Advancements in biotransformation pathway prediction: enhancements, datasets, and novel functionalities in enviPath.

enviPath is a widely used database and prediction system for microbial biotransformation pathways of primarily xenobiotic compounds. Data and prediction system are freely available both via a web interface and a public REST API. Since its initial release in 2016, we extended the data available in enviPath and improved the performance of the prediction system and usability of the overall system. We now provide three diverse data sets, covering microbial biotransformation in different environments and under different experimental conditions. This also enabled developing a pathway prediction model that is applicable to a more diverse set of chemicals. In the prediction engine, we implemented a new evaluation tailored towards pathway prediction, which returns a more honest and holistic view on the performance. We also implemented a novel applicability domain algorithm, which allows the user to estimate how well the model will perform on their data. Finally, we improved the implementation to speed up the overall system and provide new functionality via a plugin system. SCIENTIFIC CONTRIBUTION: The main scientific contributions are the development of a pathway prediction model applicable to diverse chemicals, a specialized evaluation method for holistic performance assessment, and a novel applicability domain algorithm for user-specific performance estimation. The introduction of two new data sets, and the creation of links to EC classes make enviPath a unique resource in microbial biotransformation research.

enviRule: an end-to-end system for automatic extraction of reaction patterns from environmental contaminant biotransformation pathways.

MOTIVATION: Transformation products (TPs) of man-made chemicals, formed through microbially mediated transformation in the environment, can have serious adverse environmental effects, yet the analytical identification of TPs is challenging. Rule-based prediction tools are successful in predicting TPs, especially in environmental chemistry applications that typically have to rely on small datasets, by imparting the existing knowledge on enzyme-mediated biotransformation reactions. However, the rules extracted from biotransformation reaction databases usually face the issue of being over/under-generalized and are not flexible to be updated with new reactions. RESULTS: We developed an automatic rule extraction tool called enviRule. It clusters biotransformation reactions into different groups based on the similarities of reaction fingerprints, and then automatically extracts and generalizes rules for each reaction group in SMARTS format. It optimizes the genericity of automatic rules against the downstream TP prediction task. Models trained with automatic rules outperformed the models trained with manually curated rules by 30% in the area under curve (AUC) scores. Moreover, automatic rules can be easily updated with new reactions, highlighting enviRule's strengths for both automatic extraction of optimized reactions rules and automated updating thereof. AVAILABILITY AND IMPLEMENTATION: enviRule code is freely available at https://github.com/zhangky12/enviRule.

Combatting over-specialization bias in growing chemical databases.

BACKGROUND: Predicting in advance the behavior of new chemical compounds can support the design process of new products by directing the research toward the most promising candidates and ruling out others. Such predictive models can be data-driven using Machine Learning or based on researchers' experience and depend on the collection of past results. In either case: models (or researchers) can only make reliable assumptions about compounds that are similar to what they have seen before. Therefore, consequent usage of these predictive models shapes the dataset and causes a continuous specialization shrinking the applicability domain of all trained models on this dataset in the future, and increasingly harming model-based exploration of the space. PROPOSED SOLUTION: In this paper, we propose CANCELS (CounterActiNg Compound spEciaLization biaS), a technique that helps to break the dataset specialization spiral. Aiming for a smooth distribution of the compounds in the dataset, we identify areas in the space that fall short and suggest additional experiments that help bridge the gap. Thereby, we generally improve the dataset quality in an entirely unsupervised manner and create awareness of potential flaws in the data. CANCELS does not aim to cover the entire compound space and hence retains a desirable degree of specialization to a specified research domain. RESULTS: An extensive set of experiments on the use-case of biodegradation pathway prediction not only reveals that the bias spiral can indeed be observed but also that CANCELS produces meaningful results. Additionally, we demonstrate that mitigating the observed bias is crucial as it cannot only intervene with the continuous specialization process, but also significantly improves a predictor's performance while reducing the number of required experiments. Overall, we believe that CANCELS can support researchers in their experimentation process to not only better understand their data and potential flaws, but also to grow the dataset in a sustainable way. All code is available under github.com/KatDost/Cancels .

Cloning of Toll-like Receptor 3 Gene from Schizothorax prenanti (SpTLR3), and Expressions of Seven SpTLRs and SpMyD88 after Lipopolysaccharide Induction.

Toll-like receptor 3 (SpTLR3) from Schizothorax prenanti (S. prenanti) was cloned and identified, and the tissue distribution of the SpTLR3 gene was examined in this study. Moreover, the relative mRNA expression levels of myeloid differentiation factor 88 gene (SpMyD88) and seven TLR genes (SpTLR2, SpTLR3, SpTLR4, SpTLR18, SpTLR22-1, SpTLR22-2 and SpTLR22-3) from S. prenanti after lipopolysaccharide (LPS) challenge were analyzed through quantitative real-time polymerase chain reaction (qRT-PCR). The full length of SpTLR3 gene is 3097 bp, and complete coding sequence (CDS) is 2715 bp, which encodes 904 amino acids. The SpTLR3 amino acid sequence shared 43.94−100% identity with TLR3 sequences from other vertebrates; SpTLR3 was expressed in all eight tissues examined; and the highest level appeared in the liver, which was significantly higher than in all other tissues (p < 0.05), followed by the levels in the heart and muscles. LPS significantly up-regulated all eight genes in the S. prenanti tissues at 12 or 24 h (p < 0.05). Compared with the PBS control group, no significant transcripts changes were found in SpTLR2 or SpTLR3 at 12 h after LPS induction, but they were significantly up-regulated at 24 h (p < 0.001). The most abundant transcripts were found in the head kidney SpTLR22 genes after 24 h LPS induction, with high to low levels, which were SpTLR22-1 (564-fold), SpTLR22-3 (508-fold) and SpTLR22-2 (351-fold). Among these eight genes, the expression level of SpTLR4 was the least up-regulated. Overall, SpTLR4 in the head kidney was involved in the antibacterial immune response earlier, and the level was increased at 12 h with extreme significance after LPS stimulation (p < 0.001), while the other seven genes were the most significantly up-regulated at 24 h post injection. Taken together, the results suggest that SpMyD88, SpTLR2, SpTLR3, SpTLR4, SpTLR18, SpTLR22-1, SpTLR22-2 and SpTLR22-3 participate in an innate immune response stimulated by LPS, and the response intensity of the genes was organ-specific, with differing kinetics. Our findings will contribute to a more complete understanding of the roles of these TLR genes in antibacterial immunity.

Schizothorax prenanti Heat Shock Protein 27 Gene: Cloning, Expression, and Comparison with Other Heat Shock Protein Genes after Poly (I:C) Induction.

We identified and cloned cDNA encoding the heat shock protein (Hsp) 27 gene from Schizothorax prenanti (SpHsp27), and compared its expression with that of SpHsp60, SpHsp70, and SpHsp90 in the liver, head kidney, hindgut, and spleen of S. prenanti that were injected with polyinosinic-polycytidylic acid [Poly (I:C)]. The SpHsp27 partial cDNA (sequence length, 653 bp; estimated molecular mass, 5.31 kDa; theoretical isoelectric point, 5.09) contained an open reading frame of 636 bp and a gene encoding 211 amino acids. The SpHsp27 amino acid sequence shared 61.0−92.89% identity with Hsp27 sequences from other vertebrates and SpHsp27 was expressed in seven S. prenanti tissues. Poly (I:C) significantly upregulated most SpHsps genes in the tissues at 12 or 24 h (p < 0.05) compared with control fish that were injected with phosphate-buffered saline. However, the intensity of responses of the four SpHsps was organ-specifically increased. The expression of SpHsp27 was increased 163-fold in the head kidney and 26.6-fold SpHsp27 in the liver at 24 h after Poly (I:C) injection. In contrast, SpHsp60 was increased 0.97−1.46-fold in four tissues and SpHsp90 was increased 1.21- and 1.16-fold in the liver and spleen at 12 h after Poly (I:C) injection. Our findings indicated that Poly (I:C) induced SpHsp27, SpHsp60, SpHsp70, and SpHsp90 expression and these organ-specific SpHsps are potentially involved in S. prenanti antiviral immunity or mediate pathological process.

Microbial Cleavage of C-F Bonds in Two C6 Per- and Polyfluorinated Compounds via Reductive Defluorination.

The C-F bond is one of the strongest single bonds in nature. Although microbial reductive dehalogenation is well known for the other organohalides, no microbial reductive defluorination has been documented for perfluorinated compounds except for a single, nonreproducible study on trifluoroacetate. Here, we report on C-F bond cleavage in two C6 per- and polyfluorinated compounds via reductive defluorination by an organohalide-respiring microbial community. The reductive defluorination was demonstrated by the release of F- and the formation of the corresponding product when lactate was the electron donor, and the fluorinated compound was the sole electron acceptor. The major dechlorinating species in the seed culture, Dehalococcoides, were not responsible for the defluorination as no growth of Dehalococcoides or active expression of Dehalococcoides-reductive dehalogenases was observed. It suggests that minor phylogenetic groups in the community might be responsible for the reductive defluorination. These findings expand our fundamental knowledge of microbial reductive dehalogenation and warrant further studies on the enrichment, identification, and isolation of responsible microorganisms and enzymes. Given the wide use and emerging concerns of fluorinated organics (e.g., per- and polyfluoroalkyl substances), particularly the perfluorinated ones, the discovery of microbial defluorination under common anaerobic conditions may provide valuable insights into the environmental fate and potential bioremediation strategies of these notorious contaminants.

Photoreactivity of Metal-Organic Frameworks in Aqueous Solutions: Metal Dependence of Reactive Oxygen Species Production.

Promising applications of metal-organic frameworks (MOFs) in various fields have raised concern over their environmental fate and safety upon inevitable discharge into aqueous environments. Currently, no information regarding the transformation processes of MOFs is available. Due to the presence of repetitive π-bond structure and semiconductive property, photochemical transformations are an important fate process that affects the performance of MOFs in practical applications. In the current study, the generation of reactive oxygen species (ROS) in isoreticular MIL-53s was studied. Scavengers were employed to probe the production of (1)O2, O2(•-), and •OH, respectively. In general, MIL-53(Cr) and MIL-53(Fe) are dominated by type I and II photosensitization reactions, respectively, and MIL-53(Al) appears to be less photoreactive. The generation of ROS in MIL-53(Fe) may be underestimated due to dismutation. Further investigation of MIL-53(Fe) encapsulated diclofenac transformation revealed that diclofenac can be easily transformed by MIL-53(Fe) generated ROS. However, the cytotoxicity results implied that the ROS generated from MIL-53s have little effect on the viability of the human hepatocyte (HepG2) cell line. These results suggest that the photogeneration of ROS by MOFs may be metal-node dependent, and the application of MIL-53s as drug carriers needs to be carefully considered due to their high photoreactivity.

Understanding the Adsorption of PFOA on MIL-101(Cr)-Based Anionic-Exchange Metal-Organic Frameworks: Comparing DFT Calculations with Aqueous Sorption Experiments.

To examine the effects of different functionalization methods on adsorption behavior, anionic-exchange MIL-101(Cr) metal-organic frameworks (MOFs) were synthesized using preassembled modification (PAM) and postsynthetic modification (PSM) methods. Perfluorooctanoic acid (PFOA) adsorption results indicated that the maximum PFOA adsorption capacity was 1.19 and 1.89 mmol g(-1) for anionic-exchange MIL-101(Cr) prepared by PAM and PSM, respectively. The sorption equilibrium was rapidly reached within 60 min. Our results indicated that PSM is a better modification technique for introducing functional groups onto MOFs for adsorptive removal because PAM places functional groups onto the aperture of the nanopore, which hinders the entrance of organic contaminants. Our experimental results and the results of complementary density functional theory calculations revealed that in addition to the anion-exchange mechanism, the major PFOA adsorption mechanism is a combination of Lewis acid/base complexation between PFOA and Cr(III) and electrostatic interaction between PFOA and the protonated carboxyl groups of the bdc (terephthalic acid) linker.

In vivo studies of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) based polymers: biodegradation and tissue reactions.

The in vivo tissue reactions and biodegradations of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBHHx), poly(lactide) (PLA), poly(3-hydroxybutyrate) (PHB), blends of PHBHHx (X) and poly(ethylene glycol) (PEG) (E) with ratios of 1:1 (E1X1) and 1:5 (E1X5), respectively, were evaluated by subcutaneous implantation in rabbits. Results revealed that the degradation rate increased in the order of PHB < PHBHHx < PLA. During the implantation period, crystallinity of PHBHHx increased from 19% to 22% and then dropped to 14%. Gel permeation chromatography (GPC) displayed increasing polydispersity and typical bimodal distribution from 3 to 6 months. The above results suggested that rapid PHBHHx degradation occurred in amorphous region rather than in crystalline region. While the in vivo hydrolysis of PHB was found to start from a random chain scission both in amorphous and crystalline regions of the polymer matrix, as demonstrated by its hydrolysis process accompanied by a decrease in molecular weight with unimodal distribution and relatively narrow polydispersity. Compared to pure PHBHHx, PHBHHx-PEG blends showed accelerated weight loss of PHBHHx with weak molecular weight reduction. In general, PHBHHx elicited a very mild tissue response during implantation lasting 6 months compared with relative acute immunological reactions observed among PHB and PLA objects, respectively. Pronounced tissue responses were observed in the capsule surrounding E1X1 and E1X5 as characterized by the presence of lymphocytes, eosinophils and vascularization, which might be resulted from the continuous leaching of PEG.