Environmental microbiome diversity and stability is a barrier to antimicrobial resistance gene accumulation.

When antimicrobial resistant bacteria (ARB) and genes (ARGs) reach novel habitats, they can become part of the habitat's microbiome in the long term if they are able to overcome the habitat's biotic resilience towards immigration. This process should become more difficult with increasing biodiversity, as exploitable niches in a given habitat are reduced for immigrants when more diverse competitors are present. Consequently, microbial diversity could provide a natural barrier towards antimicrobial resistance by reducing the persistence time of immigrating ARB and ARG. To test this hypothesis, a pan-European sampling campaign was performed for structured forest soil and dynamic riverbed environments of low anthropogenic impact. In soils, higher diversity, evenness and richness were significantly negatively correlated with relative abundance of >85% of ARGs. Furthermore, the number of detected ARGs per sample were inversely correlated with diversity. However, no such effects were present in the more dynamic riverbeds. Hence, microbiome diversity can serve as a barrier towards antimicrobial resistance dissemination in stationary, structured environments, where long-term, diversity-based resilience against immigration can evolve.

Contrary effects of increasing temperatures on the spread of antimicrobial resistance in river biofilms.

River microbial communities regularly act as the first barrier of defense against the spread of antimicrobial resistance genes (ARGs) that enter environmental microbiomes through wastewater. However, how the invasion dynamics of wastewater-borne ARGs into river biofilm communities will shift due to climate change with increasing average and peak temperatures remains unknown. Here, we aimed to elucidate the effects of increasing temperatures on the naturally occurring river biofilm resistome, as well as the invasion success of foreign ARGs entering through wastewater. Natural biofilms were grown in a low-anthropogenic impact river and transferred to artificial laboratory recirculation flume systems operated at three different temperatures (20°C, 25°C, and 30°C). After 1 week of temperature acclimatization, significant increases in the abundance of the naturally occurring ARGs in biofilms were detected at higher temperatures. After this acclimatization period, biofilms were exposed to a single pulse of wastewater, and the invasion dynamics of wastewater-borne ARGs were analyzed over 2 weeks. After 1 day, wastewater-borne ARGs were able to invade the biofilms successfully with no observable effect of temperature on their relative abundance. However, thereafter, ARGs were lost at a far increased rate at 30°C, with ARG levels dropping to the initial natural levels after 14 days. Contrary to the lower temperatures, ARGs were either lost at slower rates or even able to establish themselves in biofilms with stable relative abundances above natural levels. Hence, higher temperatures come with contrary effects on river biofilm resistomes: naturally occurring ARGs increase in abundance, while foreign, invading ARGs are lost at elevated speeds.IMPORTANCEInfections with bacteria that gained resistance to antibiotics are taking millions of lives annually, with the death toll predicted to increase. River microbial communities act as a first defense barrier against the spread of antimicrobial resistance genes (ARGs) that enter the environment through wastewater after enrichment in human and animal microbiomes. The global increase in temperature due to climate change might disrupt this barrier effect by altering microbial community structure and functions. We consequently explored how increasing temperatures alter ARG spread in river microbial communities. At higher temperatures, naturally occurring ARGs increased in relative abundance. However, this coincided with a decreased success rate of invading foreign ARGs from wastewater to establish themselves in the communities. Therefore, to predict the effects of climate change on ARG spread in river microbiomes, it is imperative to consider if the river ecosystem and its resistome are dominated by naturally occurring or invading foreign ARGs.

Trimethoprim resistance in surface and wastewater is mediated by contrasting variants of the dfrB gene.

Trimethoprim (TMP) is a low-cost, widely prescribed antibiotic. Its effectiveness is increasingly challenged by the spread of genes coding for TMP-resistant dihydrofolate reductases: dfrA, and the lesser-known, evolutionarily unrelated dfrB. Despite recent reports of novel variants conferring high level TMP resistance (dfrB10 to dfrB21), the prevalence of dfrB is still unknown due to underreporting, heterogeneity of the analyzed genetic material in terms of isolation sources, and limited bioinformatic processing. In this study, we explored a coherent set of shotgun metagenomic sequences to quantitatively estimate the abundance of dfrB gene variants in aquatic environments. Specifically, we scanned sequences originating from influents and effluents of municipal sewage treatment plants as well as river-borne microbiomes. Our analyses reveal an increased prevalence of dfrB1, dfrB2, dfrB3, dfrB4, dfrB5, and dfrB7 in wastewater microbiomes as compared to freshwater. These gene variants were frequently found in genomic neighborship with other resistance genes, transposable elements, and integrons, indicating their mobility. By contrast, the relative abundances of the more recently discovered variants dfrB9, dfrB10, and dfrB13 were significantly higher in freshwater than in wastewater microbiomes. Moreover, their direct neighborship with other resistance genes or markers of mobile genetic elements was significantly less likely. Our findings suggest that natural freshwater communities form a major reservoir of the recently discovered dfrB gene variants. Their proliferation and mobilization in response to the exposure of freshwater communities to selective TMP concentrations may promote the prevalence of high-level TMP resistance and thus limit the future effectiveness of antimicrobial therapies.

Quantification of the mobility potential of antibiotic resistance genes through multiplexed ddPCR linkage analysis.

There is a clear need for global monitoring initiatives to evaluate the risks of antibiotic resistance genes (ARGs) towards human health. Therefore, not only ARG abundances within a given environment, but also their potential mobility, hence their ability to spread to human pathogenic bacteria needs to be quantified. We developed a novel, sequencing-independent method for assessing the linkage of an ARG to a mobile genetic element by statistical analysis of multiplexed droplet digital PCR (ddPCR) carried out on environmental DNA sheared into defined, short fragments. This allows quantifying the physical linkage between specific ARGs and mobile genetic elements, here demonstrated for the sulfonamide ARG sul1 and the Class 1 integron integrase gene intI1. The method's efficiency is demonstrated using mixtures of model DNA fragments with either linked and unlinked target genes: Linkage of the two target genes can be accurately quantified based on high correlation coefficients between observed and expected values (R2) as well as low mean absolute errors (MAE) for both target genes, sul1 (R2 = 0.9997, MAE = 0.71%, n = 24) and intI1 (R2 = 0.9991, MAE = 1.14%, n = 24). Furthermore, we demonstrate that adjusting the fragmentation length of DNA during shearing allows controlling rates of false positives and false negative detection of linkage. The presented method allows rapidly obtaining reliable results in a labor- and cost-efficient manner.

Shifts from cooperative to individual-based predation defense determine microbial predator-prey dynamics.

Predation defense is an important feature of predator-prey interactions adding complexity to ecosystem dynamics. Prey organisms have developed various strategies to escape predation which differ in mode (elude vs. attack), reversibility (inducible vs. permanent), and scope (individual vs. cooperative defenses). While the mechanisms and controls of many singular defenses are well understood, important ecological and evolutionary facets impacting long-term predator-prey dynamics remain underexplored. This pertains especially to trade-offs and interactions between alternative defenses occurring in prey populations evolving under predation pressure. Here, we explored the dynamics of a microbial predator-prey system consisting of bacterivorous flagellates (Poteriospumella lacustris) feeding on Pseudomonas putida. Within five weeks of co-cultivation corresponding to about 35 predator generations, we observed a consistent succession of bacterial defenses in all replicates (n = 16). Initially, bacteria expressed a highly effective cooperative defense based on toxic metabolites, which brought predators close to extinction. This initial strategy, however, was consistently superseded by a second mechanism of predation defense emerging via de novo mutations. Combining experiments with mathematical modeling, we demonstrate how this succession of defenses is driven by the maximization of individual rather than population benefits, highlighting the role of rapid evolution in the breakdown of social cooperation.

Evaluating the sensitivity of droplet digital PCR for the quantification of SARS-CoV-2 in wastewater.

Wastewater surveillance for SARS-CoV-2 has been demonstrated to be a valuable tool in monitoring community-level virus circulation and assessing new outbreaks. It may become a useful tool in the early detection and response to future pandemics, enabling public health authorities to implement timely interventions and mitigate the spread of infectious diseases with the fecal excretion of their agents. It also offers a chance for cost-effective surveillance. Reverse transcription-quantitative polymerase chain reaction (RTqPCR) is the most commonly used method for viral RNA detection in wastewater due to its sensitivity, reliability, and widespread availability. However, recent studies have indicated that reverse transcription droplet digital PCR (RTddPCR) has the potential to offer improved sensitivity and accuracy for quantifying SARS-CoV-2 RNA in wastewater samples. In this study, we compared the performance of RTqPCR and RTddPCR approaches for SARS-CoV-2 detection and quantification on wastewater samples collected during the third epidemic wave in Saxony, Germany, characterized by low-incidence infection periods. The determined limits of detection (LOD) and quantification (LOQ) were within the same order of magnitude, and no significant differences were observed between the PCR approaches with respect to the number of positive or quantifiable samples. Our results indicate that both RTqPCR and RTddPCR are highly sensitive methods for detecting SARS-CoV-2. Consequently, the actual gain in sensitivity associated with ddPCR lags behind theoretical expectations. Hence, the choice between the two PCR methods in further environmental surveillance programs is rather a matter of available resources and throughput requirements.

Antibiotic Resistance Genes in River Biofilms: A Metagenomic Approach toward the Identification of Sources and Candidate Hosts.

Treated wastewater is a major pathway by which antibiotic resistance genes (ARG) enter aquatic ecosystems. However, knowledge gaps remain concerning the dissemination of specific ARG and their association with bacterial hosts. Here, we employed shotgun metagenomics to track ARG and taxonomic markers in river biofilms along a gradient of fecal pollution depicted by crAssphage signatures. We found strong evidence for an impact of wastewater effluents on both community composition and resistomes. In the light of such simultaneity, we employed a model comparison technique to identify ARG-host relationships from nonassembled metagenomic DNA. Hereby, a major cause of spurious associations otherwise encountered in correlation-based ARG-host analyses was suppressed. For several families of ARG, namely those conferring resistance to beta-lactams, particular bacterial orders were identified as candidate hosts. The found associations of blaFOX and cphA with Aeromonadales or blaPER with Chromatiales support the outcome of independent evolutionary analyses and thus confirm the potential of the methodology. For other ARG families including blaIMP or tet, clusters of bacterial orders were identified which potentially harbor a major proportion of host species. For yet other ARG, like, for example, ant or erm, no particular host candidates were identifiable, indicating their spread across various taxonomic groups.

Multiwalled Carbon Nanotubes Promote Bacterial Conjugative Plasmid Transfer.

Multiwalled carbon nanotubes (MWCNTs) regularly enter aquatic environments due to their ubiquity in consumer products and engineering applications. However, the effects of MWCNT pollution on the environmental microbiome are poorly understood. Here, we evaluated whether these carbon nanoparticles can elevate the spread of antimicrobial resistance by promoting bacterial plasmid transfer, which has previously been observed for copper nanomaterials with antimicrobial properties as well as for microplastics. Through a combination of experimental liquid mating assays between Pseudomonas putida donor and recipient strains with plasmid pKJK5::gfpmut3b and mathematical modeling, we here demonstrate that the presence of MWCNTs leads to increased plasmid transfer rates in a concentration-dependent manner. The percentage of transconjugants per recipient significantly increased from 0.21 ± 0.04% in absence to 0.41 ± 0.09% at 10 mg L-1 MWCNTs. Similar trends were observed when using an Escherichia coli donor hosting plasmid pB10. The identified mechanism underlying the observed dynamics was the agglomeration of MWCNTs. A significantly increased number of particles with >6 µm diameter was detected in the presence of MWCNTs, which can in turn provide novel surfaces for bacterial interactions between donor and recipient cells after colonization. Fluorescence microscopy confirmed that MWCNT agglomerates were indeed covered in biofilms that contained donor bacteria as well as elevated numbers of green fluorescent transconjugant cells containing the plasmid. Consequently, MWCNTs provide bacteria with novel surfaces for intense cell-to-cell interactions in biofilms and can promote bacterial plasmid transfer, hence potentially elevating the spread of antimicrobial resistance. IMPORTANCE In recent decades, the use of carbon nanoparticles, especially multiwalled carbon nanotubes (MWCNTs), in a variety of products and engineering applications has been growing exponentially. As a result, MWCNT pollution into environmental compartments has been increasing. We here demonstrate that the exposure to MWCNTs can affect bacterial plasmid transfer rates in aquatic environments, an important process connected to the spread of antimicrobial resistance genes in microbial communities. This is mechanistically explained by the ability of MWCNTs to form bigger agglomerates, hence providing novel surfaces for bacterial interactions. Consequently, increasing pollution with MWCNTs has the potential to elevate the ongoing spread of antimicrobial resistance, a major threat to human health in the 21st century.

The spread of the plasmid RP4 in a synthetic bacterial community is dependent on the particular donor strain.

The rapid spread of antibiotic resistance challenges modern medicine. So far, mechanistic and quantitative knowledge concerning the spread of resistance genes mainly relies on laboratory experiments with simplified setups, e.g. two strain communities. Thus, the transferability of the obtained process rates might be limited. To investigate the role of a diverse community concerning the dissemination of the multidrug resistance plasmid RP4, an Escherichia coli harboring RP4 invaded a microbial community consisting of 21 species. Changes in the community composition as well as plasmid uptake by community members were monitored for 22 days. Special focus was laid on the question of whether the observed changes were dependent on the actual invading donor isolate and the ambient antibiotic concentration. In our microcosm experiment, the community composition was primarily influenced by the given environmental variables and only secondarily by the particular invader E. coli. The establishment of resistance within the community, however, was directly dependent on the donor identity. The extent to which ambient conditions influence the spread of RP4 depended on the E. coli donor strain. These results emphasize that even within one species there are great differences in the ability to conquer an ecological niche and to spread antibiotic resistance.

Simultaneous estimation of parameters governing the vertical and horizontal transfer of antibiotic resistance genes.

The accelerated spread of antibiotic resistance genes (ARG) in the environment occurs mainly through plasmid transfer facilitated via bacterial conjugation. To predict and efficiently counteract the problems associated with ARG transmission, it is important to estimate conjugation rates under different experimental conditions. The classical models typically used to estimate parameters for mating experiments, while pragmatic in calculating growth and plasmid transfer, often ignore processes such as the reduction in growth due to plasmid bearing costs and are non-inclusive of environmental influences like temperature effects. Here, we present a process-based numerical model taking into account the fitness cost associated with plasmid carriage and temperature dependencies in vertical and horizontal gene transfer processes. Observations from liquid culture conjugation experiments using Escherichia coli and the plasmid pB10 were used to validate our proposed model. We present a comparison between the parameters estimated using the existing and the proposed model. Uncertainties in the estimated parameters were quantified using classical and advanced Bayesian methods. For our mating experiments, we found that at temperatures between 20 and 37 °C, the plasmid bearing costs reduced the growth rates by > 35%. The temperature dependency model of conjugation showed a good fit (mean absolute percentage error < 10%) independent of the bacteria and the plasmid under study. The proposed model simultaneously estimates growth and plasmid transfer rate constants for all three strains (donor, recipient, and transconjugant). Simultaneous estimation of growth and conjugation parameters is particularly useful to estimate the spread of ARG when one of the mating partners inhibits the growth of the other, which is common in multi-species mating or when the incurred plasmid costs are situation dependent (e.g., increased plasmid cost in a mating environment) as observed in this study.

High variability of plasmid uptake rates in Escherichia coli isolated from sewage and river sediments.

The horizontal transfer of plasmids is a key mechanism behind the spread of antibiotic resistance in bacteria. So far, transfer rate constants were measured for a variety of plasmids, donors and recipients. The employed strains typically had a long history in laboratories. Existing data are, therefore, not necessarily representative for real-world environments. Moreover, information on the inter-strain variability of plasmid transfer rates is scarce. Using a high-throughput approach, we studied the uptake of RP4 by various Escherichia coli recipients using Serratia marcescens as the donor. The recipient strains were isolated from human-borne sewage and river sediments. The rate constants of plasmid transfer generally followed a log-normal distribution with considerable variance. The rate constants for good and poor recipients (95 and 5% quantile) differed by more than three orders of magnitude. Specifically, the inter-strain variability of the rate constant was large in comparison to alterations induced by low-level antibiotic exposure. We did not find evidence for diverging efficiencies of plasmid uptake between E. coli recipients of different origin. On average, strains isolated from river bottom sediments were equally efficient in the acquisition of RP4 as isolates extracted from sewage. We conclude that E. coli strains persisting in the aquatic environment and those of direct human origin share a similar intrinsic potential for the conjugative uptake of certain plasmids. In view of the large inter-strain variability, we propose to work towards probabilistic modeling of the environmental spread of antibiotic resistance.

Sewage from Airplanes Exhibits High Abundance and Diversity of Antibiotic Resistance Genes.

Airplane sanitary facilities are shared by an international audience. We hypothesized the corresponding sewage to be an extraordinary source of antibiotic-resistant bacteria (ARB) and resistance genes (ARG) in terms of diversity and quantity. Accordingly, we analyzed ARG and ARB in airplane-borne sewage using complementary approaches: metagenomics, quantitative polymerase chain reaction (qPCR), and cultivation. For the purpose of comparison, we also quantified ARG and ARB in the inlets of municipal treatment plants with and without connection to airports. As expected, airplane sewage contained an extraordinarily rich set of mobile ARG, and the relative abundances of genes were mostly increased compared to typical raw sewage of municipal origin. Moreover, combined resistance against third-generation cephalosporins, fluorochinolones, and aminoglycosides was unusually common (28.9%) among Escherichia coli isolated from airplane sewage. This percentage exceeds the one reported for German clinical isolates by a factor of 8. Our findings suggest that airplane-borne sewage can effectively contribute to the fast and global spread of antibiotic resistance.

Optimum positioning of wastewater treatment plants in a river network: A model-based approach to minimize microbial pollution.

Microbial pollution in river networks is widespread, threatening human health and activities. Wastewater treatment plants are a major source of microbial pollution that affects downstream communities. We propose a simple modeling approach to identify possible hot-spots of microbial pollution in river networks receiving treated wastewater. We consider every reach in a river network as a potential site for the disposal of treated wastewater and we identify the corresponding section of the downstream river where the concentration of indicator bacteria exceeds a prescribed threshold value. In this paper, we introduce the methodology and demonstrate its application to a small river basin (Lockwitzbach, Germany). We computed the lengths of the polluted river sections for different scenarios in order to separately identify the impacts of hydrological boundary conditions and bacterial retention processes. Effective parameters describing bacterial retention were inferred from field samples. The proposed modeling approach can be used to generate dynamic maps of safe and vulnerable zones in a river network. Our approach helps disentangle the effects of network structure, hydrological variability and in-stream processes on the location and length of unsafe river sections. Our model can be used to identify optimal sites for the discharge of treated wastewater. For example, in the Lockwitzbach basin, we show that relocating the existing effluent discharge could reduce the stream length affected by severe microbial pollution by almost 30%.

High prevalence of colistin resistance genes in German municipal wastewater.

Bacterial resistance against the last-resort antibiotic colistin is of increasing concern on a global scale. Wastewater is suspected to be one of the pathways by which resistant bacteria and the respective genes are disseminated. We employed a metagenomics approach to detect and quantify colistin resistance genes in raw municipal wastewater sampled at 9 locations all over Germany (14 samples in total, collected in 2016/2017). Our data support the findings of earlier studies according to which the prevalence of the colistin resistance gene mcr-1 is still low. However, we were able to demonstrate that the total prevalence of colistin resistance genes is dramatically underestimated if the focus is put on that specific gene alone. In comparison to mcr-1, other gene variants like mcr-3 and mcr-7 proved to be 10 to 100 times more abundant in samples of untreated wastewater. The average relative abundances expressed as copies per 16S rRNA gene copies were 2.3×10-3 for mcr-3, 2.2×10-4 for mcr-4, 3.0×10-4 for mcr-5, and 4.4×10-4 for mcr-7. While these four gene variants were ubiquitous in all 14 samples, mcr-1 was detected only once at a relative abundance of 1.4×10-5. Our results suggest a high risk of increasing incidence of colistin resistance as large amounts of mcr genes are continuously disseminated to diverse microbial communities via the wastewater path.

Antibiotic resistance genes in treated wastewater and in the receiving water bodies: A pan-European survey of urban settings.

There is increasing public concern regarding the fate of antibiotic resistance genes (ARGs) during wastewater treatment, their persistence during the treatment process and their potential impacts on the receiving water bodies. In this study, we used quantitative PCR (qPCR) to determine the abundance of nine ARGs and a class 1 integron associated integrase gene in 16 wastewater treatment plant (WWTP) effluents from ten different European countries. In order to assess the impact on the receiving water bodies, gene abundances in the latter were also analysed. Six out of the nine ARGs analysed were detected in all effluent and river water samples. Among the quantified genes, intI1 and sul1 were the most abundant. Our results demonstrate that European WWTP contribute to the enrichment of the resistome in the receiving water bodies with the particular impact being dependent on the effluent load and local hydrological conditions. The ARGs concentrations in WWTP effluents were found to be inversely correlated to the number of implemented biological treatment steps, indicating a possible option for WWTP management. Furthermore, this study has identified blaOXA-58 as a possible resistance gene for future studies investigating the impact of WWTPs on their receiving water.

Antibiotic resistance in European wastewater treatment plants mirrors the pattern of clinical antibiotic resistance prevalence.

Integrated antibiotic resistance (AR) surveillance is one of the objectives of the World Health Organization global action plan on antimicrobial resistance. Urban wastewater treatment plants (UWTPs) are among the most important receptors and sources of environmental AR. On the basis of the consistent observation of an increasing north-to-south clinical AR prevalence in Europe, this study compared the influent and final effluent of 12 UWTPs located in seven countries (Portugal, Spain, Ireland, Cyprus, Germany, Finland, and Norway). Using highly parallel quantitative polymerase chain reaction, we analyzed 229 resistance genes and 25 mobile genetic elements. This first trans-Europe surveillance showed that UWTP AR profiles mirror the AR gradient observed in clinics. Antibiotic use, environmental temperature, and UWTP size were important factors related with resistance persistence and spread in the environment. These results highlight the need to implement regular surveillance and control measures, which may need to be appropriate for the geographic regions.

A high-throughput approach to the culture-based estimation of plasmid transfer rates.

Horizontal gene transfer is an essential component of bacterial evolution. Quantitative information on transfer rates is particularly useful to better understand and possibly predict the spread of antimicrobial resistance. A variety of methods has been proposed to estimate the rates of plasmid-mediated gene transfer all of which require substantial labor input or financial resources. A cheap but reliable method with high-throughput capabilities is yet to be developed in order to better capture the variability of plasmid transfer rates, e.g. among strains or in response to environmental cues. We explored a new approach to the culture-based estimation of plasmid transfer rates in liquid media allowing for a large number of parallel experiments. It deviates from established approaches in the fact that it exploits data on the absence/presence of transconjugant cells in the wells of a well plate observed over time. Specifically, the binary observations are compared to the probability of transconjugant detection as predicted by a dynamic model. The bulk transfer rate is found as the best-fit value of a designated model parameter. The feasibility of the approach is demonstrated on mating experiments where the RP4 plasmid is transfered from Serratia marcescens to several Escherichia coli recipients. The method's uncertainty is explored via split sampling and virtual experiments.