHC) was used to quantify protein expression in TMA samples and this was correlated with chromosome number evaluated with fluorescent in-situ hybridization (FISH). Intestinal tissue from a Smad4^+/- mouse model was used to detect entero-endocrine cell hyperplasia with IHC.

RESULTS

Analyzing the CGH arrays we found loss of chromosome 18q and SMAD4 in 71% of SINETs and that focal loss of chromosome 12 affecting the CDKN1B was present in 9.4% of SINETs. No homozygous loss of chromosome 18 was detected. Hemizygous loss of SMAD4, but not CDKN1B, significantly correlated with reduced protein levels but hemizygous loss of SMAD4 did not induce entero-endocrine cell hyperplasia in the Smad4^+/- mouse model. In addition, patients with low SMAD4 protein expression in primary tumors more often presented with metastatic disease.

CONCLUSIONS

Hemizygous loss of chromosome 18q and the SMAD4 gene is the most common genetic event in SINETs and our results suggests that this could influence SMAD4 protein expression and spread of metastases. Although SMAD4 haploinsufficiency alone did not induce tumor initiation, loss of chromosome 18 could represent an evolutionary advantage in SINETs explaining the high prevalence of this aberration. Functional consequences of reduced SMAD4 protein levels could hypothetically be a potential mechanism as to why loss of chromosome 18 appears to be clonally selected in SINETs.

Predicting clinical resistance prevalence using sewage metagenomic data

Antibiotic resistance surveillance through regional and up-to-date testing of clinical isolates is a foundation for implementing effective empirical treatment. Surveillance data also provides an overview of geographical and temporal changes that are invaluable for guiding interventions. Still, due to limited infrastructure and resources, clinical surveillance data is lacking in many parts of the world. Given that sewage is largely made up of human fecal bacteria from many people, sewage epidemiology could provide a cost-efficient strategy to partly fill the current gap in clinical surveillance of antibiotic resistance. Here we explored the potential of sewage metagenomic data to assess clinical antibiotic resistance prevalence using environmental and clinical surveillance data from across the world. The sewage resistome correlated to clinical surveillance data of invasive Escherichia coli isolates, but none of several tested approaches provided a sufficient resolution for clear discrimination between resistance towards different classes of antibiotics. However, in combination with socioeconomic data, the overall clinical resistance situation could be predicted with good precision. We conclude that analyses of bacterial genes in sewage could contribute to informing management of antibiotic resistance.

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.

When mycologists describe new species, not all relevant information is provided (clearly enough)

Taxonomic mycology struggles with what seems to be a perpetual shortage of resources. Logically, fungal taxonomists should therefore leverage every opportunity to highlight and visualize the importance of taxonomic work, the usefulness of taxonomic data far beyond taxonomy, and the integrative and collaborative nature of modern taxonomy at large. Is mycology really doing that, though? In this study, we went through ten years' worth (2009-2018) of species descriptions of extant fungal taxa - 1,097 studies describing at most ten new species - in five major mycological journals plus one plant journal. We estimated the frequency at which a range of key words, illustrations, and concepts related to ecology, geography, taxonomy, molecular data, and data availability were provided with the descriptions. We also considered a range of science-demographical aspects such as gender bias and the rejuvenation of taxonomy and taxonomists as well as public availability of the results. Our results show that the target audience of fungal species descriptions appears to be other fungal taxonomists, because many aspects of the new species were presented only implicitly, if at all. Although many of the parameters we estimated show a gradual, and in some cases marked, change for the better over time, they still paint a somewhat bleak picture of mycological taxonomy as a male-dominated field where the wants and needs of an extended target audience are often not understood or even considered. This study hopes to leave a mark on the way fungal species are described by putting the focus on ways in which fungal taxonomy can better anticipate the end users of species descriptions - be they mycologists, other researchers, the public at large, or even algorithms. In the end, fungal taxonomy, too, is likely to benefit from such measures.

A comprehensive survey of integron-associated genes present in metagenomes

Background

Integrons are genomic elements that mediate horizontal gene transfer by inserting and removing genetic material using site-specific recombination. Integrons are commonly found in bacterial genomes, where they maintain a large and diverse set of genes that plays an important role in adaptation and evolution. Previous studies have started to characterize the wide range of biological functions present in integrons. However, the efforts have so far mainly been limited to genomes from cultivable bacteria and amplicons generated by PCR, thus targeting only a small part of the total integron diversity. Metagenomic data, generated by direct sequencing of environmental and clinical samples, provides a more holistic and unbiased analysis of integron-associated genes. However, the fragmented nature of metagenomic data has previously made such analysis highly challenging.

Results

Here, we present a systematic survey of integron-associated genes in metagenomic data. The analysis was based on a newly developed computational method where integron-associated genes were identified by detecting their associated recombination sites. By processing contiguous sequences assembled from more than 10 terabases of metagenomic data, we were able to identify 13,397 unique integron-associated genes. Metagenomes from marine microbial communities had the highest occurrence of integron-associated genes with levels more than 100-fold higher than in the human microbiome. The identified genes had a large functional diversity spanning over several functional classes. Genes associated with defense mechanisms and mobility facilitators were most overrepresented and more than five times as common in integrons compared to other bacterial genes. As many as two thirds of the genes were found to encode proteins of unknown function. Less than 1% of the genes were associated with antibiotic resistance, of which several were novel, previously undescribed, resistance gene variants.

Conclusions

Our results highlight the large functional diversity maintained by integrons present in unculturable bacteria and significantly expands the number of described integron-associated genes.

MYO5B mutations in pheochromocytoma/paraganglioma promote cancer progression

Identification of additional cancer-associated genes and secondary mutations driving the metastatic progression in pheochromocytoma and paraganglioma (PPGL) is important for subtyping, and may provide optimization of therapeutic regimens. We recently reported novel recurrent nonsynonymous mutations in the MYO5B gene in metastatic PPGL. Here, we explored the functional impact of these MYO5B mutations, and analyzed MYO5B expression in primary PPGL tumor cases in relation to mutation status. Immunohistochemistry and mRNA expression analysis in 30 PPGL tumors revealed an increased MYO5B expression in metastatic compared to non-metastatic cases. In addition, subcellular localization of MYO5B protein was altered from cytoplasmic to membranous in some metastatic tumors, and the strongest and most abnormal expression pattern was observed in a paraganglioma harboring a somatic MYO5B:p.G1611S mutation. In addition to five previously discovered MYO5B mutations, the present study of 30 PPGL (8 previous and 22 new samples) also revealed two, and hence recurrent, mutations in the gene paralog MYO5A. The three MYO5B missense mutations with the highest prediction scores (p.L587P, p.G1611S and p.R1641C) were selected and functionally validated using site directed mutagenesis and stable transfection into human neuroblastoma cells (SK-N-AS) and embryonic kidney cells (HEK293). In vitro analysis showed a significant increased proliferation rate in all three MYO5B mutated clones. The two somatically derived mutations, p.L587P and p.G1611S, were also found to increase the migration rate. Expression analysis of MYO5B mutants compared to wild type clones, demonstrated a significant enrichment of genes involved in migration, proliferation, cell adhesion, glucose metabolism, and cellular homeostasis. Our study validates the functional role of novel MYO5B mutations in proliferation and migration, and suggest the MYO5-pathway to be involved in the malignant progression in some PPGL tumors.

Up to 25% of pheochromocytoma/paraganglioma (PPGL) cases develop metastatic disease with poor outcome and few treatment options. The disease mechanism is not fully understood, and to date there are no reliable markers to predict malignancy. We have recently discovered novel missense mutations in the non-conventional myosin 5 gene (MYO5B), an endosomal transport protein, which we now show enhances progression and migration in PPGLs. MYO5B mutations were preferentially found in patients with metastatic disease and SDH deficiency (germline SDHB-mutations). Abolished SDH activity result in a metabolic switch to aerobic glycolysis requiring increased glucose consumption. Since the MYO5B mutations were found to drive progression through downstream up-regulation of glucose metabolism genes, e.g. glucagon, we hypothesize that these mutations may fuel the pseudohypoxic state by altering glucose uptake in cancer cells. Our result is the first to link the myosin 5 genes to PPGL tumorigenesis. Further, it shows that the tumor progression route in PPGL is complex, with contribution from several genetic factors. An increasing number of studies show dysregulation and importance of the MYO5-proteins in cancer, but little is still known about the precise role and mechanism of mutations, hence more research in this area is needed.

Cultivation-Free Typing of Bacteria Using Optical DNA Mapping

A variety of pathogenic bacteria can infect humans, and rapid species identification is crucial for the correct treatment. However, the identification process can often be time-consuming and depend on the cultivation of the bacterial pathogen(s). Here, we present a stand-alone, enzyme-free, optical DNA mapping assay capable of species identification by matching the intensity profiles of large DNA molecules to a database of fully assembled bacterial genomes (>10 000). The assay includes a new data analysis strategy as well as a general DNA extraction protocol for both Gram-negative and Gram-positive bacteria. We demonstrate that the assay is capable of identifying bacteria directly from uncultured clinical urine samples, as well as in mixtures, with the potential to be discriminative even at the subspecies level. We foresee that the assay has applications both within research laboratories and in clinical settings, where the time-consuming step of cultivation can be minimized or even completely avoided.

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.