Differentiating Toxicities of Conazole Fungicides Through Metabonomic Analyses of Multiple Tissues

Differentiating Toxicities of Conazole Fungicides

Through Metabonomic Analyses
of Multiple

Drew R. Ekman1, Hector C. Keun2, Charles D. Eads3, Carrie M. Furnish3, David J. Dix4

'ORD/NERL/ERD, Athens GA

2Bioiogical Chemistry, Biomedical Sciences Division, Faculty of Medicine, Imperial College of Science, Technology and Medicine, London, U.K.

3Miami Valley Innovation Center, The Procter & Gamble Company, Cincinnati OH
4ORD/NHEERL/RTD, Research Triangle Park, NC.

Abstract

The conazole fungicides represent a large group of compounds widely
used agriculturally for the protection of crop plants (Hutson, 1998) and
pharmaceutical^ in the treatment of topical and systemic infections
(Sheehan, 1999). In 1999, the latest period for which agricultural usage
estimates are available, 79 and 556 million pounds of lungicide active
ingredient were used in the U.S. and world markets, respectively
(Donaldson, 2002), creating concern over the impact these compounds
may have through environmental exposure to humans and other
organisms. In an attempt to better understand the toxicities of these
compounds, an NMR (Nuclear Magnetic Resonance)-based
metabonomics approach was used to determine differences in the
toxicities of two conazole fungicides (myclobutanil and triadimefon) by
analyses of metabolite changes occurring in blood serum, liver tissue,
and testicular tissue of control and exposed rats. Metabonomics is the
quantitative measurement of a broad spectrum of metabolic responses of
living systems in response to disease onset or genetic modification. By
monitoring changes in cellular metabolites in response to the introduction
of a toxicant, the biochemical pathways affected can be determined and
the specific toxic response characterized on a molecular level.
Furthermore, metabonomic data can be used in conjunction with genomic
and proteomic data to more fully characterize environmental effects.
Through the combined efforts of the U.S. Environmental Protection
Agency (U.S. EPA), the Procter and Gamble Company, and the Imperial
College (London, England), distinct metabolite profiles produced by
exposure to conazole fungicides were identified. These metabonomic
profiles identify potential biological pathways responding to the
exposures. One distinct change observed was induction of betaine levels
in rats exposed to myclobutanil versus those exposed to triadimefon or
control rats. This betaine effect indicates altered homocysteine
metabolism. Homocysteine is an intermediate metabolite of the amino
acid methionine, and altered homocysteine levels have been linked to a
variety of health problems. These preliminary results support the case for
metabonomics as part of the Computational Toxicology program in the
ORD and suggest the potential of metabonomics for assessing the
toxicity of compounds regulated by the U.S. EPA.

Introduction

Extensive use of conazole fungicides both agriculturally and
pharmaceutically has created concern regarding the threat these
compounds may pose as a result of environmental exposure to humans
and other organisms. Toxicity studies conducted in rodents have shown
the conazoles to target a variety of organs producing multiple effects.
Among these are the production of liver tumors in mice, thyroid tumors in
rats, and developmental and reproductive lesions (Zarn, 2003). Although
grouped into a single class, the specific biological effects produced by
individual members vary widely, presenting difficulty in fully assessing
risk from conazoles. Therefore, the ability to rapidly differentiate the
toxicities these compounds induce on a molecular scale will provide a
route for more effectively setting risk assessments for individual members
of this class of chemicals.

A recently developed approach involves the use of advanced analytical
techniques such as NMR (Nuclear Magnetic Resonance) spectroscopy
(figure 1) to analyze changes in the levels of cellular metabolites (e.g.
sugars, carbohydrates, amino acids, etc.) that relate to the toxic
mechanism(s) involved in responding to the presence of a given
chemical. This approach, known as metabonomics (figure 2), has proven
to be a powerful tool in the assessment of toxicity or other physiological
alterations in a variety of different organisms (Bailey, 2003; Coen, 2003;
Viant, 2003). We have employed metabonomics for the determination of
changes in metabolite profiles in a variety of tissues measured using
NMR spectroscopy for rats exposed to both toxic and non-toxic levels of
conazole fungicides. For the present study, two conazoles producing
different toxicities (triadimefon produces liver toxicity and myclobutanil is
a testicular toxin) have been chosen to determine the feasibility of using
this approach to differentiate responses.

Figure 1 - NMR spectroscopy

Nuclear Magnetic Resonance (NMR) spectroscopy is an
analytical technique that allows one to observe the levels
of metabolites in a variety of
tissues and biofluids for
metabonomic analyses.

it?

iit

A portion of an NMR spectrum of a rat
liver tissue extract with several
m etab ol ites I abeled. Chan ges in th e
levels of these metabolites (e.g.
sugars, carbohydrates, amino acids,
etc.) can allow one to determine the
nature of toxicity induced by exposure
to a given compound.

Figure 2 - Metabonomics

Disease states or exposure to drugs or other
biologically active compounds produces
changes in the levels of metabolites present in
tissues and biofluids (e.g. blood, urine, etc.).
The identification of these effected metabolites
yields valuable information for determining
the nature of a disease or toxic response.

Using metabonomics, the presence of disease
or toxicity can be determined rapidly and
inexpensively in comparison to other
approaches (e.g. genomics, proteomics, etc.).

Shown here are urine metabolite profiles in
mice resulting from exposure to organ-specific
toxins (i.e. liver, heart, and kidney)

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Figure 3 - Differential Responses to Specific
Conazole Fungicides

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Metabonomic analyses of liver tissues from both control rats and those
dosed separately with two conazole fungicides with different toxicities
revealed several changes in the levels of cellular metabolites. For
example, a severe alteration in the level of betaine in those rats exposed
to myclobutanil was observed. Betaine often serves in a protective
capacity in the liver.

Figure 4 - Chemometric/Statisticai Methods for
Rapidly Determining Changes in Metaboiites

The large number of metabolites changing in response to a given toxic
insult can be overwhelming without the use of statistical tools that can
quickly identify changes.

Various computational methods designed to simplify the analysis of large
amounts of data (e.g., principal components analysis (PCA)) provide the
ability to quickly determine metabolite changes as opposed to assessing
changes simply by eye.

While these methods are effective, more- advanced methods are needed
to observe very subtle changes that may carry information crucial to more
accurately defining organism responses.

We are currently working with researchers at Sandia National
Laboratory (Albuquerque, NM) to develop these methods (see poster
titled: "Multivariate Curve Resolution of NMR Spectroscopy Metabonomic
Data").

PCA plot of rat liver extracts from animals exposed to myclobutanil
and triadimefon. Using ptots like this, one can determine with
relative ease the metabolites that are changing due to toxicity.

Figure 5 - Coiiaboration with Academia and
industry to Strengthen ORD's Metabonomics
Program

The Procter and
Gamble Company

The Imperial College of
London

Sandia National
Laboratory

ional

"i I

EPA

For the metabonomics program in ORD to succeed in the early stages
of its development, support from researchers in both industry and
academia was essential.

Fortunately, a platform for collaboration with researchers at The
Procter and Gamble Company (Cincinnati, OH) and those at The
Imperial College of London (London, UK) was established. This
collaboration has been successful not only in the pursuit of current
projects (e.g. the work outlined here) but also in the establishment of
potential future projects.

Results

While the concentration of a number of metabolites changed in response
to exposure to both of the conazoles used separately in this study, the
major goal was to determine if differences between the two compounds
(myclobutanil and triadimefon) could be determined. Analyses of the
effects of the conazoles on liver metabolite composition revealed distinct
differences (figure 3). One of the most notable responses was a marked
change in the levels of betaine ( be' tan) that differed among treatments.
While triadimefon only produced a slight change in this metabolite,
myclobutanil produced a much larger change. As betaine serves a
protective function in the liver, it is likely that this change reflects the
liver's ability to cope with the toxic effects of myclobutanil. Rats exposed
to triadimefon, a recognized liver toxin, do not show this large change
potentially indicating the absence of this protective response. Both blood
serum and testicular tissue were also analyzed using this approach and
these displayed a number of metabolite changes in response to exposure
(data not shown).

Conclusions

The potential for metabonomics to supply rapid and accurate information
on the toxicity of compounds of interest to the EPA has been shown here
through the differentiation of the effects of conazole fungicides in rats, in
addition, the results of this work are being compared to genomic data
derived from rats exposed to the same conazoles to determine
correlations in gene expression changes and metabolite changes in order
to integrate the two approaches. Furthermore, we are developing
methods for advanced data analysis which will provide the means to
more fully realize the potential of this new method for studying toxicity
(figure 4). In addition to rodent studies, we have also begun working with
environmental fish models (fathead minnow, zebra fish, and rainbow
trout) in collaboration with other EPA researchers (NERL and NHEERL)
and the University of Georgia to extend metabonomics into the
ecotoxicology realm. As a result of Agency support and collaboratative
efforts (figure 5) this initial study serves as a major step in the
establishment of an integrated metabonomics program at EPA.

References

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5. Sheehan, D.J., Hitchcock, C.A., and Sibley, C.M. (1999). Current and
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DISCLAIMER: Although this work was reviewed by EPA and approved for presentation, it may not necessarily reflect official Agency policy. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

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