Metagenomic Approaches to Analyze Antimicrobial Resistance: An Overview

The occurrence of banana Fusarium wilt aggravates antibiotic resistance genes dissemination in soil

The spread of antibiotic resistance genes (ARGs) and subsequent soil-borne disease outbreaks are major threats to soil health and sustainable crop production. However, the relationship between occurrences of soil-borne diseases and the transmission of soil ARGs remains unclear. Here, soil ARGs, mobile genetic elements and microbial communities from co-located disease suppressive and conducive banana orchards were deciphered using metagenomics and metatranscriptomics approaches. In total, 23 ARG types, with 399 subtypes, were detected using a metagenomics approach, whereas 23 ARG types, with 452 subtypes, were discovered using a metatranscriptomics method. Furthermore, the metagenomics analysis revealed that the ARG total abundance levels were greater in rhizospheres (0.45 ARGs/16S rRNA on average) compared with bulk (0.32 ARGs/16S rRNA on average) soils. Interestingly, metatranscriptomics revealed that the total ARG abundances were greater in disease-conducive (8.85 ARGs/16S rRNA on average) soils than disease suppressive (1.45 ARGs/16S rRNA on average) soils. Mobile genetic elements showed the same trends as ARGs. Network and binning analyses indicated that Mycobacterium, Streptomyces, and Blastomonas are the main potential hosts of ARGs. Furthermore, Bacillus was significantly and negatively correlated with Fusarium (P < 0.05, r = -0.84) and hosts of ARGs (i.e., Mycobacterium, Streptomyces, and Blastomonas). By comparing metagenomic and metatranscriptomic analyses，this study demonstrated that metatranscriptomics may be more sensitive in indicating ARGs activities in soil. Our findings enable the more accurate assessment of the transmission risk of ARGs. The data provide a new perspective for recognizing soil health, in which soil-borne disease outbreaks appear to be associated with ARG spread, whereas beneficial microbe enrichment may mitigate wilt disease and ARG transmission.

Metagenomics analysis of sewage for surveillance of antimicrobial resistance in South Africa

Our 24-month study used metagenomics to investigate antimicrobial resistance (AMR) abundance in raw sewage from wastewater treatment works (WWTWs) in two municipalities in Gauteng Province, South Africa. At the AMR class level, data showed similar trends at all WWTWs, showing that aminoglycoside, beta-lactam, sulfonamide and tetracycline resistance was most abundant. AMR abundance differences were shown between municipalities, where Tshwane Metropolitan Municipality (TMM) WWTWs showed overall higher abundance of AMR compared to Ekurhuleni Metropolitan Municipality (EMM) WWTWs. Also, within each municipality, there were differing trends in AMR abundance. Notably, within TMM, certain AMR classes (macrolides and macrolides_streptogramin B) were in higher abundance at a WWTW serving an urban high-income area, while other AMR classes (aminoglycosides) were in higher abundance at a WWTW serving a semi-urban low income area. At the AMR gene level, all WWTWs samples showed the most abundance for the sul1 gene (encoding sulfonamide resistance). Following this, the next 14 most abundant genes encoded resistance to sulfonamides, aminoglycosides, macrolides, tetracyclines and beta-lactams. Notably, within TMM, some macrolide-encoding resistance genes (mefC, msrE, mphG and mphE) were in highest abundance at a WWTW serving an urban high-income area; while sul1, sul2 and tetC genes were in highest abundance at a WWTW serving a semi-urban low income area. Differential abundance analysis of AMR genes at WWTWs, following stratification of data by season, showed some notable variance in six AMR genes, of which blaKPC-2 and blaKPC-34 genes showed the highest prevalence of seasonal abundance differences when comparing data within a WWTW. The general trend was to see higher abundances of AMR genes in colder seasons, when comparing seasonal data within a WWTW. Our study investigated wastewater samples in only one province of South Africa, from WWTWs located within close proximity to one another. We would require a more widespread investigation at WWTWs distributed across all regions/provinces of South Africa, in order to describe a more comprehensive profile of AMR abundance across the country.

A metagenomic study of antibiotic resistance genes in a hypereutrophic subtropical lake contaminated by anthropogenic sources

Antibiotic resistance genes (ARGs) are a major threat to human and environmental health. This study investigated the occurrence and distribution of ARGs in Lake Cajititlán, a hypereutrophic subtropical lake in Mexico contaminated by anthropogenic sources (urban wastewater and runoff from crop and livestock production). ARGs (a total of 475 genes) were detected in 22 bacterial genera, with Pseudomonas (144 genes), Stenotrophomonas (88 genes), Mycobacterium (54 genes), and Rhodococcus (27 genes) displaying the highest frequencies of ARGs. Among these, Pseudomonas aeruginosa and Stenotrophomonas maltophilia showed the highest number of ARGs. The results revealed a diverse array of ARGs, including resistance to macrolides (11.55 %), aminoglycosides (8.22 %), glycopeptides (6.22 %), tetracyclines (4 %), sulfonamides (4 %), carbapenems (1.11 %), phenicols (0.88 %), fluoroquinolones (0.44 %), and lincosamides (0.22 %). The most frequently observed ARGs were associated with multidrug resistance (63.33 %), with MexF (42 genes), MexW (36 genes), smeD (31 genes), mtrA (25 genes), and KHM-1 (22 genes) being the most common. Lake Cajititlán is a recreational area for swimming, fishing, and boating, while also supporting irrigation for agriculture and potentially acting as a drinking water source for some communities. This raises concerns about the potential for exposure to antibiotic-resistant bacteria through these activities. The presence of ARGs in Lake Cajititlán poses a significant threat to both human and environmental health. Developing strategies to mitigate the risks of antibiotic resistance, including improving wastewater treatment, and promoting strategic antibiotic use and disposal, is crucial. This study represents a significant advancement in the understanding of antibiotic resistance dynamics in a hypereutrophic subtropical lake in a developing country, providing valuable insights for the scientific community and policymakers.

A one health approach for monitoring antimicrobial resistance: developing a national freshwater pilot effort

Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue has led to the development of action plans to combat AMR, including improved antimicrobial stewardship, development of new antimicrobials, and advanced monitoring. The National Antimicrobial Resistance Monitoring System (NARMS) led by the United States (U.S) Food and Drug Administration along with the U.S. Centers for Disease Control and U.S. Department of Agriculture has monitored antimicrobial resistant bacteria in retail meats, humans, and food animals since the mid 1990's. NARMS is currently exploring an integrated One Health monitoring model recognizing that human, animal, plant, and environmental systems are linked to public health. Since 2020, the U.S. Environmental Protection Agency has led an interagency NARMS environmental working group (EWG) to implement a surface water AMR monitoring program (SWAM) at watershed and national scales. The NARMS EWG divided the development of the environmental monitoring effort into five areas: (i) defining objectives and questions, (ii) designing study/sampling design, (iii) selecting AMR indicators, (iv) establishing analytical methods, and (v) developing data management/analytics/metadata plans. For each of these areas, the consensus among the scientific community and literature was reviewed and carefully considered prior to the development of this environmental monitoring program. The data produced from the SWAM effort will help develop robust surface water monitoring programs with the goal of assessing public health risks associated with AMR pathogens in surface water (e.g., recreational water exposures), provide a comprehensive picture of how resistant strains are related spatially and temporally within a watershed, and help assess how anthropogenic drivers and intervention strategies impact the transmission of AMR within human, animal, and environmental systems.

The impact of antibiotic exposure on antibiotic resistance gene dynamics in the gut microbiota of inflammatory bowel disease patients

Background

While antibiotics are commonly used to treat inflammatory bowel disease (IBD), their widespread application can disturb the gut microbiota and foster the emergence and spread of antibiotic resistance. However, the dynamic changes to the human gut microbiota and direction of resistance gene transmission under antibiotic effects have not been clearly elucidated.

Methods

Based on the Human Microbiome Project, a total of 90 fecal samples were collected from 30 IBD patients before, during and after antibiotic treatment. Through the analysis workflow of metagenomics, we described the dynamic process of changes in bacterial communities and resistance genes pre-treatment, during and post-treatment. We explored potential consistent relationships between gut microbiota and resistance genes, and established gene transmission networks among species before and after antibiotic use.

Results

Exposure to antibiotics can induce alterations in the composition of the gut microbiota in IBD patients, particularly a reduction in probiotics, which gradually recovers to a new steady state after cessation of antibiotics. Network analyses revealed intra-phylum transfers of resistance genes, predominantly between taxonomically close organisms. Specific resistance genes showed increased prevalence and inter-species mobility after antibiotic cessation.

Conclusion

This study demonstrates that antibiotics shape the gut resistome through selective enrichment and promotion of horizontal gene transfer. The findings provide insights into ecological processes governing resistance gene dynamics and dissemination upon antibiotic perturbation of the microbiota. Optimizing antibiotic usage may help limit unintended consequences like increased resistance in gut bacteria during IBD management.

Understanding the gut microbiota by considering human evolution: a story of fire, cereals, cooking, molecular ingenuity, and functional cooperation

SUMMARYThe microbial community inhabiting the human colon, referred to as the gut microbiota, is mostly composed of bacterial species that, through extensive metabolic networking, degrade and ferment components of food and human secretions. The taxonomic composition of the microbiota has been extensively investigated in metagenomic studies that have also revealed details of molecular processes by which common components of the human diet are metabolized by specific members of the microbiota. Most studies of the gut microbiota aim to detect deviations in microbiota composition in patients relative to controls in the hope of showing that some diseases and conditions are due to or exacerbated by alterations to the gut microbiota. The aim of this review is to consider the gut microbiota in relation to the evolution of Homo sapiens which was heavily influenced by the consumption of a nutrient-dense non-arboreal diet, limited gut storage capacity, and acquisition of skills relating to mastering fire, cooking, and cultivation of cereal crops. The review delves into the past to gain an appreciation of what is important in the present. A holistic view of "healthy" microbiota function is proposed based on the evolutionary pathway shared by humans and gut microbes.

Genome-centric analyses of 165 metagenomes show that mobile genetic elements are crucial for the transmission of antimicrobial resistance genes to pathogens in activated sludge and wastewater

Wastewater is considered a reservoir of antimicrobial resistance genes (ARGs), where the abundant antimicrobial-resistant bacteria and mobile genetic elements facilitate horizontal gene transfer. However, the prevalence and extent of these phenomena in different taxonomic groups that inhabit wastewater are still not fully understood. Here, we determined the presence of ARGs in metagenome-assembled genomes (MAGs) and evaluated the risks of MAG-carrying ARGs in potential human pathogens. The potential of these ARGs to be transmitted horizontally or vertically was also determined. A total of 5,916 MAGs (completeness >50%, contamination <10%) were recovered, covering 68 phyla and 279 genera. MAGs were dereplicated into 1,204 genome operational taxonomic units (gOTUs) as a proxy for species ( average nucleotide identity >0.95). The dominant ARG classes detected were bacitracin, multi-drug, macrolide-lincosamide-streptogramin (MLS), glycopeptide, and aminoglycoside, and 10.26% of them were located on plasmids. The main hosts of ARGs belonged to Escherichia, Klebsiella, Acinetobacter, Gresbergeria, Mycobacterium, and Thauera. Our data showed that 253 MAGs carried virulence factor genes (VFGs) divided into 44 gOTUs, of which 45 MAGs were carriers of ARGs, indicating that potential human pathogens carried ARGs. Alarmingly, the MAG assigned as Escherichia coli contained 159 VFGs, of which 95 were located on chromosomes and 10 on plasmids. In addition to shedding light on the prevalence of ARGs in individual genomes recovered from activated sludge and wastewater, our study demonstrates a workflow that can identify antimicrobial-resistant pathogens in complex microbial communities.

IMPORTANCE

Antimicrobial resistance (AMR) threatens the health of humans, animals, and natural ecosystems. In our study, an analysis of 165 metagenomes from wastewater revealed antibiotic-targeted alteration, efflux, and inactivation as the most prevalent AMR mechanisms. We identified several genera correlated with multiple ARGs, including Klebsiella, Escherichia, Acinetobacter, Nitrospira, Ottowia, Pseudomonas, and Thauera, which could have significant implications for AMR transmission. The abundance of bacA, mexL, and aph(3")-I in the genomes calls for their urgent management in wastewater. Our approach could be applied to different ecosystems to assess the risk of potential pathogens containing ARGs. Our findings highlight the importance of managing AMR in wastewater and can help design measures to reduce the transmission and evolution of AMR in these systems.

Source Attribution of Antibiotic Resistance Genes in Estuarine Aquaculture: A Machine Learning Approach

Aquaculture located in urban river estuaries, where other anthropogenic activities may occur, has an impact on and may be affected by the environment where they are inserted, namely by the exchange of antimicrobial resistance genes. The latter may ultimately, through the food chain, represent a source of resistance genes to the human resistome. In an exploratory study of the presence of resistance genes in aquaculture sediments located in urban river estuaries, two machine learning models were applied to predict the source of 34 resistome observations in the aquaculture sediments of oysters and gilt-head sea bream, located in the estuaries of the Sado and Lima Rivers and in the Aveiro Lagoon, as well as in the sediments of the Tejo River estuary, where Japanese clams and mussels are collected. The first model included all 34 resistomes, amounting to 53 different antimicrobial resistance genes used as source predictors. The most important antimicrobial genes for source attribution were tetracycline resistance genes tet(51) and tet(L); aminoglycoside resistance gene aadA6; beta-lactam resistance gene blaBRO-2; and amphenicol resistance gene cmx_1. The second model included only oyster sediment resistomes, amounting to 30 antimicrobial resistance genes as predictors. The most important antimicrobial genes for source attribution were the aminoglycoside resistance gene aadA6, followed by the tetracycline genes tet(L) and tet(33). This exploratory study provides the first information about antimicrobial resistance genes in intensive and semi-intensive aquaculture in Portugal, helping to recognize the importance of environmental control to maintain the integrity and the sustainability of aquaculture farms.

Metagenome and Resistome Analysis of Beta-Lactam-Resistant Bacteria Isolated from River Waters in Surabaya, Indonesia

Antimicrobial agents are administered to humans and livestock, and bacterial antimicrobial resistance (AMR) and antimicrobial agents are released into the environment. In this study, to investigate the trend of AMR in humans, livestock, and the environment, we performed a metagenomic analysis of multidrug-resistant bacteria with CHROMagar ESBL in environmental river water samples, which were collected using syringe filter units from waters near hospitals, downtown areas, residential areas, and water treatment plants in Surabaya, Indonesia. Our results showed that Acinetobacter, Pseudomonas, Aeromonas, Enterobacter, Escherichia, and Klebsiella grew in CHROMagar ESBL; they were most frequently detected in water samples from rivers surrounding hospitals contaminated with various AMR genes (ARGs) in high levels. These results identified bacteria as ARG reservoirs and revealed that hospitals could be sources for various ARGs disseminated into the environment. In conclusion, this study details a novel metagenomic analysis of collected bacteria in environmental water samples using a syringe filter unit for an AMR epidemiological study based on the One Health approach.

Biocontrol in built environments to reduce pathogen exposure and infection risk

The microbiome of the built environment comprises bacterial, archaeal, fungal, and viral communities associated with human-made structures. Even though most of these microbes are benign, antibiotic-resistant pathogens can colonize and emerge indoors, creating infection risk through surface transmission or inhalation. Several studies have catalogued the microbial composition and ecology in different built environment types. These have informed in vitro studies that seek to replicate the physicochemical features that promote pathogenic survival and transmission, ultimately facilitating the development and validation of intervention techniques used to reduce pathogen accumulation. Such interventions include using Bacillus-based cleaning products on surfaces or integrating bacilli into printable materials. Though this work is in its infancy, early research suggests the potential to use microbial biocontrol to reduce hospital- and home-acquired multidrug-resistant infections. Although these techniques hold promise, there is an urgent need to better understand the microbial ecology of built environments and to determine how these biocontrol solutions alter species interactions. This review covers our current understanding of microbial ecology of the built environment and proposes strategies to translate that knowledge into effective biocontrol of antibiotic-resistant pathogens.

Applicability of Bronchoalveolar Lavage Fluid and Plasma Metagenomic Next-Generation Sequencing Assays in the Diagnosis of Pneumonia

Background

Metagenomic next-generation sequencing (mNGS) provides innovative solutions for predicting complex infections. A comprehensive understanding of its strengths and limitations in real-world clinical settings is necessary to ensure that it is not overused or misinterpreted.

Methods

Two hundred nine cases with suspected pneumonia were recruited to compare the capabilities of 2 available mNGS assays (bronchoalveolar lavage fluid [BALF] mNGS and plasma mNGS) to identify pneumonia-associated DNA/RNA pathogens and predict antibiotic resistance.

Results

Compared to clinical diagnosis, BALF mNGS demonstrated a high positive percent agreement (95.3%) but a low negative percent agreement (63.1%). Plasma mNGS revealed a low proportion of true negatives (30%) in predicting pulmonary infection. BALF mNGS independently diagnosed 65.6% (61/93) of coinfections and had a remarkable advantage in detecting caustic, rare, or atypical pathogens. Pathogens susceptible to invasive infection or bloodstream transmission, such as Aspergillus spp, Rhizopus spp, Chlamydia psittaci, and human herpesviruses, are prone to be detected by plasma mNGS. BALF mNGS tests provided a positive impact on the diagnosis and treatment of 128 (61.2%) patients. Plasma mNGS, on the other hand, turned out to be more suitable for diagnosing patients who received mechanical ventilation, developed severe pneumonia, or developed sepsis (all P < .01). BALF mNGS was able to identify resistance genes that matched the phenotypic resistance of 69.4% (25/36) of multidrug-resistant pathogens.

Conclusions

Our data reveal new insights into the advantages and disadvantages of 2 different sequencing modalities in pathogen identification and antibiotic resistance prediction for patients with suspected pneumonia.

NCRD: A non-redundant comprehensive database for detecting antibiotic resistance genes

Antibiotic resistance genes (ARGs) are emerging pollutants present in various environments. Identifying ARGs has become a growing concern in recent years. Several databases, including the Antibiotic Resistance Genes Database (ARDB), Comprehensive Antibiotic Resistance Database (CARD), and Structured Antibiotic Resistance Genes (SARG), have been applied to detect ARGs. However, these databases have limitations, which hinder the comprehensive profiling of ARGs in environmental samples. To address these issues, we constructed a non-redundant antibiotic resistance genes database (NRD) by consolidating sequences from ARDB, CARD, and SARG. We identified the homologous proteins of NRD from Non-redundant Protein Database (NR) and the Protein DataBank Database (PDB) and clustered them to establish a non-redundant comprehensive antibiotic resistance genes database (NCRD) with similarities of 100% (NCRD100) and 95% (NCRD95). To demonstrate the advantages of NCRD, we compared it with other databases by using metagenome datasets. Results revealed its strong ability in detecting potential ARGs.

ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization

Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a special focus on pathogens. A number of computational pipelines are available and under development to support environmental ARG monitoring; the pipeline we present here is promising for general adoption for the purpose of harmonized global monitoring. Specifically, ARGem is a user-friendly pipeline that provides full-service analysis, from the initial DNA short reads to the final visualization of results. The capture of extensive metadata is also facilitated to support comparability across projects and broader monitoring goals. The ARGem pipeline offers efficient analysis of a modest number of samples along with affordable computational components, though the throughput could be increased through cloud resources, based on the user's configuration. The pipeline components were carefully assessed and selected to satisfy tradeoffs, balancing efficiency and flexibility. It was essential to provide a step to perform short read assembly in a reasonable time frame to ensure accurate annotation of identified ARGs. Comprehensive ARG and mobile genetic element databases are included in ARGem for annotation support. ARGem further includes an expandable set of analysis tools that include statistical and network analysis and supports various useful visualization techniques, including Cytoscape visualization of co-occurrence and correlation networks. The performance and flexibility of the ARGem pipeline is demonstrated with analysis of aquatic metagenomes. The pipeline is freely available at https://github.com/xlxlxlx/ARGem.

Risk assessment and dissemination mechanism of antibiotic resistance genes in compost

In recent years, the excessive of antibiotics in livestock and poultry husbandry, stemming from extensive industry experience, has resulted in the accumulation of residual antibiotics and antibiotic resistance genes (ARGs) in livestock manure. Composting, as a crucial approach for the utilization of manure resources, has the potential to reduce the levels of antibiotics and ARGs in manure, although complete elimination is challenging. Previous studies have primarily focused on the diversity and abundance of ARGs in compost or have solely examined the correlation between ARGs and their carriers, potentially leading to a misjudgment of the actual risk associated with ARGs in compost. To address this gap, this study investigated the transfer potential of ARGs in compost and their co-occurrence with opportunistic pathogenic bacteria by extensively analyzing metagenomic sequencing data of compost worldwide. The results demonstrated that the potential risk of ARGs in compost was significantly lower than in manure, suggesting that composting effectively reduces the risk of ARGs. Further analysis showed that the microbes shifted their life history strategy in manure and compost due to antibiotic pressure and formed metabolic interactions dominated by antibiotic-resistant microbes, increasing ARG dissemination frequency. Therefore, husbandry practice without antibiotic addition was recommended to control ARG evolution, dissemination, and abatement both at the source and throughout processing.

Metagenomic profiling of antibiotic resistance genes in Red Sea brine pools

Antibiotic resistance (AR) is an alarming global health concern, causing an annual death rate of more than 35,000 deaths in the US. AR is a natural phenomenon, reported in several pristine environments. In this study, we report AR in pristine Red Sea deep brine pools. Antimicrobial resistance genes (ARGs) were detected for several drug classes with tetracycline and macrolide resistance being the most abundant. As expected, ARGs abundance increased in accordance with the level of human impact with pristine Red Sea samples having the lowest mean ARG level followed by estuary samples, while activated sludge samples showed a significantly higher ARG level. ARG hierarchical clustering grouped drug classes for which resistance was detected in Atlantis II Deep brine pool independent of the rest of the samples. ARG abundance was significantly lower in the Discovery Deep brine pool. A correlation between integrons and ARGs abundance in brine pristine samples could be detected, while insertion sequences and plasmids showed a correlation with ARGs abundance in human-impacted samples not seen in brine pristine samples. This suggests different roles of distinct mobile genetic elements (MGEs) in ARG distribution in pristine versus human-impacted sites. Additionally, we showed the presence of mobile antibiotic resistance genes in the Atlantis II brine pool as evidenced by the co-existence of integrases and plasmid replication proteins on the same contigs harboring predicted multidrug-resistant efflux pumps. This study addresses the role of non-pathogenic environmental bacteria as a silent reservoir for ARGs, and the possible horizontal gene transfer mechanism mediating ARG acquisition.

Nanopore Sequencing Discloses Compositional Quality of Commercial Probiotic Feed Supplements

The market for the application of probiotics as a livestock health improvement supplement has increased in recent years. However, most of the available products are quality-controlled using low-resolution techniques and un-curated databases, resulting in misidentification and incorrect product labels. In this work, we deployed two workflows and compared results obtained by full-length 16S rRNA genes (16S) and metagenomic (Meta) data to investigate their reliability for the microbial composition of both liquid and solid forms of animal probiotic products using Oxford Nanopore long-read-only (without short-read). Our result revealed that 16S amplicon data permits to detect the bacterial microbiota even with the low abundance in the samples. Moreover, the 16S approach has the potential to provide species-level resolution for prokaryotes but not for assessing yeast communities. Whereas, Meta data has more power to recover of high-quality metagenome-assembled genomes that enables detailed exploration of both bacterial and yeast populations, as well as antimicrobial resistance genes, and functional genes in the population. Our findings clearly demonstrate that implementing these workflows with long-read-only monitoring could be applied to assessing the quality and safety of probiotic products for animals and evaluating the quality of probiotic products on the market. This would benefit the sustained growth of the livestock probiotic industry.

Low-Level Tetracycline Resistance Gene tet(O)_3 in Campylobacter jejuni

Campylobacter (C.) spp. are the most important foodborne, bacterial, and zoonotic pathogens worldwide. Resistance monitoring of foodborne bacterial pathogens is an important tool to control antimicrobial resistance as a part of the “One Health” approach. The detection and functionality of new resistance genes are of paramount importance in applying more effective screening methods based on whole genome sequencing (WGS). Most tetracycline-resistant C. spp. isolates harbor tet(O), a gene that encodes a ribosomal protection protein. Here we describe tet(O)_3, which has been identified in two food isolates of C. jejuni and is very similar to the tet(O) gene in Streptococcus pneumoniae, having a truncated promoter sequence. This gene confers resistance to tetracycline below 1 mg/L, which is the epidemiological cut-off value. We have analyzed the entire genome of these two isolates, together with a C. jejuni isolate found to have high-level resistance to tetracycline. In contrast to the highly resistant isolate, the promoter of tet(O)_3 is highly responsive to tetracycline, as observed by reverse transcription polymerase chain reaction (RT-PCR). In addition, the two isolates possess a CRISPR repeat, fluoroquinolone resistance due to the gyrA point mutation C257T, a β-lactamase resistance gene blaOXA-184, a multidrug efflux pump CmeABC and its repressor CmeR, but no plasmid. Low-level antibiotic resistant C. jejuni might therefore have an advantage for surviving in non-host environments.

Prevalence and distribution of antimicrobial resistance in effluent wastewater from animal slaughter facilities: A systematic review

The extensive use of antibiotics in food animal production and disposal of untreated wastewater from food animal slaughter facilities may create a shift in microbiomes of different ecosystems by generating reservoirs of antimicrobial resistance along the human-animal-environmental interface. This epidemiological problem has been studied, but its magnitude and impact on a global scale is poorly characterised. A systematic review was done to determine global prevalence and distribution patterns of antimicrobial resistance in effluent wastewater from animal slaughter facilities. Extracted data were stratified into rational groups for secondary analyses and presented as percentages. Culture and sensitivity testing was the predominant method; Escherichia spp., Enterococcus spp., and Staphylococcus aureus were the most targeted isolates. Variable incidences of resistance were detected against all major antimicrobial classes including reserved drugs such as ceftazidime, piperacillin, gentamicin, ciprofloxacin, and chloramphenicol; the median frequency and range in resistant Gram-negative isolates were: 11 (0-100), 62 (0-100), 8 (0-100), 14 (0-93) and 12 (0-62) respectively. Ciprofloxacin was the most tested drug with the highest incidences of resistance in livestock slaughterhouses in Iran (93%), Nigeria (50%) and China (20%), and poultry slaughterhouses in Germany (21-81%) and Spain (56%). Spatial global distribution patterns for antimicrobial resistance were associated with previously reported magnitude of antibiotic use in livestock or poultry farming and, the implicit existence of jurisdictional policies to regulate antibiotic use. These data indicate that anthropogenic activities in farming systems are a major contributor to the cause and dissemination of antimicrobial resistance into the environment via slaughterhouse effluents.

The K-mer antibiotic resistance gene variant analyzer (KARGVA)

Characterization of antibiotic resistance genes (ARGs) from high-throughput sequencing data of metagenomics and cultured bacterial samples is a challenging task, with the need to account for both computational (e.g., string algorithms) and biological (e.g., gene transfers, rearrangements) aspects. Curated ARG databases exist together with assorted ARG classification approaches (e.g., database alignment, machine learning). Besides ARGs that naturally occur in bacterial strains or are acquired through mobile elements, there are chromosomal genes that can render a bacterium resistant to antibiotics through point mutations, i.e., ARG variants (ARGVs). While ARG repositories also collect ARGVs, there are only a few tools that are able to identify ARGVs from metagenomics and high throughput sequencing data, with a number of limitations (e.g., pre-assembly, a posteriori verification of mutations, or specification of species). In this work we present the k-mer, i.e., strings of fixed length k, ARGV analyzer - KARGVA - an open-source, multi-platform tool that provides: (i) an ad hoc, large ARGV database derived from multiple sources; (ii) input capability for various types of high-throughput sequencing data; (iii) a three-way, hash-based, k-mer search setup to process data efficiently, linking k-mers to ARGVs, k-mers to point mutations, and ARGVs to k-mers, respectively; (iv) a statistical filter on sequence classification to reduce type I and II errors. On semi-synthetic data, KARGVA provides very high accuracy even in presence of high sequencing errors or mutations (99.2 and 86.6% accuracy within 1 and 5% base change rates, respectively), and genome rearrangements (98.2% accuracy), with robust performance on ad hoc false positive sets. On data from the worldwide MetaSUB consortium, comprising 3,700+ metagenomics experiments, KARGVA identifies more ARGVs than Resistance Gene Identifier (4.8x) and PointFinder (6.8x), yet all predictions are below the expected false positive estimates. The prevalence of ARGVs is correlated to ARGs but ecological characteristics do not explain well ARGV variance. KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.

Clinically Relevant β-Lactam Resistance Genes in Wastewater Treatment Plants

Antimicrobial resistance (AMR) is one of the largest global concerns due to its influence in multiple areas, which is consistent with One Health's concept of close interconnections between people, animals, plants, and their shared environments. Antibiotic-resistant bacteria (ARB) and antibiotic-resistance genes (ARGs) circulate constantly in various niches, sediments, water sources, soil, and wastes of the animal and plant sectors, and is linked to human activities. Sewage of different origins gets to the wastewater treatment plants (WWTPs), where ARB and ARG removal efficiency is still insufficient, leading to their transmission to discharge points and further dissemination. Thus, WWTPs are believed to be reservoirs of ARGs and the source of spreading AMR. According to a World Health Organization report, the most critical pathogens for public health include Gram-negative bacteria resistant to third-generation cephalosporins and carbapenems (last-choice drugs), which represent β-lactams, the most widely used antibiotics. Therefore, this paper aimed to present the available research data for ARGs in WWTPs that confer resistance to β-lactam antibiotics, with a particular emphasis on clinically important life-threatening mechanisms of resistance, including extended-spectrum β-lactamases (ESBLs) and carbapenemases (KPC, NDM).

Insights into coastal microbial antibiotic resistome through a meta-transcriptomic approach in Yucatan

Antibiotic resistance (AR) is one of the greatest human and clinical challenges associated with different pathogenic organisms. However, in recent years it has also become an environmental problem due to the widespread use of antibiotics in humans and livestock activities. The ability to resist antibiotics comes from antibiotic resistance genes (ARGs) and our understanding of their presence in coastal environments is still limited. Therefore, the objective of the present study was to explore the presence and possible differences in the microbial resistome of four sites from the Yucatan coast through the evaluation of the composition and abundance of ARGs using a high-throughput analysis of metatranscriptomic sequences. In total, 3,498 ARGs were uncovered, which participate in the resistance to tetracycline, macrolide, rifamycin, fluoroquinolone, phenicol, aminoglycoside, cephalosporin, and other antibiotics. The molecular mechanisms of these ARGs were mainly efflux pump, antibiotic target alteration and antibiotic target replacement. In the same way, ARGs were detected in the samples but showing dissimilar enrichment levels. With respect to the sampling sites, the ARGs were present in all the samples collected, either from preserved or contaminated areas. Importantly, sediments of the preserved area of Dzilam presented the second highest level of ARGs detected, probably as a consequence of the antibiotics dragged to the coast by submarine groundwater discharge. In general, the resistance to a single antibiotic was greater than multiresistance, both at the level of gene and organisms; and multiresistance in organisms is acquired mainly by recruiting different monoresistance genes. To our knowledge, this is the first study that describes and compares the resistome of different samples of the Yucatan coast. This study contributes to generating information about the current state of antibiotic resistance on the Yucatan coasts for a better understanding of ARGs dissemination and could facilitate the management of ARGs pollution in the environment.

Exploring Bacterial Attributes That Underpin Symbiont Life in the Monogastric Gut

The large bowel of monogastric animals, such as that of humans, is home to a microbial community (microbiota) composed of a diversity of mostly bacterial species. Interrelationships between the microbiota as an entity and the host are complex and lifelong and are characteristic of a symbiosis. The relationships may be disrupted in association with disease, resulting in dysbiosis. Modifications to the microbiota to correct dysbiosis require knowledge of the fundamental mechanisms by which symbionts inhabit the gut. This review aims to summarize aspects of niche fitness of bacterial species that inhabit the monogastric gut, especially of humans, and to indicate the research path by which progress can be made in exploring bacterial attributes that underpin symbiont life in the gut.

Antimicrobial Resistance and Its Spread Is a Global Threat

Antimicrobial resistance (AMR) is a challenge to human wellbeing the world over and is one of the more serious public health concerns. AMR has the potential to emerge as a serious healthcare threat if left unchecked, and could put into motion another pandemic. This establishes the need for the establishment of global health solutions around AMR, taking into account microdata from different parts of the world. The positive influences in this regard could be establishing conducive social norms, charting individual and group behavior practices that favor global human health, and lastly, increasing collective awareness around the need for such action. Apart from being an emerging threat in the clinical space, AMR also increases treatment complexity, posing a real challenge to the existing guidelines around the management of antibiotic resistance. The attribute of resistance development has been linked to many genetic elements, some of which have complex transmission pathways between microbes. Beyond this, new mechanisms underlying the development of AMR are being discovered, making this field an important aspect of medical microbiology. Apart from the genetic aspects of AMR, other practices, including misdiagnosis, exposure to broad-spectrum antibiotics, and lack of rapid diagnosis, add to the creation of resistance. However, upgrades and innovations in DNA sequencing technologies with bioinformatics have revolutionized the diagnostic industry, aiding the real-time detection of causes of AMR and its elements, which are important to delineating control and prevention approaches to fight the threat.

Metaomics in Clinical Laboratory: Potential Driving Force for Innovative Disease Diagnosis

Currently, more and more studies suggested that reductionism was lack of holistic and integrative view of biological processes, leading to limited understanding of complex systems like microbiota and the associated diseases. In fact, microbes are rarely present in individuals but normally live in complex multispecies communities. With the recent development of a variety of metaomics techniques, microbes could be dissected dynamically in both temporal and spatial scales. Therefore, in-depth understanding of human microbiome from different aspects such as genomes, transcriptomes, proteomes, and metabolomes could provide novel insights into their functional roles, which also holds the potential in making them diagnostic biomarkers in many human diseases, though there is still a huge gap to fill for the purpose. In this mini-review, we went through the frontlines of the metaomics techniques and explored their potential applications in clinical diagnoses of human diseases, e.g., infectious diseases, through which we concluded that novel diagnostic methods based on human microbiomes shall be achieved in the near future, while the limitations of these techniques such as standard procedures and computational challenges for rapid and accurate analysis of metaomics data in clinical settings were also examined.

Sustainability of the rice-crayfish co-culture aquaculture model: microbiome profiles based on multi-kingdom analyses

While the rice-crayfish culture (RCFP) model, an important aquaculture model in Asia, is generally considered a sustainable model, its sustainability in terms of microbial community profiles has not been evaluated. In this study, multi-kingdom analyses of microbiome profiles (i.e., bacteria, archaea, viruses, and eukaryotes) were performed using environmental (i.e., water and sediment) and animal gut (i.e., crayfish and crab gut) microbial samples from the RCFP and other aquaculture models, including the crab-crayfish co-culture, crayfish culture, and crab culture models, to evaluate the sustainability of the RCFP systematically. Results showed that RCFP samples are enriched with a distinct set of microbes, including Shewanella, Ferroplasma, Leishmania, and Siphoviridae, when compared with other aquaculture models. Additionally, most microbes in the RCFP samples, especially microbes from different kingdoms, were densely and positively connected, which indicates their robustness against environmental stress. Whereas microbes in different aquaculture models demonstrated moderate levels of horizontal gene transfer (HGT) across kingdoms, the RCFP showed relatively lower frequencies of HGT events, especially those involving antibiotic resistance genes. Finally, environmental factors, including pH, oxidation-reduction potential, temperature, and total nitrogen, contributed profoundly to shaping the microbial communities in these aquaculture models. Interestingly, compared with other models, the microbial communities of the RCFP model were less influenced by these environmental factors, which suggests that microbes in the latter have stronger ability to resist environmental stress. The findings collectively reflect the unique multi-kingdom microbial patterns of the RCFP model and suggest that this model is a sustainable model from the perspective of microbiome profiles.

Comparative Metagenomic Study of Rhizospheric and Bulk Mercury-Contaminated Soils in the Mining District of Almadén

Soil contamination by heavy metals, particularly mercury (Hg), is a problem that can seriously affect the environment, animals, and human health. Hg has the capacity to biomagnify in the food chain. That fact can lead to pathologies, of those which affect the central nervous system being the most severe. It is convenient to know the biological environmental indicators that alert of the effects of Hg contamination as well as the biological mechanisms that can help in its remediation. To contribute to this knowledge, this study conducted comparative analysis by the use of Shotgun metagenomics of the microbial communities in rhizospheric soils and bulk soil of the mining region of Almadén (Ciudad Real, Spain), one of the most affected areas by Hg in the world The sequences obtained was analyzed with MetaPhlAn2 tool and SUPER-FOCUS. The most abundant taxa in the taxonomic analysis in bulk soil were those of Actinobateria and Alphaproteobacteria. On the contrary, in the rhizospheric soil microorganisms belonging to the phylum Proteobacteria were abundant, evidencing that roots have a selective effect on the rhizospheric communities. In order to analyze possible indicators of biological contamination, a functional potential analysis was performed. The results point to a co-selection of the mechanisms of resistance to Hg and the mechanisms of resistance to antibiotics or other toxic compounds in environments contaminated by Hg. Likewise, the finding of antibiotic resistance mechanisms typical of the human clinic, such as resistance to beta-lactams and glycopeptics (vancomycin), suggests that these environments can behave as reservoirs. The sequences involved in Hg resistance (operon mer and efflux pumps) have a similar abundance in both soil types. However, the response to abiotic stress (salinity, desiccation, and contaminants) is more prevalent in rhizospheric soil. Finally, sequences involved in nitrogen fixation and metabolism and plant growth promotion (PGP genes) were identified, with higher relative abundances in rhizospheric soils. These findings can be the starting point for the targeted search for microorganisms suitable for further use in bioremediation processes in Hg-contaminated environments.

Optimizing Nanopore Sequencing for Rapid Detection of Microbial Species and Antimicrobial Resistance in Patients at Risk of Surgical Site Infections

Surgical site infections (SSI) are a significant burden to patients and health care systems. We evaluated the use of Nanopore sequencing (NS) to rapidly detect microbial species and antimicrobial resistance (AMR) genes present in intraoperative bile aspirates. Bile aspirates from 42 patients undergoing pancreatic head resection were included. Three methods of DNA extraction using mechanical cell lysis or protease cell lysis were compared to determine the optimum method of DNA extraction. The impact of host DNA depletion, sequence run duration, and use of different AMR gene databases was also assessed. To determine clinical value, NS results were compared to standard culture (SC) results. NS identified microbial species in all culture positive samples. Mechanical lysis improved NS detection of cultured species from 60% to 76%, enabled detection of fungal species, and increased AMR predictions. Host DNA depletion improved detection of streptococcal species and AMR correlation with SC. Selection of AMR database influenced the number of AMR hits and resistance profile of 13 antibiotics. AMR prediction using CARD and ResFinder 4.1 correctly predicted 79% and 81% of the bile antibiogram, respectively. Sequence run duration positively correlated with detection of AMR genes. A minimum of 6 h was required to characterize the biliary microbes, resulting in a turnaround time of 14 h. Rapid identification of microbial species and AMR genes can be achieved by NS. NS results correlated with SC, suggesting that NS may be useful in guiding early antimicrobial therapy postsurgery. IMPORTANCE Surgical site infections (SSI) are a significant burden to patients and health care systems. They increase mortality rates, length of hospital stays, and associated health care costs. To reduce the risk of SSI, surgical patients are administered broad-spectrum antibiotics that are later adapted to target microbial species detected at the site of surgical incision. Use of broad-spectrum antibiotics can be harmful to the patient. We wanted to develop a rapid method of detecting microbial species and their antimicrobial resistance phenotypes. We developed a method of detecting microbial species and predicting resistance phenotypes using Nanopore sequencing. Results generated using Nanopore sequencing were similar to current methods of detection but were obtained in a significantly shorter amount of time. This suggests that Nanopore sequencing could be used to tailor antibiotics in surgical patients and reduce use of broad-spectrum antibiotics.

Pilot Study on Poultry Meat from Antibiotic Free and Conventional Farms: Can Metagenomics Detect Any Difference?

Antibiotic free farms are increasing in the poultry sector in order to address new EU regulations and consumer concerns. In this pilot study, we investigated whether the efforts of raising chickens without the use antibiotics make any difference in the microbiome of poultry meat eaten by consumers. To this aim we compared the microbiomes characterizing caeca and the corresponding carcasses of two groups of chickens reared, one reared on a conventional farm and one on an antibiotic-free intensive farm. The results showed a clear separation between the taxonomic, functional and antibiotic resistant genes in the caeca of the birds reared on the conventional and antibiotic free farm. However, that separation was completely lost on carcasses belonging to the two groups. The antibiotic-free production resulted in statistically significant lower antimicrobial resistance load in the caeca in comparison to the conventional production. Moreover, the antimicrobial resistance load on carcasses was much higher than in the caeca, without any significant difference between carcasses coming from the two types of farms. All in all, the results of this research highlighted the need to reduce sources of microbial contamination and antimicrobial resistance not only at the farm level but also at the post-harvest one.

Phage therapeutics: from promises to practices and prospectives

The rise in multi-drug resistant bacteria and the inability to develop novel antibacterial agents limits our arsenal against infectious diseases. Antibiotic resistance is a global issue requiring an immediate solution, including the development of new antibiotic molecules and other alternative modes of therapy. This article highlights the mechanism of bacteriophage treatment that makes it a real solution for multidrug-resistant infectious diseases. Several case reports identified phage therapy as a potential solution to the emerging challenge of multi-drug resistance. Bacteriophages, unlike antibiotics, have special features, such as host specificity and do not impact other commensals. A new outlook has also arisen with recent advancements in the understanding of phage immunobiology, where phages are repurposed against both bacterial and viral infections. Thus, the potential possibility of phages in COVID-19 patients with secondary bacterial infections has been briefly elucidated. However, significant obstacles that need to be addressed are to design better clinical studies that may contribute to the widespread use of bacteriophage therapy against multi-drug resistant pathogens. In conclusion, antibacterial agents can be used with bacteriophages, i.e. bacteriophage-antibiotic combination therapy, or they can be administered alone in cases when antibiotics are ineffective.Key points• AMR, a consequence of antibiotic generated menace globally, has led to the resurgence of phage therapy as an effective and sustainable solution without any side effects and high specificity against refractory MDR bacterial infections.• Bacteriophages have fewer adverse reactions and can thus be used as monotherapy as well as in conjunction with antibiotics.• In the context of the COVID-19 pandemic, phage therapy may be a viable option.

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 Journey on the Skin Microbiome: Pitfalls and Opportunities

The human skin microbiota is essential for maintaining homeostasis and ensuring barrier functions. Over the years, the characterization of its composition and taxonomic diversity has reached outstanding goals, with more than 10 million bacterial genes collected and cataloged. Nevertheless, the study of the skin microbiota presents specific challenges that need to be addressed in study design. Benchmarking procedures and reproducible and robust analysis workflows for increasing comparability among studies are required. For various reasons and because of specific technical problems, these issues have been investigated in gut microbiota studies, but they have been largely overlooked for skin microbiota. After a short description of the skin microbiota, the review tackles methodological aspects and their pitfalls, covering NGS approaches and high throughput culture-based techniques. Recent insights into the "core" and "transient" types of skin microbiota and how the manipulation of these communities can prevent or combat skin diseases are also covered. Finally, this review includes an overview of the main dermatological diseases, the changes in the microbiota composition associated with them, and the recommended skin sampling procedures. The last section focuses on topical and oral probiotics to improve and maintain skin health, considering their possible applications for skin diseases.