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.

BacMet: antibacterial biocide and metal resistance genes database

Antibiotic resistance has become a major human health concern due to widespread use, misuse and overuse of antibiotics. In addition to antibiotics, antibacterial biocides and metals can contribute to the development and maintenance of antibiotic resistance in bacterial communities through co-selection. Information on metal and biocide resistance genes, including their sequences and molecular functions, is, however, scattered. Here, we introduce BacMet (http://bacmet.biomedicine.gu.se)—a manually curated database of antibacterial biocide- and metal-resistance genes based on an in-depth review of the scientific literature. The BacMet database contains 470 experimentally verified resistance genes. In addition, the database also contains 25 477 potential resistance genes collected from public sequence repositories. All resistance genes in the BacMet database have been organized according to their molecular function and induced resistance phenotype.

Intraspecific ITS variability in the kingdom fungi as expressed in the international sequence databases and its implications for molecular species identification

The internal transcribed spacer (ITS) region of the nuclear ribosomal repeat unit is the most popular locus for species identification and subgeneric phylogenetic inference in sequence-based mycological research. The region is known to show certain variability even within species, although its intraspecific variability is often held to be limited and clearly separated from interspecific variability. The existence of such a divide between intra- and interspecific variability is implicitly assumed by automated approaches to species identification, but whether intraspecific variability indeed is negligible within the fungal kingdom remains contentious. The present study estimates the intraspecific ITS variability in all fungi presently available to the mycological community through the international sequence databases. Substantial differences were found within the kingdom, and the results are not easily correlated to the taxonomic affiliation or nutritional mode of the taxa considered. No single unifying yet stringent upper limit for intraspecific variability, such as the canonical 3% threshold, appears to be applicable with the desired outcome throughout the fungi. Our results caution against simplified approaches to automated ITS-based species delimitation and reiterate the need for taxonomic expertise in the translation of sequence data into species names.

Co-occurrence of resistance genes to antibiotics, biocides and metals reveals novel insights into their co-selection potential

BACKGROUND

Antibacterial biocides and metals can co-select for antibiotic resistance when bacteria harbour resistance or tolerance genes towards both types of compounds. Despite numerous case studies, systematic and quantitative data on co-occurrence of such genes on plasmids and chromosomes is lacking, as is knowledge on environments and bacterial taxa that tend to carry resistance genes to such compounds. This effectively prevents identification of risk scenarios. Therefore, we aimed to identify general patterns for which biocide/metal resistance genes (BMRGs) and antibiotic resistance genes (ARGs) that tend to occur together. We also aimed to quantify co-occurrence of resistance genes in different environments and taxa, and investigate to what extent plasmids carrying both types of genes are conjugative and/or are carrying toxin-antitoxin systems.

RESULTS

Co-occurrence patterns of resistance genes were derived from publicly available, fully sequenced bacterial genomes (n = 2522) and plasmids (n = 4582). The only BMRGs commonly co-occurring with ARGs on plasmids were mercury resistance genes and the qacE∆1 gene that provides low-level resistance to quaternary ammonium compounds. Novel connections between cadmium/zinc and macrolide/aminoglycoside resistance genes were also uncovered. Several clinically important bacterial taxa were particularly prone to carry both BMRGs and ARGs. Bacteria carrying BMRGs more often carried ARGs compared to bacteria without (p < 0.0001). BMRGs were found in 86 % of bacterial genomes, and co-occurred with ARGs in 17 % of the cases. In contrast, co-occurrences of BMRGs and ARGs were rare on plasmids from all external environments (<0.7 %) but more common on those of human and domestic animal origin (5 % and 7 %, respectively). Finally, plasmids with both BMRGs and ARGs were more likely to be conjugative (p < 0.0001) and carry toxin-antitoxin systems (p < 0.0001) than plasmids without resistance genes.

CONCLUSIONS

This is the first large-scale identification of compounds, taxa and environments of particular concern for co-selection of resistance against antibiotics, biocides and metals. Genetic co-occurrences suggest that plasmids provide limited opportunities for biocides and metals to promote horizontal transfer of antibiotic resistance through co-selection, whereas ample possibilities exist for indirect selection via chromosomal BMRGs. Taken together, the derived patterns improve our understanding of co-selection potential between biocides, metals and antibiotics, and thereby provide guidance for risk-reducing actions.

Evolutionary conservation of human drug targets in organisms used for environmental risk assessments

Pharmaceuticals are typically found in very low concentrations in the aquatic environment. Accordingly, environmental effects clearly assigned to residual drugs are consistent with high affinity interactions with conserved targets in affected wildlife species rather than with a general toxic effect. Thus, evolutionarily well-conserved targets in a given species are associated with an increased risk. In this study orthologs for 1318 human drug targets were predicted in 16 species of which several are relevant for ecotoxicity testing. The conservation of different functional categories of targets was also analyzed. Zebrafish had orthologs to 86% of the drug targets while only 61% were conserved in Daphnia and 35% in green alga. The predicted presence and absence of orthologs agrees well with published experimental data on the potential for specific drug target interaction in various species. Based on the conservation of targets we propose that aquatic environmental risk assessments for human drugs should always include comprehensive studies on aquatic vertebrates. Furthermore, individual targets, especially enzymes, are well conserved suggesting that tests on evolutionarily distant organisms would be highly relevant for certain drugs. We propose that the results can guide environmental risk assessments by improving the possibilities to identify species sensitive to certain types of pharmaceuticals or to other contaminants that act through well defined mechanisms of action. Moreover, we suggest that the results can be used to interpret the relevance of existing ecotoxicity data.

Taxonomic reliability of DNA sequences in public sequence databases: a fungal perspective

BACKGROUND

DNA sequences are increasingly seen as one of the primary information sources for species identification in many organism groups. Such approaches, popularly known as barcoding, are underpinned by the assumption that the reference databases used for comparison are sufficiently complete and feature correctly and informatively annotated entries.

METHODOLOGY/PRINCIPAL FINDINGS

The present study uses a large set of fungal DNA sequences from the inclusive International Nucleotide Sequence Database to show that the taxon sampling of fungi is far from complete, that about 20% of the entries may be incorrectly identified to species level, and that the majority of entries lack descriptive and up-to-date annotations.

CONCLUSIONS

The problems with taxonomic reliability and insufficient annotations in public DNA repositories form a tangible obstacle to sequence-based species identification, and it is manifest that the greatest challenges to biological barcoding will be of taxonomical, rather than technical, nature.

Pyrosequencing of antibiotic-contaminated river sediments reveals high levels of resistance and gene transfer elements

The high and sometimes inappropriate use of antibiotics has accelerated the development of antibiotic resistance, creating a major challenge for the sustainable treatment of infections world-wide. Bacterial communities often respond to antibiotic selection pressure by acquiring resistance genes, i.e. mobile genetic elements that can be shared horizontally between species. Environmental microbial communities maintain diverse collections of resistance genes, which can be mobilized into pathogenic bacteria. Recently, exceptional environmental releases of antibiotics have been documented, but the effects on the promotion of resistance genes and the potential for horizontal gene transfer have yet received limited attention. In this study, we have used culture-independent shotgun metagenomics to investigate microbial communities in river sediments exposed to waste water from the production of antibiotics in India. Our analysis identified very high levels of several classes of resistance genes as well as elements for horizontal gene transfer, including integrons, transposons and plasmids. In addition, two abundant previously uncharacterized resistance plasmids were identified. The results suggest that antibiotic contamination plays a role in the promotion of resistance genes and their mobilization from environmental microbes to other species and eventually to human pathogens. The entire life-cycle of antibiotic substances, both before, under and after usage, should therefore be considered to fully evaluate their role in the promotion of resistance.

The structure and diversity of human, animal and environmental resistomes

BACKGROUND

Antibiotic resistance genes (ARGs) are widespread but cause problems only when present in pathogens. Environments where selection and transmission of antibiotic resistance frequently take place are likely to be characterized by high abundance and diversity of horizontally transferable ARGs. Large-scale quantitative data on ARGs is, however, lacking for most types of environments, including humans and animals, as is data on resistance genes to potential co-selective agents, such as biocides and metals. This paucity prevents efficient identification of risk environments.

RESULTS

We provide a comprehensive characterization of resistance genes, mobile genetic elements (MGEs) and bacterial taxonomic compositions for 864 metagenomes from humans (n = 350), animals (n = 145) and external environments (n = 369), all deeply sequenced using Illumina technology. Environment types showed clear differences in both resistance profiles and bacterial community compositions. Human and animal microbial communities were characterized by limited taxonomic diversity and low abundance and diversity of biocide/metal resistance genes and MGEs but a relatively high abundance of ARGs. In contrast, external environments showed consistently high taxonomic diversity which in turn was linked to high diversity of both biocide/metal resistance genes and MGEs. Water, sediment and soil generally carried low relative abundance and few varieties of known ARGs, whereas wastewater/sludge was on par with the human gut. The environments with the largest relative abundance and/or diversity of ARGs, including genes encoding resistance to last resort antibiotics, were those subjected to industrial antibiotic pollution and a limited set of deeply sequenced air samples from a Beijing smog event.

CONCLUSIONS

Our study identifies air and antibiotic-polluted environments as under-investigated transmission routes and reservoirs for antibiotic resistance. The high taxonomic and genetic diversity of external environments supports the hypothesis that these also form vast sources of unknown resistance genes, with potential to be transferred to pathogens in the future.

Elucidating selection processes for antibiotic resistance in sewage treatment plants using metagenomics

Sewage treatment plants (STPs) have repeatedly been suggested as "hotspots" for the emergence and dissemination of antibiotic-resistant bacteria. A critical question still unanswered is if selection pressures within STPs, caused by residual antibiotics or other co-selective agents, are sufficient to specifically promote resistance. To address this, we employed shotgun metagenomic sequencing of samples from different steps of the treatment process in three Swedish STPs. In parallel, concentrations of selected antibiotics, biocides and metals were analyzed. We found that concentrations of tetracycline and ciprofloxacin in the influent were above predicted concentrations for resistance selection, however, there was no consistent enrichment of resistance genes to any particular class of antibiotics in the STPs, neither for biocide and metal resistance genes. The most substantial change of the bacterial communities compared to human feces occurred already in the sewage pipes, manifested by a strong shift from obligate to facultative anaerobes. Through the treatment process, resistance genes against antibiotics, biocides and metals were not reduced to the same extent as fecal bacteria. The OXA-48 gene was consistently enriched in surplus and digested sludge. We find this worrying as OXA-48, still rare in Swedish clinical isolates, provides resistance to carbapenems, one of our most critically important classes of antibiotics. Taken together, metagenomics analyses did not provide clear support for specific antibiotic resistance selection. However, stronger selective forces affecting gross taxonomic composition, and with that resistance gene abundances, limit interpretability. Comprehensive analyses of resistant/non-resistant strains within relevant species are therefore warranted.

The ITS region as a target for characterization of fungal communities using emerging sequencing technologies

The advent of new high-throughput DNA-sequencing technologies promises to redefine the way in which fungi and fungal communities--as well as other groups of organisms--are studied in their natural environment. With read lengths of some few hundred base pairs, massively parallel sequencing (pyrosequencing) stands out among the new technologies as the most apt for large-scale species identification in environmental samples. Although parallel pyrosequencing can generate hundreds of thousands of sequences at an exceptional speed, the limited length of the reads may pose a problem to the species identification process. This study explores whether the discrepancy in read length between parallel pyrosequencing and traditional (Sanger) sequencing will have an impact on the perceived taxonomic affiliation of the underlying species. Based on all 39,200 publicly available fungal environmental DNA sequences representing the nuclear ribosomal internal transcribed spacer (ITS) region, the results show that the two approaches give rise to quite different views of the diversity of the underlying samples. Standardization of which subregion from the ITS region should be sequenced, as well as a recognition that the composition of fungal communities as depicted through different sequencing methods need not be directly comparable, appear crucial to the integration of the new sequencing technologies with current mycological praxis.

Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India

There is increasing evidence for an environmental origin of many antibiotic resistance genes. Consequently, it is important to identify environments of particular risk for selecting and maintaining such resistance factors. In this study, we described the diversity of antibiotic resistance genes in an Indian lake subjected to industrial pollution with fluoroquinolone antibiotics. We also assessed the genetic context of the identified resistance genes, to try to predict their genetic transferability. The lake harbored a wide range of resistance genes (81 identified gene types) against essentially every major class of antibiotics, as well as genes responsible for mobilization of genetic material. Resistance genes were estimated to be 7000 times more abundant than in a Swedish lake included for comparison, where only eight resistance genes were found. The sul2 and qnrD genes were the most common resistance genes in the Indian lake. Twenty-six known and 21 putative novel plasmids were recovered in the Indian lake metagenome, which, together with the genes found, indicate a large potential for horizontal gene transfer through conjugation. Interestingly, the microbial community of the lake still included a wide range of taxa, suggesting that, across most phyla, bacteria has adapted relatively well to this highly polluted environment. Based on the wide range and high abundance of known resistance factors we have detected, it is plausible that yet unrecognized resistance genes are also present in the lake. Thus, we conclude that environments polluted with waste from antibiotic manufacturing could be important reservoirs for mobile antibiotic resistance genes.

A Comprehensive, Automatically Updated Fungal ITS Sequence Dataset for Reference-Based Chimera Control in Environmental Sequencing Efforts

The nuclear ribosomal internal transcribed spacer (ITS) region is the most commonly chosen genetic marker for the molecular identification of fungi in environmental sequencing and molecular ecology studies. Several analytical issues complicate such efforts, one of which is the formation of chimeric—artificially joined—DNA sequences during PCR amplification or sequence assembly. Several software tools are currently available for chimera detection, but rely to various degrees on the presence of a chimera-free reference dataset for optimal performance. However, no such dataset is available for use with the fungal ITS region. This study introduces a comprehensive, automatically updated reference dataset for fungal ITS sequences based on the UNITE database for the molecular identification of fungi. This dataset supports chimera detection throughout the fungal kingdom and for full-length ITS sequences as well as partial (ITS1 or ITS2 only) datasets. The performance of the dataset on a large set of artificial chimeras was above 99.5%, and we subsequently used the dataset to remove nearly 1,000 compromised fungal ITS sequences from public circulation. The dataset is available at http://unite.ut.ee/repository.php and is subject to web-based third-party curation.

Fluoroquinolones and qnr genes in sediment, water, soil, and human fecal flora in an environment polluted by manufacturing discharges

There is increasing concern that environmental antibiotic pollution promotes transfer of resistance genes to the human microbiota. Here, fluoroquinolone-polluted river sediment, well water, irrigated farmland, and human fecal flora of local villagers within a pharmaceutical industrial region in India were analyzed for quinolone resistance (qnr) genes by quantitative PCR. Similar samples from Indian villages farther away from industrial areas, as well as fecal samples from Swedish study participants and river sediment from Sweden, were included for comparison. Fluoroquinolones were detected by MS/MS in well water and soil from all villages located within three km from industrially polluted waterways. Quinolone resistance genes were detected in 42% of well water, 7% of soil samples and in 100% and 18% of Indian and Swedish river sediments, respectively. High antibiotic concentrations in Indian sediment coincided with high abundances of qnr, whereas lower fluoroquinolone levels in well water and soil did not. We could not find support for an enrichment of qnr in fecal samples from people living in the fluoroquinolone-contaminated villages. However, as qnr was detected in 91% of all Indian fecal samples (24% of the Swedish) it suggests that the spread of qnr between people is currently a dominating transmission route.

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.

ShotgunFunctionalizeR: an R-package for functional comparison of metagenomes

Microorganisms are ubiquitous in nature and constitute intrinsic parts of almost every ecosystem. A culture-independent and powerful way to study microbial communities is metagenomics. In such studies, functional analysis is performed on fragmented genetic material from multiple species in the community. The recent advances in high-throughput sequencing have greatly increased the amount of data in metagenomic projects. At present, there is an urgent need for efficient statistical tools to analyse these data. We have created ShotgunFunctionalizeR, an R-package for functional comparison of metagenomes. The package contains tools for importing, annotating and visualizing metagenomic data produced by shotgun high-throughput sequencing. ShotgunFunctionalizeR contains several statistical procedures for assessing functional differences between samples, both for individual genes and for entire pathways. In addition to standard and previously published methods, we have developed and implemented a novel approach based on a Poisson model. This procedure is highly flexible and thus applicable to a wide range of different experimental designs. We demonstrate the potential of ShotgunFunctionalizeR by performing a regression analysis on metagenomes sampled at multiple depths in the Pacific Ocean.

AVAILABILITY

http://shotgun.zool.gu.se

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.

Mining metadata from unidentified ITS sequences in GenBank: a case study in Inocybe (Basidiomycota)

BACKGROUND

The lack of reference sequences from well-identified mycorrhizal fungi often poses a challenge to the inference of taxonomic affiliation of sequences from environmental samples, and many environmental sequences are thus left unidentified. Such unidentified sequences belonging to the widely distributed ectomycorrhizal fungal genus Inocybe (Basidiomycota) were retrieved from GenBank and divided into species that were identified in a phylogenetic context using a reference dataset from an ongoing study of the genus. The sequence metadata of the unidentified Inocybe sequences stored in GenBank, as well as data from the corresponding original papers, were compiled and used to explore the ecology and distribution of the genus. In addition, the relative occurrence of Inocybe was contrasted to that of other mycorrhizal genera.

RESULTS

Most species of Inocybe were found to have less than 3% intraspecific variability in the ITS2 region of the nuclear ribosomal DNA. This cut-off value was used jointly with phylogenetic analysis to delimit and identify unidentified Inocybe sequences to species level. A total of 177 unidentified Inocybe ITS sequences corresponding to 98 species were recovered, 32% of which were successfully identified to species level in this study. These sequences account for an unexpectedly large proportion of the publicly available unidentified fungal ITS sequences when compared with other mycorrhizal genera. Eight Inocybe species were reported from multiple hosts and some even from hosts forming arbutoid or orchid mycorrhizae. Furthermore, Inocybe sequences have been reported from four continents and in climate zones ranging from cold temperate to equatorial climate. Out of the 19 species found in more than one study, six were found in both Europe and North America and one was found in both Europe and Japan, indicating that at least many north temperate species have a wide distribution.

CONCLUSION

Although DNA-based species identification and circumscription are associated with practical and conceptual difficulties, they also offer new possibilities and avenues for research. Metadata assembly holds great potential to synthesize valuable information from community studies for use in a species and taxonomy-oriented framework.

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.

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.

Quantitative transcriptome, proteome, and sulfur metabolite profiling of the Saccharomyces cerevisiae response to arsenite

Arsenic is ubiquitously present in nature, and various mechanisms have evolved enabling cells to evade toxicity and acquire tolerance. Herein, we explored how Saccharomyces cerevisiae (budding yeast) respond to trivalent arsenic (arsenite) by quantitative transcriptome, proteome, and sulfur metabolite profiling. Arsenite exposure affected transcription of genes encoding functions related to protein biosynthesis, arsenic detoxification, oxidative stress defense, redox maintenance, and proteolytic activity. Importantly, we observed that nearly all components of the sulfate assimilation and glutathione biosynthesis pathways were induced at both gene and protein levels. Kinetic metabolic profiling evidenced a significant increase in the pools of sulfur metabolites as well as elevated cellular glutathione levels. Moreover, the flux in the sulfur assimilation pathway as well as the glutathione synthesis rate strongly increased with a concomitant reduction of sulfur incorporation into proteins. By combining comparative genomics and molecular analyses, we pinpointed transcription factors that mediate the core of the transcriptional response to arsenite. Taken together, our data reveal that arsenite-exposed cells channel a large part of assimilated sulfur into glutathione biosynthesis, and we provide evidence that the transcriptional regulators Yap1p and Met4p control this response in concert.

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.

Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics

Background

Metagenomics is the study of microbial communities by sequencing of genetic material directly from environmental or clinical samples. The genes present in the metagenomes are quantified by annotating and counting the generated DNA fragments. Identification of differentially abundant genes between metagenomes can provide important information about differences in community structure, diversity and biological function. Metagenomic data is however high-dimensional, contain high levels of biological and technical noise and have typically few biological replicates. The statistical analysis is therefore challenging and many approaches have been suggested to date.

Results

In this article we perform a comprehensive evaluation of 14 methods for identification of differentially abundant genes between metagenomes. The methods are compared based on the power to detect differentially abundant genes and their ability to correctly estimate the type I error rate and the false discovery rate. We show that sample size, effect size, and gene abundance greatly affect the performance of all methods. Several of the methods also show non-optimal model assumptions and biased false discovery rate estimates, which can result in too large numbers of false positives. We also demonstrate that the performance of several of the methods differs substantially between metagenomic data sequenced by different technologies.

Conclusions

Two methods, primarily designed for the analysis of RNA sequencing data (edgeR and DESeq2) together with a generalized linear model based on an overdispersed Poisson distribution were found to have best overall performance. The results presented in this study may serve as a guide for selecting suitable statistical methods for identification of differentially abundant genes in metagenomes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2386-y) contains supplementary material, which is available to authorized users.