Kreft, J. | bioRxiv Science

bioRxiv2022

Plasmid Permissiveness of Wastewater Microbiomes can be Predicted from 16S rDNA sequences by Machine Learning

Wastewater Treatment Plants (WWTPs) contain a diverse microbial community with high cell density. They constantly receive antimicrobial residues and resistant strains and, therefore, may offer conditions for the Horizontal Gene Transfer (HGT) of antimicrobial resistance determinants, transmitting clinically important genes between, e.g., enteric and environmental bacteria and vice versa. Despite the clinical importance, tools for predicting HGT are still under-developed. In this study, we examined to which extent microbial community composition, as inferred by partial 16S rRNA gene sequences, can predict plasmid permissiveness, i.e., the ability of cells to receive a plasmid through conjugation, for microbial communities in the water cycle, using data from standardized filter mating assays using fluorescent bio-reporter plasmids. We leveraged a range of machine learning models for predicting the permissiveness for each taxon in the community, translating to the range of hosts a plasmid is able to transfer to, for three broad host-range resistance plasmids (pKJK5, pB10, and RP4). Our results indicate that the predicted permissiveness from the best performing model (random forest) showed a moderate-to-strong average correlation of 0.45 for pB10 (95% CI: 0.42-0.52), 0.42 for pKJK5 (0.95% CI: 0.38-0.45) and 0.52 for RP4 (0.95% CI:0.45-0.55) with the experimental permissiveness in the unseen test dataset. Predictive phylogenetic signals occurred despite these being broad host-range plasmids. Our results provide a framework that contributes to assessing the risk of AMR pollution in wastewater systems. The predictive tool is available as a an application under https://github.com/DaneshMoradigaravand/PlasmidPerm.

bioinformatics↗

bioRxiv2020

Experimental Evolution of Pseudomonas putida under Silver Ion versus Nanoparticle Stress

Whether the antibacterial properties of silver nanoparticles (AgNPs) are simply due to the release of silver ions (Ag+) or, additionally, nanoparticle-specific effects, has been debated for over a decade. We used experimental evolution of the model environmental bacterium Pseudomonas putida to ask whether bacteria respond differently to Ag+ or AgNP treatment. We pre-evolved five cultures of strain KT2440 for 70 d without Ag to reduce confounding adaptations before dividing the fittest pre-evolved culture into five cultures each, evolving in the presence of low concentrations of Ag+, well-defined AgNPs or Ag-free controls for a further 75 d. The mutations in the Ag+ or AgNP evolved populations displayed different patterns that were statistically significant. The non-synonymous mutations in AgNP-treated populations were mostly associated with cell surface proteins, including cytoskeletal membrane protein (FtsZ), membrane sensor and regulator (EnvZ and GacS) and periplasmic protein (PP_2758). In contrast, Ag+ treatment selected for mutations linked to cytoplasmic proteins, including metal ion transporter (TauB) and those with metal binding domains (ThiL and PP_2397). These results suggest the existence of AgNP-specific effects, either caused by sustained delivery of Ag+ from AgNP-dissolution, more proximate delivery from cell-surface bound AgNPs, or by direct AgNP action on the cells outer membrane. Originality-Significance StatementThe increasing use of silver nanoparticles (AgNPs) and their release into the environment may affect environmental microorganisms and their communities and evolution. It has long been debated whether the toxicity of AgNPs towards microorganisms is solely due to their dissolution into toxic Ag+ or whether distinct nanoparticle related toxicity exists. We set up an evolution experiment to explore the adaptation of the environmental model bacterium Pseudomonas putida to Ag+ versus AgNP stress in order to elucidate the potentially different toxicity mechanisms of ionic and nanoparticulate Ag. We found novel mutations and distinct mutation patterns under Ag+ and AgNP treatment by whole genome sequencing. Our work highlights the association of the mutations selected by Ag+ stress with metal ion metabolism inside the cells and the mutations specific to AgNP stress with the cells surface. The finding that P. putida cells evolved in different directions under selection by Ag+ and AgNPs demonstrates a need for assessing the toxicity of nanomaterials separately in any environmental risk assessments.

pharmacology and toxicology↗