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

Strategy to develop and validate digital droplet PCR methods for global antimicrobial resistance wastewater surveillance

According to World Health Organization (WHO), antimicrobial resistance (AMR) is currently one of the world's top 10 health threats, causing infections to become difficult or impossible to treat, increasing the risk of disease spread, severe illness, disability, and death. Accurate surveillance is a key component in the fight against AMR. Wastewater is progressively becoming a new player in AMR surveillance, with the promise of a cost-effective real-time tracking of global AMR profiles in specific regions. One of the most useful analytical methods for wastewater surveillance is currently based on real-time PCR (qPCR) and digital droplet PCR (ddPCR) technologies. As stated in the EU Wastewater Treatment Directive proposal, methodological standardization, including a workflow for method development and validation, will play a crucial role in global monitoring of AMR in wastewater. However, according to our knowledge, there are currently no qPCR and ddPCR methods for AMR surveillance available that have been validated according to international standard performance criteria. Therefore, this study proposes a workflow for the development and validation of PCR-based methods for a harmonized and global AMR surveillance, including the construction of specific sequence databases and microbial collections for an efficient method development and method specificity evaluation. Following this strategy, we have developed and validated four duplex ddPCR methods responding to international standard performance criteria, focusing on seven AMR genes (ARG's), including extended spectrum beta-lactam (blaCTX-M), carbapenem (blaKPC-2/3), tetracycline (tet(M)), erythromycin (erm(B)), vancomycin (vanA), sulfonamide (sul2), and aminoglycoside (aac(3)-IV), as well as one indicator of antibiotic (multi-) resistance and horizontal gene transfer, named the class I integron (intl1). The performance of these ddPCR methods was successfully assessed for their specificity, as no false-positive and false-negative results were observed. These ddPCR methods were also considered to be highly sensitive as showing a limit of detection below 25 copies of the targets. In addition, their applicability was confirmed using 14 wastewater samples collected from two Belgian water resource recovery facilities. The proposed study represents therefore a step forward to reinforce method harmonization in the context of the global AMR surveillance in wastewater. PRACTITIONER POINTS: In the context of wastewater surveillance, no PCR-based methods for global AMR monitoring are currently validated according to international standards. Consequently, we propose a workflow to develop and validate PCR-based methods for a harmonized and global AMR surveillance. This workflow resulted here in four duplex ddPCR methods targeting seven ARGs and one general indicator for mobilizable resistance genes. The applicability of these validated ddPCR methods was confirmed on 14 wastewater samples from two Belgian water resource recovery facilities.

A Surveillance Study of Culturable and Antimicrobial-Resistant Bacteria in Two Urban WWTPs in Northern Spain

BACKGROUND/OBJECTIVES

Wastewater treatment plants (WWTPs) are hotspots for the spread of antimicrobial resistance into the environment. This study aimed to estimate the proportion of clinically relevant antimicrobial-resistant bacteria in two Spanish urban WWTPs, located in the region of La Rioja (Spain); Methods: Ninety-four samples (48 water/46 sludge) were collected and streaked on ten different selective media, in order to recover the culturable bacterial diversity with relevant resistance phenotypes: Extended-Spectrum β-Lactamase-producing Escherichia coli/Klebsiella pneumoniae (ESBL-Ec/Kp), Carbapenem-resistant Enterobacteriaceae (CR-E), Methicillin-resistant Staphylococcus aureus (MRSA), and Vancomycin-resistant Enterococcus faecium/faecalis (VR-E. faecium/faecalis). Isolates were identified by MALDI-TOF and were tested for antimicrobial susceptibility using the disk diffusion method. The confirmation of ESBL production was performed by the double-disk test; Results: A total of 914 isolates were recovered (31 genera and 90 species). Isolates with clinically relevant resistance phenotypes such as ESBL-Ec/Kp and CR-E were recovered in the effluent (0.4 × 100-4.8 × 101 CFU/mL) and organic amendment samples (1.0-101-6.0 × 102 CFU/mL), which are discharged to surface waters/agricultural fields. We reported the presence of VR-E. faecium in non-treated sludge and in the digested sludge samples (1.3 × 101-1 × 103 CFU/mL). MRSA was also recovered, but only in low abundance in the effluent (0.2 × 101 CFU/mL); Conclusions: This study highlights the need for improved wastewater technologies and stricter regulations on the use of amendment sludge in agriculture. In addition, regular monitoring and surveillance of WWTPs are critical for early detection and the mitigation of risks associated with the spread of antimicrobial resistance.

Towards the definition of an antibiotic resistome signature in wastewater and downstream environments

Domestic wastewater is a significant reservoir of antibiotic resistance genes, which pose environmental and public health risks. We aimed to define an antibiotic resistome signature, represented by core genes, i.e., shared by ≥ 90% of the metagenomes of each of three conceptual environmental compartments - wastewater (influent, sludge, effluent), freshwater, and agricultural soil. The definition of resistome signatures would support the proposal of a framework for monitoring treatment efficacy and assessing the impact of treated wastewater discharge into the environment, such as freshwater and agricultural soil. Metagenomic data from 163 samples originating from wastewater (n = 81), freshwater (n = 58), and agricultural soils (n = 24) across different regions (29 countries, 5 continents), were analysed regarding antibiotic resistance diversity, based on annotation against a database that merged CARD and ResFinder databases. The relative abundance of the total antibiotic resistance genes (corresponding to the ratio between the antibiotic resistance genes and total reads number) was not statistically different between raw and treated wastewater, being significantly higher than in freshwater or agricultural soils. The latter had the significantly lowest relative abundance of antibiotic resistance genes. Genes conferring resistance to aminoglycosides, beta-lactams, and tetracyclines were among the most abundant in wastewater environments, while multidrug resistance was equally distributed across all environments. The wastewater resistome signature included 27 antibiotic resistance genes that were detected in at least 90% of the wastewater resistomes, and that were not frequent in freshwater or agricultural soil resistomes. Among these were genes responsible for resistance to tetracyclines (n = 8), macrolide-lincosamide-streptogramin B (n = 7), aminoglycosides (n = 4), beta-lactams (n = 3), multidrug (n = 2), sulphonamides (n = 2), and polypeptides (n = 1). This comprehensive assessment provides valuable insights into the dynamics of antibiotic resistance in urban wastewater systems and their potential ecological implications in diverse environmental settings. Furthermore, provides guidance for the implementation of One Health monitoring approaches.

National-scale antimicrobial resistance surveillance in wastewater: A comparative analysis of HT qPCR and metagenomic approaches

Wastewater serves as an important reservoir of antimicrobial resistance (AMR), and its surveillance can provide insights into population-level trends in AMR to inform public health policy. This study compared two common high-throughput screening approaches, namely (i) high-throughput quantitative PCR (HT qPCR), targeting 73 antimicrobial resistance genes, and (ii) metagenomic sequencing. Weekly composite samples of wastewater influent were taken from 47 wastewater treatment plants (WWTPs) across Wales, as part of a national AMR surveillance programme, alongside 4 weeks of daily wastewater effluent samples from a large municipal hospital. Metagenomic analysis provided more comprehensive resistome coverage, detecting 545 genes compared to the targeted 73 genes by HT qPCR. It further provided contextual information critical to risk assessment (i.e. potential bacterial hosts). In contrast, HT qPCR exhibited higher sensitivity, quantifying all targeted genes including those of clinical relevance present at low abundance. When limited to the HT qPCR target genes, both methods were able to reflect the spatiotemporal dynamics of the complete metagenomic resistome, distinguishing that of the hospital and the WWTPs. Both approaches revealed correlations between resistome compositional shifts and environmental variables like ammonium wastewater concentration, though differed in their interpretation of some potential influencing factors. Overall, metagenomics provides more comprehensive resistome profiling, while qPCR permits sensitive quantification of genes significant to clinical resistance. We highlight the importance of selecting appropriate methodologies aligned to surveillance aims to guide the development of effective wastewater-based AMR monitoring programmes.

Metagenomic evaluation of bacteria in drinking water using full-length 16S rRNA amplicons

Escherichia coli and total coliforms are important tools for identifying potential faecal contamination in drinking water. However, metagenomics offers a powerful approach for delving deeper into a bacterial community when E. coli or total coliforms are detected. Metagenomics can identify microbes native to water systems, track community changes and potential pathogens introduced by contamination events, and evaluate the effectiveness of treatment processes. Here, we demonstrate how the dual application of traditional monitoring practices and metagenomics can improve monitoring and surveillance for water resource management. The robustness of long-read metagenomics across replicates is demonstrated by the effect and interaction between manganese filters and bacterial communities, as well as the impact of chlorination after coliform detection. These examples reveal how metagenomics can identify the complex bacterial communities in the distribution system and the source waters used to supply drinking water treatment plants (DWTPs). The knowledge gained increases confidence in identified causes and mitigations of potential contamination events. By exploring bacterial communities, we can gain additional insights into the impact of faecal contamination events and treatment processes. This insight enables more precise remediation actions and enhances confidence in communicating health risks to drinking water operators and the public.

High Prevalence of Highly Pathogenic Avian Influenza: A Virus in Vietnam's Live Bird Markets

Background

In recent years, Vietnam has suffered multiple epizootics of influenza in poultry.

Methods

From 10 January 2019 to 26 April 2021, we employed a One Health influenza surveillance approach at live bird markets (LBMs) and swine farms in Northern Vietnam. When the COVID-19 pandemic permitted, each month, field teams collected oral secretion samples from poultry and pigs, animal facility bioaerosol and fecal samples, and animal worker nasal washes at 4 LBMs and 5 swine farms across 5 sites. Initially samples were screened with molecular assays followed by culture in embryonated eggs (poultry swabs) or Madin-Darby canine kidney cells (human or swine swabs).

Results

Many of the 3493 samples collected had either molecular or culture evidence for influenza A virus, including 314 (37.5%) of the 837 poultry oropharyngeal swabs, 144 (25.1%) of the 574 bioaerosol samples, 438 (34.9%) of the 1257 poultry fecal swab samples, and 16 (1.9%) of the 828 human nasal washes. Culturing poultry samples yielded 454 influenza A isolates, 83 of which were H5, and 70 (84.3%) of these were highly pathogenic. Additionally, a positive human sample had a H9N2 avian-like PB1 gene. In contrast, the prevalence of influenza A in the swine farms was much lower with only 6 (0.4%) of the 1700 total swine farm samples studied, having molecular evidence for influenza A virus.

Conclusions

This study suggests that Vietnam's LBMs continue to harbor high prevalences of avian influenza A viruses, including many highly pathogenic H5N6 strains, which will continue to threaten poultry and humans.

Antibiotic resistance monitoring in wastewater in the Nordic countries: A systematic review

The Nordic countries (Denmark, Finland, Iceland, Norway, and Sweden) have effectively kept lower antibiotic-resistant bacterial (ARB) pathogen rates than many other countries. However, in recent years, these five countries have encountered a rise in ARB cases and challenges in treating infections due to the growing prevalence of ARB pathogens. Wastewater-based surveillance (WBS) is a valuable supplement to clinical methods for ARB surveillance, but there is a lack of comprehensive understanding of WBS application for ARB in the Nordic countries. This review aims to compile the latest state-of-the-art developments in WBS for ARB monitoring in the Nordic countries and compare them with clinical surveillance practices. After reviewing 1480 papers from the primary search, 54 were found relevant, and 15 additional WBS-related papers were included. Among 69 studies analyzed, 42 dedicated clinical epidemiology, while 27 focused on wastewater monitoring. The PRISMA review of the literature revealed that Nordic countries focus on four major WBS objectives of ARB: assessing ARB in the human population, identifying ARB evading wastewater treatment, quantifying removal rates, and evaluating potential ARB evolution during the treatment process. In both clinical and wastewater contexts, the most studied targets were pathogens producing carbapenemase and extended-spectrum beta-lactamase (ESBL), primarily Escherichia coli and Klebsiella spp. However, vancomycin-resistant Enterococcus (VRE) and methicillin-resistant Staphylococcus aureus (MRSA) have received more attention in clinical epidemiology than in wastewater studies, probably due to their lower detection rates in wastewater. Clinical surveillance has mostly used culturing, antibiotic susceptibility testing, and genotyping, but WBS employed PCR-based and metagenomics alongside culture-based techniques. Imported cases resulting from international travel and hospitalization abroad appear to have frequently contributed to the rise in ARB pathogen cases in these countries. The many similarities between the Nordic countries (e.g., knowledge exchange practices, antibiotic usage patterns, and the current ARB landscape) could facilitate collaborative efforts in developing and implementing WBS for ARB in population-level screening.

City-scale monitoring of antibiotic resistance genes by digital PCR and metagenomics

BACKGROUND

Anthropogenic activities significantly contribute to the dissemination of antibiotic resistance genes (ARGs), posing a substantial threat to humankind. The development of methods that allow robust ARG surveillance is a long-standing challenge. Here, we use city-scale monitoring of ARGs by using two of the most promising cutting-edge technologies, digital PCR (dPCR) and metagenomics.

METHODS

ARG hot-spots were sampled from the urban water and wastewater distribution systems. Metagenomics was used to provide a broad view of ARG relative abundance and richness in the prokaryotic and viral fractions. From the city-core ARGs in all samples, the worldwide dispersed sul2 and tetW conferring resistance to sulfonamide and tetracycline, respectively, were monitored by dPCR and metagenomics.

RESULTS

The largest relative overall ARG abundance and richness were detected in the hospital wastewater and the WWTP inlet (up to ≈6,000 ARGs/Gb metagenome) with a large fraction of unclassified resistant bacteria. The abundance of ARGs in DNA and RNA contigs classified as viruses was notably lower, demonstrating a reduction of up to three orders of magnitude compared to contigs associated to prokaryotes. By metagenomics and dPCR, a similar abundance tendency of sul2 and tetW was obtained, with higher abundances in hospital wastewater and WWTP input (≈125-225 ARGs/Gb metagenome). dPCR absolute abundances were between 6,000 and 18,600 copies per ng of sewage DNA (≈105-7 copies/mL) and 6.8 copies/mL in seawater near the WWTP discharging point.

CONCLUSIONS

dPCR was more sensitive and accurate, while metagenomics provided broader coverage of ARG detection. While desirable, a reliable correlation of dPCR absolute abundance units into metagenomic relative abundance units was not obtained here (r2 < 0.4) suggesting methodological factors that introduce variability. Evolutionary pressure does not significantly select the targeted ARGs in natural aquatic environments.

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.

Fresh produce as a reservoir of antimicrobial resistance genes: A case study of Switzerland

Antimicrobial resistance (AMR) can be transferred to humans through food and fresh produce can be an ideal vector as it is often consumed raw or minimally processed. The production environment of fresh produce and the agricultural practices and regulations can vary substantially worldwide, and consequently, the contamination sources of AMR. In this study, 75 imported and 75 non-imported fresh produce samples purchased from Swiss retailers were tested for the presence of antimicrobial resistant bacteria (ARB) and antimicrobial resistance genes (ARGs). Moreover, the plasmidome of 4 selected samples was sequenced to have an insight on the diversity of mobile resistome. In total, 91 ARB were isolated from fresh produce, mainly cephalosporin-resistant Enterobacterales (n = 64) and carbapenem-resistant P. aeruginosa (n = 13). All P. aeruginosa, as well as 16 Enterobacterales' isolates were multidrug-resistant. No differences between imported and Swiss fresh produce were found regarding the number of ARB. In 95 % of samples at least one ARG was detected, being the most frequent sul1, blaTEM, and ermB. Abundance of sul1 and intI1 correlated strongly with the total amount of ARGs, suggesting they could be good indicators for AMR in fresh produce. Furthermore, sul1 correlated with the fecal marker yccT, indicating that fecal contamination could be one of the sources of AMR. The gene sulI was significantly higher in most imported samples, suggesting higher anthropogenic contamination in the food production chain of imported produce. The analyses of the plasmidome of coriander and carrot samples revealed the presence of several ARGs as well as genes conferring resistance to antiseptics and disinfectants in mobile genetic elements. Overall, this study demonstrated that fresh produce contributes to the dissemination of ARGs and ARB.

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.

Candidate biomarkers of antibiotic resistance for the monitoring of wastewater and the downstream environment

Urban wastewater treatment plants (UWTPs) are essential for reducing the pollutants load and protecting water bodies. However, wastewater catchment areas and UWTPs emit continuously antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), with recognized impacts on the downstream environments. Recently, the European Commission recommended to monitor antibiotic resistance in UWTPs serving more than 100 000 population equivalents. Antibiotic resistance monitoring in environmental samples can be challenging. The expected complexity of these systems can jeopardize the interpretation capacity regarding, for instance, wastewater treatment efficiency, impacts of environmental contamination, or risks due to human exposure. Simplified monitoring frameworks will be essential for the successful implementation of analytical procedures, data analysis, and data sharing. This study aimed to test a set of biomarkers representative of ARG contamination, selected based on their frequent human association and, simultaneously, rare presence in pristine environments. In addition to the 16S rRNA gene, ten potential biomarkers (intI1, sul1, ermB, ermF, aph(3'')-Ib, qacEΔ1, uidA, mefC, tetX, and crAssphage) were monitored in DNA extracts (n = 116) from raw wastewater, activated sludge, treated wastewater, and surface water (upstream and downstream of UWTPs) samples collected in the Czech Republic, Denmark, Israel, the Netherlands, and Portugal. Each biomarker was sensitive enough to measure decreases (on average by up to 2.5 log-units gene copy/mL) from raw wastewater to surface water, with variations in the same order of magnitude as for the 16S rRNA gene. The use of the 10 biomarkers allowed the typing of water samples whose origin or quality could be predicted in a blind test. The results show that, based on appropriate biomarkers, qPCR can be used for a cost-effective and technically accessible approach to monitoring wastewater and the downstream environment.

Metagenomic surveillance uncovers diverse and novel viral taxa in febrile patients from Nigeria

Effective infectious disease surveillance in high-risk regions is critical for clinical care and pandemic preemption; however, few clinical diagnostics are available for the wide range of potential human pathogens. Here, we conduct unbiased metagenomic sequencing of 593 samples from febrile Nigerian patients collected in three settings: i) population-level surveillance of individuals presenting with symptoms consistent with Lassa Fever (LF); ii) real-time investigations of outbreaks with suspected infectious etiologies; and iii) undiagnosed clinically challenging cases. We identify 13 distinct viruses, including the second and third documented cases of human blood-associated dicistrovirus, and a highly divergent, unclassified dicistrovirus that we name human blood-associated dicistrovirus 2. We show that pegivirus C is a common co-infection in individuals with LF and is associated with lower Lassa viral loads and favorable outcomes. We help uncover the causes of three outbreaks as yellow fever virus, monkeypox virus, and a noninfectious cause, the latter ultimately determined to be pesticide poisoning. We demonstrate that a local, Nigerian-driven metagenomics response to complex public health scenarios generates accurate, real-time differential diagnoses, yielding insights that inform policy.