Oxidative stress is an important consequence associated with cigarette smoke. The oxidants produced or found in cigarette smoke can react with and damage cellular macromolecules including proteins, DNA, and lipid membranes. Additionally, these oxidants can act as signaling molecules that can influence cell proliferation (Faux et al., 2009). However, cells

Metabolomics Approach for Hazard Identification in

exposure to cigarette smoke.

responses to chemical exposures.

**biochemical perturbations**

**assessment**

Human Health Assessment of Environmental Chemicals 357

2006; Spira et al., 2004) and proteomic (Carter et al., 2011; Kelsen et al., 2008; Zhang et al., 2008) investigations that also detected markers associated with the pathways affected by

Conversely, the integration of "omics" technologies has also demonstrated some limitations. For example, a study by Steiling and co-workers found a discrepancy between genomic and proteomic data. Specifically, gel electrophoresis followed by LC-MS analysis identified 41 proteins whose expression would not have been detected by microarray analysis (Steiling et al., 2009). Such data highlight the importance of assessing more downstream markers (i.e. proteins or metabolites) that may provide a more accurate understanding of the biological

Historically, human health risk assessment relied on identifying apical endpoints, defined as "observable outcomes in a whole organism, such as a clinical sign or pathologic state, indicative of a disease state that can result from exposure to a toxicant", such as birth defects, neurologic deficits, and tumor number that are obtained from high-dose animal bioassays (Krewski et al., 2010). However, the mechanistic relevance of these data can be tenuous considering the need for interspecies extrapolation and that environmental exposures may be orders of magnitude lower. Recently, the NRC report on "*Toxicity Testing in the 21st Century: A Vision and Strategy*" suggested a fundamental change in the risk assessment paradigm where the reliance on apical endpoints of toxicity would be replaced in favor of *in vitro* toxicity testing for identifying perturbations in biochemical pathways. Such an approach would employ cell lines, particularly human-based lines, and high throughput screening assays (e.g. genomics, proteomics) with computational toxicology methods. As a result, this approach would also lead to an overall increase in the efficiency of toxicity testing and decrease in animal usage [as reviewed in (Krewski et al., 2010)]. As pointed out by the NRC committee, the use of these low-dose, human-based *in vitro* systems would negate concerns associated with high-dose, animal data. Since metabolomics can identify early perturbations in biochemical pathways, this technology is poised to become

**7. Shift in the risk assessment paradigm from apical endpoints to**

an important element of this proposed risk assessment paradigm.

**8. Advantages of metabolomics approach for environmental chemical**

Metabolomics approach offers several advantages for understanding the mechanisms of toxicity of environmental chemicals and informing human health assessments. One advantage of the metabolomics approach is the relatively non-invasive (e.g. urine samples) nature of this technique. In this context, samples from humans subjected to an incidental environmental exposure can be easily collected, analyzed, and correlated to metabolomic profiles from animal studies in order to identify critical effects from the exposure. Aside from quantitative differences, metabolic pathways are evolutionally conserved across different species; metabolomics data can be qualitatively extrapolated or interpreted at the molecular level among and between species. Unlike genomics and proteomics, metabolomics databases offer information on the structural, physicochemical,

contain antioxidant defenses, such as GSH to prevent oxidative damage (Rahman & MacNee, 1999). The metabolomics approach has indeed found changes in metabolites associated with these effects of cigarette smoke. Predominant changes in metabolites from exposure to WS included glutathione and -glutamylglutamine, which showed 51 and 13 fold increases compared to control cells. The increased levels of metabolites within the glutathione pathway (i.e. glutathione and -glutamylglutamine) suggest a protective response against oxidative stress, which can result from WS. These data correlate with human microarray data that demonstrated an antioxidant response to cigarette smoke through the induction of genes associated with glutathione metabolism (Spira et al., 2004). Further, Vulimiri and colleagues (Vulimiri et al., 2009) observed increased levels (16.4-fold) of *o*-phosphoethanolamine, a marker of phospholipid degradation that may indicate cell membrane damage. Additional observations included increased arachidonic acid levels that may suggest an inflammatory response and markers (e.g. putrescine) of cell proliferation.

Conversely, there was a statistically significant decrease in glutathione levels from exposure to WTPM and GVP when compared to controls. Predominant metabolite changes in these phases were acetylcarnitine (4.5-fold increase) and palmitoleate (5.2-fold increase) for WTPM and GVP, respectively, both of which indicated changes in lipid metabolism (Vulimiri et al., 2009). In summary, these authors (Vulimiri et al., 2009) demonstrated how metabolomics could differentiate metabolic responses caused by exposure to complex mixtures (i.e. cigarette smoke) and also provided empirical data for metabolic changes for known markers of toxicity (e.g. decreased GSH, membrane damage) associated with exposure to cigarette smoke.

#### **6. Integrating "omics" data into risk assessment**

The field of toxicology is advancing with several of the high throughput screening techniques taking major roles in understanding toxicity pathways. More specifically toxicogenomics and proteomics have contributed to identifying the mechanisms of toxicity pathways (Burchiel et al., 2001; Heijne et al., 2005). Integration of data from different "omics" approaches would help clarify the mode of action of xenobiotics especially at low dose levels, which are relevant to environmental exposures. Thus, combining "omic" techniques such as toxicogenomics, transcriptomics, proteomics, and metabolomics promises to provide a robust understanding of biological responses to xenobiotics. Under this paradigm, effects on genes and their downstream products, namely proteins and the metabolites produced by proteins, can be assessed together. Researchers have utilized diverse "omics" approaches to understand the mode(s) of action or mechanism of different toxicity pathways in various experimental models. Some studies have indeed shown a good correlation between the genomics and metabolomics approaches. For example, metabolomics approach has demonstrated alterations in the pathways associated with lipid peroxidation, DNA damage and repair, and cell proliferation in rats exposed to CCl4 which was consistent with the expression of transcripts associated with steatosis/fibrosis that were specific to cell injury and regeneration (Chung et al., 2005a; Chung et al., 2005b; Fountoulakis et al., 2002). Additionally, metabolomics has identified biochemical alterations in pathways associated with oxidative stress, inflammation, cell proliferation, and cytotoxicity in human lung epithelial cells exposed to cigarette smoke (Vulimiri et al., 2009). These observations are supported by data from genomic (Harvey et al., 2007; Meng et al.,

contain antioxidant defenses, such as GSH to prevent oxidative damage (Rahman & MacNee, 1999). The metabolomics approach has indeed found changes in metabolites associated with these effects of cigarette smoke. Predominant changes in metabolites from exposure to WS included glutathione and -glutamylglutamine, which showed 51 and 13 fold increases compared to control cells. The increased levels of metabolites within the glutathione pathway (i.e. glutathione and -glutamylglutamine) suggest a protective response against oxidative stress, which can result from WS. These data correlate with human microarray data that demonstrated an antioxidant response to cigarette smoke through the induction of genes associated with glutathione metabolism (Spira et al., 2004). Further, Vulimiri and colleagues (Vulimiri et al., 2009) observed increased levels (16.4-fold) of *o*-phosphoethanolamine, a marker of phospholipid degradation that may indicate cell membrane damage. Additional observations included increased arachidonic acid levels that may suggest an inflammatory response and markers (e.g. putrescine) of cell proliferation. Conversely, there was a statistically significant decrease in glutathione levels from exposure to WTPM and GVP when compared to controls. Predominant metabolite changes in these phases were acetylcarnitine (4.5-fold increase) and palmitoleate (5.2-fold increase) for WTPM and GVP, respectively, both of which indicated changes in lipid metabolism (Vulimiri et al., 2009). In summary, these authors (Vulimiri et al., 2009) demonstrated how metabolomics could differentiate metabolic responses caused by exposure to complex mixtures (i.e. cigarette smoke) and also provided empirical data for metabolic changes for known markers of toxicity (e.g. decreased GSH, membrane damage) associated with

The field of toxicology is advancing with several of the high throughput screening techniques taking major roles in understanding toxicity pathways. More specifically toxicogenomics and proteomics have contributed to identifying the mechanisms of toxicity pathways (Burchiel et al., 2001; Heijne et al., 2005). Integration of data from different "omics" approaches would help clarify the mode of action of xenobiotics especially at low dose levels, which are relevant to environmental exposures. Thus, combining "omic" techniques such as toxicogenomics, transcriptomics, proteomics, and metabolomics promises to provide a robust understanding of biological responses to xenobiotics. Under this paradigm, effects on genes and their downstream products, namely proteins and the metabolites produced by proteins, can be assessed together. Researchers have utilized diverse "omics" approaches to understand the mode(s) of action or mechanism of different toxicity pathways in various experimental models. Some studies have indeed shown a good correlation between the genomics and metabolomics approaches. For example, metabolomics approach has demonstrated alterations in the pathways associated with lipid peroxidation, DNA damage and repair, and cell proliferation in rats exposed to CCl4 which was consistent with the expression of transcripts associated with steatosis/fibrosis that were specific to cell injury and regeneration (Chung et al., 2005a; Chung et al., 2005b; Fountoulakis et al., 2002). Additionally, metabolomics has identified biochemical alterations in pathways associated with oxidative stress, inflammation, cell proliferation, and cytotoxicity in human lung epithelial cells exposed to cigarette smoke (Vulimiri et al., 2009). These observations are supported by data from genomic (Harvey et al., 2007; Meng et al.,

exposure to cigarette smoke.

**6. Integrating "omics" data into risk assessment**

2006; Spira et al., 2004) and proteomic (Carter et al., 2011; Kelsen et al., 2008; Zhang et al., 2008) investigations that also detected markers associated with the pathways affected by exposure to cigarette smoke.

Conversely, the integration of "omics" technologies has also demonstrated some limitations. For example, a study by Steiling and co-workers found a discrepancy between genomic and proteomic data. Specifically, gel electrophoresis followed by LC-MS analysis identified 41 proteins whose expression would not have been detected by microarray analysis (Steiling et al., 2009). Such data highlight the importance of assessing more downstream markers (i.e. proteins or metabolites) that may provide a more accurate understanding of the biological responses to chemical exposures.

#### **7. Shift in the risk assessment paradigm from apical endpoints to biochemical perturbations**

Historically, human health risk assessment relied on identifying apical endpoints, defined as "observable outcomes in a whole organism, such as a clinical sign or pathologic state, indicative of a disease state that can result from exposure to a toxicant", such as birth defects, neurologic deficits, and tumor number that are obtained from high-dose animal bioassays (Krewski et al., 2010). However, the mechanistic relevance of these data can be tenuous considering the need for interspecies extrapolation and that environmental exposures may be orders of magnitude lower. Recently, the NRC report on "*Toxicity Testing in the 21st Century: A Vision and Strategy*" suggested a fundamental change in the risk assessment paradigm where the reliance on apical endpoints of toxicity would be replaced in favor of *in vitro* toxicity testing for identifying perturbations in biochemical pathways. Such an approach would employ cell lines, particularly human-based lines, and high throughput screening assays (e.g. genomics, proteomics) with computational toxicology methods. As a result, this approach would also lead to an overall increase in the efficiency of toxicity testing and decrease in animal usage [as reviewed in (Krewski et al., 2010)]. As pointed out by the NRC committee, the use of these low-dose, human-based *in vitro* systems would negate concerns associated with high-dose, animal data. Since metabolomics can identify early perturbations in biochemical pathways, this technology is poised to become an important element of this proposed risk assessment paradigm.

#### **8. Advantages of metabolomics approach for environmental chemical assessment**

Metabolomics approach offers several advantages for understanding the mechanisms of toxicity of environmental chemicals and informing human health assessments. One advantage of the metabolomics approach is the relatively non-invasive (e.g. urine samples) nature of this technique. In this context, samples from humans subjected to an incidental environmental exposure can be easily collected, analyzed, and correlated to metabolomic profiles from animal studies in order to identify critical effects from the exposure. Aside from quantitative differences, metabolic pathways are evolutionally conserved across different species; metabolomics data can be qualitatively extrapolated or interpreted at the molecular level among and between species. Unlike genomics and proteomics, metabolomics databases offer information on the structural, physicochemical,

Metabolomics Approach for Hazard Identification in

**10. Future directions/research needs**

metabolomics.

**11. Conclusions**

**12. Disclaimer**

**13. References**

Human Health Assessment of Environmental Chemicals 359

A goal of this chapter has been to highlight how metabolomics approach can be used to better understand the toxicity of environmental chemicals, with a particular focus on hazard identification and mode of action. However, due to its relative infancy compared to conventional toxicity assays and other "omic" technologies, metabolomic information for environmental chemicals is sparse. As interest in metabolomics increases and as this approach becomes more accessible to researchers focused on environmental chemicals, this database will grow. A contemporary issue regarding xenobiotics is the influence of the microbiome on immunity, metabolism, and human health [reviewed in (Han et al., 2010)]. This microbiome involves the sum of all the microorganisms (e.g. bacteria) that internally and externally reside on an individual or animal. Of these microorganisms, the gut microbiota has been shown to influence the metabolism of several xenobiotics. Accordingly, the microbiome is likely to be important in the toxicity of environmental chemicals and pertinent to human health assessments (Betts, 2011). Thus, the influence of the microbiome is an important aspect of chemical toxicity that should be further studied using

Metabolomics is an emerging medium-to-high throughput technique which measures the endogenous biochemicals affecting different metabolic pathways and can be useful in characterizing the hazards of environmental chemicals. Identifying metabolic perturbations caused in mammalian cell systems following chemical exposure helps in elucidating the predominant toxicity pathways. Some of the advantages of using metabolomic data for hazard identification—one of the key steps in risk assessment—include the ability to inform gender, genetic, and organ-specific effects in a relatively expedient manner. As briefly discussed, metabolomics can identify early biochemical perturbations associated with toxicity in the hepatic, nervous, and pulmonary systems caused by selected environmental chemicals. As surveyed, various research systems using metabolomics demonstrate how metabolomic data could be used for hazard identification and mode of action characterization for environmental chemicals. Overall, metabolomics represents an opportunity to develop a better understanding of the toxicity of environmental chemicals

The views expressed in this chapter are those of the authors and do not necessarily represent

ATSDR (1999). Toxicological profile for mercury, Agency for Toxic Substances and Disease

Azmi, J.; Connelly, J.; Holmes, E.; Nicholson, J.K.; Shore, R.F. & Griffin, J.L. (2005).

Characterization of the biochemical effects of 1-nitronaphthalene in rats using

and could further impact the human health assessment of these chemicals.

the views or policies of the U.S. Environmental Protection Agency.

http://www.atsdr.cdc.gov/toxprofiles/tp46.pdf

Registry, Atlanta, GA, Available from:

pharmacological and spectral profiles as well as biological functions of metabolites (Go, 2010). From a technical standpoint, sample preparation is relatively minimal for metabolomic analyses compared to genomics and proteomics approaches. Also, since metabolomics allows for the *a priori* selection of metabolites, the investigator has better control over the number of standards that need to be procured or synthesized for analysis.

A survey of the available literature already demonstrates the value of using metabolomics for elucidating the mode of action of environmental chemicals. Since a number of matrices are amenable to metabolomic analysis, various systems including *in vitro* and *in vivo* models can be employed to identify metabolic perturbations associated with exposure to environmental chemicals. Some of the mammalian *in vitro* systems involved exposing A549 human lung carcinoma cells to cigarette smoke (Vulimiri et al., 2009), human embryonic stem cells to various teratogens (West et al., 2010), and reaggregating neuronal cultures to methylmercury (van Vliet et al., 2008). From *in vivo* studies, intact organs from exposed experimental animals have been evaluated to include the analysis of intact lung after intratracheal instillation of silica dust (Hu et al., 2008) as well as liver and lung after exposure to 1-nitronaphthalene (Azmi et al., 2005). Also, metabolomics has been able to demonstrate different metabolic responses between mixtures of environmental chemicals. For example, in assessing the inflammatory response, Schmelzer et al (2006) found unique lipid profiles between rats exposed to 1 nitronaphthalene and those exposed to a mixture of 1-nitronaphthalene and ozone. As highlighted earlier in this chapter, metabolomics approach has been shown to differentiate the metabolic changes attributed to the complex mixtures of whole smoke versus its two constituent physical phases (Vulimiri et al., 2009).

#### **9. Limitations of metabolomics research**

Regardless of whether a chemical being investigated is a pharmaceutical or environmental pollutant, a critique of metabolomics has been the detection of metabolites that appear to be changed independent of the toxicant, its mode of action, and target tissue. Such common metabolites were previously termed the "usual suspects" by Robertson and often include 2-oxoglutarate, citrate, succinate, and trimethyl amine/trimethyl amine oxide (Robertson, 2005). From a data interpretation standpoint, these "usual suspects" may confound the identification of metabolites that have true value as specific markers of organ toxicity by skewing results from pattern separation analyses (Connor et al., 2004; Robertson, 2005). Connor et al (2004) found that urinary metabolite changes, including many of the "usual suspect" metabolites, can be associated with systemic or secondary toxicity effects, namely reductions in food intake and body weight. Additionally, the authors suggest that such metabolites may still inform mechanisms of toxicity when put into the context of diet and weight change. Conversely, the authors did identify exposures where common metabolites were specific for toxicant exposure. For example, succinate and 2-oxoglutarate were specifically associated with exposure to the hepatotoxicant αnaphthylisothiocyanate, rather than resulting from secondary toxicity (Connor et al., 2004). Research by other investigators has identified metabolites as novel biomarkers associated with specific diseases and for specific toxicities. For example, 5-oxoproline has been demonstrated to be a specific marker of bromobenzene-induced hepatotoxicity (Waters et al., 2006).

### **10. Future directions/research needs**

A goal of this chapter has been to highlight how metabolomics approach can be used to better understand the toxicity of environmental chemicals, with a particular focus on hazard identification and mode of action. However, due to its relative infancy compared to conventional toxicity assays and other "omic" technologies, metabolomic information for environmental chemicals is sparse. As interest in metabolomics increases and as this approach becomes more accessible to researchers focused on environmental chemicals, this database will grow. A contemporary issue regarding xenobiotics is the influence of the microbiome on immunity, metabolism, and human health [reviewed in (Han et al., 2010)]. This microbiome involves the sum of all the microorganisms (e.g. bacteria) that internally and externally reside on an individual or animal. Of these microorganisms, the gut microbiota has been shown to influence the metabolism of several xenobiotics. Accordingly, the microbiome is likely to be important in the toxicity of environmental chemicals and pertinent to human health assessments (Betts, 2011). Thus, the influence of the microbiome is an important aspect of chemical toxicity that should be further studied using metabolomics.

#### **11. Conclusions**

358 Metabolomics

pharmacological and spectral profiles as well as biological functions of metabolites (Go, 2010). From a technical standpoint, sample preparation is relatively minimal for metabolomic analyses compared to genomics and proteomics approaches. Also, since metabolomics allows for the *a priori* selection of metabolites, the investigator has better control over the number of standards that need to be procured or synthesized for analysis. A survey of the available literature already demonstrates the value of using metabolomics for elucidating the mode of action of environmental chemicals. Since a number of matrices are amenable to metabolomic analysis, various systems including *in vitro* and *in vivo* models can be employed to identify metabolic perturbations associated with exposure to environmental chemicals. Some of the mammalian *in vitro* systems involved exposing A549 human lung carcinoma cells to cigarette smoke (Vulimiri et al., 2009), human embryonic stem cells to various teratogens (West et al., 2010), and reaggregating neuronal cultures to methylmercury (van Vliet et al., 2008). From *in vivo* studies, intact organs from exposed experimental animals have been evaluated to include the analysis of intact lung after intratracheal instillation of silica dust (Hu et al., 2008) as well as liver and lung after exposure to 1-nitronaphthalene (Azmi et al., 2005). Also, metabolomics has been able to demonstrate different metabolic responses between mixtures of environmental chemicals. For example, in assessing the inflammatory response, Schmelzer et al (2006) found unique lipid profiles between rats exposed to 1 nitronaphthalene and those exposed to a mixture of 1-nitronaphthalene and ozone. As highlighted earlier in this chapter, metabolomics approach has been shown to differentiate the metabolic changes attributed to the complex mixtures of whole smoke

Regardless of whether a chemical being investigated is a pharmaceutical or environmental pollutant, a critique of metabolomics has been the detection of metabolites that appear to be changed independent of the toxicant, its mode of action, and target tissue. Such common metabolites were previously termed the "usual suspects" by Robertson and often include 2-oxoglutarate, citrate, succinate, and trimethyl amine/trimethyl amine oxide (Robertson, 2005). From a data interpretation standpoint, these "usual suspects" may confound the identification of metabolites that have true value as specific markers of organ toxicity by skewing results from pattern separation analyses (Connor et al., 2004; Robertson, 2005). Connor et al (2004) found that urinary metabolite changes, including many of the "usual suspect" metabolites, can be associated with systemic or secondary toxicity effects, namely reductions in food intake and body weight. Additionally, the authors suggest that such metabolites may still inform mechanisms of toxicity when put into the context of diet and weight change. Conversely, the authors did identify exposures where common metabolites were specific for toxicant exposure. For example, succinate and 2-oxoglutarate were specifically associated with exposure to the hepatotoxicant αnaphthylisothiocyanate, rather than resulting from secondary toxicity (Connor et al., 2004). Research by other investigators has identified metabolites as novel biomarkers associated with specific diseases and for specific toxicities. For example, 5-oxoproline has been demonstrated to be a specific marker of bromobenzene-induced hepatotoxicity

versus its two constituent physical phases (Vulimiri et al., 2009).

**9. Limitations of metabolomics research**

(Waters et al., 2006).

Metabolomics is an emerging medium-to-high throughput technique which measures the endogenous biochemicals affecting different metabolic pathways and can be useful in characterizing the hazards of environmental chemicals. Identifying metabolic perturbations caused in mammalian cell systems following chemical exposure helps in elucidating the predominant toxicity pathways. Some of the advantages of using metabolomic data for hazard identification—one of the key steps in risk assessment—include the ability to inform gender, genetic, and organ-specific effects in a relatively expedient manner. As briefly discussed, metabolomics can identify early biochemical perturbations associated with toxicity in the hepatic, nervous, and pulmonary systems caused by selected environmental chemicals. As surveyed, various research systems using metabolomics demonstrate how metabolomic data could be used for hazard identification and mode of action characterization for environmental chemicals. Overall, metabolomics represents an opportunity to develop a better understanding of the toxicity of environmental chemicals and could further impact the human health assessment of these chemicals.

#### **12. Disclaimer**

The views expressed in this chapter are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

#### **13. References**

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Metabolomics Approach for Hazard Identification in

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### *Edited by Ute Roessner*

Metabolomics is a rapidly emerging field in life sciences, which aims to identify and quantify metabolites in a biological system. Analytical chemistry is combined with sophisticated informatics and statistics tools to determine and understand metabolic changes upon genetic or environmental perturbations. Together with other 'omics analyses, such as genomics and proteomics, metabolomics plays an important role in functional genomics and systems biology studies in any biological science. This book will provide the reader with summaries of the state-of-the-art of technologies and methodologies, especially in the data analysis and interpretation approaches, as well as give insights into exciting applications of metabolomics in human health studies, safety assessments, and plant and microbial research.

Metabolomics

Metabolomics

*Edited by Ute Roessner*

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