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Title: Xenobiotic biotransformation in the era of exposome: database fusion, computer assisted prediction, and chemical-chemical interaction
Authors: Peng, Bo
Keywords: Engineering::Environmental engineering::Environmental pollution
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Peng, B. (2022). Xenobiotic biotransformation in the era of exposome: database fusion, computer assisted prediction, and chemical-chemical interaction. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: Human and biota are chronically exposed to thousands of chemicals from numerous environmental sources through various pathways. Pesticides, plasticizers, flame retardants, pharmaceuticals, and other synthetic chemicals, for example, can enter the environment and food chain, triggering adverse effects and illness. Absorption, distribution, metabolism, and elimination (ADME) are the general disposition processes when living organisms like fish, birds, humans, rodents and some other mammals, are exposed to a foreign chemical (i.e., xenobiotic). Fundamentally, these processes regulate xenobiotics’ concentration at the action site, as well as the occurrence of adverse events, thereby becoming major contributors to the toxicity potential of compounds. Among all ADME processes, biotransformation (i.e., metabolism) plays a crucial role because it has the ability to directly transform the chemical structures of such compounds, therefore altering their lifetimes, bioavailability, and biological effects. To date, the prediction of xenobiotic biotransformation largely depends on experience and most prediction models have been challenged with low accuracy. In addition, living organisms are exposed to hundreds to thousands of chemicals at the same time in the era of exposome. However, there is very little information on the chemical-chemical interaction on the xenobiotic transformation. This thesis begins with the development of a comprehensive biotransformation database, which contains multi-species data on common environmental contaminants, pharmaceuticals, and human endogenous metabolites. Text mining and database fusion were used to collect biotransformation information from multiple species, comprising 7,800 biotransformation reactions from 1,599 substrates. Unlike earlier biotransformation-related databases, the species gathered in this collection include birds, fish, rodents, and other mammals in addition to humans. This database covers substrate structures and their associated products, reaction types, the names or kinds of enzymes catalyzing biotransformation, biosystem types, and references. For the first time, environmental contaminants and various species are being addressed as a focus for data curation in biotransformation studies. Following that, this thesis has developed a novel computational approach for biotransformation prediction based on the database. The prediction approach began with automatically retrieved reaction templates, which were obtained by comparing the SMARTS pattern, atomic number, total number of hydrogens, formal charge, degree, number of radical electrons, aromaticity, bond orders, and atomic number of neighbouring atoms of the mapped atom-to-atom reaction of reactants and products. Subsequentially, chemical similarity metrics were used to rank prediction candidates. The results revealed that chemical similarity was a useful metric for predicting metabolite structure. Extensive evaluations showed that the current model outcompeted previous methods including Biotransformer, GLORYx, and SyGMa. These findings suggest that the proposed method can give a simple and automated solution that does not require any expert knowledge. We also combined the first two parts as an open-access data portal, EcoBioTrans ( . Users are allowed to query by compound name and simplified molecular input line entry specification (SMILES) for retrieving the database or submit compound structure for retrieving prediction results. The third part of the thesis explored the biotransformation behavior of environmental phenolic compounds under single exposure and concurrent exposure. Bisphenol A (BPA) was chosen as a model molecule to explore its biotransformation in liver microsome and cell models after single/co-exposure to additional phenolic xenobiotics (Triclosan (TCS), Tetrabromobisphenol A (TBBPA), Bisphenol S (BPS)) and a combination of 22 phenolic compounds. The results suggested that biotransformation of phenolic xenobiotics can be significantly altered by co-exposure, which provides referential evidence on underestimated risks of simultaneous exposure to environmental toxicants. This thesis further tentatively discovered the possible interplay between the gut microbiome and biotransformation of environmental contaminants via both in vivo and in vitro experiments. Bisphenol A (BPA) and p-cresol were utilized as model compounds. The results indicated that biotransformation behaviors differed between the in vitro and in vivo results. In vivo mouse examination using p-cresol injection exhibited enhancing effect on BPA metabolism, which is rarely found in mixture studies. However, in both in vitro models of liver S9 fractions and HepG2 cell line, p-cresol is found as a strong inhibitor in a non-competitive pattern for BPA biotransformation. The subsequent close investigation revealed that the expression of biotransformation enzyme genes including Ugt1a1, Ugt2b1, or Sult1a1 were dynamically induced after the p-cresol treatment. In sum, this thesis work has built a comprehensive biotransformation database, provided a novel xenobiotic biotransformation prediction platform, and further extended our insight into the biotransformation interaction between chemicals. The results can be applied as some fundamental tools and knowledge in xenobiotic biotransformation.
DOI: 10.32657/10356/160287
Schools: School of Civil and Environmental Engineering 
Research Centres: Nanyang Environment and Water Research Institute 
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:CEE Theses

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