Background: Antibiotics and microplastics are two major aquatic pollutants that have been associated to antibiotic resistance selection in the environment and are considered a risk to human health. However, little is known about the interaction of these pollutants at environmental concentrations and the response of the microbial communities in the plastisphere to sub-lethal antibiotic pollution. Here, we describe the bacterial dynamics underlying this response in surface water bacteria at the community, resistome and mobilome level using a combination of methods (next-generation sequencing and qPCR), sequencing targets (16S rRNA gene, pre-clinical and clinical class 1 integron cassettes and metagenomes), technologies (short and long read sequencing), and assembly approaches (non-assembled reads, genome assembly, bacteriophage and plasmid assembly). Results: Our results show a shift in the microbial community response to antibiotics in the plastisphere microbiome compared to surface water communities and describe the bacterial subpopulations that respond differently to antibiotic and microplastic pollution. The plastisphere showed an increased tolerance to antibiotics and selected different antibiotic resistance bacteria (ARB) and antibiotic resistance genes (ARGs). Several metagenome assembled genomes (MAGs) derived from the antibiotic-exposed plastisphere contained ARGs, virulence factors, and genes involved in plasmid conjugation. These include Comamonas, Chryseobacterium, the opportunistic pathogen Stenotrophomonas maltophilia, and other MAGs belonging to genera that have been associated to human infections, such as Achromobacter. The abundance of the integron-associated ciprofloxacin resistance gene aac(6’)-Ib-cr increased under ciprofloxacin exposure in both freshwater microbial communities and in the plastisphere. Regarding the antibiotic mobilome, although no significant changes in ARG load in class 1 integrons and plasmids were observed in polluted samples, we identified three ARG-containing viral contigs that were integrated into MAGs as prophages. Conclusions: This study illustrates how the selective nature of the plastisphere influences bacterial response to antibiotics at sub-lethal selective pressure. The microbial changes identified here help define the selective role of the plastisphere and its impact on the maintenance of environmental antibiotic resistance in combination with other anthropogenic pollutants. This research highlights the need to evaluate the impact of aquatic pollutants in environmental microbial communities using complex scenarios with combined stresses.

Antibiotics released into the environment at low (sub-inhibitory) concentrations could select for antibiotic resistance that might disseminate to the human microbiome. In this case, low-level anthropogenic sources of antibiotics would have a significant impact on human health risk. In order to provide data necessary for the evaluation of this risk, we implemented river water microcosms at both sub-inhibitory and inhibitory concentrations of gentamicin as determined previously based on bacterial growth in enriched media. Using metagenomic sequencing and qPCR/RT-qPCR, we assessed the effects of gentamicin on water bacterial communities and their resistome. A change in the composition of total and active communities, as well as a gentamicin resistance gene selection identified via mobile genetic elements, was observed during a two-day exposure. We demonstrated the effects of sub-inhibitory concentrations of gentamicin on bacterial communities and their associated resistome in microcosms (simulating in situ conditions). In addition, we established relationships between antibiotic dose and the magnitude of the community response in the environment. The scope of resistance selection under sub-inhibitory concentrations of antibiotics and the mechanisms underlying this process might provide the basis for understanding resistance dispersion and associated risks in relatively low impacted ecosystems.

Freshwater pollution with compounds used during anthropogenic activities could be a major driver of antibiotic resistance emergence and dissemination in environmental settings. Fluoroquinolones and heavy metals are two widely used aquatic pollutants that show a high stability in the environment and have well-known effects on antibiotic resistance selection. However, the impact of these compounds on antibiotic resistance maintenance in aquatic ecosystems remains unknown. In this study, we used a microcosm approach to determine the persistence of two fluoroquinolones (ciprofloxacin, ofloxacin) and two heavy metals (copper and zinc) in the Rhône river over 27 days. In addition, we established links between antibiotic and metal pollution, alone and in combination, and the composition of freshwater bacterial communities, the selection of specific members and the selection and maintenance of antibiotic and metal resistance genes (ARGs and MRGs) using a metagenomics approach. Whereas ofloxacin was detected at higher levels in freshwater after 27 days, copper had the strongest influence on bacterial communities and antibiotic and metal resistance gene selection. In addition, heavy metal exposure selected for some ARG-harboring bacteria that contained MRGs. Our research shows a heavy metal-driven transient co-selection for fluoroquinolone resistance in an aquatic ecosystem that could be largely explained by the short-term selection of Pseudomonas subpopulations harboring both fluoroquinolone efflux pumps and copper resistance genes. This research highlights the complexity and compound-specificity of dose-response relationships in freshwater ecosystems and provides new insights into the medium-term community structure modifications induced by overall sub-inhibitory levels of antibiotic and heavy metal pollution that may lead to the selection and maintenance of antibiotic resistance in low-impacted ecosystems exposed to multiple pollutants.

Antibiotics at sub-inhibitory concentrations are often found in the environment. Here they could impose selective pressure on bacteria, leading to the selection and dissemination of antibiotic resistance, despite being under the inhibitory threshold. The goal of this study was to evaluate the effects of sub-inhibitory concentrations of gentamicin on environmental class 1 integron cassettes in natural river microbial communities. Gentamicin at sub-inhibitory concentrations promoted the integration and selection of gentamicin resistance genes (GmRG) in class 1 integrons after only a one-day exposure. Therefore, sub-inhibitory concentrations of gentamicin induced integron rearrangements, increasing the mobilization potential of gentamicin resistance genes and potentially increasing their dissemination in the environment. This study demonstrates the effects of antibiotics at sub-inhibitory concentrations in the environment and supports concerns about antibiotics as emerging pollutants.

Although Next-Generation Sequencing techniques have increased our access to the soil microbiome, each step of soil metagenomics presents inherent biases that prevent the accurate definition of the soil microbiome and its ecosystem function. In this study, we compared the effects of DNA extraction and sequencing depth on bacterial richness discovery from two soil samples. Four DNA extraction methods were used, and sequencing duplicates were generated for each DNA sample. The V3–V4 region of the 16S rRNA gene was sequenced to determine the taxonomical richness measured by each method at the amplicon sequence variant (ASV) level. Both the overall functional richness and antibiotic resistance gene (ARG) richness were evaluated by metagenomics sequencing. Despite variable DNA extraction methods, sequencing depth had a greater influence on bacterial richness discovery at both the taxonomical and functional levels. Sequencing duplicates from the same sample provided access to different portions of bacterial richness, and this was related to differences in the sequencing depth. Thus, the sequencing depth introduced biases in the comparison of DNA extraction methods. An optimisation of the soil metagenomics workflow is needed in order to sequence at a sufficient and equal depth. This would improve the accuracy of metagenomic comparisons and soil microbiome profiles.