Can microplastics and disinfectant resistance genes pose conceivable threats to water disinfection process?

Microplastic pollution in the environment has aroused widespread concerns, however, the potential environmental risks caused by excessive use of disinfectants are still unknown. Disinfectants with doses below the threshold can enhance the communication of resistance genes in pathogenic microorganisms, promoting the development and spread of antimicrobial activity. Problematically, the intensification of microplastic pollution and the increase of disinfectant consumption will become a key driving force for the growth of disinfectant resistance bacteria (DRB) and disinfectant resistance genes (DRGs) in the environment. Disinfection plays a crucial role in ensuring water safety, however, the presence of microplastics and DRGs seriously disturb the water disinfection process. Microplastics can reduce the concentration of disinfectant in the local environment around microorganisms and improve their tolerance. Microorganisms can improve their resistance to disinfectants or generate resistance genes via phenotypic adaptation, gene mutations, and horizontal gene transfer. However, very limited information is available on the impact of DRB and DRGs on disinfection process. In this paper, the contribution of microplastics to the migration and transmission of DRGs was analyzed. The challenges posed by the presence of microplastics and DRGs on conventional disinfection were thoroughly discussed. The knowledge gaps faced by relevant current research and further research priorities have been proposed in order to provide a scientific basis in the future.

Building of soft-hard compound brush in porous PVA/NH2@TAtZnO plural gel and the high-efficiency anti-interference removal on Pb(II).

In order to promote the heavy metal ions removal of porous gel adsorbent and protect the adsorbent from other pollutants in wastewater, the tetrapod ZnO whiskers (tZnO) modified by amino-chain brush was introduced into the polyvinyl alcohol (PVA) matrix to prepare the PVA/NH2@TAtZnO composites with brush structure for toxic Pb(II) removal. The adsorption property, adsorption process and adsorption mechanism were studied by adsorption isotherms, adsorption kinetics, adsorption thermodynamics, SEM-EDS analysis and XPS analysis. And the anti-interference ability and anti-interference mechanism were researched by SEM-EDS analysis and XPS analysis. It was found that the PVA/NH2@TAtZnO composites displayed a soft-hard compound pore-brush structure and showed a good selective adsorption on Pb(II). The research of isotherms and kinetics indicated that the adsorption process was fitted well to Langmuir model and pseudo-second-order model, respectively, and the research of thermodynamics revealed the endothermic nature. The adsorption mechanism was inferred as the combination of predominant chemisorption and subsidiary physisorption. Comparing with the neat PVA matrix, the PVA/NH2@TAtZnO composites displayed a good anti-interference property on Pb(II) adsorption and showed an alleviative clogging pore-canal structure in the wastewater with SiO2 NPs or PAC flocculants. The anti-interference intensity ΔQ and anti-interference factor χ were proposed to reflect the anti-interference ability of this adsorbent which was promoted with the increasing amino brush length or density. By the analysis of SEM-EDS and XPS, the anti-interference mechanism was explored as the steric-hinerance effect of tZnO hard brush to suspended SiO2 NPs pollutant and the coordination effect of functional amino soft brush to soluble PAC pollutant. Besides, the prepared PVA/NH2@TAtZnO adsorbent possessed a good reusability under multiple adsorption-desorption processes and also presented a well applicability in real water matrix. The research indicated the huge potential of prepared PVA/NH2@TAtZnO adsorbent in heavy metal ions removal.

Disrupted metabolic pathways and potential human diseases induced by bisphenol S.

Although the toxicity of bisphenol S has been studied in some species, the global metabolic network disrupted by bisphenol S remains unclear. To this end, published datasets related to the genes, proteins, and metabolites disturbed by bisphenol S were investigated through omics methods. The dataset revealed that bisphenol S at high concentrations tended to downregulate biomolecules, while low concentrations of bisphenol S tended to enhance metabolic reactions. The results showed that exposure to bisphenol S upregulated estrogen and downregulated androgen metabolism in humans, mice, rats, and zebrafish. Fatty acid metabolism and phospholipid metabolism in mice were upregulated. Reactions in amino acid metabolism were upregulated, with the exception of the suppressive conversion of arginine to ornithine. In zebrafish, fatty acid synthesis was promoted, while nucleotide metabolism was primarily depressed through the downregulation of pyruvate 2-o-phosphotransferase. The interference in amino acid metabolism by bisphenol S could trigger Alzheimer's disease, while its disturbance of glucose metabolism was associated with type II diabetes. Disturbed glycolipid metabolism and vitamin metabolism could induce Alzheimer's disease and diabetes. These findings based on omics data provide scientific insight into the metabolic network regulated by bisphenol S and the diseases triggered by its metabolic disruption.

The Significance of Nonlinear Screening and the pH Interference Mechanism in Field-Effect Transistor Molecular Sensors.

Electrolyte screening is well known for its detrimental impact on the sensitivity of liquid-gated field-effect transistor (FET) molecular sensors and is mostly described by the linearized Debye-Hückel model. However, charged and pH-sensitive FET sensing surfaces can limit the FET molecular sensitivity beyond the Debye-Hückel screening formalism. Pre-existing surface charges can lead to the breakdown of Debye-Hückel screening and induce enhanced nonlinear Poisson-Boltzmann screening. Moreover, the charging of the pH-sensitive surface groups interferes with biomolecule sensing resulting in a pH interference mechanism. With analytical equations and TCAD simulations, we highlight that the Debye-Hückel approximation can underestimate screening and overestimate FET molecular sensitivity by more than an order of magnitude. Screening strengthens significantly beyond Debye-Hückel in the proximity of even moderately charged surfaces and biomolecule charge densities (≥1 × 1012 q/cm2). We experimentally show the strong impact of both nonlinear screening and the pH interference effect on charge-based biomolecular sensing using a model system based on the covalent binding of single-stranded DNA on silicon FET sensors. The DNA signal increases from 24 mV at pH 7 to 96 mV at pH 3 in 1.5 mM PBS for a DNA density of 7 × 1012 DNA/cm2. Our model quantitatively explains the signal's pH dependence with roughly equal nonlinear screening and pH interference contributions. This work shows the importance of reducing the net charge and the pH sensitivity of the sensing surface to improve molecular sensing. Therefore, tailoring the gate dielectric and functional layer of FET sensors is a promising route to strong silicon FET molecular sensitivity boosts.

Reprint of "Modeling the intracellular replication of influenza A virus in the presence of defective interfering RNAs.

Like many other viral pathogens, influenza A viruses can form defective interfering particles (DIPs). These particles carry a large internal deletion in at least one of their genome segments. Thus, their replication depends on the co-infection of cells by standard viruses (STVs), which supply the viral protein(s) encoded by the defective segment. However, DIPs also interfere with STV replication at the molecular level and, despite considerable research efforts, the mechanism of this interference remains largely elusive. Here, we present a mechanistic mathematical model for the intracellular replication of DIPs. In this model, we account for the common hypothesis that defective interfering RNAs (DI RNAs) possess a replication advantage over full-length (FL) RNAs due to their reduced length. By this means, the model captures experimental data from yield reduction assays and from studies testing different co-infection timings. In addition, our model predicts that one important aspect of interference is the competition for viral proteins, namely the heterotrimeric viral RNA-dependent RNA polymerase (RdRp) and the viral nucleoprotein (NP), which are needed for encapsidation of naked viral RNA. Moreover, we find that there may be an optimum for both the DI RNA synthesis rate and the time point of successive co-infection of a cell by DIPs and STVs. Comparing simulations for the growth of DIPs with a deletion in different genome segments suggests that DI RNAs derived from segments which encode for the polymerase subunits are more competitive than others. Overall, our model, thus, helps to elucidate the interference mechanism of DI RNAs and provides a novel hypothesis why DI RNAs derived from the polymerase-encoding segments are more abundant in DIP preparations.

Modeling the intracellular replication of influenza A virus in the presence of defective interfering RNAs.

Like many other viral pathogens, influenza A viruses can form defective interfering particles (DIPs). These particles carry a large internal deletion in at least one of their genome segments. Thus, their replication depends on the co-infection of cells by standard viruses (STVs), which supply the viral protein(s) encoded by the defective segment. However, DIPs also interfere with STV replication at the molecular level and, despite considerable research efforts, the mechanism of this interference remains largely elusive. Here, we present a mechanistic mathematical model for the intracellular replication of DIPs. In this model, we account for the common hypothesis that defective interfering RNAs (DI RNAs) possess a replication advantage over full-length (FL) RNAs due to their reduced length. By this means, the model captures experimental data from yield reduction assays and from studies testing different co-infection timings. In addition, our model predicts that one important aspect of interference is the competition for viral proteins, namely the heterotrimeric viral RNA-dependent RNA polymerase (RdRp) and the viral nucleoprotein (NP), which are needed for encapsidation of naked viral RNA. Moreover, we find that there may be an optimum for both the DI RNA synthesis rate and the time point of successive co-infection of a cell by DIPs and STVs. Comparing simulations for the growth of DIPs with a deletion in different genome segments suggests that DI RNAs derived from segments which encode for the polymerase subunits are more competitive than others. Overall, our model, thus, helps to elucidate the interference mechanism of DI RNAs and provides a novel hypothesis why DI RNAs derived from the polymerase-encoding segments are more abundant in DIP preparations.