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Environmental Sciences
Human beings and wild organisms are exposed daily to a broad range of environmental stressors. Among them are the persistent organic pollutants that can trigger adverse effects on these organisms due to their toxicity properties. There is evidence that metabolomics can be used to identify biomarkers of effect by altering the profiles of endogenous metabolites in biological fluids or tissues. This approach is relatively new and has been used in vitro studies mainly.
- metabolomics
- biomarkers
- POPs
- disease
- environmental exposure
1. Introduction
The presence of a wide range of compounds in the environment, coming from anthropogenic sources such as industrial processes, agricultural activities, combustion of wood and fossil fuels, incinerators, and uncontrolled landfills, has generated a negative impact on ecosystems, representing a risk for the wildlife and human health [1]. Compounds include the persistent organic pollutants (POPs), a variety of organic chemicals that feature a slow rate of biological, photolytic, and chemical degradation [2]. Due to these characteristics, the POPs can persist for an extended period in the environment, even at trace concentrations. POPs can be found in various environmental compartments, such as air [3], soil [4], food [5,6], sediments, and water [7]. Likewise, they can be transported long distances by wind and water currents, far from where they are used and released [8,9,10]. Their high lipid solubility gives rise to accumulation in fatty tissue and passes from one lower trophic level to the next through the food chain. They can enter the body through inhalation, ingestion, and dermal pathway [11].
The POPs are toxic chemicals of significant concern that adversely affect wildlife and human health worldwide. Endocrine disruption, reproductive, hepatic, neurological, and immune dysfunction, behavioral changes, and mutagenic and carcinogenic effects have been reported [12,13,14,15,16,17].
To address this global concern, diverse countries joined forces to sign and establish the Stockholm Convention, which came into force in 2004, and is a mechanism to protect human health and the environment by reducing or eliminating the production, use, and/or release of POPs. Currently, 30 pollutants are regulated by categories: A) subject to elimination of production and use, B) restriction of production and use c) reduction of unintentional release (Table 1) [18].
Table 1. POPs considered in the Stockholm Convention.
| Classification | ||||||
|---|---|---|---|---|---|---|
| POPs | A | B | C | Pesticides | Industrial Chemicals | Unintentional Production |
| Perfluorooctanoic acid (PFOA), its salts and related compounds with PFOA |
x | x | ||||
| Perfluorooctane sulfonic acid, its salts and Perfluorooctane sulfonyl fluoride |
x | x | x | |||
| Aldrin | x | x | ||||
| Polychlorinated biphenyls (PCB) | x | x | x | x | ||
| Chlordane | x | x | ||||
| Chlordecone | x | x | ||||
| Dichlorodiphenyltrichloroethane (DDT) | x | x | ||||
| Decabromodiphenyl ether (commercial mixture, c-decaBDE) | x | x | ||||
| Polychlorinated dibenzofurans (PCDF) | x | x | ||||
| Polychlorinated dibenzo-p-dioxins (PCDD) | x | x | ||||
| Dicofol | x | x | ||||
| Dieldrín | x | x | ||||
| Technical endosulfan and its related isomers | x | x | ||||
| Endrin | x | x | ||||
| Heptachlor | x | x | ||||
| Hexabromobiphenyl | x | x | ||||
| Hexabromocyclododecane (HBCDD) | x | x | ||||
| Hexabromodiphenyl ether and heptabromodiphenyl ether | x | x | ||||
| Hexachlorobenzene (HCB) | x | x | x | x | x | |
| Hexachlorabutadiene (HCBD) | x | x | x | x | ||
| Lindane | x | x | ||||
| Mirex | x | x | ||||
| Polychlorinated naphthalenes | x | x | x | x | ||
| Short-chains chlorinated paraffin (PCCC) | x | x | x | x | ||
| Pentachlorobenzene | x | x | x | x | x | |
| Pentachlorophenol and its salts and esters | x | x | ||||
| Tetrabromodiphenyl ether and pentabromodiphenyl ether | x | x | ||||
| Toxaphene | x | x | ||||
| α-hexachlorocyclohexane | x | x | ||||
| β- hexachlorocyclohexane | x | x | ||||
Once POPs enter the environment, wildlife and human beings are exposed to them. Consequently, various methodologies have been designed to assess or estimate the potential risk that the POPs pose to biota, which involves environmental analysis and mathematical modeling. The first encompasses measuring a broad range of analytes incorporated into environmental matrices using highly sensitive analytical instruments and techniques. The second methodology implies mathematical tools useful for simulating the physicochemical processes involved in the environmental kinetics and bioavailability of pollutants [19].
However, the risk estimation through the environmental assessment is not enough to guarantee the absence of adverse effects because both the individual compounds and the mixture or their possible transformations can modify their toxicity mechanism. From there, standardized toxicity assays can be employed to assess organisms’ responses; lethality and reproductive bioassays test to measure alterations in clinical signs and histopathological abnormalities [20]. Nevertheless, these techniques have limitations by ignoring the systemic effects produced by the pollutants. For this reason, new tools have been developed over the last two decades, such as omic biomarkers, which include the analysis of a set of molecular data, especially genomic, proteomic, and metabolomic biomarkers, to elucidate adverse effects and possible mechanisms of toxicity [21].
Omic biomarkers are promising tools for detecting subclinical effects associated with exposure to environmental pollutants and therefore play an essential role in risk assessment. However, in order for them to reach their maximum potential, their validation is required, through well-structured studies, analyzing and relating the exposure to a compound with the response of a biomarker or sets of them and deciphering that response as a transitory or specific event [22].
Omics are a set of disciplines focused on obtaining a significant quantity of molecules involved in the functioning of an organism. Accordingly, these have been included in diverse fields of study to delve into and improve the collection of specific responses on the effects caused by environmental stressors [23].Among these fields comes ecotoxicogenomics, defined as the integration of omics technology in ecotoxicology studies [24]. That is to say, it is the study of gene expression (Genomics), proteins (Proteomics), and the identification–quantification of endogenous and/or exogenous metabolites (Metabolomics) in wildlife and human population as the response in the light of exposure to environmental pollutants [25,26,27]. It is becoming a promising tool by increasing the sensitivity and specificity of other risk assessment criteria. It has elucidated the mechanisms of pollutants toxicity and helped us to understand how environmental toxicants are associated with responses at complex organizational levels such as populations and ecosystems, and has also contributed to the monitoring of adverse effects in organisms exposed to polluted environments [23,27,28].
The application of ecotoxicogenomics is still at a starting point. Most studies currently have been carried out on model organisms under controlled conditions. However, the challenge is to assess the risk to wildlife under natural conditions to better understand population dynamics [19].
2. Metabolomics
One of the tools employed for ecotoxicogenomics is metabolomics, which takes charge of a comprehensive analysis of endogenous and exogenous metabolites in cells, tissues and/or biofluids in response to diverse factors such as lifestyle, genetic effects, various pathologies, and environmental stressors [29].
The Human Metabolome Database (HMDB) currently lists around 250,000 total metabolites [30,31]. They perform multiple functions in the body, including signaling cascades, energy production, and macromolecule synthesis. Consequently, a metabolic alteration can unleash an adverse effect or exacerbate an existing one [29,32]. Such an alteration can correspond to the modification of a specific metabolite or the changes pattern of several metabolites. Therefore, their identification has become a new generation of biomarkers [33].
Furthermore, metabolomics has advantages over other omic technologies, such as processing a smaller number of biomolecules compared to the amount analyzed in genomics and proteomics. Likewise, metabolites have a well-conserved chemical structure in all organisms representing the final products of the cell regulatory processes. Therefore, the response of biological systems facing a variety of stressors is being best represented by it. In addition, the biological sample collection is less invasive, allowing multiple measurements to assess the temporal effects. On the other hand, the concentration of metabolites can change significantly, even though an enzyme concentration or metabolic fluxes does not alter [34,35].
The high sensitivity and efficacy of metabolomics in analyzing the metabolic pathways responses in cells, tissues, and biofluids exposed to environmental stressors promises to be important in the ecological risk assessment through the identification of new biomarkers and toxicity mechanism of pollutants [36].
3. Methodologies and Techniques in Metabolomics
In general, metabolomics studies follow a steps sequence to obtain the desired results: (1) study purpose, (2) sample collection and processing, (3) metabolite detection and quantification, and (4) data processing.
The first step is to determine the focus of the study to be conducted. For this, it is necessary to define whether analyzing as many metabolites as possible or only a specific group is required. Regarding the former, metabolomics has two approaches: untargeted and targeted focus [37]. The first one concerns obtaining data about the modifications of the greatest number of metabolites found in the sample, which allows for generating a hypothesis that gives way to more specific studies. The second approach is aimed to identify and quantify a finite number of metabolites according to the pre-established research hypothesis [38].
The second step is crucial in metabolomics analyses because it consists of collecting and processing the sample. However, acquiring and preserving samples under optimal conditions is essential to achieve adequate, reliable, and comparable results [39]. Blood plasma [40], urine [41], saliva [42], and amniotic fluid [43] are the biofluids most used by metabolomics, as well as different cells and tissues [44].
Depending on the biofluid or tissue, a specific treatment is carried out to extract the sample metabolites. In most cases, this consists of applying extraction techniques in a solid or liquid phase. Once the extracts have been obtained, they are stored at low temperatures until analysis [45].
Thirdly, metabolomics detects and quantifies metabolites using Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS) techniques. NMR is commonly used in untargeted exploratory screening, and its advantages include its speed and high reproducibility by measuring multiple metabolites at once without requiring complex processing and sample destruction. The quantification of metabolites is carried out by comparing the areas of the spectral peaks with the internal reference standard. NMR provides partial information on the chemical structure of the molecule. As a disadvantage, NMR has low sensitivity and resolution compared to MS techniques [45].
On the other hand, MS requires sample processing through the use of separation techniques such as gas chromatography (GC) and high-performance liquid chromatography (HPLC) [46,47]. Usually, this process is complex because several chromatographic separations are often necessary (up to 72 h per sample), and specialized staff is required [48]. However, its sensitivity is high thanks to the extensive development of mass analyzers that allow both qualitative and quantitative metabolite profiles to be obtained. Major analyzers include single, triple, and time-of-flight (Q-TOF) quadrupole instruments, Ion Cycloton Resonance (ICR-FTMS), and Orbitrap, making it ideal for targeted analysis [49,50,51].
Using tandem mass spectrometry (MS/MS) is very useful for analyzing target compounds at trace levels (ppt-ppb range), and when high chemical noise is observed or the co-elution of characteristic ions. When the structure of the compound is unknown and/or additional structural information is required, MS/MS should be used. MS/MS exhibits higher sensitivity and specificity of the assay, especially in very complex matrices with the presence of interferences, such as fluid and tissue samples [52].
As the fourth step, data processing is accomplished, which turns out to be the most challenging since it consists of obtaining the raw data from the analytical techniques employed and converting them into data that allow the metabolites to be easily identified in data mining afterward. Once the raw data have been collected, these are analyzed through a database or spectral library searching; some used are Human Metabolome Database (HMDB), METLIN, MetaboLights, the Metabolomics Workbench, and Lipid Maps, KEGG, MassBank, SpectraBase, and BMRB) [30].
After this identification, the data sets are usually vast, so data mining tools are employed. For example, principal components analyses, partial least squares, discriminant analyses, and orthogonal projection to latent structures are used to identify significant differences, patterns, or correlations among data groups [53].
Finally, the pathways involved in the metabolic profile molecules are analyzed, thus identifying those that may be participating in a particular disease. For this, various databases contain pathways of multiple organisms, such as KEGG, Reactome, HumanCyc, SMPDB, HMDB, and MetaboAnalyst [54]. The latter is the most widely used (>300,000 users) as it allows high-throughput analysis in targeted and non-targeted metabolomics and integrates pathway topology and enrichment analysis for 26 model organisms with over 1600 pathways [55].
This entry is adapted from the peer-reviewed paper 10.3390/toxics10070380
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