Integrating Statistical and Machine-Learning Approach for Meta-Analysis of Bisphenol A-Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival

A Machine Learning Force Field for Bio-Macromolecular Modeling Based on Quantum Chemistry-Calculated Interaction Energy Datasets

Accurate energy data from noncovalent interactions are essential for constructing force fields for molecular dynamics simulations of bio-macromolecular systems. There are two important practical issues in the construction of a reliable force field with the hope of balancing the desired chemical accuracy and working efficiency. One is to determine a suitable quantum chemistry level of theory for calculating interaction energies. The other is to use a suitable continuous energy function to model the quantum chemical energy data. For the first issue, we have recently calculated the intermolecular interaction energies using the SAPT0 level of theory, and we have systematically organized these energies into the ab initio SOFG-31 (homodimer) and SOFG-31-heterodimer datasets. In this work, we re-calculate these interaction energies by using the more advanced SAPT2 level of theory with a wider series of basis sets. Our purpose is to determine the SAPT level of theory proper for interaction energies with respect to the CCSD(T)/CBS benchmark chemical accuracy. Next, to utilize these energy datasets, we employ one of the well-developed machine learning techniques, called the CLIFF scheme, to construct a general-purpose force field for biomolecular dynamics simulations. Here we use the SOFG-31 dataset and the SOFG-31-heterodimer dataset as the training and test sets, respectively. Our results demonstrate that using the CLIFF scheme can reproduce a diverse range of dimeric interaction energy patterns with only a small training set. The overall errors for each SAPT energy component, as well as the SAPT total energy, are all well below the desired chemical accuracy of ~1 kcal/mol.

Bisphenol A (BPA) induces apoptosis of mouse Leydig cells via oxidative stress

As one of the most frequently produced synthetic compounds worldwide, bisphenol A (BPA) has been widely used in many kinds of products such as appliances, housewares, and beverage cans. BPA has been shown to cause damage to male reproductive system; however, the potential mechanism remains to be investigated. In the present study, BPA exposure decreased the testis and epididymis coefficient, caused a disintegration of germinal epithelium, decreased the density and motility of sperm in the epididymis tissue, and increased the number of abnormal sperm morphology, which indicated that BPA exposure could cause damage to testis. BPA was also shown to induce apoptosis and oxidative stress in the testis tissue. The serum testosterone concentration was decreased in the BPA-treated group, suggesting that BPA could lead to Leydig cell damage. Subsequently, mouse TM3 cell, a kind of mouse Leydig cell line, was utilized to investigate the potential mechanism. Herein, we showed that BPA exposure could inhibit cell viability and induce apoptosis of TM3 cells. Furthermore, oxidative stress in the cells could also be induced by BPA, while the inhibition of oxidative stress by N-acetyl-L-cysteine (NAC), an oxidative stress scavenger, could reverse the inhibition of cell viability and induction of apoptosis by BPA exposure, indicating that oxidative stress was involved in BPA-induced apoptosis of TM3 cells. Finally, RNA-sequencing and real-time PCR were utilized to screen and validate the potential oxidative stress-related genes involving in BPA-induced apoptosis. We found that BPA exposure increased the mRNA levels of oxidative stress-related genes such as Lonp1, Klf4, Rack1, Egln1, Txn2, Msrb1, Atox1, Mtr, and Atp2a2, as well as decreased the mRNA level of Dhfr gene; while NAC could rescue the expression of these genes. Taken together, oxidative stress was involved in BPA-induced apoptosis of mouse Leydig cells.

Generation of Endogenous Promoter-Driven Luciferase Reporter System Using CRISPR/Cas9 for Investigating Transcriptional Regulation of the Core Clock Gene BMAL1

Humans and other organisms are continuously exposed to thousands of chemicals through the atmosphere, drinking water, food, or direct contact. A large proportion of such chemicals are present in very low concentrations and may have synergistic effects, even at their no-observed-adverse-effect level (NOAEL). Complex mixtures of contaminants are very difficult to assess by traditional toxicological methods. There is increasing attention on how different pollutants induce adverse physiological functions in the human body through effects on the circadian rhythm. However, it is very difficult to screen for compounds with circadian-rhythm-disrupting effects from a large number of chemicals or their complex mixtures. We established a stable firefly luciferase reporter gene knock-in U2-OS cell line by CRISPR/Cas9 to screen circadian-rhythm-disrupting pollutants. The luciferase gene was inserted downstream of the core clock gene BMAL1 and controlled by an endogenous promoter. Compared to detection systems using exogenous promoters, these cells enable the detection of compounds that interfere with the circadian rhythm system mediated by BMAL1 gene expression. The U2-OS knock-in cells showed BMAL1 and luciferase activity had parallel changes when treated with BMAL1 inhibitor and activator. Furthermore, the luciferase reporter gene has high sensitivity and is faster and more cost-effective than classic toxicology methods. The knock-in cell line can be used for high-throughput and efficient screening of circadian-rhythm-disrupting chemicals such as drugs and pollutants.

Role of the Synergistic Interactions of Environmental Pollutants in the Development of Cancer

There is a growing awareness that the large number of environmental pollutants we are exposed to on a daily basis are causing major health problems. Compared to traditional studies that focus on individual pollutants, there are relatively few studies on how pollutants mixtures interact. Several studies have reported a relationship between environmental pollutants and the development of cancer, even when pollutant levels are below toxicity reference values. The possibility of synergistic interactions between different pollutants could explain how even low concentrations can cause major health problems. These intricate that molecular interactions can occur through a wide variety of mechanisms, and our understanding of the physiological effects of mixtures is still limited. The purpose of this paper is to discuss recent reports that address possible synergistic interactions between different types of environmental pollutants that could promote cancer development. Our literature studies suggest that key biological pathways are frequently implicated in such processes. These include increased production of reactive oxygen species, activation by cytochrome P450, and aryl hydrocarbon receptor signaling, among others. We discuss the need to understand individual pathological vulnerability not only in relation to basic genetics and gene expression, but also in terms of measurable exposure to contaminants. We also mention the need for significant improvements in future studies using a multitude of disciplines, such as the development of high-throughput study models, better tools for quantifying pollutants in cancer patients, innovative pharmacological and toxicological studies, and high-efficiency computer analysis, which allow us to analyze the molecular mechanisms of mixtures.