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Aghayev Z, Szafran AT, Tran A, Ganesh HS, Stossi F, Zhou L, Mancini MA, Pistikopoulos EN, Beykal B. Machine Learning Methods for Endocrine Disrupting Potential Identification Based on Single-Cell Data. Chem Eng Sci 2023; 281:119086. [PMID: 37637227 PMCID: PMC10448728 DOI: 10.1016/j.ces.2023.119086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/29/2023]
Abstract
Humans are continuously exposed to a variety of toxicants and chemicals which is exacerbated during and after environmental catastrophes such as floods, earthquakes, and hurricanes. The hazardous chemical mixtures generated during these events threaten the health and safety of humans and other living organisms. This necessitates the development of rapid decision-making tools to facilitate mitigating the adverse effects of exposure on the key modulators of the endocrine system, such as the estrogen receptor alpha (ERα), for example. The mechanistic stages of the estrogenic transcriptional activity can be measured with high content/high throughput microscopy-based biosensor assays at the single-cell level, which generates millions of object-based minable data points. By combining computational modeling and experimental analysis, we built a highly accurate data-driven classification framework to assess the endocrine disrupting potential of environmental compounds. The effects of these compounds on the ERα pathway are predicted as being receptor agonists or antagonists using the principal component analysis (PCA) projections of high throughput, high content image analysis descriptors. The framework also combines rigorous preprocessing steps and nonlinear machine learning algorithms, such as the Support Vector Machines and Random Forest classifiers, to develop highly accurate mathematical representations of the separation between ERα agonists and antagonists. The results show that Support Vector Machines classify the unseen chemicals correctly with more than 96% accuracy using the proposed framework, where the preprocessing and the PCA steps play a key role in suppressing experimental noise and unraveling hidden patterns in the dataset.
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Affiliation(s)
- Zahir Aghayev
- Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT
- Center for Clean Energy Engineering, University of Connecticut, Storrs, CT
| | - Adam T. Szafran
- Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX
| | - Anh Tran
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX
- Texas A&M Energy Institute, Texas A&M University, College Station, TX
| | - Hari S. Ganesh
- Discipline of Chemical Engineering, Indian Institute of Technology Gandhinagar, Palaj, Gandhinagar, Gujarat - 382055, India
| | - Fabio Stossi
- Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX
- GCC Center for Advanced Microscopy and Image Informatics, Houston, TX
| | - Lan Zhou
- Department of Statistics, Texas A&M University, College Station, TX
| | - Michael A. Mancini
- Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX
- GCC Center for Advanced Microscopy and Image Informatics, Houston, TX
| | - Efstratios N. Pistikopoulos
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX
- Texas A&M Energy Institute, Texas A&M University, College Station, TX
| | - Burcu Beykal
- Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT
- Center for Clean Energy Engineering, University of Connecticut, Storrs, CT
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Cordova AC, Dodds JN, Tsai HHD, Lloyd DT, Roman-Hubers AT, Wright FA, Chiu WA, McDonald TJ, Zhu R, Newman G, Rusyn I. Application of Ion Mobility Spectrometry-Mass Spectrometry for Compositional Characterization and Fingerprinting of a Library of Diverse Crude Oil Samples. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2023; 42:2336-2349. [PMID: 37530422 PMCID: PMC10592202 DOI: 10.1002/etc.5727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/16/2023] [Accepted: 07/29/2023] [Indexed: 08/03/2023]
Abstract
Exposure characterization of crude oils, especially in time-sensitive circumstances such as spills and disasters, is a well-known analytical chemistry challenge. Gas chromatography-mass spectrometry is commonly used for "fingerprinting" and origin tracing in oil spills; however, this method is both time-consuming and lacks the resolving power to separate co-eluting compounds. Recent advances in methodologies to analyze petroleum substances using high-resolution analytical techniques have demonstrated both improved resolving power and higher throughput. One such method, ion mobility spectrometry-mass spectrometry (IMS-MS), is especially promising because it is both rapid and high-throughput, with the ability to discern among highly homologous hydrocarbon molecules. Previous applications of IMS-MS to crude oil analyses included a limited number of samples and did not provide detailed characterization of chemical constituents. We analyzed a diverse library of 195 crude oil samples using IMS-MS and applied a computational workflow to assign molecular formulas to individual features. The oils were from 12 groups based on geographical and geological origins: non-US (1 group), US onshore (3), and US Gulf of Mexico offshore (8). We hypothesized that information acquired through IMS-MS data would provide a more confident grouping and yield additional fingerprint information. Chemical composition data from IMS-MS was used for unsupervised hierarchical clustering, as well as machine learning-based supervised analysis to predict geographic and source rock categories for each sample; the latter also yielded several novel prospective biomarkers for fingerprinting of crude oils. We found that IMS-MS data have complementary advantages for fingerprinting and characterization of diverse crude oils and that proposed polycyclic aromatic hydrocarbon biomarkers can be used for rapid exposure characterization. Environ Toxicol Chem 2023;42:2336-2349. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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Affiliation(s)
- Alexandra C. Cordova
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, United States
| | - James N. Dodds
- Department of Chemistry, UNC Chapel Hill, Chapel Hill, NC 27514, United States
| | - Han-Hsuan D. Tsai
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, United States
| | - Dillon T. Lloyd
- Departments of Statistics, Biological Sciences, and Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, United States
| | - Alina T. Roman-Hubers
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, United States
| | - Fred A. Wright
- Departments of Statistics, Biological Sciences, and Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, United States
| | - Weihsueh A. Chiu
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, United States
| | - Thomas J. McDonald
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX 77843, United States
- Department of Environmental and Occupational Health, Texas A&M University, College Station, TX 77843, United States
| | - Rui Zhu
- Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station TX 77843, United States
| | - Galen Newman
- Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station TX 77843, United States
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, United States
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Cordova AC, Klaren WD, Ford LC, Grimm FA, Baker ES, Zhou YH, Wright FA, Rusyn I. Integrative Chemical-Biological Grouping of Complex High Production Volume Substances from Lower Olefin Manufacturing Streams. TOXICS 2023; 11:586. [PMID: 37505552 PMCID: PMC10385386 DOI: 10.3390/toxics11070586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 06/24/2023] [Accepted: 07/03/2023] [Indexed: 07/29/2023]
Abstract
Human cell-based test methods can be used to evaluate potential hazards of mixtures and products of petroleum refining ("unknown or variable composition, complex reaction products, or biological materials" substances, UVCBs). Analyses of bioactivity and detailed chemical characterization of petroleum UVCBs were used separately for grouping these substances; a combination of the approaches has not been undertaken. Therefore, we used a case example of representative high production volume categories of petroleum UVCBs, 25 lower olefin substances from low benzene naphtha and resin oils categories, to determine whether existing manufacturing-based category grouping can be supported. We collected two types of data: nontarget ion mobility spectrometry-mass spectrometry of both neat substances and their organic extracts and in vitro bioactivity of the organic extracts in five human cell types: umbilical vein endothelial cells and induced pluripotent stem cell-derived hepatocytes, endothelial cells, neurons, and cardiomyocytes. We found that while similarity in composition and bioactivity can be observed for some substances, existing categories are largely heterogeneous. Strong relationships between composition and bioactivity were observed, and individual constituents that determine these associations were identified. Overall, this study showed a promising approach that combines chemical composition and bioactivity data to better characterize the variability within manufacturing categories of petroleum UVCBs.
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Affiliation(s)
- Alexandra C Cordova
- Interdisciplinary Faculty of Toxicology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - William D Klaren
- Interdisciplinary Faculty of Toxicology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Lucie C Ford
- Interdisciplinary Faculty of Toxicology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Fabian A Grimm
- Interdisciplinary Faculty of Toxicology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Erin S Baker
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yi-Hui Zhou
- Departments of Statistics and Biological Sciences and Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27606, USA
| | - Fred A Wright
- Departments of Statistics and Biological Sciences and Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27606, USA
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
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Roman-Hubers AT, Cordova AC, Barrow MP, Rusyn I. Analytical chemistry solutions to hazard evaluation of petroleum refining products. Regul Toxicol Pharmacol 2023; 137:105310. [PMID: 36473579 PMCID: PMC9771979 DOI: 10.1016/j.yrtph.2022.105310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 11/26/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022]
Abstract
Products of petroleum refining are substances that are both complex and variable. These substances are produced and distributed in high volumes; therefore, they are heavily scrutinized in terms of their potential hazards and risks. Because of inherent compositional complexity and variability, unique challenges exist in terms of their registration and evaluation. Continued dialogue between the industry and the decision-makers has revolved around the most appropriate approach to fill data gaps and ensure safe use of these substances. One of the challenging topics has been the extent of chemical compositional characterization of products of petroleum refining that may be necessary for substance identification and hazard evaluation. There are several novel analytical methods that can be used for comprehensive characterization of petroleum substances and identification of most abundant constituents. However, translation of the advances in analytical chemistry to regulatory decision-making has not been as evident. Therefore, the goal of this review is to bridge the divide between the science of chemical characterization of petroleum and the needs and expectations of the decision-makers. Collectively, mutual appreciation of the regulatory guidance and the realities of what information these new methods can deliver should facilitate the path forward in ensuring safety of the products of petroleum refining.
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Affiliation(s)
- Alina T Roman-Hubers
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA
| | - Alexandra C Cordova
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA
| | - Mark P Barrow
- Department of Chemistry, University of Warwick, Coventry, CV4 7AL, United Kingdom
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA.
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Next Challenges for the Comprehensive Molecular Characterization of Complex Organic Mixtures in the Field of Sustainable Energy. Molecules 2022; 27:molecules27248889. [PMID: 36558021 PMCID: PMC9786309 DOI: 10.3390/molecules27248889] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 12/06/2022] [Accepted: 12/08/2022] [Indexed: 12/23/2022] Open
Abstract
The conversion of lignocellulosic biomass by pyrolysis or hydrothermal liquefaction gives access to a wide variety of molecules that can be used as fuel or as building blocks in the chemical industry. For such purposes, it is necessary to obtain their detailed chemical composition to adapt the conversion process, including the upgrading steps. Petroleomics has emerged as an integral approach to cover a missing link in the investigation bio-oils and linked products. It relies on ultra-high-resolution mass spectrometry to attempt to unravel the contribution of many compounds in complex samples by a non-targeted approach. The most recent developments in petroleomics partially alter the discriminating nature of the non-targeted analyses. However, a peak referring to one chemical formula possibly hides a forest of isomeric compounds, which may present a large chemical diversity concerning the nature of the chemical functions. This identification of chemical functions is essential in the context of the upgrading of bio-oils. The latest developments dedicated to this analytical challenge will be reviewed and discussed, particularly by integrating ion source features and incorporating new steps in the analytical workflow. The representativeness of the data obtained by the petroleomic approach is still an important issue.
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Roman-Hubers AT, Aeppli C, Dodds JN, Baker ES, McFarlin KM, Letinski DJ, Zhao L, Mitchell DA, Parkerton TF, Prince RC, Nedwed T, Rusyn I. Temporal chemical composition changes in water below a crude oil slick irradiated with natural sunlight. MARINE POLLUTION BULLETIN 2022; 185:114360. [PMID: 36413931 PMCID: PMC9741762 DOI: 10.1016/j.marpolbul.2022.114360] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 10/05/2022] [Accepted: 11/09/2022] [Indexed: 05/25/2023]
Abstract
Photooxidation can alter the environmental fate and effects of spilled oil. To better understand this process, oil slicks were generated on seawater mesocosms and exposed to sunlight for 8 days. The molecular composition of seawater under irradiated and non-irradiated oil slicks was characterized using ion mobility spectrometry-mass spectrometry and polyaromatic hydrocarbons analyses. Biomimetic extraction was performed to quantify neutral and ionized constituents. Results show that seawater underneath irradiated oil showed significantly higher amounts of hydrocarbons with oxygen- and sulfur-containing by-products peaking by day 4-6; however, concentrations of dissolved organic carbon were similar. Biomimetic extraction indicated toxic units in irradiated mesocosms increased, mainly due to ionized components, but remained <1, suggesting limited potential for ecotoxicity. Because the experimental design mimicked important aspects of natural conditions (freshly collected seawater, natural sunlight, and relevant oil thickness and concentrations), this study improves our understanding of the effects of photooxidation during a marine oil spill.
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Affiliation(s)
| | - Christoph Aeppli
- Bigelow Laboratory for Ocean Sciences, East Boothbay, ME, United States of America
| | - James N Dodds
- North Carolina State University, Raleigh, NC, United States of America
| | - Erin S Baker
- North Carolina State University, Raleigh, NC, United States of America
| | - Kelly M McFarlin
- ExxonMobil Biomedical Sciences, Clinton, NJ, United States of America
| | - Daniel J Letinski
- ExxonMobil Biomedical Sciences, Clinton, NJ, United States of America
| | - Lin Zhao
- ExxonMobil Upstream Research Company, Spring, TX, United States of America
| | | | | | - Roger C Prince
- Stonybrook Apiary, Pittstown, NJ, United States of America
| | - Tim Nedwed
- ExxonMobil Upstream Research Company, Spring, TX, United States of America
| | - Ivan Rusyn
- Texas A&M University, College Station, TX, United States of America.
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