Environmental Metabolomics: Applications in field and laboratory studies to understand from exposome to metabolome

Environmental Metabolomics Applications in Field and Laboratory Studies: From the Exposome to the Metabolome presents an overview of the current state of aquatic environments and problems caused by human pressure and daily life. The presence of contaminants in nature and their effects are evaluated, along with recommendations for preservation. This book not only shows readers how to implement techniques, it also guides them through the process. As metabolomics becomes a more routine technique for environmental studies and future perspectives, a guide for validation and globalization of current approaches is needed.

• Presents relevant and reliable information on the use of different analytical techniques for establishing the environmental metabolomics of polluted systems
• Includes a critical review of each central topic in every chapter, together with a bibliography and future trends
• Provides, for the first time, a global opinion and guide for achieving standardized results

• Language: English
• Publisher: Elsevier Science
• Release date: May 19, 2020
• ISBN: 9780128181973

Book preview

Environmental Metabolomics

Applications in Field and Laboratory Studies to Understand from Exposome to Metabolome

Edited by

Diana Álvarez-Muñoz

Marinella Farré

Water and Soil Quality Research Group, Department of Environmental Chemistry, IDAEA-CSIC, Barcelona, Spain

Table of Contents

Cover image

Title page

Copyright

Contributors

Preface

Acknowledgments

Chapter 1. Fundamentals of environmental metabolomics

1. Environmental stressors

2. Ecotoxicology

3. Metabolomics

4. Environmental metabolomics

5. Exposure to contaminant mixtures

6. Summary and environmental biomonitoring efforts

Chapter 2. Analytical techniques in metabolomics

1. Introduction

2. Sample preparation methods for metabolomics

3. Separation and identification methods

4. Summary and future trends

Chapter 3. Metabolic profiling of biofluids in fish for identifying biomarkers of exposure and effects for assessing aquatic pollution

1. Introduction

2. Metabolomics of biofluid

3. Methodological approach and platforms

4. Fish biofluid metabolome profiling in environmental studies

5. Advantages, drawbacks, and future perspectives

Chapter 4. Environmental metallomics and metabolomics in free-living and model organisms: an approach for unraveling metal exposure mechanisms

1. Introduction

2. Typical analytical approaches for environmental metallomics/metabolomics

3. Application of metallomics/metabolomics approaches to laboratory exposure experiments to toxic metals

4. Application of metallomics/metabolomics to environmental issues caused by metal exposure

5. Final remarks

Conflict of interest

Acknowledgments

Chapter 5. The metabolic responses of aquatic animal exposed to POPs

1. Introduction

2. Types and sources of pollution

3. Occurrence in the aquatic environment and biota

4. Toxic effects on aquatic animals

5. Application of metabolomics in aquatic animals for the profiling of POPs

6. Future challenges and possibilities

Chapter 6. Metabolomics in plant protection product research and development: discovering the mode(s)-of-action and mechanisms of toxicity

1. Introduction

2. Discovery and study of the MoA of PPPs and assessment of their toxicity using model biological systems employing metabolomics

3. R&D of the next-generation PPPs: focusing on the potential and contribution of metabolomics in the research on bioelicitors and nano-PPPs

4. Summary and future trends

Chapter 7. Metabolomics strategies and analytical techniques for the investigation of contaminants of industrial origin

1. Introduction

2. Metabolomics strategies for testing toxicity of chemicals from industrial origin

3. Analytical techniques

4. Future trends

Chapter 8. Mass spectrometry to explore exposome and metabolome of organisms exposed to pharmaceuticals and personal care products

1. Pharmaceuticals and personal care products are widespread in the environment

2. PPCPs can disturb the normal functioning of organisms

3. Contribution of high-resolution mass spectrometry–based approaches to exposome characterization

4. Metabolomics provides information on expected and unexpected molecular effects in organisms

5. Environmental metabolomics may contribute to the definition and application of adverse outcome pathways

6. Summary and future research

Chapter 9. Metabolomics effects of nanomaterials: an ecotoxicological perspective

1. Introduction

2. Metabolomics strategies

3. Common analytical tools for metabolomics

4. Metabolomics in nanotoxicology

5. Conclusions and future works

Chapter 10. Environmental metabolomics and xenometabolomics for the assessment of exposure to contaminant mixtures

1. Introduction

2. Application of metabolomics/xenometabolomics for chemical mixtures

3. Biomarkers discovering

4. Challenges and future research

Chapter 11. A snapshot of biomarkers of exposure for environmental monitoring

1. Introduction

2. Biomarkers' identity

3. Pathways disrupted

4. Conclusions and future trends

Chapter 12. Future trends in environmental metabolomics analysis

Index

Copyright

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Notices

Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary.

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Contributors

Konstantinos A. Aliferis

Pesticide Science Laboratory, Agriculture University of Athens, Athens, Greece

Department of Plant Science, McGill University, Sainte-Anne-de-Bellevue, QC, Canada

Diana Álvarez-Muñoz,     Water and Soil Quality Research Group, Department of Environmental Chemistry, IDAEA-CSIC, Barcelona, Spain

Francisca Arellano-Beltrán

Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Huelva, Spain

Research Center of Natural Resources, Health and the Environment (RENSMA), University of Huelva, Campus El Carmen, Huelva, Spain

Ana Arias-Borrego

Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Huelva, Spain

Research Center of Natural Resources, Health and the Environment (RENSMA), University of Huelva, Campus El Carmen, Huelva, Spain

Òscar Aznar-Alemany,     Water and Soil Quality Research Group, Department of Environmental Chemistry, IDAEA-CSIC, Barcelona, Spain

Julián Blasco,     Institute of Marine Sciences of Andalusia (CSIC), Campus Rio San Pedro, Cádiz, Spain

Bénilde Bonnefille,     HydroSciences, Univ Montpellier, CNRS, IRD, Montpellier, France

Belén Callejón-Leblic

Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Huelva, Spain

Research Center of Natural Resources, Health and the Environment (RENSMA), University of Huelva, Campus El Carmen, Huelva, Spain

Pedro Carriquiriborde,     Centro de Investigaciones del Medioambiente (CIM), Facultad de Ciencias Exactas, Universidad Nacional de la Plata – CONICET, La Plata, Buenos Aires, Argentina

Chien-Min Chen,     Department of Environmental Resources Management, Chia Nan University of Pharmacy & Science, Tainan, Taiwan

Frédérique Courant,     HydroSciences, Univ Montpellier, CNRS, IRD, Montpellier, France

Arthur David,     Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), UMR_S 1085, Rennes, France

Xiaoping Diao

State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou, Hainan Province, China

Ministry of Education Key Laboratory of Tropical Island Ecology, Hainan Normal University, Haikou, Hainan Province, China

Thibaut Dumas,     HydroSciences, Univ Montpellier, CNRS, IRD, Montpellier, France

Marinella Farré,     Water and Soil Quality Research Group, Department of Environmental Chemistry, IDAEA-CSIC, Barcelona, Spain

Hélène Fenet,     HydroSciences, Univ Montpellier, CNRS, IRD, Montpellier, France

Tamara García-Barrera

Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Huelva, Spain

Research Center of Natural Resources, Health and the Environment (RENSMA), University of Huelva, Campus El Carmen, Huelva, Spain

Ruben Gil-Solsona,     Catalan Institute for Water Research (ICRA), Parc Científic i Tecnològic de la Universitat de Girona, Girona, Spain

Elena Gomez,     HydroSciences, Univ Montpellier, CNRS, IRD, Montpellier, France

José Luis Gómez-Ariza

Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Huelva, Spain

Research Center of Natural Resources, Health and the Environment (RENSMA), University of Huelva, Campus El Carmen, Huelva, Spain

Awadhesh N. Jha,     University of Plymouth, Plymouth, Devon, United Kingdom

Vera Kovacevic

Department of Chemistry, University of Toronto, Toronto, ON, Canada

Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada

Marta Llorca,     Water and Soil Quality Research Group, Department of Environmental Chemistry, IDAEA-CSIC, Barcelona, Spain

Gema Rodríguez-Moro

Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Huelva, Spain

Research Center of Natural Resources, Health and the Environment (RENSMA), University of Huelva, Campus El Carmen, Huelva, Spain

Sara Rodríguez-Mozaz,     Catalan Institute for Water Research (ICRA), Parc Científic i Tecnològic de la Universitat de Girona, Girona, Spain

Pawel Rostkowski,     NILU – Norwegian Institute for Air Research, Kjeller, Norway

Sara Ramírez-Acosta

Department of Chemistry, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen, Huelva, Spain

Research Center of Natural Resources, Health and the Environment (RENSMA), University of Huelva, Campus El Carmen, Huelva, Spain

Albert Serra-Compte,     Catalan Institute for Water Research (ICRA), Parc Científic i Tecnològic de la Universitat de Girona, Girona, Spain

Myrna J. Simpson

Department of Chemistry, University of Toronto, Toronto, ON, Canada

Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada

Hailong Zhou

State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou, Hainan Province, China

School of Life and Pharmaceutical Sciences, Hainan University, Haikou, Hainan Province, China

Preface

Metabolomics consists of the simultaneous characterization of the metabolites present in an organism and offers a picture of the biochemistry of the organism at any one time. Its application to the environment, known as Environmental Metabolomics, allows characterizing the interaction that occurs between organisms and the surrounding environment. Concretely, this book is focused on the interaction between organisms and contaminants that are present in the environment due to human activities and may have toxic effects.

The application of metabolomics in the environmental field for biomarkers discovery is relatively new. Scientific papers on this subject started being published about 10 years ago, but it has been in the last 5 years when the application of metabolomics for analyzing biological samples in environmental monitoring has strongly attracted the attention of researches. Consequently, an increasing number of papers are currently been published generating a high amount of data that need to be compiled and harmonized to get relevant information.

This book gathers information on environmental metabolomics when natural organisms are exposed to metals, persistent organic pollutants, and emerging pollutants. It shows the reader different experimental setups, analytical techniques, data processing, and data analysis. This book will lead you through the metabolomics workflow and will serve as a guide for implementation. Besides, it allows, for the first time, to have general biomarkers snapshot very useful for risk assessment. It also discusses the current limitations and future perspectives of environmental metabolomics.

The audience of this book is wide-ranging from undergraduate to graduate students interested in environmental research, researchers in the field of environmental toxicology and chemistry, legislators, and policy-makers.

We, the Editors, learned a lot from the authors and hope that you readers also do. We expect that the knowledge contained here will help to further gain insight and advance on environmental metabolomics science.

Diana Álvarez-Muñoz

Marinella Farré

Acknowledgments

Huge thanks to all the people who have been involved in this project, especially to the authors; without their hard work, this book would not have been possible. Thanks to Elsevier, particularly to the acquisitions editor, the editorial project manager, and the production project manager. Finally, we are thankful to our families for their support, for understanding our passion for science, and all the time dedicated to this subject.

Chapter 1

Fundamentals of environmental metabolomics

Vera Kovacevic ¹ , ² , and Myrna J. Simpson ¹ , ²       ¹ Department of Chemistry, University of Toronto, Toronto, ON, Canada      ² Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada

Abstract

There has been much progress in environmental metabolomics research, and this chapter provides an overview of what environmental metabolomics is and the methods used and highlights some results from published works. A description of the experimental design and workflow commonly used in environmental metabolomics research is also included. The common analytical techniques used in environmental metabolomics and their advantages and disadvantages are discussed. Examples of published studies with different ecosystems are also included to highlight the utility and range of information that can be obtained from environmental metabolomics experiments. The objective of this chapter is to provide background information that will support the following chapters within this book.

Keywords

Ecotoxicology; Environmental stress; Mass spectrometry; Nuclear magnetic resonance spectroscopy; Soil contamination; Water contamination

1. Environmental stressors

1.1 Contaminant stressors

2. Ecotoxicology

3. Metabolomics

4. Environmental metabolomics

4.1 Study design

4.2 Collection of organisms and experimental exposure

4.3 Sample collection, sample preparation, and metabolite extraction

4.4 Analytical techniques for data collection

4.5 Raw data preprocessing and data analysis

4.6 Biological interpretation of the results

5. Exposure to contaminant mixtures

6. Summary and environmental biomonitoring efforts

References

1. Environmental stressors

Aquatic and terrestrial ecosystems are under constant threat from various environmental stressors that arise from natural or anthropogenic activities. Environmental stressors include biotic stressors such as pathogens and abiotic stressors such as drought, flood, extreme temperatures, and salinity (Nõges et al., 2016). The release of anthropogenic contaminants into the environment from urbanization, transportation, and industrial activities is also contributing to environmental stress (Schaeffer et al., 2016). Increases in the amount and variety of synthetic chemicals produced have caused contaminants to enter the environment at a very quick pace on a global scale (Bernhardt et al., 2017). The transport and fate of contaminants is governed by their physical–chemical properties which include water solubility, n-octanol–water partition coefficients (Kow), acid dissociation constants (pKa) or base dissociation constants (pKb), and vapor pressure (De Laender et al., 2015; Pereira et al., 2016). Environmental factors such as pH, sunlight intensity, temperature, and organic matter content also influence the transport and fate of contaminants in the environment (De Laender et al., 2015; Pereira et al., 2016). Some contaminants may be transported long distances to isolated regions and some contaminants may bioaccumulate in food webs (Gao et al., 2018; Xie et al., 2017). For instance, although metals are naturally occurring, anthropogenic activities have caused increased metal concentrations in the environment and metals often accumulate in organisms as they cannot be biodegraded (Peng et al., 2018a; Wise et al., 2018). Contaminants are frequently detected in all three environmental compartments of air, water, and soil (Gavrilescu et al., 2015; Net et al., 2015). Consequently, aquatic and terrestrial organisms are exposed to various classes of contaminants such as metals, persistent organic pollutants (POPs), pharmaceuticals and personal care products (PPCPs), industrial chemicals, plasticizers, flame retardants such as organophosphate esters, and pesticides (Peng et al., 2018b; van den Brink et al., 2016; Wilkinson et al., 2018).

1.1. Contaminant stressors

Contaminants of emerging concern (CECs) are not definitively defined, and there is no comprehensive list of CECs. Instead, CECs are thought to be any naturally occurring or anthropogenic compounds which are now detected or suspected to occur in soil, air, or water and whose persistence or toxicity may significantly alter the metabolism of an organism (Sauvé and Desrosiers, 2014). The United States Environmental Protection Agency's list of CECs includes POPs, PPCPs, veterinary medicines, endocrine-disrupting chemicals (EDCs), and nanomaterials (Ankley et al., 2008, Fig. 1.1). POPs are legacy pollutants that have existed and persisted in the environment for decades and include polychlorinated biphenyls, dibenzo-p-dioxins, dibenzofurans, and organochlorine pesticides such as dichlorodiphenyltrichloroethane (Nadal et al., 2015). The Stockholm Convention on POPs is an international environmental treaty that was initiated in 2001 to protect human health and the environment from POPs (Lallas, 2001). The screening criteria for POPs include persistence, bioaccumulation, potential for long range transport in the environment, and adverse impacts to organisms (McLachlan, 2018). Other organic contaminants such as PPCPs, veterinary medicines, and EDCs can more easily degrade in soil and water depending on their properties, but their extensive use has resulted in their frequent detection in the environment (Bártíková et al., 2016; Ebele et al., 2017; Song et al., 2018). Pharmaceuticals include over-the-counter medications and prescription drugs, and personal care products are in everyday products such as shampoos, hair dyes, toothpaste, and deodorants (Boxall et al., 2012). Veterinary medications include antibiotics, hormones, anesthetics, and antiparasitic and antifungal drugs (Bártíková et al., 2016). The main entry route of veterinary medications into the environment is from treatment of livestock, aquaculture, and companion animals (Bártíková et al., 2016). EDCs include alkylphenol compounds, natural estrogens, natural androgens, synthetic hormones, and some pharmaceuticals and pesticides (Omar et al., 2016). For instance, one of the most potent endocrine disruptors is the synthetic estrogen 17α-ethynylestradiol found in birth control pills (Laurenson et al., 2014). There are also contaminants of industrial origin such as perfluorinated compounds which can be found in common products such as furniture, carpets, cookware, and firefighting materials (von der Trenck et al., 2018). Terrestrial and aquatic ecosystems are typically exposed to a mixture of pesticides from agricultural applications, and runoff water can have pesticide concentrations that are substantially above the legal limit (Lefrancq et al., 2017). Nanomaterials have electronic and mechanical applications and are being increasingly detected in the environment, most likely from sewage treatment plant sludge and solid waste (Sun et al., 2016). The common detection of organic contaminants in surface waters is mainly due to the inability of conventional wastewater treatment methods to efficiently remove compounds such as PPCPs, veterinary medications, and EDCs (Hernández et al., 2015; Rice and Westerhoff, 2017; Yang et al., 2017). Organic contaminants also enter soil and groundwater when soil is irrigated with wastewater or when soil is fertilized with sewage sludge, and from municipal soil waste landfills (Healy et al., 2017; Prosser and Sibley, 2015). The detection of even very low concentrations of CECs in the environment has raised concerns because organisms are constantly exposed to inputs of CECs which may bioaccumulate to concentrations that could cause deleterious impacts in biota (Meador et al., 2016). The potential harmful impacts of CECs on ecosystem and human health have resulted in the development of toxicity tests and the assessment and management of environmental contamination.

Figure 1.1 Names and chemical structures of some well-known contaminants of emerging concern (CECs): (A) persistent organic pollutants (POPs), (B) pharmaceuticals and personal care products (PPCPs), (C) veterinary medicines, (D) endocrine-disrupting chemicals (EDCs), and (E) nanomaterials.

2. Ecotoxicology

Ecotoxicology has traditionally been described as the study of the toxic impacts of pollutants to ecosystem constituents, including animals, plants, and microorganisms (Truhaut, 1977). As such, environmental quality standards have been initiated to preserve ecosystems and human health by placing maximum permissible concentrations of contaminants that may be detected in water, soil, or biota (Lepper, 2005). Ecological risk assessment is generally done by comparing measured environmental concentrations (MECs) of a contaminant to its predicted no effect concentrations (PNECs) from ecotoxicological data which ideally represent the most sensitive species over several trophic levels (Papadakis et al., 2015). If the risk quotient calculated from the MEC/PNEC ratio is greater than one, then the contaminant is a concern and action should be undertaken to confirm the environmental risk, identify the sources of contamination, and reduce the release of contamination (Papadakis et al., 2015; Thomaidi et al., 2016).

Toxicologists have established and used acute toxicity tests on terrestrial and aquatic organisms based on mortality or immobilization rates with increasing contaminant concentrations (Bruce, 1985; Buckler et al., 2005). Most chronic toxicity tests also assess changes in development, growth, and reproduction parameters such as amount of offspring, time to first breeding, and number of broods (Thome et al., 2017; Toumi et al., 2013; Wang et al., 2006). Other tests have studied behavioral changes, mainly with fish, and these include changes in motor activity during light and dark photoperiods as well as the ability and length of time needed to catch prey (Gaworecki and Klaine, 2008; Kristofco et al., 2016). Since these approaches are not sensitive for very low sublethal concentrations of contaminants, new techniques were developed using biomarkers (Coppola et al., 2018; Valavanidis et al., 2006). A biomarker is defined as a biological response which includes any biochemical, physiological, histological, and morphological changes measured inside an organism that arise from contaminant exposure (Van Gestel and Van Brummelen, 1996). Substantive progress has been made in measuring biochemical impacts from contaminant exposure, and this includes measuring changes in biomarkers of oxidative stress, endocrine disruption, immunomodulation, xenobiotic detoxification systems, and DNA damage (Jasinska et al., 2015; Loughery et al., 2018; Valavanidis et al., 2006). Although biomarkers give important information about the potential deleterious impacts of contaminants on a biochemical level, they are not capable of evaluating the molecular mechanism of action of contaminants (Campos et al., 2012).

There is a need to study the mechanism or mode of action of contaminants to better understand the molecular processes of how organisms respond to contaminant stressors in the environment. Environmental omics research was initiated which involves the use of omics technologies to investigate the molecular-level responses of organisms to various environmental stressors (Martyniuk and Simmons, 2016). The omics techniques include genomics to study the structure, function, and expression of genes, transcriptomics to measure gene expression, proteomics to measure proteins and peptides, and metabolomics to measure metabolites which are the end products of cellular events (Loughery et al., 2018; Marjan et al., 2017; Revel et al., 2017). The data collected from omics techniques form a systems biology approach, and their integration into the field of ecotoxicology is referred to as ecotoxicogenomics (Snape et al., 2004). Also, omics technologies are sensitive and can detect changes in organism biochemistry at lower contaminant concentrations and more rapidly than conventional morality tests, reproduction tests, or cytotoxic evaluations (de Figueirêdo et al., 2019; Shin et al., 2018).

3. Metabolomics

Metabolomics is the use of advanced analytical techniques to identify and measure low-molecular weight metabolites that are generally less than 1000   Da in cells, tissues, biofluids, organs, or whole organisms (Gao et al., 2019; Lin et al., 2006). This includes primary metabolites which are involved in the development, growth, and reproduction of an organism as well as secondary metabolites which are produced by bacteria, fungi, and plants and have various ecological functions (Mazzei et al., 2016; Palazzotto and Weber, 2018). Metabolomics can be considered as the downstream process of genomics, transcriptomics, and proteomics, and the changes of metabolite levels directly relate to biochemical activity and the phenotype (Johnson et al., 2016). Fundamental metabolic pathways such as those involved in energy, carbohydrate, amino acid, and lipid metabolism are conserved from bacteria to eukaryotes (Peregrín-Alvarez et al., 2009). Metabolomics has applications in several fields including medicine (Wishart, 2016), pharmacology (Pang et al., 2018), toxicology (Ramirez et al., 2018), plant biochemistry (Skliros et al., 2018), and the environmental sciences (Zhang et al., 2018a).

The main analytical techniques that are used to collect metabolomics data sets are nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) because of the ability for small molecule detection and the unique assets of each analytical instrument. Targeted metabolomics analysis detects a predetermined set of metabolites, usually chosen with regard to the biological sample to be analyzed or from metabolite libraries in software databases (Bingol, 2018). Nontargeted metabolomics analysis is the nonbiased analysis of as many metabolites that can be reliably identified and assigned by the analytical instrument and metabolomics databases (Bingol, 2018). Nontargeted metabolomics analysis frequently uses NMR spectroscopy or high resolution MS, while targeted metabolomics analysis often uses MS as the analytical method of choice (Emwas, 2015; Mullard et al., 2015). There are around 114,000 metabolites listed in the Human Metabolome Database (Wishart et al., 2017), but only around 1500 metabolites are identified in nontargeted analysis, 200–500 metabolites are identified in targeted analysis, and it is estimated that less than two dozen metabolites are regularly quantified in most metabolomics studies (Markley et al., 2017; Psychogios et al., 2011). Once metabolites are identified and quantified, online databases and tools may be used to aid in data interpretation and mechanistic understanding by relating the changes in metabolite levels to metabolic pathways that are likely impacted (Chong et al., 2018; Kanehisa et al., 2016). Through this process, metabolomics gives detailed information about the mode of action that may be occurring in the biological sample and may be used for high-throughput testing of individual contaminants and mixtures (Ahmed et al., 2019; Zampieri et al., 2018).

4. Environmental metabolomics

Environmental metabolomics involves applying metabolomic techniques to analyze the metabolic response of organisms as a result of their interactions with the environment (Bundy et al., 2009). Metabolomics is used to study various environmental stressors including UV light (Zhang et al., 2018b), elevated atmospheric carbon dioxide concentration (Creydt et al., 2019), ambient fine particulate matter (Xu et al., 2019), drought (Li et al., 2018b), extreme temperatures (Tomonaga et al., 2018), and contaminants (Roszkowska et al., 2018). Controlled laboratory exposures with target species are performed to acquire knowledge of the mode of action of abiotic stressors, biotic stressors, or contaminants (Garreta-Lara et al., 2016; Sivaram et al., 2019; Tang et al., 2017). Furthermore, field-based studies may be conducted to understand how the metabolome of organisms is impacted when exposed to an ecosystem under environmental stress (Gauthier et al., 2018). One of the goals of environmental metabolomics research is for utilization in environmental biomonitoring and risk assessment by applying metabolomics techniques to keystone organisms that play important roles in trophic levels and food webs (Bahamonde et al., 2016). To achieve these aims, environmental metabolomics studies have a workflow that includes study design, exposure, sample preparation, metabolite extraction, data collection, data analysis, and finally a biological interpretation of the analyzed data.

4.1. Study design

The experimental design of environmental metabolomics projects involves the selection of an environmental stressor and the target organism. Environmental metabolomics studies are done on a variety of organisms which span from microorganisms to plants and animals (Sivaram et al., 2019; Tian et al., 2017; Tomonaga et al., 2018). Microorganisms have been exposed to environmental contaminants, for instance, the yeast Saccharomyces cerevisiae has been exposed to copper (Farrés et al., 2016) and tetrachlorobisphenol A (Tian et al., 2017). Plant metabolomics has investigated the exposure to nanoparticles (Zhang et al., 2018a), how plants respond to polycyclic aromatic hydrocarbons or metals from remediation efforts (Pidatala et al., 2016; Sivaram et al., 2019), the impact of mineral deficiency (Sung et al., 2015), UV-B radiation (Zhang et al., 2018b), and drought (Khan et al., 2019). Common terrestrial organisms used in environmental metabolomics studies include nematodes (Ratnasekhar et al., 2015), earthworms (Tang et al., 2017), flies (Cox et al., 2017), and mice (Wang et al., 2018a). The choice of organism should reflect the environmental compartment under consideration, for instance, earthworms are commonly used to assess soil contamination in metabolomics studies due to their occurrence in a variety of soils worldwide (He et al., 2018; Tang et al., 2017). Aquatic organisms frequently used in environmental metabolomics studies include crustaceans (Garreta-Lara et al., 2016; Gómez-Canela et al., 2016) and fish such as medaka, rainbow trout, salmon, and fathead minnow (Kaneko et al., 2019). The studied aquatic organism should also reflect the research question, for instance, bivalves have a sessile lifestyle and can accumulate contaminants, and therefore an analysis of the metabolic profile of bivalves may reflect the contamination at the site of collection (Watanabe et al., 2015). Metabolomics studies may also be performed on a targeted selection of organisms that serve as research models. Model organisms may be represented by the rat and mouse for mammals, zebrafish Danio rerio for aquatic vertebrates, the water flea Daphnia magna for aquatic invertebrates, Arabidopsis thaliana for plants, the yeast S. cerevisiae for eukaryotes, and Escherichia coli for prokaryotes (Kim et al., 2015; Reed et al., 2017).

4.2. Collection of organisms and experimental exposure

Environmental metabolomics studies may be field-based where organisms are sampled directly from the environment or laboratory-based where organisms are cultured in the laboratory and then exposed under controlled conditions (Campillo et al., 2019; Davis et al., 2016). Both laboratory and field research should have careful planning of the number and type of control or reference site exposures and environmental stressor exposures, as well as the number of samples to be taken from each treatment group. This is important as there is natural variation in biological samples and adequate replication is needed for proper statistical analysis (Simmons et al., 2015). Regarding field-based work, there is the option of field trials which involves the sampling of free-living organisms in the environment (Gauthier et al., 2018; Melvin et al., 2018, 2019) or there is the option of field deployment which involves deploying organisms into environments that are under stress (Ekman et al., 2018). In field-based studies, the organisms that represent the stressor-exposed groups may be collected at contaminated locations and may be compared to organisms collected at more pristine locations which serve as the group from a reference site (Watanabe et al., 2015). Environmental metabolomics studies that sample free-living organisms at a field site are a step forward for validating this technique for use in environmental monitoring (Melvin et al., 2018, 2019). Also, using field-deployed organisms has a great value for environmental risk assessment. For instance, a study that used cage-deployed fathead minnows (Pimephales promelas) at sites across the Great Lakes basin noted that the profiles of endogenous polar metabolites had covariance with at most 49 contaminants (Davis et al., 2016). Taking organisms from the field takes into consideration the natural variation from different locations, for example, there are correlations between the metabolome of the pine tree (Pinus pinaster) and its original geographic origin even when grown in a common garden for 5   years (Meijón et al., 2016). Sampling organisms from the field also considers the individual variability, which may stem from genetic differences, in the metabolic profile of these organisms as they are not only one laboratory strain (Quina et al., 2019). Understanding the metabolic response of organisms which are sampled from the field may be challenging because field populations may be exposed to multiple stressors at once, including both abiotic and biotic stressors as well as contaminant stressors (Garreta-Lara et al., 2018; Mishra et al., 2019). The choice of organisms should be as close as possible to identical age and size to minimize natural variation in populations (Coppola et al., 2018). However, when sampling organisms from the field it may be difficult to distinguish gender, different life stages, and species, for instance, DNA barcoding is used to distinguish species of the genus Atlantoscia, a terrestrial isopod (Zimmermann et al., 2018). Organisms sampled from the environment have various factors that may impact the metabolome which should be recorded, such as season and geographic location (Wei et al., 2018), climate (Gargallo-Garriga et al., 2015), disease (Zacher et al., 2018), and habitat surroundings (Quina et al., 2019). Also, it is a challenge to be certain of all the current environmental stressors present at the time of collection and the history of organism exposure to environmental stressors (Olsvik et al., 2018). Field-based studies also face the difficultly of locating an ideal reference site that can act as a control which has minimal abiotic, biotic, and contaminant stressors but where the natural settings are analogous to the impacted site (Martyniuk, 2018). However, to aid in the metabolomics analysis and interpretation of field-based studies, there are standard reporting requirements for metabolomics experiments of biological samples taken from the environment (Morrison et al., 2007).

Laboratory populations are strictly controlled, and temperature, light, and diet are maintained constantly to limit any perturbations to the metabolome. Laboratory-based studies have the benefit of standard protocols that are available, for instance, the Organisation for Economic Co-operation and Development provides guidance documents for aquatic toxicity testing and soil toxicity testing that should be followed for laboratory work (OECD, 2002, 2004). Controlled laboratory conditions are optimal for determining the mode of action of contaminants as the metabolic perturbations can be directly accredited to the stressor (Gómez-Canela et al., 2016). For this reason there are standard reporting requirements for metabolomics experiments of mammalian/in vivo work (Griffin et al., 2007) and for metabolomics experiments of microbial and in vitro work (van der Werf et al., 2007). The route of exposure, such as dosing, air-borne inhalation, aqueous exposure, and others, should be carefully selected and documented (van der Werf et al., 2007). Although the metabolic disturbances from exposure to stressors in laboratory conditions can be extrapolated to predict the hazard in environmental settings, care must be taken when doing so to avoid an overestimation or an underestimation of risk (Murphy et al., 2018).

4.3. Sample collection, sample preparation, and metabolite extraction

The decision of which biological sample to analyze is important since different metabolic responses can be found across cells, tissues, organs, biological fluids, and the whole organism (Tavassoly et al., 2018). There are advantages of choosing each biological compartment. For instance, using cell cultures provides specific information on the metabolic pathways involving the changes of endogenous metabolites in cells, and different cell lines may have different metabolic alterations (Rodrigues et al., 2019). The metabolomics analysis of a certain tissue can give information about the state of an organ and different tissues of an organism contain different baseline metabolic profiles (Cappello et al., 2018). The collection of a biofluid such as blood or urine is minimally invasive and can provide information about the overall biological state of an organism (Liao et al., 2018).

Compared to DNA sequences which can be extracted from samples over 100,000 years old (Rohland et al., 2018), metabolite samples are highly unstable and there may be additional changes in metabolite levels from residual enzymatic activity (Bernini et al., 2011). Therefore, proper sample preparation is important to avoid any disturbances in the metabolome that may occur from preparing samples. Sample preparation procedures may need to quickly halt enzymatic activity with freezing in liquid nitrogen and samples must be kept cold throughout any storage (Bernini et al., 2011). Some sample types need to have water removed for analysis by NMR spectroscopy, for instance, tissue samples need to be lyophilized soon after collection and the solvent extracts of cell cultures need to be dried and reconstituted in an NMR buffer (Beckonert et al., 2007; Carrola et al., 2018). NMR-based metabolomics most frequently uses a deuterium oxide phosphate-based buffer which extracts polar metabolites (Beckonert et al., 2007). The phosphate buffer maintains a constant pH to minimize variations in chemical shift and a deuterated solvent allows for a lock signal in NMR spectroscopy (Schripsema, 2010). The metabolite extraction procedure for MS analysis typically uses solvents of varying polarity to extract polar and nonpolar metabolites and several extraction methods are based on the widely used Bligh and Dyer extraction (Bligh and Dyer, 1959; Wu et al., 2008). The metabolite extraction method must be developed and verified because one extraction protocol is usually not able to extract all the metabolites from the sample. Also, the metabolite extraction method depends on the biological matrix chosen to be analyzed, and there are well-developed protocols for metabolite extractions from mammalian and bacterial cell cultures (Dietmair et al., 2010; Winder et al., 2008), biological fluids such as blood and urine (Beckonert et al., 2007; Bruce et al., 2009), and plant- and animal-derived tissues (Valledor et al., 2014; Wu et al., 2008). To extract metabolites from cells, cold solvents such as aqueous methanol or aqueous acetonitrile are applied to cell cultures to quench the metabolism of cells (Dietmair et al., 2010; Rodrigues et al., 2019). For biological fluids such as blood, there is usually a protein precipitation step to isolate proteins from the metabolite sample by treatment with a solvent mixture such as methanol/ethanol or methanol/acetonitrile/acetone (Bruce et al., 2009). Urine samples typically have simple sample preparation and involve sample dilution with appropriate solvents or ultrafiltration (Khamis et al., 2017). For tissue samples or whole organism homogenates, there is manual grinding or homogenization with precooled extraction solvents such as methanol (Römisch-Margl et al., 2012). Tissue samples or small whole organism homogenates may be further sonicated to enhance the extraction efficiency (Wang et al., 2018b). Finally, centrifugation