Variation in the Deoxynucleotide Composition between Organic and Nonorganic Strawberries

Ecotoxicology and Environmental Safety 44, 259}270 (1999) Environmental Research, Section B Article ID eesa.1999.1832, available online at http://www.idealibrary.com on

Variation in the Deoxynucleotide Composition between Organic and Nonorganic Strawberries David Podwall, Harley S. Dresner, Joshua Lipetz,- and Jacob J. Steinberg1 Unixed Tumor Marker Laboratory, Departments of Pathology and Radiation Oncology, Albert Einstein College of Medicine, Montexore Medical Center, 111 East 210th Street, Central 312, Bronx, New York 10461 Received January 28, 1999

The di4erences in xenobiotic chemical content between organic and nonorganic products can be chemically measured. In this study, the deoxynucleotide composition of strawberry samples is used to demonstrate chromatographic methods of quantifying the di4erences between pesticide- and toxic-exposed strawberries. The samples were analyzed by 32P labeling and two-dimensional thin-layer chromatography. This technique is sensitive for detecting rare (1/1010 ) deoxynucleotide adducts and analogues (minor bases) in DNA. The results indicate di4erences in the amount and type of adduct formation between organic and nonorganic strawberry samples and within di4erent parts of the same type of sample. The elucidation of the content and e4ects of pesticides and toxics in foods is critical in di4erentiating organic from common produce. It can also aid the agricultural industry in improving the application of chemicals in pest management. Furthermore, it helps to enhance the understanding of long-term epidemiology in nutrition research, especially in susceptible populations. These 5ndings are of particular application in the pediatric population, where dietary habits are restricted to speci5c food groups. ( 1999 Academic Press Key Words: pesticides; strawberry; pediatrics; toxics; diet; produce; xenobiotics; thin-layered chromatography.

INTRODUCTION

In increasing agricultural production, pesticides provide unquestionable bene"ts. However, since pesticide residues remain on fruits and vegetables, they constitute a potential health risk to consumers (Torres et al., 1996). Strawberries, as with most fruits, have been treated with pesticides, which include insecticides, herbicides, and fungicides. For example, a survey of 342 strawberry samples on the market in California reported that the fungicide vinclozolin was detected in 49% at levels that exceeded 0.1 kg/g-raw (Nagami, 1997). -Deceased. 1To whom correspondence should be addressed. Fax: (718) 547-8349. E-mail: [email protected].

As such, the California Environmental Protection Agency (Cal EPA) keeps extensive records on the potential health e!ects caused by pesticides. The Cal EPA requires all physicians to report any suspected injury due to pesticides. Similarly, all workmen's compensation claims linked to injuries from pesticides must be reported. In 1993, 1307 occupational exposure cases and 146 nonoccupational exposure cases were reported that were de"nitely, probably, or possibly related to pesticide exposure. Of these exposures, 433 a!ected people were below the age of 20. There were 339 cases of respiratory and other systemic symptomatology associated with pesticide exposure; of these, 161 cases were systemic and 189 cases were respiratory in nature (Cal EPA, 1995). In a study of four strawberry "elds during times of little wind and/or air inversion, two common agricultural applicants were evaluated: methyl bromide (an organic halogenated aliphatic hydrocarbon) and chloropicrin (an aliphatic nitro compound). A community exposed to the fumigated "eld experienced high rates of airborne-irritant symptoms in the "rst day following the application. Common symptoms included headaches, eye irritation, and throat irritation. Several cases of shortness of breath and hallucinations were also reported (Goldman et al., 1987). Cases of organophosphate pesticide poisoning of agricultural "eld workers have also been reported. Within minutes following exposure to organophosphates like mevinphos (Phosdrin) and phosphamidon (Dimecron), workers commonly reported symptoms including blurred vision, headache, nausea, weakness, vomiting, abdominal pain, and dizziness. A 4-month follow-up of "eld workers exposed to mevinphos and phosphamidon found a decrease in intestinal acetylcholinesterase levels. This is consistent with the fact that these organophosphates are essentially permanent inhibitors of acetylcholinesterase. Following treatment with a combination of pralidoxime and atropine and a recovery time of 2 to 3 months postexposure, most of the major symptoms were alleviated. However, eye complaints

259 0147-6513/99 $30.00 Copyright ( 1999 by Academic Press All rights of reproduction in any form reserved.

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remained a distressing problem for many individuals at 4-month follow-up (Whorton and Obrinsky, 1983). Acute organophosphate pesticide poisoning often results in chronic neurological sequelae. In comparing individuals with previous acute organophosphate poisoning with controls, neuropsychological tests revealed poorer intellectual functioning, academic skills, abstraction and #exibility of thinking, and simple motor skills among those with previous poisoning. The expanded Halstead}Reitan battery includes measures of intelligence, attention, various cognitive functions, motor pro"ciency, sensory}perceptual functions, aphasia and related disorders, and learning and memory. The expanded Halstead}Reitan battery summary scores had twice as many organophosphate poisoning cases as controls scoring in a range indicative of cerebral damage or dysfunction. Results from the Minnesota Multiphasic Personality Inventory (MMPI) and the Patient's and Relative's Assessment of Patient Functioning Inventories also revealed greater distress and complaints of disability among the poisoned subjects (Savage et al., 1988). Some consequences of pesticide exposure may be particularly salient among women. Breast and other tumors of reproductive organs merit special consideration, given the links between organochlorine pesticide residues and breast cancer risk. Higher levels of organochlorine residues have been found in patients with cancer compared to nonpatients and in farmers compared to nonfarmers (McDu$e, 1994). Understanding the unique qualities of infants and children is important in evaluating the health impact of pesticides. There are signi"cant di!erences in the biochemical and physiological functionings of the major body systems of infants and children. There are also di!erences in metabolism and di!erences in body composition, in terms of the relative proportions of water and fat. Metabolic rate is relevant to food and water consumption, with infants having metabolic rate more than twice that of adults (National Research Council, 1993). Incidents such as wheat #our contaminated with parathion in Jamaica indicate that children are more susceptible than adults to organophosphate- and carbamate-induced cholinesterase inhibition and related e!ects. Consistent with this "nding, case fatality ratios were highest, i.e., 40%, in children under 4 years of age (Diggory et al., 1977). Also, in a study of 37 children poisoned with various organophosphates (i.e., Diazinon and Malathion) or carbamates (i.e., Propoxur and Furadan), 76% were under 3 years old. Pesticide toxicity was not suspected by the primary physician in 43% of these children. This high rate of misdiagnosis indicates the di$culties in identifying the signs of organophosphate and carbamate toxicity in infants and young children (Zwiener and Ginsburg, 1988). This may be because most biochemical and physiological processes mature in the "rst 2 years of life. Indeed, many consequential changes occur within the "rst few weeks of life. Finally,

women and their infants are generally considered to be at special risk for exposure to at least some organochlorine compounds because of placental transfer to the fetus and breastmilk transfer to the infant (Kuhnlein et al., 1995). A multiplicity of methods currently exist for the detection and measurement of pesticide levels in fruits and vegetables. These include, but are not limited to, single residue methods (SRMs), classical multiresidue methods (MRMs), online MRMs, coagulation methods, matrix solid-phase dispersion (MSPD), supercritical #uid extraction (SFE), gas chromatography (GC), high-performance liquid chromatography (HPLC), supercritical #uid chromatography (SFC), and a variety of immunoassay (IA) procedures. However, while all of these techniques can identify the presence of speci"c pesticide residues in fruits and vegetables, they cannot detect or assess pesticide-induced DNA damage. In this study a 32P radiolabeling and two-dimensional thin-layer chromatography (2D-TLC) technique was used to detect and quantify di!erences in xenobiotic-induced DNA adduct formation among a series of organic and nonorganic strawberry samples. The deleterious health consequences of pesticide poisoning are reviewed (especially in the pediatric population), and the current methods of pesticide measurement in fruits and vegetables are explored. Such a study becomes important as more farmers produce and consumers choose organically grown products. Concerns about pesticide-induced toxicity become even more important when we consider that the nervous, immune, and reproductive systems are developmentally immature at birth. MATERIALS AND METHODS

Materials Strawberries. Various types of strawberries (all cultivated from a hybrid combination of Fragaria x ananassa Duch.) were used to contrast organically versus nonorganically grown products. Organic strawberries were purchased from an organic farm within the Santa Cruz}Salinas Bay area, California. Nonorganic strawberries were purchased from a well-known supermarket chain in the Bronx, New York. Enzymes. Micrococcal nuclease (EC 3.1.3.1.1; activity 100}200 lmol/mg of protein) and spleen phosphodiesterase II (EC 3.1.16.1; activity 13.5 units/mg of protein) were purchased from Sigma Chemicals, Inc. (St. Louis, MO). DNase I and Escherichia coli DNA polymerase I were obtained from Boehringer-Mannheim (Indianapolis, IN). Chromatographic solvents and plates. Chromatographic solvents for the "rst dimension included 28.6 ml of glacial acetic acid (American Scienti"c Products, San Diego, CA), 471.4 ml of distilled water, and 1.95 g of solid sodium hydroxide (Fisher Scienti"c Co., Pittsburgh, PA). The pH of

DNA ADDUCTS AS BIOMARKERS OF PESTICIDE/TOXICS EXPOSURE

the solution was adjusted to 3.5. Chromatographic solvents for the second dimension included 74 g of ammonium sulfate (Sigma), 0.4 g of ammonium bisulfate (Aldrich Chemical Co., Milwaukee, WI), 4 g of Na H , and 0.22 g of solid 2 2 sodium hydroxide in 100 ml of distilled water. TLC plates, composed of polyester polyethyleneimine (PEI) cellulose, were purchased from Machery}Nagel}Merck, Inc. (Darmstadt, Germany). Reagents. Nick translation bu!er [500 mM Tris (pH 7.5), 100 mM magnesium chloride, and 10 mM DTE] was obtained from Boehringer}Mannheim. Precipitants and bu!ers (commonly available) included EDTA, ammonium acetate, 100% ethanol, and 70% ethanol. Equipment. The laser densitometer was a computing densitometer 300A manufactured by Molecular Dynamics, Inc. (Sunnyvale, CA). The densitometry data were quanti"ed using Image Quant 3.0 for Windows (Microsoft, Inc., Redmond, WA). Kodak XAR-5 "lm (20.3]25.4 cm) was produced by the Eastman Kodak Co. (Rochester, NY). DNA extraction was accomplished with a FastPrep Kit System from Bio101/Savant (Vista, CA). Last, samples were centrifuged in an Eppendorf centrifuge 5415C manufactured by Netheler}Hinz Gmblt (Hamburg, Germany). METHODS

DNA preparation and DNA extraction. Various samples were obtained from the organic and nonorganic strawberries, including seeds, leaves (nonorganic strawberries only), wet #esh, and dry #esh. After the strawberries were sliced, the dry #esh samples were dried in silica. The seeds were removed from the wet and dry #esh samples. DNA from the organic and nonorganic strawberries was then extracted in the New York Botanical Garden (Bronx, NY) using the FastPrep Kit H System. Substrate DNA, 32P labeling, and nick-translation methods for ¹¸C analysis of formed DNA adducts. The technique has been delineated in a number of previous publications, including Rigby et al. (1977) and Steinberg et al. (1992, 1996). 32P was incorporated into DNA constituent mononucleotides by &&shotgun'' 5@-phosphorlyation via [a-32P] dNTP nick translation. The nick-translation kit was purchased from Boehringer}Mannheim. The amount of DNA used was as little or less than 1 ng. The DNA samples were thawed in a 373C heating block, and 2 ml of each sample was transferred to new Eppendorf tubes. To each tube, 2 ml of 10 times concentrated nick-translation bu!er, 2 ml each of [32P]dATP, cCTP, dGTP, and dTTP, and 2 ml of enzyme mixture (DNA polymerase I and DNase I in 50% glycerol) were added. The samples were then placed in a water bath at 153C and incubated for exactly 35 min. DNA purity was calculated by OD ratios of 260/280.

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DNA was precipitated using cold ethanol as follows: 2 ml of EDTA, 40 ml of 4 M ammonium acetate, and 80 ml of 100% ethanol were added to each sample and centrifuged. To remove unincorporated nucleotides, the procedure was performed three times using 100% ethanol, 70% ethanol, and distilled water. The DNA was subsequently digested using 40 ll of spleen phosphodiesterase II and 10 ll of micrococcal nuclease. Two microliters of deoxycorfomycin (Parke-Davis, Morris Plains, NJ) was also added to block the formation of inosine. The samples were then placed in a heating block overnight at 373C. After the DNA was removed from the heating block, 0.5 ml of cold acetone was added. Samples were vortexed for 1 min and then centrifuged in an Eppendorf centrifuge 5415C for 7 min at 800g. The supernatant was then transferred to new Eppendorf tubes and desiccated in a speed vacuum until dry. DNA pellets were resuspended in 5 ml of distilled water. Two-dimensional thin-layer chromatography was performed after volumes containing 100,000}200,000 disintegrations per minute (DPM) of DNA samples were spotted on TLC plates. The monophosphate separation was easily accomplished via two-dimensional PEI cellulose TLC, using the "rst- and second-dimension solvents previously described. The TLC plates were placed in the "rst dimension solvents for 8 h, air-dried, and then placed in the second dimension solvents for 16 h. Next, a TLC scintillation count was carried out, using control DPM to account for quenching. Scintillation counts were determined using standard protocols. Autoradiography was performed after the chromatography was completed. The plates were air-dried, wrapped with plastic wrap, and loaded into cassettes with XAR-5 "lm. The cassettes were placed in a !703C freezer for 1}3 days, depending on the results of the earlier scintillation counts. Exposure times were adjusted in some cases to over- or underexpose the "lm. ¸aser densitometry analysis of ¹¸C XAR-5 autoradiographs. The "lm was developed and the autoradiographs were analyzed using a computing densitometer 300A. The densitometer was used to scan the autoradiograph and calculate the density of the spots. The data were quanti"ed using Image Quant 3.0 for Windows. Densitometry, which is nearly as sensitive as scintillation counting, aided the determination of adduct-to-nucleotide ratios and the analysis of retention factors. It also facilitated the quanti"cation of proximate adducts to known dNMPs, the areas of spot exposure, and the spot densities (on a gray scale), all of which re#ected the quantity of each labeled phosphate. Additionally, the ability to graphically superimpose each "lm with control spots facilitated the analysis of the "nal products. All R values are presented as the consequent & two-dimensional R values (X, > coordinates). The R x &

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values were determined with a ruler (cm) by measuring from the center of the spot to the X axis and the > axis. It should also be noted that adducts and/or analogues present in small amounts are seen in duplicate autoradiographs, thus generating a characteristic spot pattern for each DNA sample. Additionally, autoradiographs are monitored visually for quality control. RESULTS

The results of the following TLCs are presented and discussed herewith. Expected retention times of all normal radiolabeled monophosphates to cold UV markers were obtained. Figure 1 presents the results after TLC was performed on DNA from a nonorganic strawberry seed. The four major DNA bases are observed, in a clockwise manner, as their

FIG. 2. TLC of DNA derived from the leaf of a nonorganic strawberry. Spots approximating the migration patterns and adducts of the four major DNA bases and more minor DNA bases are provided. There are no detectable adducts near dTMP or dTGMP. The stars along the X axis represent diphosphate products.

FIG. 1. TLC of DNA derived from the seed of a nonorganic strawberry. The migration patterns and approximate adducts of the four major DNA bases (dCMP, dTMP, dGMP, and dAMP) are illustrated. There are no detectable adducts near dTMP. Approximate locations and adducts of more minor DNA bases (dUMP and dTGMP) also appear. The stars along the X axis represent diphosphate products.

respective dNMPs on the autoradiograph: dCMP (R ) x X, >"11.8, 13.5; dTMP (R ) X, >"7.4, 7.8; dGMP (R ) x x X, >"4.0, 4.3; dAMP (R ) X, >"2.2, 9.2. Adducts near x three of the four major bases are also observed and are expressed as percentage volumes of total deoxynucleotides. C1 (2.83%) is an adduct near dCMP; G1 (0.41%), G2 (0.04%), and G3 (0.03%) are adducts close to dGMP; and A1 (0.29%) and A2 (0.06%) are approximate adducts of dAMP. Two adducts approximating the cis and trans isomers of thymidylate glycol (dTGMP, 5.77%) are present in the lower right corner of the autoradiograph: TG1 (0.03%) and TG2 (0.97%). dTGMP is usually present in DNA that has been exposed to oxidative stress. Additionally, three adducts near dUMP also appear: U1 (0.15%), U2 (0.21%), and U3 (0.89%). The stars situated along the X axis signify the diphosphate products (1.42%), which appear due to the incomplete digestion of the DNA. Figure 2 illustrates the results of a TLC on the leaf of a nonorganic strawberry. The autoradiograph indicates, in a clockwise manner, the four major DNA bases as their respective dNMPs: dCMP (R ) X, >"12.6, 12.4; dTMP x (R ) X, >"7.2, 8.3; dGMP (R ) X, >"3.6, 3.6; dAMP (R ) x x x

DNA ADDUCTS AS BIOMARKERS OF PESTICIDE/TOXICS EXPOSURE

263

FIG. 3. TLC of DNA derived from the #esh of a nonorganic strawberry. Adducts near the four major DNA bases and more minor DNA bases appear in characteristic locations. Adducts near dTMP are not detected. The stars along the X axis represent diphosphate products.

X, >"2.6, 9.0. Adducts of the four major bases include C1 (0.07%), C2 (0.03%), and C3 (2.59%) near dCMP; G1 (0.04%) near dGMP; and A1 (0.96%) close to dAMP. Although dTGMP (21.13%) appears in the lower right corner, no adducts of thymidylate glycol are seen in this autoradiograph. As is the case in Fig. 1, however, three adducts within proximity of dUMP appear as U1 (0.14%), U2 (0.03%), and U3 (0.36%). Also similar to Fig. 1, the stars located along the X axis represent the diphosphate products (4.28%). The migration pattern of DNA from the #esh of a nonorganic strawberry is presented in Fig. 3. The four major DNA bases are demonstrated, in a clockwise manner, as their respective dNMPs on the autoradiograph: dCMP (R ) x X, >"10.9, 13.3; dTMP (R ) X, >"7.2, 8.0; dGMP (R ) x x X, >"3.8, 3.3; dAMP (R ) X, >"2.1, 8.0. Approximate x adducts of dCMP include C1 (2.20%) and C2 (2.30%). G1 (1.13%) and G2 (2.43%) are adducts near dGMP, while A1 (0.06%) and A2 (0.04%) are adducts close to dAMP. Approximate adducts of dTGMP (15.07%), TG1 (0.64%) and TG2 (0.19%), appear in the lower right corner of the autoradiograph. Five adducts close to dUMP are also provided: U1 (0.36%), U2 (0.05%), U3 (0.14%), U4 (0.19%), and US (0.98%). Finally, the diphosphate products (9.03%) are again indicated by stars located along the X axis. The results of the TLC performed on DNA from the #esh of a nonorganic strawberry dried with silica are presented in

Fig. 4. The autoradiograph indicates, in a clockwise manner, the four major DNA bases as their respective dNMPs: dCMP (R ) X, >"11.4, 17.8; dTMP (R ) X, >"7.7, 7.0; x x dGMP (R ) X, >"3.9, 2.8; dAMP (R ) X, >"2.0, 6.5. x x Approximate adducts of the four major bases include C1 (2.03%) and C2 (2.62%) near dCMP; G1 (3.68%) near dGMP; and A1 (0.03%) and A2 (0.02%) close to dAMP. While dTGMP (18.45%) appears in its characteristic location in the lower right corner of the autoradiograph, no adducts of thymidylate glycol appear. Similar to Fig. 3, "ve adducts close to dUMP are indicated: U1 (0.13%), U2 (0.01%), U3 (0.59%), U4 (0.03%), and U5 (0.40%). The stars positioned along the X axis represent the diphosphate products (7.83%). Figure 5 illustrates the results of a TLC performed on the DNA of a seed from an organic strawberry. The four major DNA bases are demonstrated, in a clockwise manner, as their respective dNMPs on the autoradiograph: dCMP (R ) x X, >"11.3, 12.7; dTMP (R ) X, >"6.0, 8.8; dGMP (R ) x x X, >"3.2, 4.7; dAMP (R ) X, >"1.2, 9.7. Adducts near x dCMP include C1 (0.56%), C2 (0.39%), and C3 (0.42%). T1 (0.20%) is an approximate adduct of dTMP. G1 (3.49%), G2 (2.16%), and G3 (0.10%) are adducts close to dGMP, while A1 (1.57%) and A2 (0.04%) are adducts near dAMP. dTGMP (28.42%) appears in its usual location at the lower right corner of the autoradiograph. One adduct near dUMP is indicated, U1 (0.73%). Only minimal diphosphate

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FIG. 4. TLC of DNA derived from the #esh of a nonorganic strawberry dried with silica. Spots approximating adducts of the four major DNA bases and more minor DNA bases are presented. Adducts near dTMP and dTGMP are not detected. The stars along the X axis represent diphosphate products.

products (0.06%) appear along the X axis, as illustrated by the star. The migration pattern of DNA from the #esh of an organic strawberry is demonstrated in Fig. 6. This

autoradiograph depicts, in a clockwise direction, the four major DNA bases as their respective dNMPs: dCMP (R ) x X, >"11.1, 13.0; dTMP (R ) X, >"7.4, 8.5; dGMP (R ) x x X, >"3.5, 3.3; dAMP (R ) X, >"2.2, 7.2. Adducts of the x

FIG. 5. TLC of DNA derived from the seed of an organic strawberry. Adducts near the four major DNA bases and more minor DNA bases appear in characteristic locations. Adducts near dTGMP are not detected. Minimal diphosphate products are indicated by the star along the X axis.

DNA ADDUCTS AS BIOMARKERS OF PESTICIDE/TOXICS EXPOSURE

265

FIG. 6. TLC of DNA derived from the #esh of an organic strawberry. Spots approximating adducts of the four major DNA bases and more minor DNA bases are demonstrated. Adducts near dTMP are not detected. The stars along the X axis represent diphosphate products.

four major bases include C1 (0.28%), C2 (1.32%), and C3 (3.33%) near dCMP; G1 (1.83%), G2 (0.09%), and G3 (0.03%) close to dGMP; and A1 (0.32%) near dAMP. An approximate adduct of dTGMP (18.73%), TG1 (0.49%), appears in the lower right corner of the autoradiograph. U1 (0.27%), U2 (0.10%), U3 (2.08%), and U4 (0.17%) constitute the adducts within proximity of dUMP. The stars situated along the X axis signify the diphosphate products (12.96%). Last, Fig. 7 is derived from the DNA of the #esh of an organic strawberry that has been dried out with silica. The four major DNA bases are illustrated, in a clockwise manner, as their respective dNMPs on the autoradiograph: dCMP (R ) X, >"10.5, 12.3; dTMP (R ) X, >"7.7, 7.6; x x dGMP (R ) X, >"3.3, 2.9; dAMP (R ) X, >"1.9, 6.5. C1 x x (2.16%), C2 (2.49%), and C3 (0.06%) are approximate adducts of dCMP. G1 (0.52%) is an adduct close to dGMP, and A1 (0.07%) is an adduct near dAMP. TG1 (0.44%) is an adduct near dTGMP (18.63%), which appears in its characteristic location at the lower right corner of the autoradiograph. U1 (0.86%), U2 (0.82%), U3 (1.42%), and U4 (0.47%) are approximate adducts of dUMP. The diphosphate products (15.10%) are marked by the stars located along the X axis. Computer-assisted laser densitometry was used to analyze the autoradiographs described above. Table 1 presents the percentage volumes (AU mm2) of the four major deoxynucleotide bases (adenosine, cytosine, guanine, and thymine) present within each strawberry sample. The

percentage volume of dAMP ranges from a maximum of 21.3% in the nonorganic strawberry seed sample to a minimum of 10.4% in the organic strawberry #esh sample. dCMP has a maximum percentage volume of 17.5% in the organic strawberry #esh sample and a minimum of 11.3% in the nonorganic strawberry leaf sample. dGMP ranges from a maximum percentage volume of 21.6% in the nonorganic strawberry seed sample to a minimum of 3.9% in the organic strawberry seed sample. Last, the percentage volume of dTMP ranges from a maximum of 30.7% in the nonorganic strawberry seed sample to a minimum of 15.3% in the organic strawberry #esh sample that has been dried with silica. Table 2 displays the retention factor (R ) [X, > (cm)] x coordinates of the four major deoxynucleotide bases (adenosine, cytosine, guanine, and thymine) for each of the autoradiographs presented above. Table 3 provides the individual adduct formation as a percentage of total deoxynucleotides for each of the strawberry samples. As evident in Table 3, there are considerable di!erences in the amounts and types of adduct formation between samples. Total adduct formation ranges from a maximum of 43.0% for the organic strawberry #esh sample that has been dried with silica to a minimum of 13.1% for the nonorganic strawberry seed sample. C1 (2.83%), TG2 (0.97%), and U3 (0.89%) are the most prominent adducts in the nonorganic strawberry seed sample. The major adducts in the nonorganic strawberry leaf sample are C3 (2.59%), A1 (0.96%),

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FIG. 7. TLC of DNA derived from the #esh of an organic strawberry dried with silica. The approximate migration patterns and adducts of the four major DNA bases and more minor DNA bases are shown. Adducts near dTMP are not detected. The stars along the X axis represent diphosphate products.

and U3 (0.36%). In the nonorganic strawberry #esh sample, adducts of dCMP (C1, 2.20%; C2, 2.30%), dGMP (G1, 1.13%, G2, 2.43%), and dUMP (U5, 0.98%) are present in the greatest percentages. G1 (3.68%), C1 (2.03%), and C2 (2.62%) are the major adducts in the nonorganic strawberry #esh sample that has been dried with silica. Most prominent in the organic strawberry seed sample are adducts G1 (3.49%), G2 (2.16%), and A1 (1.57%). The major adducts in the organic strawberry #esh sample are C2 (1.32%), C3 (3.33%), G1 (1.83%), and U3 (2.08%). Finally, C1 (2.16%), C2 (2.49%), and U3 (1.42%) are the most prominent adducts in the organic strawberry #esh sample that has been dried with silica. Thymidylate glycol ranges from a maximum of 28.42% in the organic strawberry seed sample to a minimum of 5.77% in the nonorganic strawberry seed sample. Total phosphates range from a maximum of

15.10% in the organic strawberry #esh sample that has been dried with silica to a minimum of 0.06% in the organic strawberry seed sample. DISCUSSION

Analytical methods are needed to screen, quantify, and con"rm the presence of pesticide residues in fruits and vegetables. Multiresidue methods and single residue methods generally require the same fundamental steps, but the MRMs are preferred for their ability to simultaneously determine the presence of multiple pesticide residues in a single analysis (Torres et al., 1996). Polar, water-miscible solvents, such as acetone and acetonitrile, are commonly used to extract pesticide residues from fruit and vegetable samples in the classical MRMs.

TABLE 1 Percentage Volumes (AU mm2) of the Four Major DNA Bases

Berry dAMP dCMP dGMP dTMP

Nonorganic seed

Nonorganic leaf

Nonorganic #esh

Nonorganic #esh w/silica

Organic seed

Organic #esh

Organic #esh w/silica

21.3 13.5 21.6 30.7

14.6 11.3 14.5 28.0

14.0 12.6 15.0 23.6

12.5 14.6 13.4 23.7

11.7 16.4 3.9 28.4

10.4 17.5 12.6 17.6

13.0 17.3 11.3 15.3

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TABLE 2 Retention Factors [Rx] [X, Y Axes (cm)] of the Four Major DNA Bases

Berry dAMP dCMP dGMP dTMP

Nonorganic seed

Nonorganic leaf

Nonorganic #esh

Nonorganic #esh w/silica

Organic seed

Organic #esh

Organic #esh w/silica

2.2, 9.2 11.8, 13.5 4.0, 4.3 7.4, 7.8

2.6, 9.0 12.6, 12.4 3.6, 3.6 7.2, 8.3

2.1, 8.0 10.9, 13.3 3.8, 3.3 7.2, 8.0

2.0, 6.5 11.4, 17.8 3.9, 2.8 7.7, 7.0

1.2, 9.7 11.3, 12.7 3.2, 4.7 6.0, 8.8

2.2, 7.2 11.1, 13.0 3.5, 3.3 7.4, 8.5

1.9, 6.5 10.5, 12.3 3.3, 2.9 7.7, 7.6

With these solvents, pesticide residues are usually separated from crude aqueous extracts by dilution with a salt solution and multiple separating funnel partitions into dichloromethane to remove hydrophilic unwanted coextractives. The dichloromethane is then dried by passage through a column of anhydrous sodium sulfate and subjected to clean-up with procedures inducing size exclusion chromatography, sweep codistillation, and column chromatograpy (Di Muccio et al., 1993). Finally, analyte determination is performed by a variety of procedures, including GC or HPLC with sensitive detectors (Pang et al., 1995; Torres et al., 1996). Under these conditions, a wide range of both polar and nonpolar pesticide residues can be recovered (Di Muccio et al., 1993). However, while these classical MRMs can detect approximately 325 di!erent pesticides, their global use is disadvantageous. They are too complex, time consuming, and labor

intensive to make them e$cient screening methods that can prevent contaminated foods from entering the marketplace (Di Muccio et al., 1993; Torres et al., 1996). Also, the food matrix is thousands of times more concentrated than the pesticide residue levels in the extract, thereby obscuring the signal from the pesticide (Schachterle and Feigel, 1996). Last, the quantities of toxic solvents and chemical reagents that are used, the occurrence of emulsions in the liquid} liquid partition (LLP) stage, the extensive preparation and maintenance of costly apparatus, and the number of handling operations pose additional barriers to the continued extensive use of the classical MRMs (Di Muccio et al., 1993; Torres et al., 1996). Improvements in the extraction and clean-up steps have been aimed at overcoming the drawbacks of the classical MRMs. Diminution of organic solvent toxicity has been achieved by replacing acetonitrile with acetone or acetone}

TABLE 3 Individual Adduct Formation as a Percentage of Total Deoxynucleotides

Sample AdductA1 AdductA2 AdductC1 AdductC2 AdductC3 AdductG1 AdductG2 AdductG3 AdductT1 AdductTG1 AdductTG2 AdductU1 AdductU2 AdductU3 AdductU4 AdductU5 DTGMP Total phosphates

Nonorganic seed

Nonorganic leaf

Nonorganic #esh

Nonorganic #esh w/silica

Organic seed

Organic #esh

0.29 0.06 2.83

0.96

0.06 0.04 2.20 2.30

0.03 0.02 2.03 2.62

0.32

0.07

1.13 2.43

3.68

1.57 0.04 0.56 0.39 0.42 3.49 2.16 0.10 0.20

0.28 1.32 3.33 1.83 0.09 0.03

2.16 2.49 0.06 0.52

0.49

0.44

0.41 0.04 0.03

0.07 0.03 2.59 0.04

0.03 0.97 0.15 0.21 0.89

0.14 0.03 0.36

5.77 1.42

Organic #esh w/silica

0.13 0.01 0.59 0.03 0.40 18.45

0.73

0.27 0.10 2.08 0.17

0.86 0.82 1.42 0.47

21.13

0.64 0.19 0.36 0.05 0.14 0.19 0.98 15.07

28.42

18.73

18.63

4.27

9.03

7.83

0.06

12.96

15.10

Note. Adducts/analogues are labelled geographically (i.e., adducts A1}A2 are close to adenine), but the true nature of these adducts is unknown. Blanks denote the absence of adducts in a certain region.

268

PODWALL ET AL.

dichloromethane in the extraction step. The LLP step has been eliminated with online MRMs that use ethyl acetate and sodium sulfate, with solid-phase extraction (SPE) methods, or with a column extraction method that uses diatomaceous earth as an adsorbent (Di Muccio et al., 1993; Torres et al., 1996). Capillary gas chromatography, coagulation methods, and gel permeation chromatography (GPC) represent techniques that have eliminated the column cleanup step. Matrix solid-phase dispersion accomplishes sample homogenization and cellular disruption, exhaustive extraction, fractionation, and puri"cation in a single process. Finally, this coupled with solid-phase sorbents such as octodecylsilane (ODS) also e!ectuates extraction and clean-up in a single step (Torres et al., 1996). Turning to the instrumental analysis of pesticides, the high resolving power associated with GC permits the separation of large numbers of pesticides with similar physicochemical characteristics. In the past 30 years, the electron capture detector (ECD) has been most used in pesticide residue analysis with GC. The ECD presents a very high sensitivity to polychlorinated hydrocarbons and other halogenated pesticides. Nevertheless, its selectivity is rather poor, as all kinds of electron-attracting functional groups produce responses on the ECD (Torres et al., 1996). The nitrogen}phosphorous detector (NPD) maintains a high selectivity for phosphorous and nitrogen containing compounds. Organophosphate pesticides, carbamates, triazines and their metabolites, and fungicides can all be determined via NPD. The #ame photometric detector (FPD), in phosphorous mode, is often the instrumental technique of choice for the analysis of organophosphate pesticides (Torres et al., 1996). Generally, however, the ECD, NPD, or FPD detectors do not yield con"rmatory results, and all are subject to the aforementioned interferences from the food matrix (Schachterle and Feigel, 1996). Last, the microwave induced plasma}atomic emission detector (MIP-AED) selectively detects #uorine, chlorine, bromine, iodine, phosphorous, sulfur, and nitrogen. As such, carbamate, pyrethroid, organochlorine, and organophosphorous pesticides can all be determined with GC-MIPAED (Torres et al., 1996). While GC-MS can also be used to detect pesticide residues, this procedure is primarily used to con"rm the results from other GC detectors. Tandem mass spectrometry (MSMS) without chromatography constitutes a procedure that detects trace pesticides in biological matrices, but this procedure is limited by the potential overlap of multiple pesticides and by the frequent need to clean the ion source. Gas chromatography coupled to tandem mass spectrometry furnishes a more direct analysis than GC-MS, primarily due to the removal of matrix interferences. GC-MS-MS can routinely analyze trace levels of pesticides with only minimal sample preparation. The method is rugged and reliable

and provides for the spectral con"rmation of target analytes at low concentrations (Schachterle and Feigel, 1996). HPLC is being extensively used in pesticide analyses where the chemicals of interest are frequently of low volatility or thermally unstable for GC separation. HPLC methods could employ reverse-phase chromatography followed by UV absorption, UV diode array, mass spectrometric, or #uorescence detection. Supercritical #uid chromatography is a chromatographic technique that combines many features of GC and HPLC. It can analyze thermolabile compounds which are not amenable to analysis by GC or HPLC. SFC provides versatility in separation and detection and o!ers the selective extraction of analytes with a small amount of organic solvent (Torres et al., 1996). Immunoassays provide rapid, highly sensitive, simple, and cost-e!ective analyses for a variety of pesticide residues. The main disadvantage of IA is that only one compound at a time can be determined with these procedures. Nevertheless, the usefulness of these techniques is evident during screening analyses when a large number of samples are analyzed in parallel for a single analyte within a short time. Among the di!erent IA procedures, the enzyme-linked immunosorbent assay (ELISA) has been the most frequently used to analyze agricultural products after solvent extraction. However, erroneous results can arise from matrix e!ects or from the inability of ELISA to di!erentiate between structurally similar compounds (cross-reactivity) (Torres et al., 1996). However, while all of the above techniques have been used with varying success to determine the presence of pesticides in fruits and vegetables, none of them can detect the nature of speci"c pesticide-induced DNA lesions in fruits and vegetables. As a result, in this study, thin-layer chromatography was performed on multiple samples obtained from organic and nonorganic strawberries. There were both organic and nonorganic seed and #esh samples. Although a nonorganic leaf sample was analyzed, no organic leaf sample was available, since the organic strawberries were shipped without leaves. Using these samples, each sequential step in the technique generated a clean preparation, characterized by minimal contamination. Sample degradation was also minimal, as evidenced by the high e$ciency of radiolabeling obtained both in the present study and in previous publications (Steinberg et al., 1992, 1996). Since only radiolabeled products were detected, the e$ciency of labeling critically in#uenced the ability to use the technique as a quantitative indicator of adduct formation. Unincorporated nucleotides were removed from radiolabeled nucleotides via a series of washings with ethanol and distilled water. The comparison of DNA base composition and adduct formation in nonorganic versus organic strawberry samples revealed the susceptibility to DNA adduct formation caused by xenobiotics, which include pesticides. The

DNA ADDUCTS AS BIOMARKERS OF PESTICIDE/TOXICS EXPOSURE

deoxynucleotide base composition of DNA from the various strawberry samples was determined by 32P shotgun labeling thin-layer chromatography. The autoradiographs of each strawberry sample revealed the presence of all four of the major deoxyribonucleotide bases, in varying amounts. The ranges in percentage volume of the DNA base composition among the strawberry samples were approximately dAMP 21.3 to 10.4%; dCMP 17.5 to 11.3%; dGMP 21.6 to 3.9%; and dTMP 30.7 to 15.3% (Table 1). In addition to the presence of the four major deoxyribonucleotide bases, all of the organic and nonorganic strawberries tested, without exception, demonstrated multiple known and unknown adducts within proximity of the four major bases. All of the organic and nonorganic strawberry samples also indicated adducts near the more minor bases dUMP and dTGMP. However, although each strawberry sample demonstrated multiple DNA adduct formation, the speci"c pro"le of adducts manifested was unique to each strawberry sample (Table 3). Speci"cally, Table 3 illustrates that the organic seed sample contained approximate adducts of cytosine (adducts C2 and C3) and thymine (adduct T1) that were not present in the nonorganic seed sample. Conversely, the nonorganic seed sample contained adducts close to thymidylate glycol (TG1 and TG2) and uracil (U2 and T3) that were not found within the organic seed sample. Similarly, the organic #esh sample demonstrated adducts near cytosine (C3) and guanine (G3) that were not found in the nonorganic #esh sample. Likewise, the nonorganic #esh sample contained adducts about adenine (A2), thymidylate glycol (TG2), and uracil (U5) that were absent in the organic #esh sample. Samples of wet strawberry #esh were compared to #esh samples dried out with silica to determine the reproducibility and integrity of the protocol. In this vein, the nonorganic #esh and nonorganic #esh with silica samples were compared with the organic #esh and organic #esh with silica samples. The variation between these two sets of samples was within the percentage error; adduct formation between the two sets was virtually identical. Thus, the silica con"rmed the integrity of the protocol; the protocol itself did not alter the DNA base composition of the strawberry samples. However, the nonorganic #esh and nonorganic #esh with silica samples did vary slightly with respect to the presence of adducts G1 and G2. As presented in Table 3, the nonorganic #esh sample contained the adducts approximately corresponding to G1 (1.13%) and G2 (2.43%), while the nonorganic #esh with silica sample demonstrated only the adduct approximating G1 (3.68%). This discrepancy was due to the extreme sensitivity of the protocol. Due to the extreme proximity of adducts G1 and G2 in the nonorganic #esh with silica sample, the adducts did not seperate su$ciently to be identi"ed as two distinct adducts. Nevertheless, the base composition and overall location on the autoradio-

269

graph were similar for adducts G1 and G2 in both samples (nonorganic #esh adducts G1#G2+nonorganic #esh with silica adduct G1). Similar results occurred when the nonorganic #esh and nonorganic #esh with silica samples were compared with respect to adducts near dTGMP, and when the organic #esh and organic #esh with silica samples were compared with respect to adducts close to guanine. Thus, the integrity of these sets remained intact. The dissimilarities in the adduct patterns among the various parts of the strawberry may indicate the di!erential e!ects of xenobiotics on each section, as well as variation in xenobiotic uptake and transport. While adduct formation in the organic samples is not attributed to direct pesticide exposure, these adducts may be the result of environmental adaptations or pesticide exposure in previous generations. Adduct formation in the organic samples may also be attributed to ecosystem factors, such as upstream contamination of the water table by pesticide run-o!, drift from pesticides used by neighboring farmers, and mosquito control fumigation. When organic strawberries are subject to such potential sources of contamination, the meaning of the term &&organic'' becomes obscured and di$cult to interpret, especially from the perspective of the public consumer. Last, although Fragaria x ananassa Duch. is the only commercially marketed species of strawberry, some species of strawberries (both organic and nonorganic) may possess inherently di!erent susceptibilities to pesticide treatment and adduct formation, a consideration that may prove critical for a truly accurate evaluation of the data. Testing multiple additional species of strawberries in future studies may elucidate the extent of these di!erential susceptibilities and interspecies variations. CONCLUSION

A thorough search was undertaken in this study to obtain a broad representation of strawberries that are currently available to consumers. As such, the comparison of organic strawberries produced in California with nonorganic strawberries grown in New York enabled the present study to approximate actual, &&real-life'' scenarios that consumers confront on a daily basis. However, for the purpose of assessing the present technique, the use of strawberries grown under strictly controlled conditions would have offered other advantages. While this poses a limitation, the present study nevertheless provides a foundation for comparison with future studies that do evaluate the technique with samples grown under identical laboratory conditions. The technique used in this study provides a powerful tool with which to elucidate the e!ects of xenobiotics such as pesticides on our food supply. This, in turn, may further our understanding of the impact of pesticides on our food supply and, ultimately, on human health. As more farmers produce and consumers choose organically grown products,

270

PODWALL ET AL.

it becomes important that the community understand the true di!erences between organic and nonorganic produce as they relate to potential admixture with pesticides and toxics. While acute pesticide toxicity is well described, the longterm e!ects remain less certain. This especially holds true for the most susceptibile, although insu$ciently studied, population*children. Concerns about toxicity in children become even more relevant when we consider that the nervous, immune, and reproductive systems continue to mature after birth (National Research Council, 1993). Effects on these or other systems may become obvious or may remain silent until such time as a given function is needed. The possibility of neurotoxic and behavioral e!ects from chronic low-level pesticide exposure, as well as the epidemiological implications of such e!ects, is still to be determined. ACKNOWLEDGMENTS This paper is dedicated to the memory of Joshua Lipetz, a gifted young research student who devoted himself to the pursuit of science from 1996 to 1999. May it serve as an enduring testimonial to his passion, wisdom, and spirit. The authors acknowledge Michele Golden, Jose Pena, Elizabeth Mendez, Ph.D., Racheline G. Habousha, Annie D'Errico, Barry Mordin, and Dolores Roberts-Roy for all contributions to this e!ort. They thank Victor A. Albert of the New York Botanical Garden and the Albert Einstein Cancer Center Scienti"c Computing Facility for the use of their facilities.

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