Characterization of novel antibiotic resistance genes identified by functional metagenomics on soil samples

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

Interplay Between Antimicrobial Resistance and Global Environmental Change

Antibiotic resistance genes predate the therapeutic uses of antibiotics. However, the current antimicrobial resistance crisis stems from our extensive use of antibiotics and the generation of environmental stressors that impose new selective pressure on microbes and drive the evolution of resistant pathogens that now threaten human health. Similar to climate change, this global threat results from human activities that change habitats and natural microbiomes, which in turn interact with human-associated ecosystems and lead to adverse impacts on human health. Human activities that alter our planet at global scales exacerbate the current resistance crisis and exemplify our central role in large-scale changes in which we are both protagonists and architects of our success but also casualties of unanticipated collateral outcomes. As cognizant participants in this ongoing planetary experiment, we are driven to understand and find strategies to curb the ongoing crises of resistance and climate change.

Metagenomic next generation sequencing for studying antibiotic resistance genes in the environment

Bacterial antimicrobial resistance (AMR) is a persisting and growing threat to human health. Characterization of antibiotic resistance genes (ARGs) in the environment is important to understand and control ARG-associated microbial risks. Numerous challenges exist in monitoring ARGs in the environment, due to the extraordinary diversity of ARGs, low abundance of ARGs with respect to the complex environmental microbiomes, difficulties in linking ARGs with bacterial hosts by molecular methods, difficulties in achieving quantification and high throughput simultaneously, difficulties in assessing mobility potential of ARGs, and difficulties in determining the specific AMR determinant genes. Advances in the next generation sequencing (NGS) technologies and related computational and bioinformatic tools are facilitating rapid identification and characterization ARGs in genomes and metagenomes from environmental samples. This chapter discusses NGS-based strategies, including amplicon-based sequencing, whole genome sequencing, bacterial population-targeted metagenome sequencing, metagenomic NGS, quantitative metagenomic sequencing, and functional/phenotypic metagenomic sequencing. Current bioinformatic tools for analyzing sequencing data for studying environmental ARGs are also discussed.

ResFinderFG v2.0: a database of antibiotic resistance genes obtained by functional metagenomics

Metagenomics can be used to monitor the spread of antibiotic resistance genes (ARGs). ARGs found in databases such as ResFinder and CARD primarily originate from culturable and pathogenic bacteria, while ARGs from non-culturable and non-pathogenic bacteria remain understudied. Functional metagenomics is based on phenotypic gene selection and can identify ARGs from non-culturable bacteria with a potentially low identity shared with known ARGs. In 2016, the ResFinderFG v1.0 database was created to collect ARGs from functional metagenomics studies. Here, we present the second version of the database, ResFinderFG v2.0, which is available on the Center of Genomic Epidemiology web server (https://cge.food.dtu.dk/services/ResFinderFG/). It comprises 3913 ARGs identified by functional metagenomics from 50 carefully curated datasets. We assessed its potential to detect ARGs in comparison to other popular databases in gut, soil and water (marine + freshwater) Global Microbial Gene Catalogues (https://gmgc.embl.de). ResFinderFG v2.0 allowed for the detection of ARGs that were not detected using other databases. These included ARGs conferring resistance to beta-lactams, cycline, phenicol, glycopeptide/cycloserine and trimethoprim/sulfonamide. Thus, ResFinderFG v2.0 can be used to identify ARGs differing from those found in conventional databases and therefore improve the description of resistomes.

Longitudinal fluctuations of common antimicrobial resistance genes in the gut microbiomes of healthy Dutch individuals

The human gut microbiome is an important reservoir of antimicrobial resistance genes (ARGs), collectively termed the 'resistome'. To date, few studies have examined the dynamics of the human gut resistome in healthy individuals. Previously, the authors observed high rates of ARG acquisition and significant abundance shifts during international travel. In order to provide insight into commonly occurring dynamics, this study investigated longitudinal fluctuations in prevalent ARGs (cfxA, tetM and ermB) in the resistomes of non-travelling healthy volunteers. In addition, this study assessed the prevalence of acquirable ARGs (bla_CTX-M, qnrB, qnrS, vanA and vanB) over time. Faecal samples from 23 participants were collected at baseline and after 2 and 4 weeks. DNA was isolated, and ARG quantification was performed by quantitative polymerase chain reaction adjusting for the total amount of bacterial 16S rDNA. vanA and qnrS were not detected in any of the samples, while the prevalence rates of vanB of non-enterococcal origin and qnrB were 73.9% and 5.7%, respectively. The ß-lactamase encoding bla_CTX-M was detected in 17.4% of healthy participants. The results were compared with previous data from 122 travellers. ARG acquisitions observed in travellers were rare in non-travelling individuals during 4 weeks of follow-up, supporting the hypothesis of ARG acquisition during international travel. However, median -1.04- to 1.04-fold abundance changes were observed for 100% of cfxA, tetM and ermB, which did not differ from those found in travellers. Thus, common abundance shifts in prevalent ARGs of the gut resistome were found to occur independent of travel behaviour.

A Cross-Validated Feature Selection (CVFS) approach for extracting the most parsimonious feature sets and discovering potential antimicrobial resistance (AMR) biomarkers

Understanding genes and their underlying mechanisms is critical in deciphering how antimicrobial-resistant (AMR) bacteria withstand detrimental effects of antibiotic drugs. At the same time the genes related to AMR phenotypes may also serve as biomarkers for predicting whether a microbial strain is resistant to certain antibiotic drugs. We developed a Cross-Validated Feature Selection (CVFS) approach for robustly selecting the most parsimonious gene sets for predicting AMR activities from bacterial pan-genomes. The core idea behind the CVFS approach is interrogating features among non-overlapping sub-parts of the datasets to ensure the representativeness of the features. By randomly splitting the dataset into disjoint sub-parts, conducting feature selection within each sub-part, and intersecting the features shared by all sub-parts, the CVFS approach is able to achieve the goal of extracting the most representative features for yielding satisfactory AMR activity prediction accuracy. By testing this idea on bacterial pan-genome datasets, we showed that this approach was able to extract the most succinct feature sets that predicted AMR activities very well, indicating the potential of these genes as AMR biomarkers. The functional analysis demonstrated that the CVFS approach was able to extract both known AMR genes and novel ones, suggesting the capabilities of the algorithm in selecting relevant features and highlighting the potential of the novel genes in expanding the antimicrobial resistance gene databases.

Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings

The success of antibiotics as a therapeutic agent has led to their ineffectiveness. The continuous use and misuse in clinical and non-clinical areas have led to the emergence and spread of antibiotic-resistant bacteria and its genetic determinants. This is a multi-dimensional problem that has now become a global health crisis. Antibiotic resistance research has primarily focused on the clinical healthcare sectors while overlooking the non-clinical sectors. The increasing antibiotic usage in the environment - including animals, plants, soil, and water - are drivers of antibiotic resistance and function as a transmission route for antibiotic resistant pathogens and is a source for resistance genes. These natural compartments are interconnected with each other and humans, allowing the spread of antibiotic resistance via horizontal gene transfer between commensal and pathogenic bacteria. Identifying and understanding genetic exchange within and between natural compartments can provide insight into the transmission, dissemination, and emergence mechanisms. The development of high-throughput DNA sequencing technologies has made antibiotic resistance research more accessible and feasible. In particular, the combination of metagenomics and powerful bioinformatic tools and platforms have facilitated the identification of microbial communities and has allowed access to genomic data by bypassing the need for isolating and culturing microorganisms. This review aimed to reflect on the different sequencing techniques, metagenomic approaches, and bioinformatics tools and pipelines with their respective advantages and limitations for antibiotic resistance research. These approaches can provide insight into resistance mechanisms, the microbial population, emerging pathogens, resistance genes, and their dissemination. This information can influence policies, develop preventative measures and alleviate the burden caused by antibiotic resistance.

The Role of Grass Compost and Zea Mays in Alleviating Toxic Effects of Tetracycline on the Soil Bacteria Community

Given their common use for disease treatment in humans, and particularly in animals, antibiotics pose an exceptionally serious threat to the soil environment. This study aimed to determine the response of soil bacteria and oxidoreductases to a tetracycline (Tc) contamination, and to establish the usability of grass compost (G) and Zea mays (Zm) in mitigating adverse Tc effects on selected microbial properties of the soil. The scope of microbiological analyses included determinations of bacteria with the conventional culture method and new-generation sequencing method (NGS). Activities of soil dehydrogenases and catalase were determined as well. Tc was found to reduce counts of organotrophic bacteria and actinobacteria in the soils as well as the activity of soil oxidoreductases. Soil fertilization with grass compost (G) and Zea mays (Zm) cultivation was found to alleviate the adverse effects of tetracycline on the mentioned group of bacteria and activity of oxidoreductases. The metagenomic analysis demonstrated that the bacteria belonging to Acidiobacteria and Proteobacteria phyla were found to prevail in the soil samples. The study results recommend soil fertilization with G and Zm cultivation as successful measures in the bioremediation of tetracycline-contaminated soils and indicate the usability of the so-called core bacteria in the bioaugmentation of such soils.

Biodiversity and Metabolic Potential of Bacteria in Bulk Soil from the Peri-Root Zone of Black Alder (Alnus glutinosa), Silver Birch (Betula pendula) and Scots Pine (Pinus sylvestris)

The formation of specific features of forest habitats is determined by the physical, chemical, and biological properties of the soil. The aim of the study was to determine the structural and functional biodiversity of soil microorganisms inhabiting the bulk soil from the peri-root zone of three tree species: Alnus glutinosa, Betula pendula, and Pinus sylvestris. Soil samples were collected from a semi-deciduous forest located in an area belonging to the Agricultural Experimental Station IUNG-PIB in Osiny, Poland. The basic chemical and biological parameters of soils were determined, as well as the structural diversity of bacteria (16S ribosomal RNA (rRNA) sequencing) and the metabolic profile of microorganisms (Biolog EcoPlates). The bulk soils collected from peri-root zone of A. glutinosa were characterized by the highest enzymatic activities. Moreover, the highest metabolic activities on EcoPlates were observed in bulk soil collected in the proximity of the root system the A. glutinosa and B. pendula. In turn, the bulk soil collected from peri-root zone of P. sylvestris had much lower biological activity and a lower metabolic potential. The most metabolized compounds were L-phenylalanine, L-asparagine, D-mannitol, and gamma-hydroxy-butyric acid. The highest values of the diversity indicators were in the soils collected in the proximity of the root system of A. glutinosa and B. pendula. The bulk soil collected from P. sylvestris peri-root zone was characterized by the lowest Shannon’s diversity index. In turn, the evenness index (E) was the highest in soils collected from the P. sylvestris, which indicated significantly lower diversity in these soils. The most abundant classes of bacteria in all samples were Actinobacteria, Acidobacteria_Gp1, and Alphaproteobacteria. The classes Bacilli, Thermoleophilia, Betaproteobacteria, and Subdivision3 were dominant in the B. pendula bulk soil. Streptosporangiales was the most significantly enriched order in the B. pendula soil compared with the A. glutinosa and P. sylvestris. There was a significantly higher mean proportion of aerobic nitrite oxidation, nitrate reduction, sulphate respiration, and sulfur compound respiration in the bulk soil of peri-root zone of A. glutinosa. Our research confirms that the evaluation of soil biodiversity and metabolic potential of bacteria can be of great assistance in a quality and health control tool in the soils of forested areas and in the forest production. Identification of bacteria that promote plant growth and have a high biotechnological potential can be assume a substantial improvement in the ecosystem and use of the forest land.

Characteristics changes on Applications of Antibiotics and Current Approaches to Enhance Productivity with Soil Microbiome

The contamination of environmental sully with antibiotics is regarded as a major problem today and predictable to attain more recognition in near future. However, human intervention resulting in antibiotic consumption is being enhancing all around the world. Our review of literature revealed the role of microbiome in sully and how antibiotic resistant genes raised. The structure of antibiotics basically influenced by natural components such as biotic and abiotic push which shifts based on different soils. Therefore, management of microbiome in soil and their expression studies were distinctively revealed. The assessment of antibiotic resistance genes with help of next generation sequencing provided a clear comprehension on genome and transcriptome of the bacterial genes. Thus, interaction of microbiome with soil can also be well understood. The current findings in our study will guide every researcher to follow logical protocol in analyzing microbiota composition is covered as well and also to understand its metagenomic and sequenced with next-generation sequencer which helps to comprehend the diverse micro-flora present in soil and its operation. Finally, later progresses in bioinformatics computer program, flow of work, and applications for analyzing metagenomic information are put in a nutshell.

A review of the emergence of antibiotic resistance in bioaerosols and its monitoring methods

Despite significant public health concerns regarding infectious diseases in air environments, potentially harmful microbiological indicators, such as antibiotic resistance genes (ARGs) in bioaerosols, have not received significant attention. Traditionally, bioaerosol studies have focused on the characterization of microbial communities; however, a more serious problem has recently arisen due to the presence of ARGs in bioaerosols, leading to an increased prevalence of horizontal gene transfer (HGT). This constitutes a process by which bacteria transfer genes to other environmental media and consequently cause infectious disease. Antibiotic resistance in water and soil environments has been extensively investigated in the past few years by applying advanced molecular and biotechnological methods. However, ARGs in bioaerosols have not received much attention. In addition, ARG and HGT profiling in air environments is greatly limited in field studies due to the absence of suitable methodological approaches. Therefore, this study comprehensively describes recent findings from published studies and some of the appropriate molecular and biotechnological methods for monitoring antibiotic resistance in bioaerosols. In addition, this review discusses the main knowledge gaps regarding current methodological issues and future research directions.

Isolation, characterization, and molecular identification of soil bacteria showing antibacterial activity against human pathogenic bacteria

BACKGROUND

The present study dealt with the screening of soil bacteria with antibacterial activity from different locations in Bangalore, India. Antibiotics play the role of self-defense mechanism for the bacteria and are produced as secondary metabolites to protect themselves from other competitive microorganisms. The need for new antibiotics arose as the pathogenic bacteria acquire resistance to various antibiotics meant for treating human diseases. Given the importance of antibiotics of bacterial origin, standard techniques have been used to isolate and characterize the soil bacteria which showed antibacterial activity.

RESULTS

The isolated bacteria were tested against human pathogenic bacteria like Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae by primary and secondary screening methods. The isolates PR1, PR2, and PR3 were confirmed to have antibacterial activity against S. aureus, E. coli, P. aeruginosa, and K. pneumoniae by both methods. Studies on the effect of filter sterilization, autoclaving, and proteinase K treatment on culture filtrates showed filter sterilization as the best method. The effect of different carbon and nitrogen sources on the antibacterial activity showed that preference by each isolate differed for carbon and nitrogen requirements. The isolates PR1, PR2, and PR3 were identified as Bacillus aryabhattai strain PR-D07, Arthrobacter humicola strain PR-F07, and Neomicrococcus lactis strain PR-F11 through 16S rRNA sequencing.

CONCLUSION

Findings from this research work are encouraging and could proceed further to applied aspects. Only 3 bacterial isolates out of 263 isolates from soil samples displayed antibacterial activity against human pathogens S. aureus, E. coli, P. aeruginosa, and K. pneumoniae. They were identified as B. aryabhattai, A. humicola, and N. lactis by 16S rRNA studies and all of them are Gram-positive. Each isolate preferred different carbon and nitrogen sources for their enhanced antibacterial activity. Efficacy of the culture filtrates of these isolates was tested by filter sterilization, autoclaving, and proteinase K treatment. Filter-sterilized culture filtrates showed higher antibacterial activity than other treatments. A comparison of the antibacterial activity of culture filtrates and antibiotic streptomycin produced an inhibition zone of 18.5 mm and 15.5 mm respectively. This is the first report on the antibacterial activity of all the 3 bacterial strains (B. aryabhattai strain PR-D07, A. humicola strain PR-F07, and N. lactis strain PR-F11), against all the human pathogens, mentioned earlier. It is also found that the antibiotic factor is proteinaceous as proteinase K considerably reduced the antibacterial activity of the culture filtrates. With the above significant results, these 3 bacteria are considered to be promising candidates for the isolation of new antibacterial agents.

Mosaic Ends Tagmentation (METa) Assembly for Highly Efficient Construction of Functional Metagenomic Libraries

Functional metagenomic libraries, physical bacterial libraries which allow the high-throughput capture and expression of microbiome genes, have been instrumental in the sequence-naive and cultivation-independent exploration of metagenomes. However, preparation of these libraries is often limited by their high DNA input requirement and their low cloning efficiency. Here, we describe a new method, mosaic ends tagmentation (METa) assembly, for highly efficient functional metagenomic library preparation. We applied tagmentation to metagenomic DNA from soil and gut microbiomes to prepare DNA inserts for high-throughput cloning into functional metagenomic libraries. The presence of mosaic end sequences in the resulting DNA fragments synergized with homology-based assembly cloning to result in a 300-fold increase in cloning efficiency compared to traditional blunt-cloning-based protocols. We show that compared to published libraries prepared by state-of-the-art protocols, METa assembly is on average ca. 20- to 200-fold more efficient and can prepare gigabase-sized libraries with as little as 200 ng of input DNA. We show the usefulness of METa assembly first by using a normative 5-μg mass of soil metagenomic DNA to prepare a 700-Gb library that allowed us to discover novel nourseothricin resistance genes and a potentially new mode of resistance to this antibiotic and second by using only 300 ng of goose fecal metagenomic DNA to prepare a 27-Gb library that captured numerous tetracycline and colistin resistance genes. METa assembly provides a streamlined, flexible, and efficient method for preparing functional metagenomic libraries, enabling new avenues of genetic and biochemical research into low-biomass or scarce microbiomes. IMPORTANCE Medically and industrially important genes can be recovered from microbial communities by high-throughput sequencing, but precise annotation is often limited to characterized genes and their relatives. Cloning a metagenome en masse into an expression host to produce a functional metagenomic library, directly connecting genes to functions, is a sequence-naive and cultivation-independent method to discover novel genes. The process of preparing these libraries is DNA greedy and inefficient, however. Here, we describe a library preparation method that is an order of magnitude more efficient and less DNA greedy. This method is consistently efficient across libraries prepared from cultures, a soil microbiome, and a goose fecal microbiome and allowed us to discover new antibiotic resistance genes and mechanisms. This library preparation method will potentially allow the functional metagenomic exploration of microbiomes that were previously off limits due to their rarity or low microbial biomass, such as biomedical swabs or exotic samples.

Abundance and Diversity of Phages, Microbial Taxa, and Antibiotic Resistance Genes in the Sediments of the River Ganges Through Metagenomic Approach

In this study, we have analyzed the metagenomic DNA from the pooled sediment sample of the river Ganges to explore the abundance and diversity of phages, microbial community, and antibiotic resistance genes (ARGs). Utilizing data from Illumina platform, 4,174 (∼0.0013%) reads were classified for the 285 different DNA viruses largely dominated by the group of 260 distinctive phages (3,602 reads, ∼86.3%). Among all, Microcystis (782 hits), Haemophilus (403), Synechococcus (386), Pseudomonas (279), Enterococcus (232), Bacillus (196), Rhodococcus (166), Caulobacter (163), Salmonella (146), Enterobacteria (143), Mycobacterium and (128) phages show the highest abundance and account for ∼90% of the total identified phages. In addition, we have also identified corresponding host pertaining to these phages. Mainly, Proteobacteria (∼69.3%) dominates the microbial population structure. Primarily, orders such as Caulobacterales (∼28%), Burkholderiales (∼13.9%), Actinomycetales (∼13.7%), and Pseudomonadales (∼7.5%) signify the core section. Furthermore, 21,869 (∼0.00695%) reads were classified in 20 ARG types (classes) and 240 ARGs (subtypes), among which 4 ARG types, namely multidrug resistance (12,041 reads, ∼55%), bacitracin (3,202 reads, ∼15%), macrolide-lincosamide-streptogramin (1,744 reads, ∼7.98%), and fosmidomycin (990 reads, ∼4.53%), have the highest abundance. Simultaneously, six resistance mechanisms were also recognized with the dominance of antibiotic efflux (72.8%, 15,919 reads). The results unveil the distribution of (pro)-phages; microbial community; and various ARGs in the Ganges river sediments.

Novel Soil-Derived Beta-Lactam, Chloramphenicol, Fosfomycin and Trimethoprim Resistance Genes Revealed by Functional Metagenomics

Antibiotic resistance genes (ARGs) in soil are considered to represent one of the largest environmental resistomes on our planet. As these genes can potentially be disseminated among microorganisms via horizontal gene transfer (HGT) and in some cases are acquired by clinical pathogens, knowledge about their diversity, mobility and encoded resistance spectra gained increasing public attention. This knowledge offers opportunities with respect to improved risk prediction and development of strategies to tackle antibiotic resistance, and might help to direct the design of novel antibiotics, before further resistances reach hospital settings or the animal sector. Here, metagenomic libraries, which comprise genes of cultivated microorganisms, but, importantly, also those carried by the uncultured microbial majority, were screened for novel ARGs from forest and grassland soils. We detected three new beta-lactam, a so far unknown chloramphenicol, a novel fosfomycin, as well as three previously undiscovered trimethoprim resistance genes. These ARGs were derived from phylogenetically diverse soil bacteria and predicted to encode antibiotic inactivation, antibiotic efflux, or alternative variants of target enzymes. Moreover, deduced gene products show a minimum identity of ~21% to reference database entries and confer high-level resistance. This highlights the vast potential of functional metagenomics for the discovery of novel ARGs from soil ecosystems.

Effect of membrane fusion protein AdeT1 on the antimicrobial resistance of Escherichia coli

Acinetobacter baumannii is a prevalent pathogen that can rapidly acquire resistance to antibiotics. Indeed, multidrug-resistant A. baumannii is a major cause of hospital-acquired infections and has been recognised by the World Health Organization as one of the most threatening bacteria to our society. Resistance-nodulation-division (RND) type multidrug efflux pumps have been demonstrated to convey antibiotic resistance to a wide range of pathogens and are the primary resistance mechanism employed by A. baumannii. A component of an RND pump in A. baumannii, AdeT1, was previously demonstrated to enhance the antimicrobial resistance of Escherichia coli. Here, we report the results of experiments which demonstrate that wild-type AdeT1 does not confer antimicrobial resistance in E. coli, highlighting the importance of verifying protein production when determining minimum inhibitory concentrations (MICs) especially by broth dilution. Nevertheless, using an agar-based MIC assay, we found that propionylation of Lys280 on AdeT1 renders E. coli cells more resistant to erythromycin.

Platforms for elucidating antibiotic resistance in single genomes and complex metagenomes

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

Prevalence of extended-spectrum β-lactamases in the local farm environment and livestock: challenges to mitigate antimicrobial resistance

The effectiveness of antibiotics has been challenged by the increasing frequency of antimicrobial resistance (AR), which has emerged as a major threat to global health. Despite the negative impact of AR on health, there are few effective strategies for reducing AR in food-producing animals. Of the antimicrobial resistant microorganisms (ARMs), extended-spectrum β-lactamases (ESBLs)-producing Enterobacteriaceae are an emerging global threat due to their increasing prevalence in livestock, even in animals raised without antibiotics. Many reviews are available for the positive selection of AR associated with antibiotic use in livestock, but less attention has been given to how other factors including soil, water, manure, wildlife, and farm workers, are associated with the emergence of ESBL-producing bacteria. Understanding of antibiotic resistance genes and bacteria transfer at the interfaces of livestock and other potential reservoirs will provide insights for the development of mitigation strategies for AR.

Clinical Resistome Screening of 1,110 Escherichia coli Isolates Efficiently Recovers Diagnostically Relevant Antibiotic Resistance Biomarkers and Potential Novel Resistance Mechanisms

Multidrug-resistant pathogens represent one of the biggest global healthcare challenges. Molecular diagnostics can guide effective antibiotics therapy but relies on validated, predictive biomarkers. Here we present a novel, universally applicable workflow for rapid identification of antimicrobial resistance (AMR) biomarkers from clinical Escherichia coli isolates and quantitatively evaluate the potential to recover causal biomarkers for observed resistance phenotypes. For this, a metagenomic plasmid library from 1,110 clinical E. coli isolates was created and used for high-throughput screening to identify biomarker candidates against Tobramycin (TOB), Ciprofloxacin (CIP), and Trimethoprim-Sulfamethoxazole (TMP-SMX). Identified candidates were further validated in vitro and also evaluated in silico for their diagnostic performance based on matched genotype-phenotype data. AMR biomarkers recovered by the metagenomics screening approach mechanistically explained 77% of observed resistance phenotypes for Tobramycin, 76% for Trimethoprim-Sulfamethoxazole, and 20% Ciprofloxacin. Sensitivity for Ciprofloxacin resistance detection could be improved to 97% by complementing results with AMR biomarkers that are undiscoverable due to intrinsic limitations of the workflow. Additionally, when combined in a multiplex diagnostic in silico panel, the identified AMR biomarkers reached promising positive and negative predictive values of up to 97 and 99%, respectively. Finally, we demonstrate that the developed workflow can be used to identify potential novel resistance mechanisms.

Sequencing-based methods and resources to study antimicrobial resistance

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

Microbial Diversity and Antimicrobial Resistance Profile in Microbiota From Soils of Conventional and Organic Farming Systems

Soil is one of the biggest reservoirs of microbial diversity, yet the processes that define the community dynamics are not fully understood. Apart from soil management being vital for agricultural purposes, it is also considered a favorable environment for the evolution and development of antimicrobial resistance, which is due to its high complexity and ongoing competition between the microorganisms. Different approaches to agricultural production might have specific outcomes for soil microbial community composition and antibiotic resistance phenotype. Therefore in this study we aimed to compare the soil microbiota and its resistome in conventional and organic farming systems that are continually influenced by the different treatment (inorganic fertilizers and pesticides vs. organic manure and no chemical pest management). The comparison of the soil microbial communities revealed no major differences among the main phyla of bacteria between the two farming styles with similar soil structure and pH. Only small differences between the lower taxa could be observed indicating that the soil community is stable, with minor shifts in composition being able to handle the different styles of treatment and fertilization. It is still unclear what level of intensity can change microbial composition but current conventional farming in Central Europe demonstrates acceptable level of intensity for soil bacterial communities. When the resistome of the soils was assessed by screening the total soil DNA for clinically relevant and soil-derived antibiotic resistance genes, a low variety of resistance determinants was detected (resistance to β-lactams, aminoglycosides, tetracycline, erythromycin, and rifampicin) with no clear preference for the soil farming type. The same soil samples were also used to isolate antibiotic resistant cultivable bacteria, which were predominated by highly resistant isolates of Pseudomonas, Stenotrophomonas, Sphingobacterium and Chryseobacterium genera. The resistance of these isolates was largely dependent on the efflux mechanisms, the soil Pseudomonas spp. relying mostly on RND, while Stenotrophomonas spp. and Chryseobacterium spp. on RND and ABC transporters.

Antibiotics in the Soil Environment-Degradation and Their Impact on Microbial Activity and Diversity

Antibiotics play a key role in the management of infectious diseases in humans, animals, livestock, and aquacultures all over the world. The release of increasing amount of antibiotics into waters and soils creates a potential threat to all microorganisms in these environments. This review addresses issues related to the fate and degradation of antibiotics in soils and the impact of antibiotics on the structural, genetic and functional diversity of microbial communities. Due to the emergence of bacterial resistance to antibiotics, which is considered a worldwide public health problem, the abundance and diversity of antibiotic resistance genes (ARGs) in soils are also discussed. When antibiotic residues enter the soil, the main processes determining their persistence are sorption to organic particles and degradation/transformation. The wide range of DT50 values for antibiotic residues in soils shows that the processes governing persistence depend on a number of different factors, e.g., physico-chemical properties of the residue, characteristics of the soil, and climatic factors (temperature, rainfall, and humidity). The results presented in this review show that antibiotics affect soil microorganisms by changing their enzyme activity and ability to metabolize different carbon sources, as well as by altering the overall microbial biomass and the relative abundance of different groups (i.e., Gram-negative bacteria, Gram-positive bacteria, and fungi) in microbial communities. Studies using methods based on analyses of nucleic acids prove that antibiotics alter the biodiversity of microbial communities and the presence of many types of ARGs in soil are affected by agricultural and human activities. It is worth emphasizing that studies on ARGs in soil have resulted in the discovery of new genes and enzymes responsible for bacterial resistance to antibiotics. However, many ambiguous results indicate that precise estimation of the impact of antibiotics on the activity and diversity of soil microbial communities is a great challenge.

Comparative Metagenomics and Network Analyses Provide Novel Insights Into the Scope and Distribution of β-Lactamase Homologs in the Environment

The β-lactams are the largest group of clinically applied antibiotics, and resistance to these is primarily associated with β-lactamases. There is increasing understanding that these enzymes are ubiquitous in natural environments and henceforth, elucidating the global diversity, distribution, and mobility of β-lactamase-encoding genes is crucial for holistically understanding resistance to these antibiotics. In this study, we screened 232 shotgun metagenomes from ten different environments against a custom-designed β-lactamase database, and subsequently analyzed β-lactamase homologs with a suite of bioinformatic platforms including cluster and network analyses. Three interrelated β-lactamase clusters encompassed all of the human and bovine feces metagenomes, while β-lactamases from soil, freshwater, glacier, marine, and wastewater grouped within a separate "environmental" cluster that displayed high levels of inter-network connectivity. Interestingly, almost no connectivity occurred between the "feces" and "environmental" clusters. We attributed this in part to the divergence in microbial community composition (dominance of Bacteroidetes and Firmicutes vs. Proteobacteria, respectively). The β-lactamase diversity in the "environmental" cluster was significantly higher than in human and bovine feces microbiomes. Several class A, B, C, and D β-lactamase homologs (bla _CTX-M, bla _KPC, bla _GES) were ubiquitous in the "environmental" cluster, whereas bovine and human feces metagenomes were dominated by class A (primarily cfxA) β-lactamases. Collectively, this study highlights the ubiquitous presence and broad diversity of β-lactamase gene precursors in non-clinical environments. Furthermore, it suggests that horizontal transfer of β-lactamases to human-associated bacteria may be more plausible from animals than from terrestrial and aquatic microbes, seemingly due to phylogenetic similarities.

Tetracyclines, sulfonamides and quinolones and their corresponding resistance genes in the Three Gorges Reservoir, China

The Three Gorges Project significantly impacted water quality and ecological balance in this area. The special engineered aquatic environment could be an important reservoir for antibiotic resistance genes (ARGs). Fifteen ARGs corresponding to three groups of antibiotics (tetracyclines, sulfonamides and quinolones) were determined in surface water, soil and sediment in this study. Total concentrations of antibiotics ranged from 21.55 to 536.86ng/L, 3.69 to 438.76ng/g, 15.78 to 213.84ng/g in water, soil and sediment, respectively. Polymerase chain reaction (PCR) of ARGs revealed the presence of two sulfonamide resistance genes (sul1, sul2), five tetracycline resistance genes (tetA, tetB, tetM, tetQ, tetG) and class 1 integron gene (intI1) in all samples. And the relative abundance of sulfonamide resistance genes was generally higher than tetracycline resistance genes in three matrices. Significant correlations (p<0.05) were found between the concentrations of intI1 and ARGs (tetA, tetB, tetM, tetQ, tetG, sul1, sul2), indicating intI1 may facilitate the proliferation and propagation of these genes. Redundancy analysis (RDA) showed distribution of ARGs was related to the certain antibiotics residues, which may exert selective pressure on bacteria and thus enrich the abundance of ARGs. The results of this study could provide useful information for both better understanding and management of the contamination caused by ARGs and related antibiotics in engineered aquatic environments.

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.

Acid-resistant genes of oral plaque microbiome from the functional metagenomics

Acid resistance is one of key properties assisting the survival of cariogenic bacteria in a dental caries environment, but only a few genes conferring acid resistance have been identified to data. Functional metagenomics provides a systematic method for investigating commensal DNA to identify genes that encode target functions. Here, the host strain Escherichia coli DH10B and a constructed bidirectional transcription vector pSKII⁺-lacZ contributed to the construction of a metagenomic library, and 46.6 Mb of metagenomic DNA was cloned from carious supragingival plaque of 8children along with screening for lethal functionality. The screen identified 2 positive clones that exhibited a similar aciduric phenotype to that of the positive controls. Bioinformatic analysis revealed that these two genes encoded an ATP/GTP-binding protein and a malate dehydrogenase. Moreover, we also performed functional screening of Streptococcus mutans, since it is one of the predominant cariogenic strains but was not identified in our initial screening. Five positive clones were retrieved. In conclusion, our improved functional metagenomics screening method helped in the identification of important acid resistance genes, thereby providing new insights into the mechanism underlying caries formation as well as in the prevention and treatment of early childhood caries (ECC).

Metagenomic analysis reveals wastewater treatment plants as hotspots of antibiotic resistance genes and mobile genetic elements

The intensive use of antibiotics results in their continuous release into the environment and the subsequent widespread occurrence of antibiotic resistant bacteria (ARB), antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs). This study used Illumina high-throughput sequencing to investigate the broad-spectrum profiles of both ARGs and MGEs in activated sludge and anaerobically digested sludge from a full-scale wastewater treatment plant. A pipeline for identifying antibiotic resistance determinants was developed that consisted of four categories: gene transfer potential, ARG potential, ARGs pathway and ARGs phylogenetic origin. The metagenomic analysis showed that the activated sludge and the digested sludge exhibited different microbial communities and changes in the types and occurrence of ARGs and MGEs. In total, 42 ARGs subtypes were identified in the activated sludge, while 51 ARG subtypes were detected in the digested sludge. Additionally, MGEs including plasmids, transposons, integrons (intI1) and insertion sequences (e.g. ISSsp4, ISMsa21 and ISMba16) were abundant in the two sludge samples. The co-occurrence pattern between ARGs and microbial taxa revealed by network analysis indicated that some environmental bacteria (e.g. Clostridium and Nitrosomonas) might be potential hosts of multiple ARGs. The findings increase our understanding of WWTPs as hotspots of ARGs and MGEs, and contribute towards preventing their release into the downstream environment.

Lessons from the Environmental Antibiotic Resistome

Antibiotic resistance is a global public health issue of growing proportions. All antibiotics are susceptible to resistance. The evidence is now clear that the environment is the single largest source and reservoir of resistance. Soil, aquatic, atmospheric, animal-associated, and built ecosystems are home to microbes that harbor antibiotic resistance elements and the means to mobilize them. The diversity and abundance of resistance in the environment is consistent with the ancient origins of antibiotics and a variety of studies support a long natural history of associated resistance. The implications are clear: Understanding the evolution of resistance in the environment, its diversity, and mechanisms is essential to the management of our existing and future antibiotic resources.

Next-generation approaches to understand and combat the antibiotic resistome

Antibiotic resistance is a natural feature of diverse microbial ecosystems. Although recent studies of the antibiotic resistome have highlighted barriers to the horizontal transfer of antibiotic resistance genes between habitats, the rapid global spread of genes that confer resistance to carbapenem, colistin and quinolone antibiotics illustrates the dire clinical and societal consequences of such events. Over time, the study of antibiotic resistance has grown from focusing on single pathogenic organisms in axenic culture to studying antibiotic resistance in pathogenic, commensal and environmental bacteria at the level of microbial communities. As the study of antibiotic resistance advances, it is important to incorporate this comprehensive approach to better inform global antibiotic resistance surveillance and antibiotic development. It is increasingly becoming apparent that although not all resistance genes are likely to geographically and phylogenetically disseminate, the threat presented by those that are is serious and warrants an interdisciplinary research focus. In this Review, we highlight seminal work in the resistome field, discuss recent advances in the studies of resistomes, and propose a resistome paradigm that can pave the way for the improved proactive identification and mitigation of emerging antibiotic resistance threats.

Functional Metagenomics as a Tool for Identification of New Antibiotic Resistance Genes from Natural Environments

Antibiotic resistance has become a major concern for human and animal health, as therapeutic alternatives to treat multidrug-resistant microorganisms are rapidly dwindling. The problem is compounded by low investment in antibiotic research and lack of new effective antimicrobial drugs on the market. Exploring environmental antibiotic resistance genes (ARGs) will help us to better understand bacterial resistance mechanisms, which may be the key to identifying new drug targets. Because most environment-associated microorganisms are not yet cultivable, culture-independent techniques are essential to determine which organisms are present in a given environmental sample and allow the assessment and utilization of the genetic wealth they represent. Metagenomics represents a powerful tool to achieve these goals using sequence-based and functional-based approaches. Functional metagenomic approaches are particularly well suited to the identification new ARGs from natural environments because, unlike sequence-based approaches, they do not require previous knowledge of these genes. This review discusses functional metagenomics-based ARG research and describes new possibilities for surveying the resistome in environmental samples.

FARME DB: a functional antibiotic resistance element database

Antibiotic resistance (AR) is a major global public health threat but few resources exist that catalog AR genes outside of a clinical context. Current AR sequence databases are assembled almost exclusively from genomic sequences derived from clinical bacterial isolates and thus do not include many microbial sequences derived from environmental samples that confer resistance in functional metagenomic studies. These environmental metagenomic sequences often show little or no similarity to AR sequences from clinical isolates using standard classification criteria. In addition, existing AR databases provide no information about flanking sequences containing regulatory or mobile genetic elements. To help address this issue, we created an annotated database of DNA and protein sequences derived exclusively from environmental metagenomic sequences showing AR in laboratory experiments. Our Functional Antibiotic Resistant Metagenomic Element (FARME) database is a compilation of publically available DNA sequences and predicted protein sequences conferring AR as well as regulatory elements, mobile genetic elements and predicted proteins flanking antibiotic resistant genes. FARME is the first database to focus on functional metagenomic AR gene elements and provides a resource to better understand AR in the 99% of bacteria which cannot be cultured and the relationship between environmental AR sequences and antibiotic resistant genes derived from cultured isolates.Database URL: http://staff.washington.edu/jwallace/farme.

Distribution and Classification of Serine β-Lactamases in Brazilian Hospital Sewage and Other Environmental Metagenomes Deposited in Public Databases

β-lactam is the most used antibiotic class in the clinical area and it acts on blocking the bacteria cell wall synthesis, causing cell death. However, some bacteria have evolved resistance to these antibiotics mainly due the production of enzymes known as β-lactamases. Hospital sewage is an important source of dispersion of multidrug-resistant bacteria in rivers and oceans. In this work, we used next-generation DNA sequencing to explore the diversity and dissemination of serine β-lactamases in two hospital sewage from Rio de Janeiro, Brazil (South Zone, SZ and North Zone, NZ), presenting different profiles, and to compare them with public environmental data available. Also, we propose a Hidden-Markov-Model approach to screen potential serine β-lactamases genes (in public environments samples and generated hospital sewage data), exploring its evolutionary relationships. Due to the high variability in β-lactamases, we used a position-specific scoring matrix search method (RPS-BLAST) against conserved domain database profiles (CDD, Pfam, and COG) followed by visual inspection to detect conserved motifs, to increase the reliability of the results and remove possible false positives. We were able to identify novel β-lactamases from Brazilian hospital sewage and to estimate relative abundance of its types. The highest relative abundance found in SZ was the Class A (50%), while Class D is predominant in NZ (55%). CfxA (65%) and ACC (47%) types were the most abundant genes detected in SZ, while in NZ the most frequent were OXA-10 (32%), CfxA (28%), ACC (21%), CEPA (20%), and FOX (19%). Phylogenetic analysis revealed β-lactamases from Brazilian hospital sewage grouped in the same clade and close to sequences belonging to Firmicutes and Bacteroidetes groups, but distant from potential β-lactamases screened from public environmental data, that grouped closer to β-lactamases of Proteobacteria. Our results demonstrated that HMM-based approach identified homologs of serine β-lactamases, indicating the specificity and high sensitivity of this approach in large datasets, contributing for the identification and classification of a large number of homologous genes, comprising possible new ones. Phylogenetic analysis revealed the potential reservoir of β-lactam resistance genes in the environment, contributing to understanding the evolution and dissemination of these genes.

Exploring divergent antibiotic resistance genes in ancient metagenomes and discovery of a novel beta-lactamase family

Antibiotic resistance in pathogenic bacteria is a major problem for human health. We analyzed metagenomic datasets from ancient and remote samples from diverse environmental sources and observed the presence of all the eleven antibiotic resistance genes (ARG) groups evaluated. Since ancient samples are not subjected to modern effects of antibiotic misuse, they represent a clean model to explore the natural diversity of ARG in the environment. Most sequences showed high divergence compared with known ARG, representing a much larger universe than the currently known and characterized ARGs. We explored whether proteins within the "divergent resistome" may correspond to functional ARG by characterizing a beta-lactamase hit with very low similarity to any known sequence (<45% to best BLAST hit in NCBI). By starting from purely in-silico data, we revived a new family of class B beta-lactamases from ancient medieval samples, which exhibited a very high penicillinase activity. In this work, we explored ancient resistomes and added novel support to previous works showing that the universe of ARG is naturally vast and diverse in microbial communities. Our results bring a new perspective to the exploration of environmental ARG and indicate that this gigantic reservoir represents a natural endless source of emerging resistances.

Structural and Biochemical Characterization of Rm3, a Subclass B3 Metallo-β-Lactamase Identified from a Functional Metagenomic Study

β-Lactamase production increasingly threatens the effectiveness of β-lactams, which remain a mainstay of antimicrobial chemotherapy. New activities emerge through both mutation of previously known β-lactamases and mobilization from environmental reservoirs. The spread of metallo-β-lactamases (MBLs) represents a particular challenge because of their typically broad-spectrum activities encompassing carbapenems, in addition to other β-lactam classes. Increasingly, genomic and metagenomic studies have revealed the distribution of putative MBLs in the environment, but in most cases their activity against clinically relevant β-lactams and, hence, the extent to which they can be considered a resistance reservoir remain uncharacterized. Here we characterize the product of one such gene, blaRm3, identified through functional metagenomic sampling of an environment with high levels of biocide exposure. blaRm3 encodes a subclass B3 MBL that, when expressed in a recombinant Escherichia coli strain, is exported to the bacterial periplasm and hydrolyzes clinically used penicillins, cephalosporins, and carbapenems with an efficiency limited by high Km values. An Rm3 crystal structure reveals the MBL superfamily αβ/βα fold, which more closely resembles that in mobilized B3 MBLs (AIM-1 and SMB-1) than other chromosomal enzymes (L1 or FEZ-1). A binuclear zinc site sits in a deep channel that is in part defined by a relatively extended N terminus. Structural comparisons suggest that the steric constraints imposed by the N terminus may limit its affinity for β-lactams. Sequence comparisons identify Rm3-like MBLs in numerous other environmental samples and species. Our data suggest that Rm3-like enzymes represent a distinct group of B3 MBLs with a wide distribution and can be considered an environmental reservoir of determinants of β-lactam resistance.

Phages rarely encode antibiotic resistance genes: a cautionary tale for virome analyses

Antibiotic resistance genes (ARGs) are pervasive in gut microbiota, but it remains unclear how often ARGs are transferred, particularly to pathogens. Traditionally, ARG spread is attributed to horizontal transfer mediated either by DNA transformation, bacterial conjugation or generalized transduction. However, recent viral metagenome (virome) analyses suggest that ARGs are frequently carried by phages, which is inconsistent with the traditional view that phage genomes rarely encode ARGs. Here we used exploratory and conservative bioinformatic strategies found in the literature to detect ARGs in phage genomes, and experimentally assessed a subset of ARG predicted using exploratory thresholds. ARG abundances in 1181 phage genomes were vastly overestimated using exploratory thresholds (421 predicted vs 2 known), due to low similarities and matches to protein unrelated to antibiotic resistance. Consistent with this, four ARGs predicted using exploratory thresholds were experimentally evaluated and failed to confer antibiotic resistance in Escherichia coli. Reanalysis of available human- or mouse-associated viromes for ARGs and their genomic context suggested that bona fide ARG attributed to phages in viromes were previously overestimated. These findings provide guidance for documentation of ARG in viromes, and reassert that ARGs are rarely encoded in phages.

Dissemination of Antimicrobial Resistance in Microbial Ecosystems through Horizontal Gene Transfer

The emergence and spread of antibiotic resistance among pathogenic bacteria has been a rising problem for public health in recent decades. It is becoming increasingly recognized that not only antibiotic resistance genes (ARGs) encountered in clinical pathogens are of relevance, but rather, all pathogenic, commensal as well as environmental bacteria—and also mobile genetic elements and bacteriophages—form a reservoir of ARGs (the resistome) from which pathogenic bacteria can acquire resistance via horizontal gene transfer (HGT). HGT has caused antibiotic resistance to spread from commensal and environmental species to pathogenic ones, as has been shown for some clinically important ARGs. Of the three canonical mechanisms of HGT, conjugation is thought to have the greatest influence on the dissemination of ARGs. While transformation and transduction are deemed less important, recent discoveries suggest their role may be larger than previously thought. Understanding the extent of the resistome and how its mobilization to pathogenic bacteria takes place is essential for efforts to control the dissemination of these genes. Here, we will discuss the concept of the resistome, provide examples of HGT of clinically relevant ARGs and present an overview of the current knowledge of the contributions the various HGT mechanisms make to the spread of antibiotic resistance.

Next-generation sequencing (NGS) for assessment of microbial water quality: current progress, challenges, and future opportunities

Water quality is an emergent property of a complex system comprised of interacting microbial populations and introduced microbial and chemical contaminants. Studies leveraging next-generation sequencing (NGS) technologies are providing new insights into the ecology of microbially mediated processes that influence fresh water quality such as algal blooms, contaminant biodegradation, and pathogen dissemination. In addition, sequencing methods targeting small subunit (SSU) rRNA hypervariable regions have allowed identification of signature microbial species that serve as bioindicators for sewage contamination in these environments. Beyond amplicon sequencing, metagenomic and metatranscriptomic analyses of microbial communities in fresh water environments reveal the genetic capabilities and interplay of waterborne microorganisms, shedding light on the mechanisms for production and biodegradation of toxins and other contaminants. This review discusses the challenges and benefits of applying NGS-based methods to water quality research and assessment. We will consider the suitability and biases inherent in the application of NGS as a screening tool for assessment of biological risks and discuss the potential and limitations for direct quantitative interpretation of NGS data. Secondly, we will examine case studies from recent literature where NGS based methods have been applied to topics in water quality assessment, including development of bioindicators for sewage pollution and microbial source tracking, characterizing the distribution of toxin and antibiotic resistance genes in water samples, and investigating mechanisms of biodegradation of harmful pollutants that threaten water quality. Finally, we provide a short review of emerging NGS platforms and their potential applications to the next generation of water quality assessment tools.

Characterization of BKC-1 class A carbapenemase from Klebsiella pneumoniae clinical isolates in Brazil

Three Klebsiella pneumoniae clinical isolates demonstrating carbapenem resistance were recovered from different patients hospitalized at two medical centers in São Paulo, Brazil. Resistance to all β-lactams, quinolones, and some aminoglycosides was observed for these isolates that were susceptible to polymyxin B. Carbapenem hydrolysis, which was inhibited by clavulanic acid, was observed for all K. pneumoniae isolates that belonged to the same pulsed-field gel electrophoresis (PFGE) type and a novel sequence type (ST), ST1781 (clonal complex 442 [CC442]). A 10-kb nonconjugative incompatibility group Q (IncQ) plasmid, denominated p60136, was transferred to Escherichia coli strain TOP10 cells by electroporation. The full sequencing of p60136 showed that it was composed of a mobilization system, ISKpn23, the phosphotransferase aph3A-VI, and a 941-bp open reading frame (ORF) that codified a 313-amino acid protein. This ORF was named bla BKC-1. Brazilian Klebsiella carbapenemase-1 (BKC-1) showed a pI of 6.0 and possessed the highest identity (63%) with a β-lactamase of Sinorhizobium meliloti, an environmental bacterium. Hydrolysis studies demonstrated that purified BKC-1 not only hydrolyzed carbapenems but also penicillins, cephalosporins, and monobactams. However, the carbapenems were less efficiently hydrolyzed due to their very low kcat values (0.0016 to 0.031 s(-1)). In fact, oxacillin was the best substrate for BKC-1 (kcat /Km , 53,522.6 mM(-1) s(-1)). Here, we report a new class A carbapenemase, confirming the diversity and rapid evolution of β-lactamases in K. pneumoniae clinical isolates.

A response regulator from a soil metagenome enhances resistance to the β-lactam antibiotic carbenicillin in Escherichia coli

Functional metagenomic analysis of soil metagenomes is a method for uncovering as-yet unidentified mechanisms for antibiotic resistance. Here we report an unconventional mode by which a response regulator derived from a soil metagenome confers resistance to the β-lactam antibiotic carbenicillin in Escherichia coli. A recombinant clone (βlr16) harboring a 5,169 bp DNA insert was selected from a metagenomic library previously constructed from a remote Alaskan soil. The βlr16 clone conferred specific resistance to carbenicillin, with limited increases in resistance to other tested antibiotics, including other β-lactams (penicillins and cephalosporins), rifampin, ciprofloxacin, erythromycin, chloramphenicol, nalidixic acid, fusidic acid, and gentamicin. Resistance was more pronounced at 24°C than at 37°C. Zone-of-inhibition assays suggested that the mechanism of carbenicillin resistance was not due to antibiotic inactivation. The DNA insert did not encode any genes known to confer antibiotic resistance, but did have two putative open reading frames (ORFs) that were annotated as a metallopeptidase and a two-component response regulator. Transposon mutagenesis and subcloning of the two ORFs followed by phenotypic assays showed that the response regulator gene was necessary and sufficient to confer the resistance phenotype. Quantitative reverse transcriptase PCR showed that the response regulator suppressed expression of the ompF porin gene, independently of the small RNA regulator micF, and enhanced expression of the acrD, mdtA, and mdtB efflux pump genes. This work demonstrates that antibiotic resistance can be achieved by the modulation of gene regulation by heterologous DNA. Functional analyses such as these can be important for making discoveries in antibiotic resistance gene biology and ecology.

Proteomics as the final step in the functional metagenomics study of antimicrobial resistance

The majority of clinically applied antimicrobial agents are derived from natural products generated by soil microorganisms and therefore resistance is likely to be ubiquitous in such environments. This is supported by the fact that numerous clinically important resistance mechanisms are encoded within the genomes of such bacteria. Advances in genomic sequencing have enabled the in silico identification of putative resistance genes present in these microorganisms. However, it is not sufficient to rely on the identification of putative resistance genes, we must also determine if the resultant proteins confer a resistant phenotype. This will require an analysis pipeline that extends from the extraction of environmental DNA, to the identification and analysis of potential resistance genes and their resultant proteins and phenotypes. This review focuses on the application of functional metagenomics and proteomics to study antimicrobial resistance in diverse environments.

High rates of antimicrobial drug resistance gene acquisition after international travel, The Netherlands

We investigated the effect of international travel on the gut resistome of 122 healthy travelers from the Netherlands by using a targeted metagenomic approach. Our results confirm high acquisition rates of the extended-spectrum β-lactamase encoding gene bla_CTX-M, documenting a rise in prevalence from 9.0% before travel to 33.6% after travel (p<0.001). The prevalence of quinolone resistance encoding genes qnrB and qnrS increased from 6.6% and 8.2% before travel to 36.9% and 55.7% after travel, respectively (both p<0.001). Travel to Southeast Asia and the Indian subcontinent was associated with the highest acquisition rates of qnrS and both bla_CTX-M and qnrS, respectively. Investigation of the associations between the acquisitions of the bla_CTX-M and qnr genes showed that acquisition of a bla_CTX-M gene was not associated with that of a qnrB (p = 0.305) or qnrS (p = 0.080) gene. These findings support the increasing evidence that travelers contribute to the spread of antimicrobial drug resistance.

High rates of antimicrobial drug resistance gene acquisition after international travel, The Netherlands

We investigated the effect of international travel on the gut resistome of 122 healthy travelers from the Netherlands by using a targeted metagenomic approach. Our results confirm high acquisition rates of the extended-spectrum β-lactamase encoding gene blaCTX-M, documenting a rise in prevalence from 9.0% before travel to 33.6% after travel (p<0.001). The prevalence of quinolone resistance encoding genes qnrB and qnrS increased from 6.6% and 8.2% before travel to 36.9% and 55.7% after travel, respectively (both p<0.001). Travel to Southeast Asia and the Indian subcontinent was associated with the highest acquisition rates of qnrS and both blaCTX-M and qnrS, respectively. Investigation of the associations between the acquisitions of the blaCTX-M and qnr genes showed that acquisition of a blaCTX-M gene was not associated with that of a qnrB (p = 0.305) or qnrS (p = 0.080) gene. These findings support the increasing evidence that travelers contribute to the spread of antimicrobial drug resistance.

Insights into novel antimicrobial compounds and antibiotic resistance genes from soil metagenomes

In recent years a major worldwide problem has arisen with regard to infectious diseases caused by resistant bacteria. Resistant pathogens are related to high mortality and also to enormous healthcare costs. In this field, cultured microorganisms have been commonly focused in attempts to isolate antibiotic resistance genes or to identify antimicrobial compounds. Although this strategy has been successful in many cases, most of the microbial diversity and related antimicrobial molecules have been completely lost. As an alternative, metagenomics has been used as a reliable approach to reveal the prospective reservoir of antimicrobial compounds and antibiotic resistance genes in the uncultured microbial community that inhabits a number of environments. In this context, this review will focus on resistance genes as well as on novel antibiotics revealed by a metagenomics approach from the soil environment. Biotechnology prospects are also discussed, opening new frontiers for antibiotic development.

Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology

Antibiotic resistance is a dire clinical problem with important ecological dimensions. While antibiotic resistance in human pathogens continues to rise at alarming rates, the impact of environmental resistance on human health is still unclear. To investigate the relationship between human-associated and environmental resistomes, we analyzed functional metagenomic selections for resistance against 18 clinically relevant antibiotics from soil and human gut microbiota as well as a set of multidrug-resistant cultured soil isolates. These analyses were enabled by Resfams, a new curated database of protein families and associated highly precise and accurate profile hidden Markov models, confirmed for antibiotic resistance function and organized by ontology. We demonstrate that the antibiotic resistance functions that give rise to the resistance profiles observed in environmental and human-associated microbial communities significantly differ between ecologies. Antibiotic resistance functions that most discriminate between ecologies provide resistance to β-lactams and tetracyclines, two of the most widely used classes of antibiotics in the clinic and agriculture. We also analyzed the antibiotic resistance gene composition of over 6000 sequenced microbial genomes, revealing significant enrichment of resistance functions by both ecology and phylogeny. Together, our results indicate that environmental and human-associated microbial communities harbor distinct resistance genes, suggesting that antibiotic resistance functions are largely constrained by ecology.