In-depth resistome analysis by targeted metagenomics

Hybrid-Capture Target Enrichment in Human Pathogens: Identification, Evolution, Biosurveillance, and Genomic Epidemiology

High-throughput sequencing (HTS) has revolutionised the field of pathogen genomics, enabling the direct recovery of pathogen genomes from clinical and environmental samples. However, pathogen nucleic acids are often overwhelmed by those of the host, requiring deep metagenomic sequencing to recover sufficient sequences for downstream analyses (e.g., identification and genome characterisation). To circumvent this, hybrid-capture target enrichment (HC) is able to enrich pathogen nucleic acids across multiple scales of divergences and taxa, depending on the panel used. In this review, we outline the applications of HC in human pathogens-bacteria, fungi, parasites and viruses-including identification, genomic epidemiology, antimicrobial resistance genotyping, and evolution. Importantly, we explored the applicability of HC to clinical metagenomics, which ultimately requires more work before it is a reliable and accurate tool for clinical diagnosis. Relatedly, the utility of HC was exemplified by COVID-19, which was used as a case study to illustrate the maturity of HC for recovering pathogen sequences. As we unravel the origins of COVID-19, zoonoses remain more relevant than ever. Therefore, the role of HC in biosurveillance studies is also highlighted in this review, which is critical in preparing us for the next pandemic. We also found that while HC is a popular tool to study viruses, it remains underutilised in parasites and fungi and, to a lesser extent, bacteria. Finally, weevaluated the future of HC with respect to bait design in the eukaryotic groups and the prospect of combining HC with long-read HTS.

ERS International Congress 2023: highlights from the Basic and Translational Sciences Assembly

Early career members of Assembly 3 (Basic and Translational Sciences) of the European Respiratory Society (ERS) summarise the key messages discussed during six selected sessions that took place at the ERS International Congress 2023 in Milan, Italy. Aligned with the theme of the congress, the first session covered is "Micro- and macro-environments and respiratory health", which is followed by a summary of the "Scientific year in review" session. Next, recent advances in experimental methodologies and new technologies are discussed from the "Tissue modelling and remodelling" session and a summary provided of the translational science session, "What did you always want to know about omics analyses for clinical practice?", which was organised as part of the ERS Translational Science initiative's aims. The "Lost in translation: new insights into cell-to-cell crosstalk in lung disease" session highlighted how next-generation sequencing can be integrated with laboratory methods, and a final summary of studies is presented from the "From the transcriptome landscape to innovative preclinical models in lung diseases" session, which links the transcriptome landscape with innovative preclinical models. The wide range of topics covered in the selected sessions and the high quality of the research discussed demonstrate the strength of the basic and translational science being presented at the international respiratory conference organised by the ERS.

Modeling the limits of detection for antimicrobial resistance genes in agri-food samples: a comparative analysis of bioinformatics tools

BACKGROUND

Although the spread of antimicrobial resistance (AMR) through food and its production poses a significant concern, there is limited research on the prevalence of AMR bacteria in various agri-food products. Sequencing technologies are increasingly being used to track the spread of AMR genes (ARGs) in bacteria, and metagenomics has the potential to bypass some of the limitations of single isolate characterization by allowing simultaneous analysis of the agri-food product microbiome and associated resistome. However, metagenomics may still be hindered by methodological biases, presence of eukaryotic DNA, and difficulties in detecting low abundance targets within an attainable sequence coverage. The goal of this study was to assess whether limits of detection of ARGs in agri-food metagenomes were influenced by sample type and bioinformatic approaches.

RESULTS

We simulated metagenomes containing different proportions of AMR pathogens and analysed them for taxonomic composition and ARGs using several common bioinformatic tools. Kraken2/Bracken estimates of species abundance were closest to expected values. However, analysis by both Kraken2/Bracken indicated presence of organisms not included in the synthetic metagenomes. Metaphlan3/Metaphlan4 analysis of community composition was more specific but with lower sensitivity than the Kraken2/Bracken analysis. Accurate detection of ARGs dropped drastically below 5X isolate genome coverage. However, it was sometimes possible to detect ARGs and closely related alleles at lower coverage levels if using a lower ARG-target coverage cutoff (< 80%). While KMA and CARD-RGI only predicted presence of expected ARG-targets or closely related gene-alleles, SRST2 (which allows read to map to multiple targets) falsely reported presence of distantly related ARGs at all isolate genome coverage levels. The presence of background microbiota in metagenomes influenced the accuracy of ARG detection by KMA, resulting in mcr-1 detection at 0.1X isolate coverage in the lettuce but not in the beef metagenome.

CONCLUSIONS

This study demonstrates accurate detection of ARGs in synthetic metagenomes using various bioinformatic methods, provided that reads from the ARG-encoding organism exceed approximately 5X isolate coverage (i.e. 0.4% of a 40 million read metagenome). While lowering thresholds for target gene detection improved sensitivity, this led to the identification of alternative ARG-alleles, potentially confounding the identification of critical ARGs in the resistome. Further advancements in sequencing technologies providing increased coverage depth or extended read lengths may improve ARG detection in agri-food metagenomic samples, enabling use of this approach for tracking clinically important ARGs in agri-food samples.

Examining the taxonomic distribution of tetracycline resistance in a wastewater plant

Microbial communities serve as reservoirs of antibiotic resistance genes (ARGs) and facilitate the dissemination of these genes to bacteria that infect humans. Relatively little is known about the taxonomic distribution of bacteria harboring ARGs in these reservoirs and the avenues of transmission due to the technical hurdles associated with characterizing the contents of complex microbial populations and the assignment of genes to particular genomes. Focusing on the array of tetracycline resistance (Tcr) genes in the primary and secondary phases of wastewater treatment, 17 of the 22 assayed Tcr genes were detected in at least one sample. We then applied emulsion, paired isolation, and concatenation PCR (epicPCR) to link tetracycline resistance genes to specific bacterial hosts. Whereas Tcr genes tend to vary in their distributions among bacterial taxa according to their modes of action, there were numerous instances in which a particular Tcr gene was associated with a host that was distantly related to all other bacteria bearing the same gene, including several hosts not previously identified. Tcr genes are far less host-restricted than previously assumed, indicating that complex microbial communities serve as settings where ARGs are spread among divergent bacterial phyla.

Sequencing-based analysis of the microbiomes of Spanish food processing facilities reveals environment-specific variation in the dominant taxa and antibiotic resistance genes

In the last years, advances in high throughput sequencing technologies have opened the possibility to broaden environmental monitoring activities in facilities processing food, offering expanded opportunities for characterizing in an untargeted manner the microbiome and resistome of foods and food processing environments (FPE) with huge potential benefits in food safety management systems. Here the microbiome and resistome of FPE from slaughterhouses (n = 3), dairy (n = 12) and meat (n = 10) processing plants were assessed through whole metagenome sequencing of 2 composite samples for each facility, comprising 10 FPE swabs taken from food contact surfaces and 10 FPE samples from non-food contact surfaces, respectively. FPE from slaughterhouses had more diverse microbiomes and resistomes, while FPE from dairy processing plants showed the highest β-dispersion, consistent with a more heterogeneous microbiome and resistome composition. The predominant bacterial genera depended on the industry type, with Pseudomonas and Psychrobacter being highly dominant in surfaces from slaughterhouses and meat industries, while different lactic acid bacteria predominated in dairy industries. The most abundant antimicrobial resistance genes (ARG) found were associated with resistance to aminoglycosides, tetracyclines and quaternary ammonium compounds (QAC). ARGs relating to resistance to aminoglycosides and tetracyclines were significantly more prevalent in slaughterhouses than in food processing plants, while QAC resistance genes were particularly abundant in some food contact surfaces from dairy and meat processing plants, suggesting that daily sanitation under suboptimal conditions may be selecting for persistent microbiota tolerant to these biocides in some facilities. The taxonomic mapping of ARG pointed to specific bacterial genera, such as Escherichia, Bacillus, or Staphylococcus, as carriers of the most relevant resistance determinants. About 63% of all ARG reads were assigned to contigs classified as plasmid-associated, indicating that the resistome of FPE may be strongly shaped through the spread of mobile genetic elements. Overall, the relevance of FPE as reservoirs of ARG was confirmed and it was demonstrated that next generation sequencing technologies allowing a deep characterisation of sources and routes of spread of microorganisms and antimicrobial resistance determinants in food industry settings hold promise to be integrated in monitoring and food safety management programmes.

A Comprehensive Bioinformatics Resource Guide for Genome-Based Antimicrobial Resistance Studies

The use of high-throughput sequencing technologies and bioinformatic tools has greatly transformed microbial genome research. With the help of sophisticated computational tools, it has become easier to perform whole genome assembly, identify and compare different species based on their genomes, and predict the presence of genes responsible for proteins, antimicrobial resistance, and toxins. These bioinformatics resources are likely to continuously improve in quality, become more user-friendly to analyze the multiple genomic data, efficient in generating information and translating it into meaningful knowledge, and enhance our understanding of the genetic mechanism of AMR. In this manuscript, we provide an essential guide for selecting the popular resources for microbial research, such as genome assembly and annotation, antibiotic resistance gene profiling, identification of virulence factors, and drug interaction studies. In addition, we discuss the best practices in computer-oriented microbial genome research, emerging trends in microbial genomic data analysis, integration of multi-omics data, the appropriate use of machine-learning algorithms, and open-source bioinformatics resources for genome data analytics.

What are the missing pieces needed to stop antibiotic resistance?

As recognized by several international agencies, antibiotic resistance is nowadays one of the most relevant problems for human health. While this problem was alleviated with the introduction of new antibiotics into the market in the golden age of antimicrobial discovery, nowadays few antibiotics are in the pipeline. Under these circumstances, a deep understanding on the mechanisms of emergence, evolution and transmission of antibiotic resistance, as well as on the consequences for the bacterial physiology of acquiring resistance is needed to implement novel strategies, beyond the development of new antibiotics or the restriction in the use of current ones, to more efficiently treat infections. There are still several aspects in the field of antibiotic resistance that are not fully understood. In the current article, we make a non-exhaustive critical review of some of them that we consider of special relevance, in the aim of presenting a snapshot of the studies that still need to be done to tackle antibiotic resistance.

Antimicrobials and antimicrobial resistance genes in a one-year city metabolism longitudinal study using wastewater-based epidemiology

This longitudinal study tests correlations between antimicrobial agents (AA) and corresponding antimicrobial resistance genes (ARGs) generated by a community of >100 k people inhabiting one city (Bath) over a 13 month randomised monitoring programme of community wastewater. Several AAs experienced seasonal fluctuations, such as the macrolides erythromycin and clarithromycin that were found in higher loads in winter, whilst other AA levels, including sulfamethoxazole and sulfapyridine, stayed consistent over the study period. Interestingly, and as opposed to AAs, ARGs prevalence was found to be less variable, which indicates that fluctuations in AA usage might either not directly affect ARG levels or this process spans beyond the 13-month monitoring period. However, it is important to note that weekly positive correlations between individual associated AAs and ARGs were observed where seasonal variability in AA use was reported: ermB and macrolides CLR-clarithromycin and dmCLR-N-desmethyl clarithromycin, aSPY- N-acetyl sulfapyridine and sul1, and OFX-ofloxacin and qnrS. Furthermore, ARG loads normalised to 16S rRNA (gene load per microorganism) were positively correlated to the ARG loads normalised to the human population (gene load per capita), which indicates that the abundance of microorganisms is proportional to the size of human population and that the community size, and not AA levels, is a major driver of ARG levels in wastewater. Comparison of hospital and community wastewater showed higher number of AAs and their metabolites, their frequency of occurrence and concentrations in hospital wastewater. Examples include: LZD-linezolid (used only in severe bacterial infections) and AMX-amoxicillin (widely used, also in community but with very low wastewater stability) that were found only in hospital wastewater. CIP-ciprofloxacin, SMX-sulfamethoxazole, TMP-trimethoprim, MTZ-metronidazole and macrolides were found at much higher concentrations in hospital wastewater while TET-tetracycline and OTC-oxytetracycline, as well as antiretrovirals, had an opposite trend. In contrast, comparable concentrations of resistant genes were observed in both community and hospital wastewater. This supports the hypothesis that AMR levels are more of an endemic nature, developing over time in individual communities. Both hospital and community wastewater had AAs that exceeded PNEC values (e.g. CLR-clarithromycin, CIP-ciprofloxacin). In general, though, hospital effluents had a greater number of quantifiable AAs exceeding PNECs (e.g. SMX-sulfamethoxazole, ERY-erythromycin, TMP-trimethoprim). Hospitals are therefore an important consideration in AMR surveillance as could be high risk areas for AMR.

A Comprehensive Review for the Surveillance of Human Pathogenic Microorganisms in Shellfish

Bivalve molluscan shellfish have been consumed for centuries. Being filter feeders, they may bioaccumulate some microorganisms present in coastal water, either naturally or through the discharge of human or animal sewage. Despite regulations set up to avoid microbiological contamination in shellfish, human outbreaks still occur. After providing an overview showing their implication in disease, this review aims to highlight the diversity of the bacteria or enteric viruses detected in shellfish species, including emerging pathogens. After a critical discussion of the available methods and their limitations, we address the interest of technological developments using genomics to anticipate the emergence of pathogens. In the coming years, further research needs to be performed and methods need to be developed in order to design the future of surveillance and to help risk assessment studies, with the ultimate objective of protecting consumers and enhancing the microbial safety of bivalve molluscan shellfish as a healthy food.

Gut Colonization by ESBL-Producing Escherichia coli in Dogs Is Associated with a Distinct Microbiome and Resistome Composition

The gut microbiome of humans and animals acts as a reservoir of extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-EC). Dogs are known for having a high prevalence of ESBL-EC in their gut microbiota, although their ESBL-EC carrier status often shifts over time. We hypothesized that the gut microbiome composition of dogs is implicated in ESBL-EC colonization status. Therefore, we assessed whether ESBL-EC carriage in dogs is associated with changes in the gut microbiome and resistome. Fecal samples were collected longitudinally from 57 companion dogs in the Netherlands every 2 weeks for a total of 6 weeks (n = 4 samples/dog). Carriage of ESBL-EC was determined through selective culturing and PCR and in line with previous studies, we observed a high prevalence of ESBL-EC carriage in dogs. Using 16s rRNA gene profiling we found significant associations between detected ESBL-EC carriage and an increased abundance of Clostridium sensu stricto 1, Enterococcus, Lactococcus, and the shared genera of Escherichia-Shigella in the dog microbiome. A resistome capture sequencing approach (ResCap) furthermore, revealed associations between detected ESBL-EC carriage and the increased abundance of the antimicrobial resistance genes: cmlA, dfrA, dhfR, floR, and sul3. In summary, our study showed that ESBL-EC carriage is associated with a distinct microbiome and resistome composition. IMPORTANCE The gut microbiome of humans and animals is an important source of multidrug resistant pathogens, including beta-lactamase-producing Escherichia coli (ESBL-EC). In this study, we assessed if the carriage of ESBL-EC in dogs was associated with changes in gut composition of bacteria and antimicrobial resistant genes (ARGs). Therefore, stool samples from 57 dogs were collected every 2 weeks for a total of 6 weeks. Sixty eight percent of the dogs carried ESBL-EC during at least one of the time points analyzed. By investigating the gut microbiome and resistome composition, we observed specific changes at time points when dogs were colonized with ESBL-EC compared to time points whenESBL-EC were not detected. In conclusion, our study highlights the importance to study the microbial diversity in companion animals, as gut colonization of particular antimicrobial resistant bacteria might be an indication of a changed microbial composition that is associated with the selection of particular ARGs.

Targeted metagenomics using bait-capture to detect antibiotic resistance genes in retail meat and seafood

Metagenomics analysis of foods has the potential to provide comprehensive data on the presence and prevalence of antimicrobial resistance (AMR) genes in the microbiome of foods. However, AMR genes are generally present in low abundance compared to other bacterial genes in the food microbiome and consequently require multiple rounds of in-depth sequencing for detection. Here, a metagenomics approach, using bait-capture probes targeting antimicrobial resistance and plasmid genes, is used to characterize the resistome and plasmidome of retail beef, chicken, oyster, shrimp, and veal enrichment cultures (n = 15). Compared to total shotgun metagenomics, bait-capture required approximately 40-fold fewer sequence reads to detect twice the number of AMR gene classes, AMR gene families, and plasmid genes across all sample types. For the detection of critically important extended spectrum beta-lactamase (ESBL) genes the bait capture method had a higher overall positivity rate (44%) compared to shotgun metagenomics (26%), and a culture-based method (29%). Overall, the results support the use of bait-capture for the identification of low abundance genes such as AMR genes from food samples.

Crosstalk between the Resident Microbiota and the Immune Cells Regulates Female Genital Tract Health

The female genital tract (FGT) performs several functions related to reproduction, but due to its direct exposure to the external environment, it may suffer microbial infections. Both the upper (uterus and cervix) and lower (vagina) FGT are covered by an epithelium, and contain immune cells (macrophages, dendritic cells, T and B lymphocytes) that afford a robust protection to the host. Its upper and the lower part differ in terms of Lactobacillus spp., which are dominant in the vagina. An alteration of the physiological equilibrium between the local microbiota and immune cells leads to a condition of dysbiosis which, in turn, may account for the outcome of FGT infection. Aerobic vaginitis, bacterial vaginosis, and Chlamydia trachomatis are the most frequent infections, and can lead to severe complications in reproduction and pregnancy. The use of natural products, such as probiotics, polyphenols, and lactoferrin in the course of FGT infections is an issue of current investigation. In spite of positive results, more research is needed to define the most appropriate administration, according to the type of patient.

Antimicrobial Resistance in the Global Health Network: Known Unknowns and Challenges for Efficient Responses in the 21st Century

Antimicrobial resistance (AMR) is one of the Global Health challenges of the 21st century. The inclusion of AMR on the global map parallels the scientific, technological, and organizational progress of the healthcare system and the socioeconomic changes of the last 100 years. Available knowledge about AMR has mostly come from large healthcare institutions in high-income countries and is scattered in studies across various fields, focused on patient safety (infectious diseases), transmission pathways and pathogen reservoirs (molecular epidemiology), the extent of the problem at a population level (public health), their management and cost (health economics), cultural issues (community psychology), and events associated with historical periods (history of science). However, there is little dialogue between the aspects that facilitate the development, spread, and evolution of AMR and various stakeholders (patients, clinicians, public health professionals, scientists, economic sectors, and funding agencies). This study consists of four complementary sections. The first reviews the socioeconomic factors that have contributed to building the current Global Healthcare system, the scientific framework in which AMR has traditionally been approached in such a system, and the novel scientific and organizational challenges of approaching AMR in the fourth globalization scenario. The second discusses the need to reframe AMR in the current public health and global health contexts. Given that the implementation of policies and guidelines are greatly influenced by AMR information from surveillance systems, in the third section, we review the unit of analysis ("the what" and "the who") and the indicators (the "operational units of surveillance") used in AMR and discuss the factors that affect the validity, reliability, and comparability of the information to be applied in various healthcare (primary, secondary, and tertiary), demographic, and economic contexts (local, regional, global, and inter-sectorial levels). Finally, we discuss the disparities and similarities between distinct stakeholders' objectives and the gaps and challenges of combatting AMR at various levels. In summary, this is a comprehensive but not exhaustive revision of the known unknowns about how to analyze the heterogeneities of hosts, microbes, and hospital patches, the role of surrounding ecosystems, and the challenges they represent for surveillance, antimicrobial stewardship, and infection control programs, which are the traditional cornerstones for controlling AMR in human health.

Exploiting a targeted resistome sequencing approach in assessing antimicrobial resistance in retail foods

BACKGROUND

With the escalating risk of antimicrobial resistance (AMR), there are limited analytical options available that can comprehensively assess the burden of AMR carried by clinical/environmental samples. Food can be a potential source of AMR bacteria for humans, but its significance in driving the clinical spread of AMR remains unclear, largely due to the lack of holistic-yet-sensitive tools for surveillance and evaluation. Metagenomics is a culture-independent approach well suited for uncovering genetic determinants of defined microbial traits, such as AMR, present within unknown bacterial communities. Despite its popularity, the conventional approach of non-selectively sequencing a sample's metagenome (namely, shotgun-metagenomics) has several technical drawbacks that lead to uncertainty about its effectiveness for AMR assessment; for instance, the low discovery rate of resistance-associated genes due to their naturally small genomic footprint within the vast metagenome. Here, we describe the development of a targeted resistome sequencing method and demonstrate its application in the characterization of the AMR gene profile of bacteria associated with several retail foods.

RESULT

A targeted-metagenomic sequencing workflow using a customized bait-capture system targeting over 4,000 referenced AMR genes and 263 plasmid replicon sequences was validated against both mock and sample-derived bacterial community preparations. Compared to shotgun-metagenomics, the targeted method consistently provided for improved recovery of resistance gene targets with a much-improved target detection efficiency (> 300-fold). Targeted resistome analyses conducted on 36 retail-acquired food samples (fresh sprouts, n = 10; ground meat, n = 26) and their corresponding bacterial enrichment cultures (n = 36) reveals in-depth features regarding the identity and diversity of AMR genes, most of which were otherwise undetected by the whole-metagenome shotgun sequencing method. Furthermore, our findings suggest that foodborne Gammaproteobacteria could be the major reservoir of food-associated AMR genetic determinants, and that the resistome structure of the selected high-risk food commodities are, to a large extent, dictated by microbiome composition.

CONCLUSIONS

For metagenomic sequencing-based surveillance of AMR, the target-capture method presented herein represents a more sensitive and efficient approach to evaluate the resistome profile of complex food or environmental samples. This study also further implicates retail foods as carriers of diverse resistance-conferring genes indicating a potential impact on the dissemination of AMR.

Quantitative PCR versus metagenomics for monitoring antibiotic resistance genes: balancing high sensitivity and broad coverage

The widespread occurrence of clinically relevant antibiotic resistance within humans, animals, and environment motivates the development of sensitive and accurate detection and quantification methods. Metagenomics and quantitative PCR (qPCR) are amongst the most used approaches. In this study, we aimed to evaluate and compare the performance of these methods to screen antibiotic resistance genes in animal faecal, wastewater, and water samples. Water and wastewater samples were from hospital effluent, different treatment stages of two treatment plants, and of the receiving river at the discharge point. The animal samples were from pig and chicken faeces. Antibiotic resistance gene coverage, sensitivity, and usefulness of the quantitative information were analyzed and discussed. While both methods were able to distinguish the resistome profiles and detect gradient stepwise mixtures of pig and chicken faeces, qPCR presented higher sensitivity for the detection of a few antibiotic resistance genes in water/wastewater. In addition, the comparison of predicted and observed antibiotic resistance gene quantifications unveiled the higher accuracy of qPCR. Metagenomics analyses, while less sensitive, provided a markedly higher coverage of antibiotic resistance genes compared to qPCR. The complementarity of both methods and the importance of selecting the best method according to the study purpose are discussed.

Multiplexed Target Enrichment Enables Efficient and In-Depth Analysis of Antimicrobial Resistome in Metagenomes

Antibiotic resistance genes (ARGs) pose a serious threat to public health and ecological security in the 21st century. However, the resistome only accounts for a tiny fraction of metagenomic content, which makes it difficult to investigate low-abundance ARGs in various environmental settings. Thus, a highly sensitive, accurate, and comprehensive method is needed to describe ARG profiles in complex metagenomic samples. In this study, we established a high-throughput sequencing method based on targeted amplification, which could simultaneously detect ARGs (n = 251), mobile genetic element genes (n = 8), and metal resistance genes (n = 19) in metagenomes. The performance of amplicon sequencing was compared with traditional metagenomic shotgun sequencing (MetaSeq). A total of 1421 primer pairs were designed, achieving extremely high coverage of target genes. The amplicon sequencing significantly improved the recovery of target ARGs (~9 × 104-fold), with higher sensitivity and diversity, less cost, and computation burden. Furthermore, targeted enrichment allows deep scanning of single nucleotide polymorphisms (SNPs), and elevated SNPs detection was shown in this study. We further performed this approach for 48 environmental samples (37 feces, 20 soils, and 7 sewage) and 16 clinical samples. All samples tested in this study showed high diversity and recovery of targeted genes. Our results demonstrated that the approach could be applied to various metagenomic samples and served as an efficient tool in the surveillance and evolution assessment of ARGs. Access to the resistome using the enrichment method validated in this study enabled the capture of low-abundance resistomes while being less costly and time-consuming, which can greatly advance our understanding of local and global resistome dynamics. IMPORTANCE ARGs, an increasing global threat to human health, can be transferred into health-related microorganisms in the environment by horizontal gene transfer, posing a serious threat to public health. Advancing profiling methods are needed for monitoring and predicting the potential risks of ARGs in metagenomes. Our study described a customized amplicon sequencing assay that could enable a high-throughput, targeted, in-depth analysis of ARGs and detect a low-abundance portion of resistomes. This method could serve as an efficient tool to assess the variation and evolution of specific ARGs in the clinical and natural environment.

Urban monitoring of antimicrobial resistance during a COVID-19 surge through wastewater surveillance

During the early phase of the COVID-19 pandemic, infected patients presented with symptoms similar to bacterial pneumonias and were treated with antibiotics before confirmation of a bacterial or fungal co-infection. We reasoned that wastewater surveillance could reveal potential relationships between reduced antimicrobial stewardship, specifically misprescribing antibiotics to treat viral infections, and the occurrence of antimicrobial resistance (AMR) in an urban community. Here, we analyzed microbial communities and AMR profiles in sewage samples from a wastewater treatment plant (WWTP) and a community shelter in Las Vegas, Nevada during a COVID-19 surge in December 2020. Using a respiratory pathogen and AMR enrichment next-generation sequencing panel, we identified four major phyla in the wastewater, including Actinobacteria, Firmicutes, Bacteroidetes and Proteobacteria. Consistent with antibiotics that were reportedly used to treat COVID-19 infections (e.g., fluoroquinolones and beta-lactams), we also measured a significant spike in corresponding AMR genes in the wastewater samples. AMR genes associated with colistin resistance (mcr genes) were also identified exclusively at the WWTP, suggesting that multidrug resistant bacterial infections were being treated during this time. We next compared the Las Vegas sewage data to local 2018-2019 antibiograms, which are antimicrobial susceptibility profile reports about common clinical pathogens. Similar to the discovery of higher levels of beta-lactamase resistance genes in sewage during 2020, beta-lactam antibiotics accounted for 51 ± 3 % of reported antibiotics used in antimicrobial susceptibility tests of 2018-2019 clinical isolates. Our data highlight how wastewater-based epidemiology (WBE) can be leveraged to complement more traditional surveillance efforts by providing community-level data to help identify current and emerging AMR threats.

Systems Biology: New Insight into Antibiotic Resistance

Over the past few decades, antimicrobial resistance (AMR) has emerged as an important threat to public health, resulting from the global propagation of multidrug-resistant strains of various bacterial species. Knowledge of the intrinsic factors leading to this resistance is necessary to overcome these new strains. This has contributed to the increased use of omics technologies and their extrapolation to the system level. Understanding the mechanisms involved in antimicrobial resistance acquired by microorganisms at the system level is essential to obtain answers and explore options to combat this resistance. Therefore, the use of robust whole-genome sequencing approaches and other omics techniques such as transcriptomics, proteomics, and metabolomics provide fundamental insights into the physiology of antimicrobial resistance. To improve the efficiency of data obtained through omics approaches, and thus gain a predictive understanding of bacterial responses to antibiotics, the integration of mathematical models with genome-scale metabolic models (GEMs) is essential. In this context, here we outline recent efforts that have demonstrated that the use of omics technology and systems biology, as quantitative and robust hypothesis-generating frameworks, can improve the understanding of antibiotic resistance, and it is hoped that this emerging field can provide support for these new efforts.

Target-enriched long-read sequencing (TELSeq) contextualizes antimicrobial resistance genes in metagenomes

BACKGROUND

Metagenomic data can be used to profile high-importance genes within microbiomes. However, current metagenomic workflows produce data that suffer from low sensitivity and an inability to accurately reconstruct partial or full genomes, particularly those in low abundance. These limitations preclude colocalization analysis, i.e., characterizing the genomic context of genes and functions within a metagenomic sample. Genomic context is especially crucial for functions associated with horizontal gene transfer (HGT) via mobile genetic elements (MGEs), for example antimicrobial resistance (AMR). To overcome this current limitation of metagenomics, we present a method for comprehensive and accurate reconstruction of antimicrobial resistance genes (ARGs) and MGEs from metagenomic DNA, termed target-enriched long-read sequencing (TELSeq).

RESULTS

Using technical replicates of diverse sample types, we compared TELSeq performance to that of non-enriched PacBio and short-read Illumina sequencing. TELSeq achieved much higher ARG recovery (>1,000-fold) and sensitivity than the other methods across diverse metagenomes, revealing an extensive resistome profile comprising many low-abundance ARGs, including some with public health importance. Using the long reads generated by TELSeq, we identified numerous MGEs and cargo genes flanking the low-abundance ARGs, indicating that these ARGs could be transferred across bacterial taxa via HGT.

CONCLUSIONS

TELSeq can provide a nuanced view of the genomic context of microbial resistomes and thus has wide-ranging applications in public, animal, and human health, as well as environmental surveillance and monitoring of AMR. Thus, this technique represents a fundamental advancement for microbiome research and application. Video abstract.

NanoRTax, a real-time pipeline for taxonomic and diversity analysis of nanopore 16S rRNA amplicon sequencing data

Background

The study of microbial communities and their applications have been leveraged by advances in sequencing techniques and bioinformatics tools. The Oxford Nanopore Technologies long-read sequencing by nanopores provides a portable and cost-efficient platform for sequencing assays. While this opens the possibility of sequencing applications outside specialized environments and real-time analysis of data, complementing the existing efficient library preparation protocols with streamlined bioinformatic workflows is required.

Results

Here we present NanoRTax, a Nextflow pipeline for nanopore 16S rRNA gene amplicon data that features state-of-the-art taxonomic classification tools and real-time capability. The pipeline is paired with a web-based visual interface to enable user-friendly inspections of the experiment in progress. NanoRTax workflow and a simulated real-time analysis were used to validate the prediction of adult Intensive Care Unit patient mortality based on full-length 16S rRNA sequencing data from respiratory microbiome samples.

Conclusions

This constitutes a proof-of-concept simulation study of how real-time bioinformatic workflows could be used to shorten the turnaround times in critical care settings and provides an instrument for future research on early-response strategies for sepsis.

mobileOG-db: a Manually Curated Database of Protein Families Mediating the Life Cycle of Bacterial Mobile Genetic Elements

Bacterial mobile genetic elements (MGEs) encode functional modules that perform both core and accessory functions for the element, the latter of which are often only transiently associated with the element. The presence of these accessory genes, which are often close homologs to primarily immobile genes, incur high rates of false positives and, therefore, limits the usability of these databases for MGE annotation. To overcome this limitation, we analyzed 10,776,849 protein sequences derived from eight MGE databases to compile a comprehensive set of 6,140 manually curated protein families that are linked to the “life cycle” (integration/excision, replication/recombination/repair, transfer, stability/transfer/defense, and phage-specific processes) of plasmids, phages, integrative, transposable, and conjugative elements. We overlay experimental information where available to create a tiered annotation scheme of high-quality annotations and annotations inferred exclusively through bioinformatic evidence. We additionally provide an MGE-class label for each entry (e.g., plasmid or integrative element), and assign to each entry a major and minor category. The resulting database, mobileOG-db (for mobile orthologous groups), comprises over 700,000 deduplicated sequences encompassing five major mobileOG categories and more than 50 minor categories, providing a structured language and interpretable basis for an array of MGE-centered analyses. mobileOG-db can be accessed at mobileogdb.flsi.cloud.vt.edu/, where users can select, refine, and analyze custom subsets of the dynamic mobilome.

IMPORTANCE The analysis of bacterial mobile genetic elements (MGEs) in genomic data is a critical step toward profiling the root causes of antibiotic resistance, phenotypic or metabolic diversity, and the evolution of bacterial genera. Existing methods for MGE annotation pose high barriers of biological and computational expertise to properly harness. To bridge this gap, we systematically analyzed 10,776,849 proteins derived from eight databases of MGEs to identify 6,140 MGE protein families that can serve as candidate hallmarks, i.e., proteins that can be used as “signatures” of MGEs to aid annotation. The resulting resource, mobileOG-db, provides a multilevel classification scheme that encompasses plasmid, phage, integrative, and transposable element protein families categorized into five major mobileOG categories and more than 50 minor categories. mobileOG-db thus provides a rich resource for simple and intuitive element annotation that can be integrated seamlessly into existing MGE detection pipelines and colocalization analyses.

Performance Characteristics of Next-Generation Sequencing for the Detection of Antimicrobial Resistance Determinants in Escherichia coli Genomes and Metagenomes

Short-read sequencing can provide detection of multiple genomic determinants of antimicrobial resistance from single bacterial genomes and metagenomic samples. Despite its increasing application in human, animal, and environmental microbiology, including human clinical trials, the performance of short-read Illumina sequencing for antimicrobial resistance gene (ARG) detection, including resistance-conferring single nucleotide polymorphisms (SNPs), has not been systematically characterized. Using paired-end 2 × 150 bp (base pair) Illumina sequencing and an assembly-based method for ARG prediction, we determined sensitivity, positive predictive value (PPV), and sequencing depths required for ARG detection in an Escherichia coli isolate of sequence type (ST) 38 spiked into a synthetic microbial community at varying abundances. Approximately 300,000 reads or 15× genome coverage was sufficient to detect ARGs in E. coli ST38, with comparable sensitivity and PPV to ~100× genome coverage. Using metagenome assembly of mixed microbial communities, ARG detection at E. coli relative abundances of 1% would require assembly of approximately 30 million reads to achieve 15× target coverage. The minimum sequencing depths were validated using public data sets of 948 E. coli genomes and 10 metagenomic rectal swab samples. A read-based approach using k-mer alignment (KMA) for ARG prediction did not substantially improve minimum sequencing depths for ARG detection compared to assembly of the E. coli ST38 genome or the combined metagenomic samples. Analysis of sequencing depths from recent studies assessing ARG content in metagenomic samples demonstrated that sequencing depths had a median estimated detection frequency of 84% (interquartile range: 30%-92%) for a relative abundance of 1%. IMPORTANCE Systematically determining Illumina sequencing performance characteristics for detection of ARGs in metagenomic samples is essential to inform study design and appraisal of human, animal, and environmental metagenomic antimicrobial resistance studies. In this study, we quantified the performance characteristics of ARG detection in E. coli genomes and metagenomes and established a benchmark of ~15× coverage for ARG detection for E. coli in metagenomes. We demonstrate that for low relative abundances, sequencing depths of ~30 million reads or more may be required for adequate sensitivity for many applications.

ROCker Models for Reliable Detection and Typing of Short-Read Sequences Carrying β-Lactamase Genes

Identification of genes encoding β-lactamases (BLs) from short-read sequences remains challenging due to the high frequency of shared amino acid functional domains and motifs in proteins encoded by BL genes and related non-BL gene sequences. Divergent BL homologs can be frequently missed during similarity searches, which has important practical consequences for monitoring antibiotic resistance. To address this limitation, we built ROCker models that targeted broad classes (e.g., class A, B, C, and D) and individual families (e.g., TEM) of BLs and challenged them with mock 150-bp- and 250-bp-read data sets of known composition. ROCker identifies most-discriminant bit score thresholds in sliding windows along the sequence of the target protein sequence and hence can account for nondiscriminative domains shared by unrelated proteins. BL ROCker models showed a 0% false-positive rate (FPR), a 0% to 4% false-negative rate (FNR), and an up-to-50-fold-higher F1 score [2 × precision × recall/(precision + recall)] compared to alternative methods, such as similarity searches using BLASTx with various e-value thresholds and BL hidden Markov models, or tools like DeepARG, ShortBRED, and AMRFinder. The ROCker models and the underlying protein sequence reference data sets and phylogenetic trees for read placement are freely available through http://enve-omics.ce.gatech.edu/data/rocker-bla. Application of these BL ROCker models to metagenomics, metatranscriptomics, and high-throughput PCR gene amplicon data should facilitate the reliable detection and quantification of BL variants encoded by environmental or clinical isolates and microbiomes and more accurate assessment of the associated public health risk, compared to the current practice.

IMPORTANCE Resistance genes encoding β-lactamases (BLs) confer resistance to the widely prescribed antibiotic class β-lactams. Therefore, it is important to assess the prevalence of BL genes in clinical or environmental samples for monitoring the spreading of these genes into pathogens and estimating public health risk. However, detecting BLs in short-read sequence data is technically challenging. Our ROCker model-based bioinformatics approach showcases the reliable detection and typing of BLs in complex data sets and thus contributes toward solving an important problem in antibiotic resistance surveillance. The ROCker models developed substantially expand the toolbox for monitoring antibiotic resistance in clinical or environmental settings.

Inferring antibiotic susceptibility from metagenomic data: dream or reality?

BACKGROUND

The diagnosis of bacterial infections continues to rely on culture, a slow process in which antibiotic susceptibility profiles of potential pathogens are made available to clinicians 48h after sampling, at best. Recently, clinical metagenomics (CMg), the metagenomic sequencing of samples with the purpose of identifying microorganisms and determining their susceptibility to antimicrobials, has emerged as a potential diagnostic tool that could prove faster than culture. CMg indeed has the potential to detect antibiotic resistance genes (ARGs) and mutations associated with resistance. Nevertheless, many challenges have yet to be overcome in order to make rapid phenotypic inference of antibiotic susceptibility from metagenomic data a reality.

OBJECTIVES

The objective of this narrative review is to discuss the challenges underlying the phenotypic inference of antibiotic susceptibility from metagenomic data.

SOURCES

We conducted a narrative review using published articles available in the NCBI Pubmed database.

CONTENT

We review the current ARG databases with a specific emphasis on those which now provide associations with phenotypic data. Next, we discuss the bioinformatic tools designed to identify ARGs in metagenomes. We then report on the performance of phenotypic inference from genomic data and the issue predicting the expression of ARGs. Finally, we address the challenge of linking an ARG to this host.

IMPLICATIONS

Significant improvements have recently been made in associating ARG and phenotype, and the inference of susceptibility from genomic data has been demonstrated in pathogenic bacteria such as Staphylococci and Enterobacterales. Resistance involving gene expression is more challenging however, and inferring susceptibility from species such as Pseudomonas aeruginosa remains difficult. Future research directions include the consideration of gene expression via RNA sequencing and machine learning.

Metatranscriptomic Analysis of the Chicken Gut Resistome Response to In-Feed Antibiotics and Natural Feed Additives

The emergence of resistance against common antibiotics in the gut microbiota is a major issue for both human and livestock health. This highlights the need for understanding the impact of such application on the reservoir of antibiotic resistance genes in poultry gut and devising means to circumvent the potential resistome expansion. Phytogenic feed additives (PFAs) are potential natural alternative to antibiotic to improve animal health and performance, supposedly via positively affecting the gut microbial ecosystem, but there is little systematic information available. In this time-course study, we applied a shotgun meta-transcriptomics approach to investigate the impact of a PFA product as well as the commonly used antibiotic, zinc bacitracin either at AGP concentration or therapeutic concentration on the gut microbiome and resistome of broiler chickens raised for 35 days. Over the course of the trial, PFA treatments increased the abundance of Firmicutes such as Lactobacillus and resulted in a lower abundance of Escherichia, while the latter group increased significantly in the feces of chickens that received either AGP or AB doses of bacitracin. Tetracycline resistance and aminoglycoside resistance were the predominant antibiotic resistance gene (ARG) classes found, regardless of the treatment. PFA application resulted in a decrease in abundance of ARGs compared to those in the control group and other antibiotic treatment groups. In summary, the findings from this study demonstrate the potential of phytogenic feed additives could be an alternative to antibiotics in poultry farming, with the added benefit of counteracting antimicrobial resistance development.

The Bacterial Urban Resistome: Recent Advances

Cities that are densely populated are reservoirs of antibiotic resistant genes (ARGs). The overall presence of all resistance genes in a specific environment is defined as a resistome. Spatial proximity of surfaces and different hygienic conditions leads to the transfer of antibiotic resistant bacteria (ARB) within urban environments. Built environments, public transportation, green spaces, and citizens’ behaviors all support persistence and transfer of antimicrobial resistances (AMR). Various unique aspects of urban settings that promote spread and resilience of ARGs/ARB are discussed: (i) the role of hospitals and recreational parks as reservoirs; (ii) private and public transportation as carriers of ARGs/ARB; (iii) the role of built environments as a hub for horizontal gene transfer even though they support lower microbial biodiversity than outdoor environments; (iv) the need to employ ecological and evolutionary concepts, such as modeling the fate of a specific ARG/ARB, to gain enhanced health risk assessments. Our understanding and our ability to control the rise of AMR in an urban setting is linked to our knowledge of the network connecting urban reservoirs and the environment.

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

Antimicrobial Resistance in Rivers: A Review of the Genes Detected and New Challenges

River ecosystems are very important parts of the water cycle and an excellent habitat, food, and drinking water source for many organisms, including humans. Antibiotics are emerging contaminants which can enter rivers from various sources. Several antibiotics and their related antibiotic resistance genes (ARGs) have been detected in these ecosystems by various research programs and could constitute a substantial problem. The presence of antibiotics and other resistance cofactors can boost the development of ARGs in the chromosomes or mobile genetic elements of natural bacteria in rivers. The ARGs in environmental bacteria can also be transferred to clinically important pathogens. However, antibiotics and their resistance genes are both not currently monitored by national or international authorities responsible for controlling the quality of water bodies. For example, they are not included in the contaminant list in the European Water Framework Directive or in the US list of Water-Quality Benchmarks for Contaminants. Although ARGs are naturally present in the environment, very few studies have focused on non-impacted rivers to assess the background ARG levels in rivers, which could provide some useful indications for future environmental regulation and legislation. The present study reviews the antibiotics and associated ARGs most commonly measured and detected in rivers, including the primary analysis tools used for their assessment. In addition, other factors that could enhance antibiotic resistance, such as the effects of chemical mixtures, the effects of climate change, and the potential effects of the coronavirus disease 2019 pandemic, are discussed. Environ Toxicol Chem 2022;41:687-714. © 2022 SETAC.

Altered Ecology of the Respiratory Tract Microbiome and Nosocomial Pneumonia

Nosocomial pneumonia is one of the most frequent infections in critical patients. It is primarily associated with mechanical ventilation leading to severe illness, high mortality, and prolonged hospitalization. The risk of mortality has increased over time due to the rise in multidrug-resistant (MDR) bacterial infections, which represent a global public health threat. Respiratory tract microbiome (RTM) research is growing, and recent studies suggest that a healthy RTM positively stimulates the immune system and, like the gut microbiome, can protect against pathogen infection through colonization resistance (CR). Physiological conditions of critical patients and interventions as antibiotics administration and mechanical ventilation dramatically alter the RTM, leading to dysbiosis. The dysbiosis of the RTM of ICU patients favors the colonization by opportunistic and resistant pathogens that can be part of the microbiota or acquired from the hospital environments (biotic or built ones). Despite recent evidence demonstrating the significance of RTM in nosocomial infections, most of the host-RTM interactions remain unknown. In this context, we present our perspective regarding research in RTM altered ecology in the clinical environment, particularly as a risk for acquisition of nosocomial pneumonia. We also reflect on the gaps in the field and suggest future research directions. Moreover, expected microbiome-based interventions together with the tools to study the RTM highlighting the "omics" approaches are discussed.

Impact of long-term dietary habits on the human gut resistome in the Dutch population

The human gut microbiome plays a central role in health and disease. Environmental factors, such as lifestyle and diet, are known to shape the gut microbiome as well as the reservoir of resistance genes that these microbes harbour; the resistome. In this study we assessed whether long-term dietary habits within a single geographical region (the Netherlands) impact the human gut resistome. Faecal samples from Dutch omnivores, pescatarians, vegetarians and vegans were analysed by metagenomic shotgun sequencing (MSS) (n = 149) and resistome capture sequencing approach (ResCap) (n = 64). Among all diet groups, 119 and 145 unique antibiotic resistance genes (ARGs) were detected by MSS or ResCap, respectively. Five or fifteen ARGs were shared between all diet groups, based on MSS and ResCap, respectively. The total number of detected ARGs by MSS or ResCap was not significantly different between the groups. MSS also revealed that vegans have a distinct microbiome composition, compared to other diet groups. Vegans had a lower abundance of Streptococcus thermophilus and Lactococcus lactis compared to pescatarians and a lower abundance of S. thermophilus when compared to omnivores. In summary, our study showed that long-term dietary habits are not associated with a specific resistome signature.

Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Antibiotic Resistance: One Health One World Outlook

Antibiotic resistance (ABR) is a growing public health concern worldwide, and it is now regarded as a critical One Health issue. One Health’s interconnected domains contribute to the emergence, evolution, and spread of antibiotic-resistant microorganisms on a local and global scale, which is a significant risk factor for global health. The persistence and spread of resistant microbial species, and the association of determinants at the human-animal-environment interface can alter microbial genomes, resulting in resistant superbugs in various niches. ABR is motivated by a well-established link between three domains: human, animal, and environmental health. As a result, addressing ABR through the One Health approach makes sense. Several countries have implemented national action plans based on the One Health approach to combat antibiotic-resistant microbes, following the Tripartite’s Commitment Food and Agriculture Organization (FAO)-World Organization for Animal Health (OIE)-World Health Organization (WHO) guidelines. The ABR has been identified as a global health concern, and efforts are being made to mitigate this global health threat. To summarize, global interdisciplinary and unified approaches based on One Health principles are required to limit the ABR dissemination cycle, raise awareness and education about antibiotic use, and promote policy, advocacy, and antimicrobial stewardship.

A review: antimicrobial resistance data mining models and prediction methods study for pathogenic bacteria

Antimicrobials have paved the way for medical and social development over the last century and are indispensable for treating infections in humans and animals. The dramatic spread and diversity of antibiotic-resistant pathogens have significantly reduced the efficacy of essentially all antibiotic classes and is a global problem affecting human and animal health. Antimicrobial resistance is influenced by complex factors such as resistance genes and dosing, which are highly nonlinear, time-lagged and multivariate coupled, and the amount of resistance data is large and redundant, making it difficult to predict and analyze. Based on machine learning methods and data mining techniques, this paper reviews (1) antimicrobial resistance data storage and analysis techniques, (2) antimicrobial resistance assessment methods and the associated risk assessment methods for antimicrobial resistance, and (3) antimicrobial resistance prediction methods. Finally, the current research results on antimicrobial resistance and the development trend are summarized to provide a systematic and comprehensive reference for the research on antimicrobial resistance.

Future potential of metagenomics in clinical laboratories

INTRODUCTION

Rapid and sensitive diagnostic strategies are necessary for patient care and public health. Most of the current conventional microbiological assays detect only a restricted panel of pathogens at a time or require a microbe to be successfully cultured from a sample. Clinical metagenomics next-generation sequencing (mNGS) has the potential to unbiasedly detect all pathogens in a sample, increasing the sensitivity for detection and enabling the discovery of unknown infectious agents.

AREAS COVERED

High expectations have been built around mNGS; however, this technique is far from widely available. This review highlights the advances and currently available options in terms of costs, turnaround time, sensitivity, specificity, validation, and reproducibility of mNGS as a diagnostic tool in clinical microbiology laboratories.

EXPERT OPINION

The need for a novel diagnostic tool to increase the sensitivity of microbial diagnostics is clear. mNGS has the potential to revolutionise clinical microbiology. However, its role as a diagnostic tool has yet to be widely established, which is crucial for successfully implementing the technique. A clear definition of diagnostic algorithms that include mNGS is vital to show clinical utility. Similarly to real-time PCR, mNGS will one day become a vital tool in any testing algorithm.

Novel methods of microbiome analysis in the food industry

The study of the food microbiome has gained considerable interest in recent years, mainly due to the wide range of applications that can be derived from the analysis of metagenomes. Among these applications, it is worth mentioning the possibility of using metagenomic analyses to determine food authenticity, to assess the microbiological safety of foods thanks to the detection and tracking of pathogens, antibiotic resistance genes and other undesirable traits, as well to identify the microorganisms responsible for food processing defects. Metataxonomics and metagenomics are currently the gold standard methodologies to explore the full potential of metagenomes in the food industry. However, there are still a number of challenges that must be solved in order to implement these methods routinely in food chain monitoring, and for the regulatory agencies to take them into account in their opinions. These challenges include the difficulties of analysing foods and food-related environments with a low microbial load, the lack of validated bioinformatics pipelines adapted to food microbiomes and the difficulty of assessing the viability of the detected microorganisms. This review summarizes the methods of microbiome analysis that have been used, so far, in foods and food-related environments, with a specific focus on those involving Next-Generation Sequencing technologies.

Knowledge gaps in the assessment of antimicrobial resistance in surface waters

The spread of antibiotic resistance in the water environment has been widely described. However, still many knowledge gaps exist regarding the selection pressure from antibiotics, heavy metals and other substances present in surface waters as a result of anthropogenic activities, as well as the extent and impact of this phenomenon on aquatic organisms and humans. In particular, the relationship between environmental concentrations of antibiotics and the acquisition of ARGs by antibiotic-sensitive bacteria as well as the impact of heavy metals and other selective agents on antimicrobial resistance (AMR) need to be defined. Currently, established safety values are based on the effects of antibiotic toxicity neglecting the question of AMR spread. In turn, risk assessment of antibiotics in waterbodies remains a complex question implicating multiple variables and unknowns reinforced by the lack of harmonized protocols and official guidelines. In the present review, we discussed current state-of-the-art and the knowledge gaps related to pressure exerted by antibiotics and heavy metals on aquatic environments and their relationship to the spread of AMR. Along with this latter, we reflected on (i) the risk assessment in surface waters, (ii) selective pressures contributing to its transfer and propagation and (iii) the advantages of metagenomics in investigating AMR. Furthermore, the role of microplastics in co-selection for metal and antibiotic resistance, together with the need for more studies in freshwater are highlighted.

Probiotic lactobacilli in formulas and hygiene products for the health of the urogenital tract

Lactobacilli are the predominant microorganisms of the healthy human vagina. A novel alternative for the prevention and treatment of female urogenital tract infections (UGTI) is the inclusion of these microorganisms as active pharmaceutical ingredients in probiotic formulas, and more recently in female hygienic products. Probiotics are defined as “live microorganisms that, when administered in adequate amounts, confer a health benefit on the host.” A list of requirements must be considered during the development of probiotic product/formula for the female urogenital tract (UGT). This review aims to resume the requirements, probiotic characteristics, and clinical trial applied to determine the effect of probiotic and potentially probiotic strains on different woman’s physiological and pathological conditions, and in preterm birth prevention. A revision of female hygienic products available in the world market is included, together with novel studies applying nanotechnology for Lactobacillus incorporation in hygienic products. Further studies and well‐designed clinical trials are urgently required to complement the current knowledge and applications of probiotics in the female UGT. The use of probiotic formulas and products will improve and restore the ecological equilibrium of the UGT microbiome to prevent and treat UGTI in women under different conditions.

Escaping the fate of Sisyphus: assessing resistome hybridization baits for antimicrobial resistance gene capture

Finding, characterizing and monitoring reservoirs for antimicrobial resistance (AMR) is vital to protecting public health. Hybridization capture baits are an accurate, sensitive and cost-effective technique used to enrich and characterize DNA sequences of interest, including antimicrobial resistance genes (ARGs), in complex environmental samples. We demonstrate the continued utility of a set of 19 933 hybridization capture baits designed from the Comprehensive Antibiotic Resistance Database (CARD)v1.1.2 and Pathogenicity Island Database (PAIDB)v2.0, targeting 3565 unique nucleotide sequences that confer resistance. We demonstrate the efficiency of our bait set on a custom-made resistance mock community and complex environmental samples to increase the proportion of on-target reads as much as >200-fold. However, keeping pace with newly discovered ARGs poses a challenge when studying AMR, because novel ARGs are continually being identified and would not be included in bait sets designed prior to discovery. We provide imperative information on how our bait set performs against CARDv3.3.1, as well as a generalizable approach for deciding when and how to update hybridization capture bait sets. This research encapsulates the full life cycle of baits for hybridization capture of the resistome from design and validation (both in silico and in vitro) to utilization and forecasting updates and retirement.

Mobile Genetic Elements of Vibrio cholerae and the Evolution of Its Antimicrobial Resistance

Vibrio cholerae (VC) is the causative agent of the severe dehydrating diarrheal disease cholera. The primary treatment for cholera is oral rehydration therapy (ORT). However, in case of moderate to severe dehydration, antibiotics are administered to reduce morbidity. Due to the emergence of multidrug resistant (MDR) strains of VC routinely used antibiotics fail to be effective in cholera patients. Antimicrobial resistance (AMR) is encoded in the genome of bacteria and is usually acquired from other organisms cohabiting in the environment or in the gut with which it interacts in the gut or environmental niche. The antimicrobial resistance genes (ARGs) are usually borne on mobile genetic elements (MGEs) like plasmids, transposons, integrons and SXT constin. Horizontal gene transfer (HGT) helps in the exchange of ARGs among bacteria leading to dissemination of AMR. In VC the acquisition and loss of AMR to many antibiotics have been found to be a dynamic process. This review describes the different AMR determinants and mechanisms of resistance that have been discovered in VC. These ARGs borne usually on MGEs have been recovered from isolates associated with past and present epidemics worldwide. These are responsible for resistance of VC to common antibiotics and are periodically lost and gained contributing to its genetic evolution. These resistance markers can be routinely used for AMR surveillance in VC. The review also presents a precise perspective on the importance of the gut microbiome in the emergence of MDR VC and concludes that the gut microbiome is a potential source of molecular markers and networks which can be manipulated for the interception of AMR in the future.

Threats of antibiotic resistance: an obliged reappraisal

We are living in a society of fear, where the objectivity in estimating risks is distorted by the media and the interested parties. During more than half of a century, the feeling of antibiotic resistance as an apocalyptic phenomenon able to push our society to the high mortality rates caused by infectious diseases in the dark pre-antibiotic ages has been steadily rising. However, at the current status of modern medicine, at least in the high-medium income countries, mortality by lack of efficacy of the antibiotic armamentarium in the therapy of infections is a problem, but not a catastrophe. The threat of antibiotic resistance has many other aspects than failures of therapy in the individual patient. Among them, the increase in the frequency of severe and potentially lethal infections, as bacteremia, the population biology alterations of the healthy microbiota, the global acceleration of bacterial evolution by selecting natural genetic tools mediating microbial interactions, and, most importantly, by modifying the equilibrium and composition of environmental microbial communities. All these threats have huge implications for human health as members of a Biosphere entirely rooted in a menaced microbiosphere.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.

Targeted metagenomics reveals inferior resilience of farm soil resistome compared to soil microbiome after manure application

Application of animal manure to soils results in the introduction of manure-derived bacteria and their antimicrobial resistance genes (ARGs) into soils. ResCap is a novel targeted-metagenomic approach that allows the detection of minority components of the resistome gene pool without the cost-prohibitive coverage depths and can provide a valuable tool to study the spread of antimicrobial resistance (AMR) in the environment. We used high-throughput sequencing and qPCR for 16S rRNA gene fragments as well as ResCap to explore the dynamics of bacteria, and ARGs introduced to soils and adjacent water ditches, both at community and individual scale, over a period of three weeks. The soil bacteriome and resistome showed strong resilience to the input of manure, as manuring did not impact the overall structure of the bacteriome, and its effects on the resistome were transient. Initially, manure application resulted in a substantial increase of ARGs in soils and adjacent waters, while not affecting the overall bacterial community composition. Still, specific families increased after manure application, either through the input of manure (e.g., Dysgonomonadaceae) or through enrichment after manuring (e.g., Pseudomonadaceae). Depending on the type of ARG, manure application resulted mostly in an increase (e.g., aph(6)-Id), but occasionally also in a decrease (e.g., dfrB3) of the absolute abundance of ARG clusters (FPKM/kg or L). This study shows that the structures of the bacteriome and resistome are shaped by different factors, where the bacterial community composition could not explain the changes in ARG diversity or abundances. Also, it highlights the potential of applying targeted metagenomic techniques, such as ResCap, to study the fate of AMR in the environment.

The lung microbiome in lung transplantation

Culture-independent study of the lower respiratory tract after lung transplantation has enabled an understanding of the microbiome - that is, the collection of bacteria, fungi, and viruses, and their respective gene complement - in this niche. The lung has unique features as a microbial environment, with balanced entry from the upper respiratory tract, clearance, and local replication. There are many pressures impacting the microbiome after transplantation, including donor allograft factors, recipient host factors such as underlying disease and ongoing exposure to the microbe-rich upper respiratory tract, and transplantation-related immunosuppression, antimicrobials, and postsurgical changes. To date, we understand that the lung microbiome after transplant is dysbiotic; that is, it has higher biomass and altered composition compared to a healthy lung. Emerging data suggest that specific microbiome features may be linked to host responses, both immune and non-immune, and clinical outcomes such as chronic lung allograft dysfunction (CLAD), but many questions remain. The goal of this review is to put into context our burgeoning understanding of the lung microbiome in the postlung transplant patient, the interactions between microbiome and host, the role the microbiome may play in post-transplant complications, and critical outstanding research questions.

Biosolids as a Source of Antibiotic Resistance Plasmids for Commensal and Pathogenic Bacteria

Antibiotic resistance (AR) is a threat to modern medicine, and plasmids are driving the global spread of AR by horizontal gene transfer across microbiomes and environments. Determining the mobile resistome responsible for this spread of AR among environments is essential in our efforts to attenuate the current crisis. Biosolids are a wastewater treatment plant (WWTP) byproduct used globally as fertilizer in agriculture. Here, we investigated the mobile resistome of biosolids that are used as fertilizer. This was done by capturing resistance plasmids that can transfer to human pathogens and commensal bacteria. We used a higher-throughput version of the exogenous plasmid isolation approach by mixing several ESKAPE pathogens and a commensal Escherichia coli with biosolids and screening for newly acquired resistance to about 10 antibiotics in these strains. Six unique resistance plasmids transferred to Salmonella typhimurium, Klebsiella aerogenes, and E. coli. All the plasmids were self-transferable and carried 3-6 antibiotic resistance genes (ARG) conferring resistance to 2-4 antibiotic classes. These plasmids-borne resistance genes were further embedded in genetic elements promoting intracellular recombination (i.e., transposons or class 1 integrons). The plasmids belonged to the broad-host-range plasmid (BHR) groups IncP-1 or PromA. Several of them were persistent in their new hosts when grown in the absence of antibiotics, suggesting that the newly acquired drug resistance traits would be sustained over time. This study highlights the role of BHRs in the spread of ARG between environmental bacteria and human pathogens and commensals, where they may persist. The work further emphasizes biosolids as potential vehicles of highly mobile plasmid-borne antibiotic resistance genes.

Spare and repair the gut microbiota from antibiotic-induced dysbiosis: state-of-the-art

Homeostasis of the intestinal microbiota is currently recognized as a major contributor to human health. Furthermore, intestinal dysbiosis is associated with a multitude of consequences, including intestinal colonization by antibiotic-resistant or pathogenic bacteria, such as Clostridioides difficile, and reduced efficacy of promising anticancer immunotherapies. By far, the most immediate and drastic exposure leading to dysbiosis is antibiotic treatment. Many attempts have been made to prevent or repair antibiotic-associated dysbiosis. Here, we review these innovations and the difficulties associated with their development.

Antibiotic prophylaxis and the gastrointestinal resistome in paediatric patients with acute lymphoblastic leukaemia: a cohort study with metagenomic sequencing analysis

Background

Although antibiotic prophylaxis with levofloxacin can reduce the risk of serious infection in immunocompromised patients, the potential contribution of prophylaxis to antibiotic resistance is a major drawback. We aimed to identify the effects of levofloxacin prophylaxis, given to paediatric patients with acute lymphoblastic leukaemia to prevent infections during induction chemotherapy, on antibiotic resistance in gastrointestinal microbiota after completion of induction and consolidation therapy.

Methods

This prospective, single-centre (St Jude Children's Research Hospital, Memphis, TN, USA) cohort study included children (≤18 years) receiving therapy for newly diagnosed acute lymphoblastic leukaemia and who received either primary levofloxacin prophylaxis or no antibacterial prophylaxis (aside from Pneumocystis jirovecii prophylaxis with trimethoprim-sulfamethoxazole) and provided at least two stool samples, including one after completion of induction therapy. We used metagenomic sequencing to identify bacterial genes that confer resistance to fluoroquinolones, trimethoprim-sulfamethoxazole, or other antibiotics, and to identify point mutations in bacterial topoisomerases (gyrA, parC) that confer resistance to fluoroquinolones. We then used generalised linear mixed models to compare the prevalence and relative abundance of antibiotic resistance gene groups after completion of induction and consolidation therapy between participants who had received levofloxacin and those who received no prophylaxis.

Findings

Between Feb 1, 2012, and April 30, 2016, 118 stool samples (32 baseline, 49 after induction, and 37 after consolidation) were collected from 49 evaluable participants; of these participants, 31 (63%) received levofloxacin prophylaxis during induction therapy and 18 (37%) received no antibacterial prophylaxis. Over the course of induction therapy, there was an overall increase in the relative abundance of trimethoprim-sulfamethoxazole resistance genes (estimated mean fold change 5·9, 95% CI 3·6-9·6; p<0·0001), which was not modified by levofloxacin prophylaxis (p=0·46). By contrast, the prevalence of topoisomerase point mutations increased over the course of induction therapy in levofloxacin recipients (mean prevalence 10·4% [95% CI 3·2-25·4] after induction therapy vs 3·7% [0·2-22·5] at baseline) but not other participants (0% vs 0%; p<0·0001). There was no significant difference between prophylaxis groups with respect to changes in aminoglycoside, β-lactam, vancomycin, or multidrug resistance genes after completion of induction or consolidation therapy.

Interpretation

Analysing the gastrointestinal resistome can provide insights into the effects of antibiotics on the risk of antibiotic-resistant infections. In this study, antibiotic prophylaxis with trimethoprim-sulfamethoxazole or levofloxacin during induction therapy for acute lymphoblastic leukaemia appeared to increase the short-term and medium-term risk of colonisation with bacteria resistant to these antibiotics, but not to other drugs. More research is needed to determine the longer-term effects of antibacterial prophylaxis on colonisation with antibiotic-resistant bacteria.

Funding

Children's Infection Defense Center at St Jude Children's Research Hospital, American Lebanese Syrian Associated Charities, and National Institutes of Health.

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

Isolation and Visualization of Plasmids from Gram-Positive Bacteria of Interest in Public Health

This chapter describes the methods to extract and characterize plasmids of Gram-positive bacterial species of interest in public health (biomedicine, veterinary, and food safety) as Staphylococcus, Streptococcus, Enterococcus, Listeria, and Clostridium and lactic acid bacteria. References for detailed plasmid classification are given in order to provide a comprehensive landscape in the interpretation of their plasmidomes.