Capturing the Resistome: a Targeted Capture Method To Reveal Antibiotic Resistance Determinants in Metagenomes

Photorhabdus africana sp. nov. isolated from Heterorhabditis entomopathogenic nematodes

One Gram-negative, rod-shaped bacterial strain, isolated from an undescribed Heterorhabditis entomopathogenic nematode species was characterized to determine its taxonomic position. The 16S rRNA gene sequences indicate that it belongs to the class Gammaproteobacteria, to the family Morganellaceae, to the genus Photorhabdus, and likely represents a novel bacterial species. This strain, designated here as CRI-LCT, was therefore molecularly, biochemically, and morphologically characterized to describe the novel bacterial species. Phylogenetic reconstructions using 16S rRNA gene sequences show that CRI-LCT is closely related to P. laumondii subsp. laumondii TT01T and to P. laumondii subsp. clarkei BOJ-47T. The 16rRNA gene sequences between CRI-LCT and P. laumondii subsp. laumondii TT01T are 99.1% identical, and between CRI-LCT and P. laumondii subsp. clarkei BOJ-47T are 99.2% identical. Phylogenetic reconstructions using whole genome sequences show that CRI-LCT is closely related to P. laumondii subsp. laumondii TT01T and to P. laumondii subsp. clarkei BOJ-47T. Moreover, digital DNA-DNA hybridization (dDDH) values between CRI-LCT and its two relative species P. laumondii subsp. laumondii TT01T and P. laumondii subsp. clarkei BOJ-47T are 65% and 63%, respectively. In addition, we observed that average nucleotide identity (ANI) values between CRI-LCT and its two relative species P. laumondii subsp. laumondii TT01T and P. laumondii subsp. clarkei BOJ-47T are 95.8% and 95.5%, respectively. These values are below the 70% dDDH and the 95-96% ANI divergence thresholds that delimits prokaryotic species. Based on these genomic divergence values, and the phylogenomic separation, we conclude that CRI-LCT represents a novel bacterial species, for which we propose the name Photorhabdus africana sp. nov. with CRI-LCT (= CCM 9390T = CCOS 2112T) as the type strain. The following biochemical tests allow to differentiate P. africana sp. nov. CRI-LCT from other species of the genus, including its more closely related taxa: β-Galactosidase, citrate utilization, urease and tryptophan deaminase activities, indole and acetoin production, and glucose and inositol oxidation. Our study contributes to a better understanding of the taxonomy and biodiversity of this important bacterial group with great biotechnological and agricultural potential.

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.

Improved Equine Fecal Microbiome Characterization Using Target Enrichment by Hybridization Capture

GITDs are among the most common causes of death in adult and young horses in the United States (US). Previous studies have indicated a connection between GITDs and the equine gut microbiome. However, the low taxonomic resolution of the current microbiome sequencing methods has hampered the identification of specific bacterial changes associated with GITDs in horses. Here, we have compared TEHC, a new approach for 16S rRNA gene selection and sequencing, with conventional 16S rRNA gene amplicon sequencing for the characterization of the equine fecal microbiome. Both sequencing approaches were used to determine the fecal microbiome of four adult horses and one commercial mock microbiome. Our results show that TEHC yielded significantly more operational taxonomic units (OTUs) than conventional 16S amplicon sequencing when the same number of reads were used in the analysis. This translated into a deeper and more accurate characterization of the fecal microbiome when the samples were sequenced with TEHC according to the relative abundance analysis. Alpha and beta diversity metrics corroborated these findings and demonstrated that the microbiome of the fecal samples was significantly richer when sequenced with TEHC compared to 16S amplicon sequencing. Altogether, our study suggests that the TEHC strategy provides a more extensive characterization of the fecal microbiome of horses than the current alternative based on the PCR amplification of a portion of the 16S rRNA gene.

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.

Antipsychotic quetiapine alters the mouse fecal resistome by impacting antibiotic efflux, cell membrane, and cell wall synthesis genes

IMPORTANCE

This study significantly contributes to our understanding of how certain medications can unintentionally contribute to a major global health issue, i.e., antibiotic resistance. Quetiapine, a widely used antipsychotic medication, was found to increase key resistance mechanisms of gut bacteria to antibiotics in mice. Specifically, these data suggest that quetiapine may target elements of the bacterial cell membrane. If similar effects are found in humans, this medicine could unexpectedly make it harder to treat certain infections. This research emphasizes the importance of being mindful about not just antibiotics themselves, but also about other medications that could inadvertently contribute to this problem. Ultimately, these findings underline the necessity for more in-depth research on the broader impact of pharmaceuticals.

Bioinformatic approaches for studying the microbiome of fermented food

High-throughput DNA sequencing-based approaches continue to revolutionise our understanding of microbial ecosystems, including those associated with fermented foods. Metagenomic and metatranscriptomic approaches are state-of-the-art biological profiling methods and are employed to investigate a wide variety of characteristics of microbial communities, such as taxonomic membership, gene content and the range and level at which these genes are expressed. Individual groups and consortia of researchers are utilising these approaches to produce increasingly large and complex datasets, representing vast populations of microorganisms. There is a corresponding requirement for the development and application of appropriate bioinformatic tools and pipelines to interpret this data. This review critically analyses the tools and pipelines that have been used or that could be applied to the analysis of metagenomic and metatranscriptomic data from fermented foods. In addition, we critically analyse a number of studies of fermented foods in which these tools have previously been applied, to highlight the insights that these approaches can provide.

Phenotypic and genotypic analysis of antimicrobial resistance in Nocardia species

BACKGROUND

Antimicrobial resistance is common in Nocardia species but data regarding the molecular mechanisms beyond their resistance traits are limited. Our study aimed to determine the species distribution, the antimicrobial susceptibility profiles, and investigate the associations between the resistance traits and their genotypic determinants.

METHODS

The study included 138 clinical strains of Nocardia from nine Israeli microbiology laboratories. MIC values of 12 antimicrobial agents were determined using broth microdilution. WGS was performed on 129 isolates of the eight predominant species. Bioinformatic analysis included phylogeny and determination of antimicrobial resistance genes and mutations.

RESULTS

Among the isolates, Nocardia cyriacigeorgica was the most common species (36%), followed by Nocardia farcinica (16%), Nocardia wallacei (13%), Nocardia abscessus (9%) and Nocardia brasiliensis (8%). Linezolid was active against all isolates, followed by trimethoprim/sulfamethoxazole (93%) and amikacin (91%). Resistance to other antibiotics was species-specific, often associated with the presence of resistance genes or mutations: (1) aph(2″) in N. farcinica and N. wallacei (resistance to tobramycin); (ii) blaAST-1 in N. cyriacigeorgica and Nocardia neocaledoniensis (resistance to amoxicillin/clavulanate); (iii) blaFAR-1 in N. farcinica (resistance to ceftriaxone); (iv) Ser83Ala substitution in the gyrA gene in four species (resistance to ciprofloxacin); and (v) the 16S rRNA m1A1408 methyltransferase in N. wallacei isolates (correlating with amikacin resistance).

CONCLUSIONS

Our study provides a comprehensive understanding of Nocardia species diversity, antibiotic resistance patterns, and the molecular basis of antimicrobial resistance. Resistance appears to follow species-related patterns, suggesting a lesser role for de novo evolution or transmission of antimicrobial resistance.

Xenorhabdus aichiensis sp. nov., Xenorhabdus anantnagensis sp. nov., and Xenorhabdus yunnanensis sp. nov., Isolated from Steinernema Entomopathogenic Nematodes

Three bacterial strains, XENO-2T, XENO-7T, and XENO-10T, isolated from Steinernema entomopathogenic nematodes, were found to represent novel Xenorhabdus species. In this study, we describe these new species by whole-genome and whole-proteome phylogenomic reconstructions, by calculating sequence identity scores using core genome sequences, and by phenotypic characterization. Phylogenomic reconstructions using ribosomal and house-keeping genes, and whole-genome and whole-proteome sequences show that XENO-2T and XENO-10T are closely related to Xenorhabdus japonica DSM 16522T and that XENO-7T is closely related to Xenorhabdus bovienii subsp. africana XENO-1T and to X. bovienii subsp. bovienii T228T. The dDDH values between XENO-2T and XENO-10T and between XENO-2T and X. japonica DSM 16522T are 56.4 and 51.8%, respectively. The dDDH value between XENO-10T and X. japonica DSM 16522T is 53.4%. The dDDH values between XENO-7T and X. bovienii subsp. africana XENO-1T and between XENO-7T and X. bovienii subsp. bovienii T228T are 63.6 and 69.4%, respectively. These dDDH values are below the 70% divergence threshold for prokaryotic species delineation. The newly described species are highly pathogenic to G. mellonella larvae, grow at pH between 5 and 9 (optimum 5-7), at salt concentrations of 1-3% (optimum 1-2%), and temperatures between 20 and 37 °C (optimum 28-30 °C). Biochemical tests such as lysine decarboxylase, ornithine decarboxylase, urease, gelatinase, citrate utilization, indole and acetoin production, and cytochrome oxidase tests allow to differentiate the novel species from their more closely related species. Considering these genetic and phenotypic divergencies, we propose the following new species: Xenorhabdus aichiensis sp. nov. with XENO-7T (= CCM 9233T = CCOS 2024T) as the type strain, Xenorhabdus anantnagensis sp. nov., with XENO-2T (= CCM 9237T = CCOS 2023T) as the type strain, and Xenorhabdus yunnanensis sp. nov., with XENO-10T (= CCM 9322T = CCOS 2071T) as the type strain. Our study contributes to a better understanding of the biodiversity and phylogenetic relationships of entomopathogenic bacteria associated with insect parasitic nematodes.

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.

Photorhabdus aballayi sp. nov. and Photorhabdus luminescens subsp. venezuelensis subsp. nov., isolated from Heterorhabditis amazonensis entomopathogenic nematodes

Six Gram-negative, rod-shaped bacterial strains isolated from Heterorhabditis amazonensis entomopathogenic nematodes were characterized to determine their taxonomic position. 16S rRNA and gyrB gene sequences indicate that they belong to the class Gammaproteobacteria, family Morganellaceae and genus Photorhabdus, and that some of them are conspecifics. Two of them, APURE^T and JAR^T, were selected for further molecular characterization using whole genome- and whole-proteome-based phylogenetic reconstructions and sequence comparisons. Phylogenetic reconstructions using whole genome and whole proteome sequences show that strains APURE^T and JAR^T are closely related to Photorhabdus luminescens subsp. luminescens ATCC 29999^T and to P. luminescens subsp. mexicana MEX47-22^T. Moreover, digital DNA-DNA hybridization (dDDH) values between APURE^T and P. luminescens subsp. luminescens ATCC 29999^T, APURE^T and P. luminescens subsp. mexicana MEX47-22^T, and APURE^T and JAR^T are 61.6, 61.2 and 64.1 %, respectively. These values are below the 70 % divergence threshold that delimits prokaryotic species. dDDH scores between JAR^T and P. luminescens subsp. luminescens ATCC 29999^T and between JAR^T and P. luminescens subsp. mexicana MEX47-22^T are 71.9 and 74.8 %, respectively. These values are within the 70 and 79 % divergence thresholds that delimit prokaryotic subspecies. Based on these genomic divergence values, APURE^T and JAR^T represent two different taxa, for which we propose the names: Photorhabdus aballayi sp. nov. with APURE^T (=CCM 9236^T =CCOS 2019^T) as type strain and Photorhabdus luminescens subsp. venezuelensis subsp. nov. with JAR^T (=CCM 9235^T =CCOS 2021^T) as type strain. Our study contributes to a better understanding of the biodiversity of an important bacterial group with enormous biotechnological and agricultural potential.

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.

A case for investment in clinical metagenomics in low-income and middle-income countries

Clinical metagenomics is the diagnostic approach with the broadest capacity to detect both known and novel pathogens. Clinical metagenomics is costly to run and requires infrastructure, but the use of next-generation sequencing for SARS-CoV-2 molecular epidemiology in low-income and middle-income countries (LMICs) offers an opportunity to direct this infrastructure to the establishment of clinical metagenomics programmes. Local implementation of clinical metagenomics is important to create relevant systems and evaluate cost-effective methodologies for its use, as well as to ensure that reference databases and result interpretation tools are appropriate to local epidemiology. Rational implementation, based on the needs of LMICs and the available resources, could ultimately improve individual patient care in instances in which available diagnostics are inadequate and supplement emerging infectious disease surveillance systems to ensure the next pandemic pathogen is quickly identified.

Dynamics of Microbial Community and Potential Microbial Pollutants in Shopping Malls

Shopping malls offer various niches for microbial populations, potentially serving as sources and reservoirs for the spread of microorganisms of public health concern. However, knowledge about the microbiome and the distribution of human pathogens in malls is largely unknown. Here, we examine the microbial community dynamics and genotypes of potential pathogens from floor and escalator surfaces in shopping malls and adjacent road dusts and greenbelt soils. The distribution pattern of microbial communities is driven primarily by habitats and seasons. A significant enrichment of human-associated microbiota in the indoor environment indicates that human interactions with surfaces might be another strong driver for mall microbiomes. Neutral community models suggest that the microbial community assembly is strongly driven by stochastic processes. Distinct performances of microbial taxonomic signatures for environmental classifications indicate the consistent differences of microbial communities of different seasons/habitats and the strong anthropogenic effect on homogenizing microbial communities of shopping malls. Indoor environments harbored higher concentrations of human pathogens than outdoor samples, also carrying a high proportion of antimicrobial resistance-associated multidrug efflux genes and virulence genes. These findings enhanced the understanding of the microbiome in the built environment and the interactions between humans and the built environment, providing a basis for tracking biothreats and communicable diseases and developing sophisticated early warning systems. IMPORTANCE Shopping malls are distinct microbial environments which can facilitate a constant transmission of microorganisms of public health concern between humans and the built environment or between human and human. Despite extensive investigation of the natural environmental microbiome, no comprehensive profile of microbial ecology has been reported in malls. Characterizing microbial distribution, potential pathogens, and antimicrobial resistance will enhance our understanding of how these microbial communities are formed, maintained, and transferred and help establish a baseline for biosurveillance of potential public health threats in malls.

Validation and Application of Long-Read Whole-Genome Sequencing for Antimicrobial Resistance Gene Detection and Antimicrobial Susceptibility Testing

Next-generation sequencing applications are increasingly used for detection and characterization of antimicrobial-resistant pathogens in clinical settings. Oxford Nanopore Technologies (ONT) sequencing offers advantages for clinical use compared with other sequencing methodologies because it enables real-time basecalling, produces long sequencing reads that increase the ability to correctly assemble DNA fragments, provides short turnaround times, and requires relatively uncomplicated sample preparation. A drawback of ONT sequencing, however, is its lower per-read accuracy than short-read sequencing. We sought to identify best practices in ONT sequencing protocols. As some variability in sequencing results may be introduced by the DNA extraction methodology, we tested three DNA extraction kits across three independent laboratories using a representative set of six bacterial isolates to investigate accuracy and reproducibility of ONT technology. All DNA extraction techniques showed comparable performance; however, the DNeasy PowerSoil Pro kit had the highest sequencing yield. This kit was subsequently applied to 42 sequentially collected bacterial isolates from blood cultures to assess Ares Genetics's pipelines for predictive whole-genome sequencing antimicrobial susceptibility testing (WGS-AST) performance compared to phenotypic triplicate broth microdilution results. WGS-AST results ranged across the organisms and resulted in an overall categorical agreement of 95% for penicillins, 82.4% for cephalosporins, 76.7% for carbapenems, 86.9% for fluoroquinolones, and 96.2% for aminoglycosides. Very major errors/major errors were 0%/16.7% (penicillins), 11.7%/3.6% (cephalosporins), 0%/24.4% (carbapenems), 2.5%/7.7% (fluoroquinolones), and 0%/4.1% (aminoglycosides), respectively. This work showed that, although additional refinements are necessary, ONT sequencing demonstrates potential as a method to perform WGS-AST on cultured isolates for patient care.

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.

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.

CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database

The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded β-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systematic curation of resistance-modifying agents. This expanded curation includes 180 new AMR gene families, 15 new drug classes, 1 new resistance mechanism, and two new ontological relationships: evolutionary_variant_of and is_small_molecule_inhibitor. In silico prediction of resistomes and prevalence statistics of ARGs has been expanded to 377 pathogens, 21,079 chromosomes, 2,662 genomic islands, 41,828 plasmids and 155,606 whole-genome shotgun assemblies, resulting in collation of 322,710 unique ARG allele sequences. New features include the CARD:Live collection of community submitted isolate resistome data and the introduction of standardized 15 character CARD Short Names for ARGs to support machine learning efforts.

Photorhabdus antumapuensis sp. nov., a novel symbiotic bacterial species associated with Heterorhabditis atacamensis entomopathogenic nematodes

One motile, Gram-negative, non-spore-forming and rod-shaped symbiotic bacterium, strain UCH-936T, was isolated from Heterorhabditis atacamensis nematodes. Results of biochemical, physiological, molecular and genomic analyses suggest that it represents a new species, which we propose to name Photorhabdus antumapuensis sp. nov. Digital DNA–DNA hybridization shows that strain UCH-936T is more closely related to Photorhabdus kleinii DSM 23513T, but shares solely 50.5 % similarity, which is below the 70% cut-off value that delimits species boundaries in bacteria. Phylogenetic reconstructions using whole-genome sequences show that strain UCH-936T forms a unique clade, suggesting its novel and distinct taxonomic status again. Similarly, comparative genomic analyses shows that the virulence factor flagella-related gene fleR, the type IV pili-related gene pilL and the vibriobactin-related gene vibE are present in the genome of strain UCH-936T but absent in the genomes of its closest relatives. Biochemically and physiologically, UCH-936T differs also from all closely related Photorhabdus species. Therefore, Photorhabdus antumapuensis sp. nov. is proposed as a new species with the type strain UCH-936T (CCCT 21.06T=CCM 9188T=CCOS 1991T).

Metagenomic exploration of antibiotic resistance genes and their hosts in aquaculture waters of the semi-closed Dongshan Bay (China)

In marine environments, increasing occurrence and numbers of microbial Antibiotic Resistance Gene (ARG) subtypes, especially of new beta-lactamases, have received lots of attention in recent years. Updated databases with novel developed tools provide new opportunities to obtain more comprehensive ARG profiles as well as ARG-carrying hosts. Yet, ARGs in human-associated marine aquaculture environments, e.g. in China, remains largely unknown. Using metagenomic data, we revealed high numbers of Multi-drug Resistance, beta-lactamase and aminoglycoside genes throughout the year. Thereby, Alpha- and Gamma-proteobacteria were assigned to the majority of beta-lactamase-carrying hosts. From Metagenome-assembled genomes, three blaF-like beta-lactamases (91.7-94.7% identity with beta-lactamase from Mycobacterium fortuitum (blaF)) were exclusively observed in an unclassified Mycobacterium genus. Notably, other new beta-lactamases, VMB-1-like (n = 3) (58.5-67.4% identity to Vibrio metallo-beta-lactamase 1 (VMB-1)), were found in Gammaproteobacteria. Additionally, 175 Multi-drug Resistant Organisms possessed at least 3 ARG subtypes, and seven of the potentially pathogenic genera (n = 17) were assigned to Gammaproteobacteria. These results, together with high-risk ARGs (e.g. tetM, dfrA14 and dfrA17), provide hosts and new beta-lactamases of ARGs in Chinese coastal aquaculture.

Detection of Klebsiella pneumoniae human gut carriage: a comparison of culture, qPCR, and whole metagenomic sequencing methods

Klebsiella pneumoniae is an important opportunistic healthcare-associated pathogen and major contributor to the global spread of antimicrobial resistance. Gastrointestinal colonization with K. pneumoniae is a major predisposing risk factor for infection and forms an important hub for the dispersal of resistance. Current culture-based detection methods are time consuming, give limited intra-sample abundance and strain diversity information, and have uncertain sensitivity. Here we investigated the presence and abundance of K. pneumoniae at the species and strain level within fecal samples from 103 community-based adults by qPCR and whole metagenomic sequencing (WMS) compared to culture-based detection. qPCR demonstrated the highest sensitivity, detecting K. pneumoniae in 61.2% and 75.8% of direct-fecal and culture-enriched sweep samples, respectively, including 52/52 culture-positive samples. WMS displayed lower sensitivity, detecting K. pneumoniae in 71.2% of culture-positive fecal samples at a 0.01% abundance cutoff, and was inclined to false positives in proportion to the relative abundance of other Enterobacterales present. qPCR accurately quantified K. pneumoniae to 16 genome copies/reaction while WMS could estimate relative abundance to at least 0.01%. Quantification by both methods correlated strongly with each other (Spearman's rho = 0.91). WMS also supported accurate intra-sample K. pneumoniae sequence type (ST)-level diversity detection from fecal microbiomes to 0.1% relative abundance, agreeing with the culture-based detected ST in 16/19 samples. Our results show that qPCR and WMS are sensitive and reliable tools for detection, quantification, and strain analysis of K. pneumoniae from fecal samples with potential to support infection control and enhance insights in K. pneumoniae gastrointestinal ecology.

Capturing the antibiotic resistome of preterm infants reveals new benefits of probiotic supplementation

BACKGROUND

Probiotic use in preterm infants can mitigate the impact of antibiotic exposure and reduce rates of certain illnesses; however, the benefit on the gut resistome, the collection of antibiotic resistance genes, requires further investigation. We hypothesized that probiotic supplementation of early preterm infants (born < 32-week gestation) while in hospital reduces the prevalence of antibiotic resistance genes associated with pathogenic bacteria in the gut. We used a targeted capture approach to compare the resistome from stool samples collected at the term corrected age of 40 weeks for two groups of preterm infants (those that routinely received a multi-strain probiotic during hospitalization and those that did not) with samples from full-term infants at 10 days of age to identify if preterm birth or probiotic supplementation impacted the resistome. We also compared the two groups of preterm infants up to 5 months of age to identify persistent antibiotic resistance genes.

RESULTS

At the term corrected age, or 10 days of age for the full-term infants, we found over 80 antibiotic resistance genes in the preterm infants that did not receive probiotics that were not identified in either the full-term or probiotic-supplemented preterm infants. More genes associated with antibiotic inactivation mechanisms were identified in preterm infants unexposed to probiotics at this collection time-point compared to the other infants. We further linked these genes to mobile genetic elements and Enterobacteriaceae, which were also abundant in their gut microbiomes. Various genes associated with aminoglycoside and beta-lactam resistance, commonly found in pathogenic bacteria, were retained for up to 5 months in the preterm infants that did not receive probiotics.

CONCLUSIONS

This pilot survey of preterm infants shows that probiotics administered after preterm birth during hospitalization reduced the diversity and prevented persistence of antibiotic resistance genes in the gut microbiome. The benefits of probiotic use on the microbiome and the resistome should be further explored in larger groups of infants. Due to its high sensitivity and lower sequencing cost, our targeted capture approach can facilitate these surveys to further address the implications of resistance genes persisting into infancy without the need for large-scale metagenomic sequencing. Video Abstract.

Antibiotic resistance in chronic respiratory diseases: from susceptibility testing to the resistome

The development of resistome analysis, i.e. the comprehensive analysis of antibiotic-resistance genes (ARGs), is enabling a better understanding of the mechanisms of antibiotic-resistance emergence. The respiratory microbiome is a dynamic and interactive network of bacteria, with a set of ARGs that could influence the response to antibiotics. Viruses such as bacteriophages, potential carriers of ARGs, may also form part of this respiratory resistome. Chronic respiratory diseases (CRDs) such as cystic fibrosis, severe asthma, chronic obstructive pulmonary disease and bronchiectasis, managed with long-term antibiotic therapies, lead to multidrug resistance. Antibiotic susceptibility testing provides a partial view of the bacterial response to antibiotics in the complex lung environment. Assessing the ARG network would allow personalised, targeted therapeutic strategies and suitable antibiotic stewardship in CRDs, depending on individual resistome and microbiome signatures. This review summarises the influence of pulmonary antibiotic protocols on the respiratory microbiome, detailing the variable consequences according to antibiotic class and duration of treatment. The different resistome-profiling methods are explained to clarify their respective place in antibiotic-resistance analysis in the lungs. Finally, this review details current knowledge on the respiratory resistome related to therapeutic strategies and provides insight into the application of resistome analysis to counter the emergence of multidrug-resistant respiratory pathogens.

Harnessing Rare Actinomycete Interactions and Intrinsic Antimicrobial Resistance Enables Discovery of an Unusual Metabolic Inhibitor

Bacterial natural products have historically been a deep source of new medicines, but their slowed discovery in recent decades has put a premium on developing strategies that enhance the likelihood of capturing novel compounds. Here, we used a straightforward approach that capitalizes on the interactive ecology of “rare” actinomycetes. Specifically, we screened for interactions that triggered the production of antimicrobials that inhibited the growth of a bacterial strain with exceptionally diverse natural antimicrobial resistance. This strategy led to the discovery of a family of antimicrobials we term the dynaplanins. Heterologous expression enabled identification of the dynaplanin biosynthetic gene cluster, which was missed by typical algorithms for natural product gene cluster detection. Genome sequencing of partially resistant mutants revealed a 2-oxo acid dehydrogenase E2 subunit as the likely molecular target of the dynaplanins, and this finding was supported by computational modeling of the dynaplanin scaffold within the active site of this enzyme. Thus, this simple strategy, which leverages microbial interactions and natural antibiotic resistance, can enable discovery of molecules with unique antimicrobial activity. In addition, these results indicate that primary metabolism may be a direct target for inhibition via chemical interference in competitive microbial interactions.

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.

Syotti: scalable bait design for DNA enrichment

MOTIVATION

Bait enrichment is a protocol that is becoming increasingly ubiquitous as it has been shown to successfully amplify regions of interest in metagenomic samples. In this method, a set of synthetic probes ('baits') are designed, manufactured and applied to fragmented metagenomic DNA. The probes bind to the fragmented DNA and any unbound DNA is rinsed away, leaving the bound fragments to be amplified for sequencing. Metsky et al. demonstrated that bait-enrichment is capable of detecting a large number of human viral pathogens within metagenomic samples.

RESULTS

We formalize the problem of designing baits by defining the Minimum Bait Cover problem, show that the problem is NP-hard even under very restrictive assumptions, and design an efficient heuristic that takes advantage of succinct data structures. We refer to our method as Syotti. The running time of Syotti shows linear scaling in practice, running at least an order of magnitude faster than state-of-the-art methods, including the method of Metsky et al. At the same time, our method produces bait sets that are smaller than the ones produced by the competing methods, while also leaving fewer positions uncovered. Lastly, we show that Syotti requires only 25 min to design baits for a dataset comprised of 3 billion nucleotides from 1000 related bacterial substrains, whereas the method of Metsky et al. shows clearly super-linear running time and fails to process even a subset of 17% of the data in 72 h.

AVAILABILITY AND IMPLEMENTATION

https://github.com/jnalanko/syotti.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Oh, deer! How worried should we be about the diversity and abundance of the faecal resistome of red deer?

The emergence of antimicrobial resistance (AMR) is a global threat to public health. Antimicrobials are used in animal production and human medicine, which contribute to the circulation of antibiotic resistance genes (ARGs) in the environment. Wildlife can be reservoirs of pathogens and resistant bacteria. Furthermore, anthropogenic pressure can influence their resistome. This work aimed to study the AMR of the faecal microbiome of red deer, one of the most important game species in Europe. To this end, a high-throughput qPCR approach was employed to screen a high number of ARGs and the antimicrobial susceptibility of indicator bacteria was determined. Several genes that confer resistance to different classes of antibiotics were identified, with the most abundant being tetracycline ARGs. Other genes were also present that are considered current and future threats to human health, and some of these were relatively abundant. Multidrug-resistant E. coli and Enterococcus spp. were isolated, although the overall level of antibiotic resistance was low. These results highlight the pressing need to know the origin and transmission of AMR in wildlife. Thus, and considering the One Health concept, studies such as this one shows the need for surveillance programs to prevent the spread of drug-resistant strains and ARGs.

Diversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM): a method for detection of antimicrobial resistance in environmental samples

Effective monitoring of antibiotic resistance genes and their dissemination in environmental ecosystems has been hindered by the cost and efficiency of methods available for the task. We developed the Diversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM), a method implementing TruSeq high-throughput sequencing to simultaneously sequence thousands of antibiotic resistant gene targets representing a full-spectrum of antibiotic resistance classes common to environmental systems. In this study, we demonstrated DARTE-QM by screening 662 antibiotic resistance genes within complex environmental samples originated from manure, soil, and livestock feces, in addition to a mock-community reference to assess sensitivity and specificity. DARTE-QM offers a new approach to studying antibiotic resistance in environmental microbiomes, showing advantages in efficiency and the ability to scale for many samples. This method provides a means of data acquisition that will alleviate some of the obstacles that many researchers in this area currently face.

Smith et al. present DARTE-QM, a highthroughput sequencing method for screening environmental DNA samples for antibiotic resistance genes on a broad scale. This method is demonstrated as effective on soil, manure and livestock fecal samples, as well as a synthetic mock-community reference.

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.

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.

Probe design for simultaneous, targeted capture of diverse metagenomic targets

The compounding challenges of low signal, high background, and uncertain targets plague many metagenomic sequencing efforts. One solution has been DNA capture, wherein probes are designed to hybridize with target sequences, enriching them in relation to their background. However, balancing probe depth with breadth of capture is challenging for diverse targets. To find this balance, we have developed the HUBDesign pipeline, which makes use of sequence homology to design probes at multiple taxonomic levels. This creates an efficient probe set capable of simultaneously and specifically capturing known and related sequences. We validated HUBDesign by generating probe sets targeting the breadth of coronavirus diversity, as well as a suite of bacterial pathogens often underlying sepsis. In separate experiments demonstrating significant, simultaneous enrichment, we captured SARS-CoV-2 and HCoV-NL63 in a human RNA background and seven bacterial strains in human blood. HUBDesign (https://github.com/zacherydickson/HUBDesign) has broad applicability wherever there are multiple organisms of interest.

Comparative Evaluation of Assays for Broad Detection of Molecular Resistance Mechanisms in Enterobacterales Isolates

Rapid detection of antimicrobial resistance in both surveillance and diagnostic settings is still a major challenge for the clinical lab, compounded by the rapid evolution of antibiotic resistance mechanisms. This study compares four methods for the broad detection of antibiotic resistance genes in Enterobacterales isolates: two multiplex PCR assays (the Streck ARM-D beta-lactamase kit and the OpGen Acuitas AMR Gene Panel u5.47 (research use only [RUO]) and one microarray assay (the Check-MDR CT103XL assay), with whole-genome sequencing as a reference standard. A total of 65 Gram-negative bacterial isolates, from 56 patients, classified by phenotypic antimicrobial susceptibility testing (AST) as showing resistance to beta-lactam antimicrobials (extended-spectrum beta-lactamase [ESBL] positive or resistance to third-generation cephalosporins or carbapenems) were included in the study. Overall concordance between the molecular assays and sequencing was high. While all three assays had similar performance, the OpGen Acuitas AMR assay had the highest overall percent concordance with sequencing results. The primary differences between the assays tested were the number and diversity of targets, ranging from 9 for Streck to 34 for OpGen. This study shows that commercially available PCR-based assays can provide accurate identification of antimicrobial resistance loci in clinically significant Gram-negative bacteria. Further studies are needed to determine the clinical diagnostic role and potential benefit of such methods.

Genotypic and Phenotypic Characterization of Antimicrobial Resistance Profiles in Non-typhoidal Salmonella enterica Strains Isolated From Cambodian Informal Markets

Non-typhoidal Salmonella enterica is a pathogen of global importance, particularly in low and middle-income countries (LMICs). The presence of antimicrobial resistant (AMR) strains in market environments poses a serious health threat to consumers. In this study we identified and characterized the genotypic and phenotypic AMR profiles of 81 environmental S. enterica strains isolated from samples from informal markets in Cambodia in 2018–2019. AMR genotypes were retrieved from the NCBI Pathogen Detection website (https://www.ncbi.nlm.nih.gov/pathogens/) and using ResFinder (https://cge.cbs.dtu.dk/services/) Salmonella pathogenicity islands (SPIs) were identified with SPIFinder (https://cge.cbs.dtu.dk/services/). Susceptibility testing was performed by broth microdilution according to the Clinical and Laboratory Standards Institute (CLSI) standard guidelines M100-S22 using the National Antimicrobial Resistance Monitoring System (NARMS) Sensititre Gram Negative plate. A total of 17 unique AMR genes were detected in 53% (43/81) of the isolates, including those encoding tetracycline, beta-lactam, sulfonamide, quinolone, aminoglycoside, phenicol, and trimethoprim resistance. A total of 10 SPIs (SPI-1, 3–5, 8, 9, 12–14, and centisome 63 [C63PI]) were detected in 59 isolates. C63PI, an iron transport system in SPI-1, was observed in 56% of the isolates (n = 46). SPI-1, SPI-4, and SPI-9 were present in 13, 2, and 5% of the isolates, respectively. The most common phenotypic resistances were observed to tetracycline (47%; n = 38), ampicillin (37%; n = 30), streptomycin (20%; n = 16), chloramphenicol (17%; n = 14), and trimethoprim-sulfamethoxazole (16%; n = 13). This study contributes to understanding the AMR genes present in S. enterica isolates from informal markets in Cambodia, as well as support domestic epidemiological investigations of multidrug resistance (MDR) profiles.

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.

Accuracy of Broad-Panel PCR-Based Bacterial Identification for Blood Cultures in a Pediatric Oncology Population

Bloodstream infections are a major cause of morbidity and mortality and result in significant costs to health care systems. Rapid identification of the causative agent of bloodstream infections is critical for patient treatment and improved outcomes. Multiplex PCR systems that provide bacterial identification directly from the blood culture bottle allow for earlier detection of pathogens. The GenMark Dx ePlex blood culture identification (BCID) panels have an expanded number of targets for both identification and genotypic markers of antimicrobial resistance. The performance of the ePlex BCID Gram-negative (GN) and Gram-positive (GP) panels were evaluated in a predominantly pediatric oncology population. A total of 112 blood cultures were tested by the ePlex BCID GN and GP panels and results were compared to those from standard-of-care testing. Accuracy for on-panel organisms was 89% (CI, 76% to 95%) for the Gram-positive panel, with four misidentifications and one not detected, and 93% (CI, 82% to 98%) for the Gram-negative panel, with two misidentifications and one not detected. The results showed good overall performance of these panels for rapid, accurate detection of bloodstream pathogens in this high-risk population. IMPORTANCE Bloodstream infections are a major cause of morbidity and mortality and result in significant costs to health care systems. Rapid identification of the causative agent of bloodstream infections is critical for patient treatment and improved outcomes. Multiplex PCR systems that provide bacterial identification directly from the blood culture bottle allow for earlier characterization of pathogens. The GenMark Dx ePlex blood culture identification (BCID) panels, recently cleared by the FDA, have an expanded number of targets for both identification and resistance, much larger than other, automated, broad-panel PCR assays. The performance of the ePlex BCID Gram-negative and Gram-positive panels was evaluated in a predominantly pediatric oncology population, providing a unique look at its performance in a high-risk group, where rapid diagnostic information for bloodstream infections could be of particular value for clinical care providers.

Culture-Free Detection of Antibiotic Resistance Markers from Native Patient Samples by Hybridization Capture Sequencing

The increasing incidence of antimicrobial resistance (AMR) is a major global challenge. Routine techniques for molecular AMR marker detection are largely based on low-plex PCR and detect dozens to hundreds of AMR markers. To allow for comprehensive and sensitive profiling of AMR markers, we developed a capture-based next generation sequencing (NGS) workflow featuring a novel AMR marker panel based on the curated AMR database ARESdb. Our primary objective was to compare the sensitivity of target enrichment-based AMR marker detection to metagenomics sequencing. Therefore, we determined the limit of detection (LOD) in synovial fluid and urine samples across four key pathogens. We further demonstrated proof-of-concept for AMR marker profiling from septic samples using a selection of urine samples with confirmed monoinfection. The results showed that the capture-based workflow is more sensitive and requires lower sequencing depth compared with metagenomics sequencing, allowing for comprehensive AMR marker detection with an LOD of 1000 CFU/mL. Combining the ARESdb AMR panel with 16S rRNA gene sequencing allowed for the culture-free detection of bacterial taxa and AMR markers directly from septic patient samples at an average sensitivity of 99%. Summarizing, the newly developed ARESdb AMR panel may serve as a valuable tool for comprehensive and sensitive AMR marker detection.

Pan-proteome profiling of emerging and re-emerging zoonotic pathogen Orientia tsutsugamushi for getting insight into microbial pathogenesis

With the occurrence and evolution of antibiotic and multidrug resistance in bacteria most of the existing remedies are becoming ineffective. The pan-proteome exploration of the bacterial pathogens helps to identify the wide spectrum therapeutic targets which will be effective against all strains in a species. The current study is focused on the pan-proteome profiling of zoonotic pathogen Orientia tsutsugamushi (Ott) for the identification of potential therapeutic targets. The pan-proteome of Ott is estimated to be extensive in nature that has 1429 protein clusters, out of which 694 were core, 391 were accessory, and 344 were unique. It was revealed that 622 proteins were essential, 222 proteins were virulent factors, and 42 proteins were involved in antibiotic resistance. The potential therapeutic targets were further classified into eleven broad classes among which gene expression and regulation, transport, and metabolism were dominant. The biological interactome analysis of therapeutic targets revealed that an ample amount of interactions were present among the proteins involved in DNA replication, ribosome assembly, cellwall metabolism, cell division, and antimicrobial resistance. The predicted therapeutic targets from the pan-proteome of Ott are involved in various biological processes, virulence, and antibiotic resistance; hence envisioned as potential candidates for drug discovery to combat scrub typhus.

Preparation and Antimicrobial Activity of Chitosan and Its Derivatives: A Concise Review

Despite the advantages presented by synthetic polymers such as strength and durability, the lack of biodegradability associated with the persistence in the environment for a long time turned the attention of researchers to natural polymers. Being biodegradable, biopolymers proved to be extremely beneficial to the environment. At present, they represent an important class of materials with applications in all economic sectors, but also in medicine. They find applications as absorbers, cosmetics, controlled drug delivery, tissue engineering, etc. Chitosan is one of the natural polymers which raised a strong interest for researchers due to some exceptional properties such as biodegradability, biocompatibility, nontoxicity, non-antigenicity, low-cost and numerous pharmacological properties as antimicrobial, antitumor, antioxidant, antidiabetic, immunoenhancing. In addition to this, the free amino and hydroxyl groups make it susceptible to a series of structural modulations, obtaining some derivatives with different biomedical applications. This review approaches the physico-chemical and pharmacological properties of chitosan and its derivatives, focusing on the antimicrobial potential including mechanism of action, factors that influence the antimicrobial activity and the activity against resistant strains, topics of great interest in the context of the concern raised by the available therapeutic options for infections, especially with resistant strains.

Structural, functional, resistome and pathogenicity profiling of the Cooum river

The microbial community's structure and functions determine the health, quality, and anthropogenic conditions of the river ecosystems. The presence of Bacteria such as Arcobacter spp, Escherichia spp, and Campylobacters spp, have been shown to reflect the poor water quality of rivers. Apprehension of the microbial community in polluted water bodies is significant because it affects human health and the environment. Culture-independent metagenomic and metatranscriptomic approaches employed in the current study of the Cooum river unraveled the taxonomic classification of diverse microbes, including archaea, bacteria, viruses, and phages. The presence of abundant Macellibacteroides fermentans, Arcobacter bivolvorium, Arcobacter butzleri, Methanothrix soenhngeii, and Bacteroides graminisolvens were noted. Viruses and phages like Caudovirales, Human mastadenovirus C, Siphoviridae, Escherichia phage, Erwinia phage, Synechoccus phage, and Vibrio phage were relatively predominant. Various metabolic pathways like methane, sulfur, and nitrogen metabolism adopted by the microbiome confer dangerous gases. Mechanisms such as secretory systems, signal transduction, Chemotaxis, quorum sensing, transportation of chemicals and ions were significantly enriched. The microbes expressed antimicrobial resistance mechanisms as identified from the genes encoding beta-lactamase enzymes and aminoglycoside phosphotransferase enzymes. Metal resistance mechanisms against copper, tellurium, chromium, and cadmium were plentiful. Presence of human pathogens interactions with Yersinia pestis, Campylobacter jejuni, Escherichia coli, Helicobacter pylori, and Francisella tularensis subsp. tularensis suggested the possibilities of transmission of pathogenesis to humans. The current study is the first to apprehend the detailed microbiome composition of one of the highly polluted rivers in South India. The study elaborated the microbiome's structure, functions, and metabolic potential at a specific site of the polluted river.

Improved Microbial Community Characterization of 16S rRNA via Metagenome Hybridization Capture Enrichment

Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases, but are much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having <78% sequence identity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average > 400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely due in part to the extent and curation of the reference databases considered. Thus, enriching existing aliquots of shotgun metagenomic libraries and obtaining modest numbers of reads from them offers an efficient orthogonal method for assessment of bacterial community composition.

Genome-Based Targeted Sequencing as a Reproducible Microbial Community Profiling Assay

Current sequencing-based methods for profiling microbial communities rely on marker gene (e.g., 16S rRNA) or metagenome shotgun sequencing (mWGS) analysis. We present an approach based on a single-primer extension reaction using a highly multiplexed oligonucleotide probe pool. This approach, termed MA-GenTA (microbial abundances from genome tagged analysis), enables quantitative, straightforward, cost-effective microbiome profiling that combines desirable features of both 16S rRNA and mWGS strategies. The use of multiple probes per target genome and rigorous probe design criteria enabled robust determination of relative abundance. To test the utility of the MA-GenTA assay, probes were designed for 830 genome sequences representing bacteria present in mouse stool specimens. Comparison of the MA-GenTA data with mWGS data demonstrated excellent correlation down to 0.01% relative abundance and a similar number of organisms detected per sample. Despite the incompleteness of the reference database, nonmetric multidimensional scaling (NMDS) clustering based on the Bray-Curtis dissimilarity metric of sample groups was consistent between MA-GenTA, mWGS, and 16S rRNA data sets. MA-GenTA represents a potentially useful new method for microbiome community profiling based on reference genomes.

IMPORTANCE New methods for profiling the microbial communities can create new approaches to understanding the composition and function of those communities. In this study, we combined bacterial genome-specific probe design with a highly multiplexed single primer extension reaction as a new method to profile microbial communities, using stool from various mouse strains as a test case. This method, termed MA-GenTA, was benchmarked against 16S rRNA gene sequencing and metagenome sequencing methods and delivered similar relative abundance and clustering data. Since the probes were generated from reference genomes, MA-GenTA was also able to provide functional pathway data for the stool microbiome in the assayed samples. The method is more informative than 16S rRNA analysis while being less costly than metagenome shotgun sequencing.

The Effect of the Effluent from a Small-Scale Conventional Wastewater Treatment Plant Treating Municipal Wastewater on the Composition and Abundance of the Microbial Community, Antibiotic Resistome, and Pathogens in the Sediment and Water of a Receiving Stream

The effluents of wastewater treatment plants (WWTPs) are major contributors of nutrients, microbes—including those carrying antibiotic resistance genes (ARGs)—and pathogens to receiving waterbodies. The effect of the effluent of a small-scale activated sludge WWTP treating municipal wastewater on the composition and abundance of the microbial community as well as the antibiotic resistome and pathogens in the sediment and water of the receiving stream and river was studied using metagenome sequencing and a quantitative approach. Elevated Bacteroidetes proportions in the prokaryotic community, heightened sulfonamide and aminoglycoside resistance determinants proportions, and an increase of up to three orders of magnitude of sul1–sul2–aadA–blaOXA2 gene cluster abundances were recorded in stream water and sediments 0.3 km downstream of a WWTP discharge point. Further downstream, a gradual recovery of affected microbial communities along a distance gradient from WWTP was recorded, culminating in the mostly comparable state of river water and sediment parameters 3.7 km downstream of WWTP and stream water and sediments upstream of the WWTP discharge point. Archaea, especially Methanosarcina, Methanothrix, and Methanoregula, formed a substantial proportion of the microbial community of WWTP effluent as well as receiving stream water and sediment, and were linked to the spread of ARGs. Opportunistic environmental-origin pathogens were predominant in WWTP effluent and receiving stream bacterial communities, with Citrobacter freundii proportion being especially elevated in the close vicinity downstream of the WWTP discharge point.

Amino Acid k-mer Feature Extraction for Quantitative Antimicrobial Resistance (AMR) Prediction by Machine Learning and Model Interpretation for Biological Insights

Machine learning algorithms can learn mechanisms of antimicrobial resistance from the data of DNA sequence without any a priori information. Interpreting a trained machine learning algorithm can be exploited for validating the model and obtaining new information about resistance mechanisms. Different feature extraction methods, such as SNP calling and counting nucleotide k-mers have been proposed for presenting DNA sequences to the model. However, there are trade-offs between interpretability, computational complexity and accuracy for different feature extraction methods. In this study, we have proposed a new feature extraction method, counting amino acid k-mers or oligopeptides, which provides easier model interpretation compared to counting nucleotide k-mers and reaches the same or even better accuracy in comparison with different methods. Additionally, we have trained machine learning algorithms using different feature extraction methods and compared the results in terms of accuracy, model interpretability and computational complexity. We have built a new feature selection pipeline for extraction of important features so that new AMR determinants can be discovered by analyzing these features. This pipeline allows the construction of models that only use a small number of features and can predict resistance accurately.

Quantifying the transmission of antimicrobial resistance at the human and livestock interface with genomics

BACKGROUND

Livestock have been implicated as a reservoir for antimicrobial resistance (AMR) that can spread to humans. Close proximity and ecological interfaces involving livestock have been posited as risk factors for the transmission of AMR. In spite of this, there are sparse data and limited agreement on the transmission dynamics that occur.

OBJECTIVES

To identify how genome sequencing approaches can be used to quantify the dynamics of AMR transmission at the human-livestock interface, and where current knowledge can be improved to better understand the impact of transmission on the spread of AMR.

SOURCES

Key articles investigating various aspects of AMR transmission at the human-livestock interface are discussed, with a focus on Escherichia coli.

CONTENT

We recapitulate the current understanding of the transmission of AMR between humans and livestock based on current genomic and epidemiological approaches. We discuss how the use of well-designed, high-resolution genome sequencing studies can improve our understanding of the human-livestock interface.

IMPLICATIONS

A better understanding of the human-livestock interface will aid in the development of evidence-based and effective One Health interventions that can ultimately reduce the burden of AMR in humans.

Incorporating the plasmidome into antibiotic resistance surveillance in animal agriculture

Mobile genetic elements (MGE) carrying resistance genes represent a unique challenge to risk assessment and surveillance of antimicrobial resistance (AMR). Yet determining the mobility of resistance genes within animal microbiomes is essential to evaluating the potential dissemination from livestock to potential human pathogens, as well as evaluating co-selection mechanisms that may impact persistence of resistance genes with changing antibiotic use patterns. Current surveillance efforts utilize phenotypic testing and sequencing of individual isolates for tracking of AMR in livestock. In this work, we investigated the utility of using long-read sequencing of the plasmids from mixed Enterobacterales enrichments of swine fecal samples as a surveillance strategy for AMR plasmids. Enrichments were performed in either MacConkey broth without selection or with selection by addition of tetracycline or ceftriaxone, and plasmids were extracted and sequenced in order to evaluate the diversity of plasmids enriched by each method. Intact resistance plasmids were successfully assembled, as well as complex resistance transposons carrying multiple repeated elements that would interfere with assembly by short read sequencing technologies. Comparison of the assembled plasmids with representatives from public databases confirmed the quality of the assemblies and also revealed the occurrence of IncI2 plasmids carrying bla_CMY-2 in Ontario swine samples, which have not been found in previous studies.

Mobilization of Antibiotic Resistance: Are Current Approaches for Colocalizing Resistomes and Mobilomes Useful?

Antimicrobial resistance (AMR) poses a global human and animal health threat, and predicting AMR persistence and transmission remains an intractable challenge. Shotgun metagenomic sequencing can help overcome this by enabling characterization of AMR genes within all bacterial taxa, most of which are uncultivatable in laboratory settings. Shotgun sequencing, therefore, provides a more comprehensive glance at AMR "potential" within samples, i.e., the "resistome." However, the risk inherent within a given resistome is predicated on the genomic context of various AMR genes, including their presence within mobile genetic elements (MGEs). Therefore, resistome risk stratification can be advanced if AMR profiles are considered in light of the flanking mobilizable genomic milieu (e.g., plasmids, integrative conjugative elements (ICEs), phages, and other MGEs). Because such mediators of horizontal gene transfer (HGT) are involved in uptake by pathogens, investigators are increasingly interested in characterizing that resistome fraction in genomic proximity to HGT mediators, i.e., the "mobilome"; we term this "colocalization." We explored the utility of common colocalization approaches using alignment- and assembly-based techniques, on clinical (human) and agricultural (cattle) fecal metagenomes, obtained from antimicrobial use trials. Ordination revealed that tulathromycin-treated cattle experienced a shift in ICE and plasmid composition versus untreated animals, though the resistome was unaffected during the monitoring period. Contrarily, the human resistome and mobilome composition both shifted shortly after antimicrobial administration, though this rebounded to pre-treatment status. Bayesian networks revealed statistical AMR-MGE co-occurrence in 19 and 2% of edges from the cattle and human networks, respectively, suggesting a putatively greater mobility potential of AMR in cattle feces. Conversely, using Mobility Index (MI) and overlap analysis, abundance of de novo-assembled contigs supporting resistomes flanked by MGE increased shortly post-exposure within human metagenomes, though > 40 days after peak dose such contigs were rare (∼2%). MI was not substantially altered by antimicrobial exposure across all cattle metagenomes, ranging 0.5-4.0%. We highlight that current alignment- and assembly-based methods estimating resistome mobility yield contradictory and incomplete results, likely constrained by approach-specific data inputs, and bioinformatic limitations. We discuss recent laboratory and computational advancements that may enhance resistome risk analysis in clinical, regulatory, and commercial applications.

Molecular Characterization and Antimicrobial Susceptibilities of Nocardia Species Isolated from the Soil; A Comparison with Species Isolated from Humans

Nocardia species, one of the most predominant Actinobacteria of the soil microbiota, cause infection in humans following traumatic inoculation or inhalation. The identification, typing, phylogenetic relationship and antimicrobial susceptibilities of 38 soil Nocardia strains from Lara State, Venezuela, were studied by 16S rRNA and gyrB (subunit B of topoisomerase II) genes, multilocus sequence analysis (MLSA), whole-genome sequencing (WGS), and microdilution. The results were compared with those for human strains. Just seven Nocardia species with one or two strains each, except for Nocardia cyriacigeorgica with 29, were identified. MLSA confirmed the species assignments made by 16S rRNA and gyrB analyses (89.5% and 71.0% respectively), and grouped each soil strain with its corresponding reference and clinical strains, except for 19 N. cyriacigeorgica strains found at five locations which grouped into a soil-only cluster. The soil strains of N. cyriacigeorgica showed fewer gyrB haplotypes than the examined human strains (13 vs. 17) but did show a larger number of gyrB SNPs (212 vs. 77). Their susceptibilities to antimicrobials were similar except for beta-lactams, fluoroquinolones, minocycline, and clarithromycin, with the soil strains more susceptible to the first three (p ≤ 0.05). WGS was performed on four strains belonging to the soil-only cluster and on two outside it, and the results compared with public N. cyriacigeorgica genomes. The average nucleotide/amino acid identity, in silico genome-to-genome hybridization similarity, and the difference in the genomic GC content, suggest that some strains of the soil-only cluster may belong to a novel subspecies or even a new species (proposed name Nocardia venezuelensis).

Fast I(n)dentification of Pathogens in Neonates (FINDPATH-N): protocol for a prospective pilot cohort study of next-generation sequencing for pathogen identification in neonates with suspected sepsis

INTRODUCTION

Sepsis is a major source of morbidity and mortality in neonates; however, identification of the causative pathogens is challenging. Many neonates have negative blood cultures despite clinical evidence of sepsis. Next-generation sequencing (NGS) is a high-throughput, parallel sequencing technique for DNA. Pathogen-targeted enrichment followed by NGS has the potential to be more sensitive and faster than current gold-standard blood culture. In this pilot study, we will test the feasibility and pathogen detection patterns of pathogen-targeted NGS in neonates with suspected sepsis. Additionally, the distribution and diagnostic accuracy of biomarkers cell-free DNA and protein C levels at two time points will be explored.

METHODS AND ANALYSIS

We will conduct a prospective, pilot observational study. Neonates over 1 kg with suspected sepsis from a single tertiary care children's hospital will be recruited for the study. Recruitment will be censored at 200 events or 6 months' duration. Two blood study samples will be taken: the first simultaneous to the blood culture (time=0 hour, for NGS and biomarkers) via an exception to consent (deferred consent) and another 24 hours later after prospective consent (biomarkers only). Neonates will be adjudicated into those with clinical sepsis, culture-proven sepsis and without sepsis based on clinical criteria. Feasibility parameters (eg, recruitment) and NGS process time will be reported.For analysis, NGS results will be described in aggregate, compared with the simultaneous blood culture (sensitivity and specificity) and reviewed via expert panel for plausibility. Pilot data for biomarker distribution and diagnostic accuracy (sensitivity and specificity) for distinguishing between septic and non-septic neonates will be reported.

ETHICS AND DISSEMINATION

Ethics approval has been granted by the Hamilton Integrated Research Ethics Board. We will seek publication of study results in peer-reviewed journals.