Bacillus spp. metabolites are effective in eradicating Aedes aegypti (Diptera: Culicidae) larvae with low toxicity to non-target species.

The growing spread of dengue, chikungunya and Zika viruses demand the development of new and environmentally safe control methods for their vector, the mosquito Aedes aegypti. This study aims to find novel larvicidal agents from mutualistic (endophytic and rhizospheric) or edaphic bacteria that have no action against non-target organisms. Eleven out of the 254 bacterial strains tested were able to kill Ae. aegypti larvae. Larvicidal activity did not depend on presence of cells, since culture supernatants or crude lipopeptide extracts (CLEs) killed the larvae. Bacillus safensis BacI67 and Bacillus paranthracis C21 supernatants were the best performing supernatants, displaying the lowest lethal concentrations (LC50 = 31.11 µL/mL and 45.84 µL/mL, respectively). Bacillus velezensis B64a and Bacillus velezensis B15 produced the best performing CLEs (LC50 = 0.11 mg/mL and 0.12 mg/mL, respectively). Mass spectrometry analysis of CLEs detected a mixture of surfactins, iturins, and fengycins. The samples tested were weakly- or non-toxic to mammalian cells (RAW 264.7 macrophages and VERO cells) and non-target organisms (Caenorhabditis elegans, Galleria mellonella, Scenedesmus obliquus, and Tetrahymena pyriformis) - especially B. velezensis B15 CLE. The biosynthetic gene clusters related to secondary metabolism identified by whole genome sequencing of the four best performing bacteria strains revealed clusters for bacteriocin, beta-lactone, lanthipeptide, non-ribosomal peptide synthetases, polyketide synthases (PKS), siderophores, T3PKS, type 1 PKS-like, terpenes, thiopeptides, and trans-AT-PKS. Purification of lipopeptides may clarify the mechanisms by which these extracts kill Ae. aegypti larvae.

Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.

The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic action (MOA), including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles, and soft electrophiles. Because it is often difficult to determine correctly the mechanism of action of a compound, quantitative structure-activity relationship (QSAR) methods, which have proved their interest in toxicity prediction, can be used. In this work, several QSAR models for the prediction of MOA of 221 phenols to the ciliated protozoan Tetrahymena pyriformis, using Chemistry Development Kit descriptors, are reported. Four machine learning techniques (ML), k-nearest neighbours, support vector machine, classification trees, and artificial neural networks, have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. They showed global accuracy values between 95.9% and 97.7% and area under Receiver Operator Curve values between 0.978 and 0.998; additionally, false alarm rate values were below 8.2% for training set. In order to validate our models, cross-validation (10-folds-out) and external test-set were performed with good behaviour in all cases. These models, obtained with ML techniques, were compared with others previously reported by other researchers, and the improvement was significant.

Comparative study to predict toxic modes of action of phenols from molecular structures.

Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. Most of them showed global accuracy of over 90%, and false alarm rate values were below 2.9% for the training set. Cross-validation, complementary subsets and external test set were performed, with good behaviour in all cases. Our models compare favourably with other previously published models, and in general the models obtained with ML techniques show better results than those developed with linear techniques. We developed unsupervised and supervised consensus, and these results were better than our ML models, the results of rule-based approach and other ensemble models previously published. This investigation highlights the merits of ML-based techniques as an alternative to other more traditional methods for modelling MOA.

Use of nanofiltration for potable water from an aquifer recharged with wastewater.

This paper presents the comparison of nine nanofiltration membranes to treat water coming from an aquifer recharged with wastewater and used as municipal supply in the Tula Valley, Mexico. The comparison was made based on (a) the amount of water produced; (c) the capability to produce a <1 mg TOC/L effluent without entirely eliminating salts, (b) the removal of specific organic and microbiological pollutants, and (c) the reduction of toxicity and mutagenicity from water. From the tested membranes, only four produce an effluent with <1 TOC mg/L, and three totally retained dibutyl phthalate, diethyl phthalate and hydroxytoluene butylate. Influent mutagenicity (Ames test) was negative but these was a certain degree of toxicity when Tetrahymena pyriformis was used as indicator. Toxicity was partially reduced by some of the NF membranes. The best membrane had a flux of 95 L m(-2)h(-1) and removal efficiencies of 98% for TOC, 92% for AUV(254), and 92% for TDS. The permeate had a final hardness of 76 mg/L and an alkalinity of 124 mg/L. Additionally, this membrane removed totally specific organic compounds, total and fecal coliforms and almost all the somatic coliphages.

A novel approach to predict a toxicological property of aromatic compounds in the Tetrahymena pyriformis.

The TOPological Substructural MOlecular DEsign (TOPS-MODE) has been successfully used in order to explain the toxicity in the Tetrahymena pyriformis on a large data set. The obtained models for the training set had good statistical parameters (R(2)=0.72-0.81, p<0.05) an also the prediction power of the models found was adequate (Q(2)=0.70-0.80). A detailed study of the influence of variable numbers in the equation and the statistical outliers was carried out; leading to a good final model with a better physicochemical interpretation than the rest of the published models. Only two molecular descriptors codifying dipolar and hydrophobic features were introduced. Finally, the fragment contributions to the toxicity prediction evidenced the powerful of this topological approach.

Assessment of mutagenicity and toxicity of different-size fractions of air particulates from La Plata, Argentina, and Leipzig, Germany.

Airborne particulates, especially fine particles and bound chemical compounds, are a potential mediator of adverse health effects. In this study an analysis was done of the concentration and size distribution of air particulate matter, the content of bound polycyclic aromatic hydrocarbons (PAHs), and the biological effects of organic extracts from different fractions of dust that had been influenced by urban and industrial emissions from the regions of La Plata, Argentina, and Leipzig, Germany, along with samples from control areas. Air particulate matter was sampled in summer and winter in each region using a high-volume sampler with a six-stage cascade impactor, classifying dust in six size fractions from 10-microm particles to those less than 0.49 microm in size. Organic extracts of dust were tested for mutagenicity (Ames test, Salmonella typhimurium TA98 strain, S9+) and cytotoxicity (Tetrahymena pyriformis test system, growth rate, cell respiration). The content of PAHs was analyzed by high-performance liquid chromatography (HPLC) with diode array and fluorescence detection. Mutagenic and cytotoxic effects were found to be associated with very fine (<0.49 microm) and fine (<1.5 microm) particle-bound compounds, corresponding to a higher content of PAHs. The mutagenic potency (revertants/m(3)) associated with particles less than 0.49 microm from urban areas of La Plata was about 1 order of magnitude higher than in particles in the range of 3.0 to 0.49 microm. Fine fractions from sites with an industrial burden were also found to exhibit high mutagenic potency. A similar tendency was observed in cytotoxicity tests with T. pyriformis. This cell system proved to be very sensitive to toxicants in tested dust fractions. The observed biological effects were found to be correlated significantly with concentrations of total PAH, carcinogenic PAHs, and benzo[a]pyrene.

Assessment of toxicity and mutagenicity in air particulate matter from an urban industrial area in the coast of the Rio de la Plata.

Chemical characterization and effects assessment of semivolatile organic compounds in organic extracts from air particulate matter from the region of the greater La Plata area was undertaken. Effects covered the study of mutagenicity with the Ames test (Salmonella typhimurium TA100 and TA98 strains with metabolic activation by S9) and cytotoxicity using the Tetrahymena pyriformis test system (growth rate, cell volume, and cell respiration). Chemical analysis of organic extracts was done using gas chromatography. Results demonstrate the presence of polycyclic aromatic hydrocarbons (PAH) in the matrix, high mutagenicity, and cytotoxicity. A higher mutagenic activity detected with TA98 and TA100 strains is associated with an increment of total PAH and total five or six ring PAH content, respectively. Linked with it, a PAH dependent toxicity on Tetrahymena pyriformis has been observed. This cell system proved to be very sensitive. From the results obtained with the cell respiration assay with T. pyriformis it appears that uncoupling agents are present in the samples. The results of this study indicate that air particulate matter from the Rio de La Plata area contains significant genotoxic and cytotoxic activity probably due to the presence of PAHs.