Novel insights into the kinetics and mechanism of arsenopyrite bio-dissolution enhanced by pyrite.

Arsenopyrite and pyrite often coexist in metal deposits and tailings, thus simultaneous bioleaching of both sulfides has economic (as well as environmental) significance. Important targets in bio-oxidation operations are high solubilization rates and minimized accumulation of Fe(III)/As-bearing secondary products. This study investigated the role of pyrite bioleaching in the enhancement of arsenopyrite dissolution. At a pyrite to arsenopyrite mass ratio of 1:1, 93.6% of As and 93.0% of Fe were solubilized. The results show that pyrite bio-oxidation can promote arsenopyrite dissolution, enhance S0 bio-oxidation, and inhibit the formation of jarosites, tooeleite, and amorphous ferric arsenate. The dry weight of the pyrite & arsenopyrite residue was reduced by 95.1% after bioleaching, compared to the initial load, while only 5% weight loss was observed when pyrite was absent. A biofilm was formed on the arsenopyrite surface in the presence of pyrite, while a dense passivation layer was observed in the absence of pyrite. As(III) (as As2O3) was a dominant As species in the pyrite & arsenopyrite residue. Novel and detailed findings are presented on arsenopyrite bio-dissolution in the presence of pyrite, and the presented approach could contribute to the development of novel cost-effective extractive bioprocesses. ENVIRONMENTAL IMPLICATION: The oxidation of arsenopyrite presents significant environmental hazards, as it can contribute to acid mine drainage generation and arsenic mobilization from sulfidic mine wastes. Bioleaching is a proven cost-effective and environmentally friendly extractive technology, which has been applied for decades in metal recovery from minerals or tailings. In this work, efficient extraction of arsenic from arsenopyrite bioleaching was presented through coupling the process with bio-oxidation of pyrite, resulting in lowered accumulation of hazardous and metastable Fe(III)/As-bearing secondary phases. The results could help improve current biomining operations and/or contribute to the development of novel cost-effective bioprocesses for metal extraction.

Identification and profiling of the community structure and potential function of bacteria from the fruiting bodies of Sanghuangporus vaninii.

Sanghuangporus sp., a medicinal and edible homologous macrofungus known as 'forest gold', which has good effects on antitumor, hypolipidemia and the treatment of gynecological diseases. However, the natural resources of fruiting body are on the verge of depletion due to its long growth cycle and over exploitation. The growth and metabolism of macrofungi are known to depend on the diverse bacterial community. Here, we characterized the diversity and potential function of bacteria inhabiting in the fruiting body of the most widely applied S. vaninii using a combination method of high-throughput sequencing with pure culturing for the first time, and tested the biological activities of bacterial isolates, of which Illumina NovaSeq provided a more comprehensive results on the bacterial community structure. Total 33 phyla, 82 classes, 195 orders, 355 families, 601 genera and 679 species were identified in the fruiting body, and our results revealed that the community was predominated by the common Proteobacteria, Gammaproteobacteria, Burkholderiales, Methylophilaceae (partly consistent with pure-culturing findings), and was dominated by the genera of distinctive Methylotenera and Methylomonas (yet-uncultured taxa). Simultaneously, the functional analysis showed that companion bacteria were involved in the pathways of carbohydrate transport and metabolism, metabolism of terpenoids and polyketides, cell wall/membrane/envelope biogenesis, etc. Hence, it was inferred that bacteria associated with fruiting body may have the potential to adjust the growth, development and active metabolite production of host S. vaninii combined with the tested results of indole-3-acetic acid and total antioxidant capacity. Altogether, this report first provided new findings which can be inspiring for further in-depth studies to exploit bioactive microbial resources for increased production of Sanghuangporus, as well as to explore the relationship between medicinal macrofungi and their associated endophytes.

In silico analysis of epitope-based vaccine candidate against tuberculosis using reverse vaccinology.

Tuberculosis (TB) kills more individuals in the world than any other disease, and a threat made direr by the coverage of drug-resistant strains of Mycobacterium tuberculosis (Mtb). Bacillus Calmette-Guérin (BCG) is the single TB vaccine licensed for use in human beings and effectively protects infants and children against severe military and meningeal TB. We applied advanced computational techniques to develop a universal TB vaccine. In the current study, we select the very conserved, experimentally confirmed Mtb antigens, including Rv2608, Rv2684, Rv3804c (Ag85A), and Rv0125 (Mtb32A) to design a novel multi-epitope subunit vaccine. By using the Immune Epitopes Database (IEDB), we predicted different B-cell and T-cell epitopes. An adjuvant (Griselimycin) was also added to vaccine construct to improve its immunogenicity. Bioinformatics tools were used to predict, refined, and validate the 3D structure and then docked with toll-like-receptor (TLR-3) using different servers. The constructed vaccine was used for further processing based on allergenicity, antigenicity, solubility, different physiochemical properties, and molecular docking scores. The in silico immune simulation results showed significant response for immune cells. For successful expression of the vaccine in E. coli, in-silico cloning and codon optimization were performed. This research also sets out a good signal for the design of a peptide-based tuberculosis vaccine. In conclusion, our findings show that the known multi-epitope vaccine may activate humoral and cellular immune responses and maybe a possible tuberculosis vaccine candidate. Therefore, more experimental validations should be exposed to it.

Development of novel prediction model for drug-induced mitochondrial toxicity by using naïve Bayes classifier method.

Mitochondrial dysfunction has been considered as an important contributing factor in the etiology of drug-induced organ toxicity, and even plays an important role in the pathogenesis of some diseases. The objective of this investigation was to develop a novel prediction model of drug-induced mitochondrial toxicity by using a naïve Bayes classifier. For comparison, the recursive partitioning classifier prediction model was also constructed. Among these methods, the prediction performance of naïve Bayes classifier established here showed best, which yielded average overall prediction accuracies for the internal 5-fold cross validation of the training set and external test set were 95 ± 0.6% and 81 ± 1.1%, respectively. In addition, four important molecular descriptors and some representative substructures of toxicants produced by ECFP_6 fingerprints were identified. We hope the established naïve Bayes prediction model can be employed for the mitochondrial toxicity assessment, and these obtained important information of mitochondrial toxicants can provide guidance for medicinal chemists working in drug discovery and lead optimization.

Repellent activity of essential oils extracted from five Artemisia species against Tribolium castaneum (Coleoptera: Tenebrionidae) / Actividad repelente de aceites esenciales extraídos de cinco especies de Artemisia contra Tribolium castaneum (Coleoptera: Tenebrionidae)

Artemisia genus (family Asteraceae) has been widely used as medicines and cosmetic. The chemical compositions of essential oils extracted from five Artemisia species (A. anethoides, A. giraldii, A. roxburghiana, A. rubripes and A. sacrorum) were analyzed and the repellent activities of five essential oils were investigated by testing percent repellency (PR) in petri dish against Tribolium castaneum. By GC-MS analysis, the common components of the five essential oils were eucalyptol (11.09%-50.05%), camphor (6.28%-33.10%), terpinen- 4-ol (2.46%-12.41%), ß-caryophyllene (0.63%-10.68%) and germacrene D (2.28%-10.01%). 3,3,6-trimethyl-1,4-heptadien-6-ol (11.72%), 2-isopropyl-5-methyl-3-cyclohexen-1-one (24.80%) and ß-farnesene (12.23%) were the characteristic compounds in essential oils of A. sacrorum, A. anethoides and A. rubripes respectively. The essential oils of five plants showed repellent activity against T. castaneum. The PR of others four essential oils were comparable with DEET expect for A. sacrorum. The results indicated that the essential oils of A. anethoides, A. giraldii, A. roxburghiana and A. rubripes had the potential to be developed as repellent for control of T. castaneum.

El género Artemisia (familia Asteraceae) ha sido ampliamente utilizado como medicamentos y cosméticos. Se analizaron las composiciones químicas de los aceites esenciales extraídos de cinco especies de Artemisia (A. anethoides, A. giraldii, A. roxburghiana, A. rubripes y A. sacrorum) y se investigaron las actividades repelentes de cinco aceites esenciales mediante la prueba de repelencia porcentual (PR) en placa de petri contra Tribolium castaneum. Por análisis GC-MS, los componentes comunes de los cinco aceites esenciales fueron eucaliptol (11,09% -50,05%), alcanfor (6,28% -33,10%), terpinen-4-ol (2,46% -12,41%), ß-cariofileno 0,63% -10,68%) y germacrén D (2,28% -10,01%). 3,3,6-trimetil-1,4-heptadien-6-ol (11,72%), 2-isopropil-5-metil-3-ciclohexen-1-ona (24,80%) y ß-farneseno (12,23%). Los compuestos característicos en los aceites esenciales de A. sacrorum, A. anethoides y A. rubripes respectivamente. Los aceites esenciales de cinco plantas mostraron actividad repelente contra T. castaneum. El PR de otros cuatro aceites esenciales eran comparables con DEET esperado para A. sacrorum. Los resultados indicaron que los aceites esenciales de A. anethoides, A. giraldii, A. roxburghiana y A. rubripes tienen el potencial de ser desarrollados como repelentes para el control de T. castaneum.

Development of novel in silico model for developmental toxicity assessment by using naïve Bayes classifier method.

Toxicological testing associated with developmental toxicity endpoints are very expensive, time consuming and labor intensive. Thus, developing alternative approaches for developmental toxicity testing is an important and urgent task in the drug development filed. In this investigation, the naïve Bayes classifier was applied to develop a novel prediction model for developmental toxicity. The established prediction model was evaluated by the internal 5-fold cross validation and external test set. The overall prediction results for the internal 5-fold cross validation of the training set and external test set were 96.6% and 82.8%, respectively. In addition, four simple descriptors and some representative substructures of developmental toxicants were identified. Thus, we hope the established in silico prediction model could be used as alternative method for toxicological assessment. And these obtained molecular information could afford a deeper understanding on the developmental toxicants, and provide guidance for medicinal chemists working in drug discovery and lead optimization.

Predicting drug-induced liver injury in human with Naïve Bayes classifier approach.

Drug-induced liver injury (DILI) is one of the major safety concerns in drug development. Although various toxicological studies assessing DILI risk have been developed, these methods were not sufficient in predicting DILI in humans. Thus, developing new tools and approaches to better predict DILI risk in humans has become an important and urgent task. In this study, we aimed to develop a computational model for assessment of the DILI risk with using a larger scale human dataset and Naïve Bayes classifier. The established Naïve Bayes prediction model was evaluated by 5-fold cross validation and an external test set. For the training set, the overall prediction accuracy of the 5-fold cross validation was 94.0 %. The sensitivity, specificity, positive predictive value and negative predictive value were 97.1, 89.2, 93.5 and 95.1 %, respectively. The test set with the concordance of 72.6 %, sensitivity of 72.5 %, specificity of 72.7 %, positive predictive value of 80.4 %, negative predictive value of 63.2 %. Furthermore, some important molecular descriptors related to DILI risk and some toxic/non-toxic fragments were identified. Thus, we hope the prediction model established here would be employed for the assessment of human DILI risk, and the obtained molecular descriptors and substructures should be taken into consideration in the design of new candidate compounds to help medicinal chemists rationally select the chemicals with the best prospects to be effective and safe.

Prediction of drug-induced eosinophilia adverse effect by using SVM and naïve Bayesian approaches.

Drug-induced eosinophilia is a potentially life-threatening adverse effect; clinical manifestations, eosinophilia-myalgia syndrome, mainly include severe skin eruption, fever, hematologic abnormalities, and organ system dysfunction. Using experimental methods to evaluate drug-induced eosinophilia is very complicated, time-consuming, and costly in the early stage of drug development. Thus, in this investigation, we established computational prediction models of drug-induced eosinophilia using SVM and naïve Bayesian approaches. For the SVM modeling, the overall prediction accuracy for the training set by means of fivefold cross-validation is 91.6 and for the external test set is 82.9 %. For the naïve Bayesian modeling, the overall prediction accuracy for the training set is 92.5 and for the external test set is 85.4 %. Moreover, some molecular descriptors and substructures considered as important for drug-induced eosinophilia were identified. Thus, we hope the prediction models of drug-induced eosinophilia built in this work should be applied to filter early-stage molecules for potential eosinophilia adverse effect, and the selected molecular descriptors and substructures of toxic compounds should be taken into consideration in the design of new candidate drugs to help medicinal chemists rationally select the chemicals with the best prospects to be effective and safe.

[Diversity of uncultured actinomycetes in saline-alkali soil from Jiuquan area of Hexi Corridor].

ABSTRACT: In order to more accurately understand community structure and diversity of actinomycetes in saline-alkali soil from Jiuquan area of Hexi Corridor, the community structure and diversity from three kinds of soil samples (primary, secondary saline alkali soil and farmland soil) were analyzed using uncultured methods. The results showed that the 16S rDNA clone library of actinomycetales from the primary saline-alkali soil belonged to 19 OTUs, Micrococcineae, Propionibacterineae, Corynebacterineae, Frankineae, Pseudonocardineae and unknown groups of Actinomycetales; the 16S r DNA clone library of actinomycetales from the secondary saline-alkali soil belonged to 14 OTUs, Micrococcineae, Propionibacterineae, Corynebacterineae, Frankineae, Pseudonocardineae and unknown groups of Actinomycetales; the 16S rDNA clone library of farmland soil belonged to 7 OTUs, Micrococcineae, Propionibacterineae, Corynebacterineae, Frankineae, Pseudonocardineae and unknown groups of Actinomycetales; Micrococcineae was the common population in the three soils, and also was the dominant population in primary saline alkali soil and farmland soil. The diversity index and rarefaction curves analysis showed that actinomycetes species richness was in order of primary saline-alkali soil > secondary saline-alkali soil > farmland soil. The dilution curves of primary saline-alkali soil and secondary saline-alkali soil were not leveled off, which indicated the actinomycetes diversity in saline-alkali soil was more enriched than the actual. The rich and diverse actinomycetes resources in saline-alkali soil from Jiuquan area of Hexi Corridor provide important data on the actinomycetes ecology distribution research, exploitation and utilization in saline-alkali soil.