Abstract Exposure to pesticides can trigger genotoxic and mutagenic processes through different pathways. However, epidemiological studies are scarce, and further work is needed to find biomarkers sensitive to the health of exposed populations. Considering that there are few evaluations of soybean farmers, the aim of this study was to assess the effects of human exposure to complex mixtures of pesticides. The alkaline comet assay modified with restriction enzyme (hOGG1: human 8-oxoguanine DNA glycosylase) was used to detect oxidised guanine, and compared with the buccal micronucleus cytome assay, global methylation, haematological parameters, biochemical analyses (serum glutamic oxaloacetic transaminase, serum glutamic pyruvic transaminase, gamma-glutamyl-transferase and butyrylcholinesterase), and particle-induced X-ray emission (PIXE) for the analysis of inorganic elements. Farm workers (n = 137) exposed to different types of pesticides were compared with a non-exposed reference group (control; n = 83). Results of the enzyme-modified comet assay suggest oxidation of guanine in DNA generated by pesticides exposure. It was observed that DNA damage (comet assay and micronucleus test) was significantly increased in exposed individuals compared to the unexposed group. The micronucleus test demonstrated elimination of nuclear material by budding, defective cytokinesis and dead cells. Occupationally exposed individuals also showed genomic hypermethylation of DNA, which correlated with micronucleus frequency. No differences were detected regarding the haematological and biochemical parameters. Finally, significantly higher concentrations of Al and P were observed in the urine of the soybean farmers. DNA damage could be a consequence of the ability of the complex mixture, including Al and P, to cause oxidative damage. These data indicate that persistent genetic instability associated with hypermethylation of DNA in soybean workers after long-term exposure to a low-level to pesticides mixtures may be critical for the development of adverse health effects such as cancer. Introduction Pesticides are used extensively around the world in the production of different types of crops, in order to control or prevent pests, diseases, weeds and other plant pathogens (1). The purchase and use of pesticides in Brazil are growing due to expanding agriculture, mainly of soybeans. The National Supply Company of Brazil (CONAB) has a projection that estimates soybean production to be ~193.6 million tons, with the area of land cultivated increasing by 10.3 million hectares (an increase of 36.9%) over the next 10 years (2). The significant increase in soybean production involves the use of several pesticides for crop protection and pest control, according to plant varieties, mechanisms of action, environmental pathogens and conditions, and any repeated applications that become necessary may occur periodically until the plant disease is eradicated. Serious toxicological consequences observed in rural workers exposed to pesticides may partly explain the link between pesticide exposure and adverse health outcomes. Pesticide exposure can alter cell components, including lipids, proteins and DNA, which, if not repaired, can lead to the development of mutations, apoptosis, uncontrolled cellular proliferation and can disturb cellular homeostasis (3). Furthermore, exposure to pesticides may induce chronic diseases, including a variety of cancers at sites such as lip, skin, prostate, colon, rectum, pancreas, lungs, bladder and brain, as well as non-Hodgkin lymphoma, Hodgkin’s disease, leukaemia and multiple myeloma (4–6). Several studies have indicated that pesticides induce chromosomal aberrations (CA) (7–9), sister chromatid exchange (SCE) (10), micronucleus (MN) formation (11–18), DNA strand breaks (9,12–16,19) and epigenetic modifications (20). It is known that chronic exposure to pesticides is associated with epigenetic changes, interfering with gene expression without altering the DNA sequence (20). However, it is necessary that more studies be carried out on exposed populations. The intensive use of pesticides can promote genetic changes cumulatively in humans, silently and without clinical evidence, commonly resulting from long-term exposure and chronic poisoning triggering genotoxic and epigenetic processes through different pathways, interactions and dosages (21). However, epidemiological studies are scarce, and further work is needed to find biomarkers sensitive to the health of exposed populations (21,22). Considering that there are few evaluations discussing mechanisms of genetic alterations in relation to human population exposed to complex mixtures of pesticides, the aim of this study was to assess genetic and epigenetic effects in soybean farmers exposed to pesticides and their relationship with oxidative stress mechanisms. Methods Study population The study population comprised 220 male individuals from Espumoso (in the northeastern region of the state of Rio Grande do Sul (RS), southern Brazil. Subjects for this study were sampled from 2008 to 2015, during the intensive use of pesticides (January and February). All sample collections periods included exposed and unexposed individuals. The exposed group was invited to participate by the Institute of Technical Assistance and Rural Extension of Rio Grande do Sul (EMATER). EMATER is responsible for monitoring the farmers’ exposure to pesticides in the region of this study. The total sample comprised 137 individuals exposed to pesticides (mean age: 47.5 ± 12.5) and 83 control individuals who were unexposed to pesticides (mean age: 43.9 ± 14.6). All individuals examined in the study were asked to answer a Portuguese version of a questionnaire prepared by the International Commission for Protection against Environmental Mutagens and Carcinogens (23) and to participate in a face-to-face interview. The questionaire included questions involving standard demographic data (age, gender, etc.), medical issues (exposure to X-rays, vaccinations, medication, etc.), lifestyle (smoking, alcohol consumption, diet, etc.) and occupation (number of working hours per day, time exposed to organic solvents, use of protective measures, etc.). The control group was comprised of male individuals who were office employees living in the same region as the exposed individuals. Blood, urine samples and buccal cells were collected during the same period for both groups. None of the unexposed individuals had recently been exposed to agrochemicals or any other suspected genotoxic agents, and they had no previous occupational exposure to genotoxicants. Individuals with a history of chronic diseases and smoking, as well as subjects with intoxication were excluded from this study. The study was approved by the Brazilian National Committee on Research Ethics (Comissão Nacional de Ética em Pesquisa), and informed written consent was obtained from each individual before the start of the study. Sample collection All blood samples were collected by venipuncture using vacutainers (with heparin and ethylenediaminetetra acetic acid (EDTA). The buccal samples for the MN assay were obtained by rubbing the inside of the cheeks with a cytobrush, according to the recommendations of Thomas et al. (24). The 5-ml urine samples were collected in disposable bottles. The samples were processed as quickly as possible, to prevent damage associated with storage; blood cell and urine samples were transported to the laboratories at 4°C until processing. Haematological parameters The haematological study was performed using an automatic analyser (Sysmed KX21) to measure haematological parameters followed by morphological analyses under the microscope of the leukocytes (banded neutrophils, segmented neutrophils, eosinophils, basophils, lymphocytes and monocytes), erythrocytes, hematocrit, haemoglobin, mean corpuscular volume, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, red blood cell distribution width and platelets. Biochemical assays To assess the effects of intensive exposure to complex mixtures of pesticides in farm workers exposed to pesticides, we evaluated the activities of butyrylcholinesterase (BChE), gamma-glutamyl-transferase (GGT), serum glutamic oxaloacetic transaminase (SGOT), serum glutamic pyruvic transaminase (SGPT) and total serum protein. Serum enzymes and parameters were measured using a Biosystems BTS 350 semi-automated analyser, according to the methods described by Labtest®. Comet assay The comet assay was performed to detect DNA strand breaks and alkali labile sites, as well as oxidised DNA bases. The DNA strand breaks were detected with a simple version of the comet assay, and oxidised DNA bases were detected by incubating DNA with bacterial restriction enzyme, human 8-oxoguanine DNA glycosylase (hOGG1; New England BioLabs), which is known for recognising the common oxidised purine 8-oxoGua. The alkaline comet assay was performed as described by Tice et al. (25). Whole blood samples (5 µl) were embedded in 95 µl of 0.75% low melting point agarose, and after the agarose solidified, slides were placed in lysis buffer (2.5 M NaCl, 100 mM EDTA and 10 mM Tris; pH 10.0–10.5) containing freshly added 1% (v/v) Triton X-100 and 10% (v/v) dimethyl sulphoxide for a minimum of 1 h and a maximum of 1 week at 4°C. After treatment with lysis buffer, slides were incubated in freshly prepared alkaline buffer solution (300 mM NaOH and 1 mM EDTA; pH > 13) for 20 min, and DNA was electrophoresed for 20 min at 25 V (0.90 V/cm) and 300 mA, after which the buffer solution was neutralised with 0.4 M Tris (pH 7.5). Slides were prepared from each subject for observing both DNA strand breaks and oxidised DNA bases using hOGG1 post-treatment (26). The slides were briefly washed three times with enzyme buffer (40 mM Hepes, 100 mM KCl, 0.5 mM Na2EDTA, 0.2 mg/ml bovine serum albumin, pH 8.0) and the enzyme was diluted immediately before use and incubated with hOGG1 (1600 U/ml), incubated for 30 min, 37°C, 100 mU per gel. All of the above steps were performed under yellow light or in the dark to prevent additional DNA damage. The positive control slide was dipped into H2O2 (100 µM in phosphate buffered saline [PBS]) solution for 5 min at 4°C, then washed with cold PBS and introduced into a lysis solution in a separate jar for at least 1 h. The slides were stained with silver nitrate. Slides were randomised and coded to blind the scorer. Images of 100 randomly selected cells (50 cells from each of two replicate slides) were analysed for each individual under a microscope using 40× magnification. Comets were scored and visually classified into five classes (from no damage = 0 to maximum damage = 4) according to tail size and shape. Damage index (DI) thus ranged from 0 (completely undamaged or undetectable tails: 100 cells × 0) to 400 (with maximum damage: 100 cells × 4); consequently the total comet score (DI) was within 0–400 arbitrary units. International guidelines and recommendations for the comet assay consider that visual scoring of comets is a well-validated evaluation method (27). Arbitrary units from the alkaline comet assay (without enzyme) represent the DNA strand breaks; and net hOGG1-sensitive sites were calculated by subtracting the arbitrary units of test without enzyme from the arbitrary units of the enzyme-treated test (which gives a measure of oxidised guanine, primarily 8-oxoGua). The human buccal micronucleus cytome assay (BMNCyt) The BMNCyt test in exfoliated epithelial cells of oral mucosa was performed according to the method described by Thomas et al. (24). Briefly, buccal cell samples were collected from the inner cheeks of the subjects, kept in cold buffer and transported under refrigeration to the laboratory. Samples were washed twice with saline solution and once with Carnoy’s fixative (methanol and glacial acetic acid, 3:1) under the same centrifugation conditions. The cell suspension was dropped onto a slide and allowed to air dry. The slides were stained with Schiff’s reagent for 60 min in the dark at room temperature, and Light Green for 20–30 s. For each individual, the frequency of the various cell types in the assay is represented as the number of cells in 2000 (1000 from each of the duplicate slides). The BMNCyt assay has been used to measure biomarkers of DNA damage (micronuclei and/or elimination of nuclear material by budding, buds), cytokinetic defects (binucleated cells) and cell death (condensed chromatin, karyorrhectic, pyknotic and karyolytic cells). Global DNA methylation analysis Global DNA methylation levels were measured in isolated DNA through relative quantification of 5-mdC using liquid chromatography by high performance liquid chromatography (HPLC) as described by Berdasco et al. (28) and Cappetta et al. (29). Briefly, 1 μg of genomic DNA (in 10 μl of ultra-pure water) from each sample was denatured at 94°C for 10 min and rapidly cooled on ice for 5 min. Then, DNA was hydrolyzsd with nuclease P1 and alkaline phosphatase to yield 2′-deoxymononucleosides, which were separated by HPLC on a dC18 reverse-phase Atlantis column (2.1 × 20 mm, Waters), protected by a pre-column, at a constant flow of 0.15 ml/min; DNA was detected by UV light. A mixture of deoxyadenosine, deoxythymidine, deoxyguanosine, deoxycytidine, 5-mdC and deoxyuridine was used as a standard. Results are expressed as percentages (%) of global genomic DNA methylation, and were calculated by integration of the 5-mdC peak area (obtained from HPLC) relative to global cytidine (methylated or not). Duplicated samples showing a difference in 5-mdC greater than 3% or with low HPLC resolution were removed. Inorganic elements analysis The inorganic element content of the urine samples was analysed through the Particle-induced X-ray emission (PIXE) technique (30). The experiments were carried out at the Ion Implantation Laboratory of the Physics Institute of the Federal University of Rio Grande do Sul (IF-UFRGS). Urine samples were filtered under pressure across 30-mm diameter filters in triplicate for each sample, pore size 0.22 mm and subsequently placed in the target holder inside the PIXE reaction chamber. A 3-MV Tandetron accelerator provides a 2.0-MeV proton beam with an average current of 5 nA at the target. The X-rays produced were detected by a Si (Li) detector (31) and the spectra were fitted to obtain the elemental concentrations using the GUPIXWIN software package (32). The results were expressed in ng/cm2. Statistical analysis The normality of the variables was evaluated by the Kolmogorov–Smirnov test, and Student’s t test was used to compare the characteristics of the study population. The statistical differences of biochemical assays, haematological parameters, damage observed by the comet assay and BMNCyt assay, % of global genomic DNA methylation and PIXE values between exposed and unexposed (control) were determined by the Mann–Whitney (normal distribution) test or corrected by Welch. P ≤ 0.05 was considered statistically significant. Correlations between two parameters were assessed using Spearman’s test (for independent samples) or Pearson’s test (for paired samples). All analyses were performed using the Graphpad PRISM statistical software (Graphpad Inc., San Diego, CA). Results The characteristics of the study population of workers exposed to pesticides and the controls are summarised in Table 1. The group consisted of farm workers regularly exposed to pesticides about three to five times a week and directly involved in the preparation and application of pesticides in soybean fields. They had been simultaneously exposed to a complex mixture of pesticides since childhood. Almost 66% of those exposed to pesticides reported not using any kind of protection during pesticide preparation and application (gloves, breathing masks, protective goggles, waterproof boots, etc.) and presented some symptoms related to exposure to pesticides such as headaches, abdominal pain, nausea and vomiting. According to the practice of spraying pesticides, in this study two different groups were defined: (i) those that use a tractor with coupled tanks; and (ii) those that use both tractors with coupled tanks and hand pumps. Hand pumps are described as useful tools for successive pesticide applications. Furthermore, besides mixing and filling the spraying equipment, soybean growers apply the pesticides using hand pumps and tank sprays. Table 1. Characteristics of the study population Variable Unexposed group Exposed group Total individuals evaluated (n) 83 137 Age (years) 43.9 ± 14.6 47.5 ± 12.5 Exposure time (years) — 29.9 ± 12.8 PPEa Use — 47 (34%) Not use — 90 (66%) Form of spraying (n) Tractor — 59 (43%) Tractor plus hand pump — 78 (57%) Variable Unexposed group Exposed group Total individuals evaluated (n) 83 137 Age (years) 43.9 ± 14.6 47.5 ± 12.5 Exposure time (years) — 29.9 ± 12.8 PPEa Use — 47 (34%) Not use — 90 (66%) Form of spraying (n) Tractor — 59 (43%) Tractor plus hand pump — 78 (57%) aUse of personal protection equipment (PPE): at least gloves, boots and mask protection. View Large Supplementary Table 1, available at Mutagenesis Online, shows the main pesticides used and their relation to DNA damage and toxicity. The confirmation of these specific pesticides was obtained directly from the vendor of agricultural products. The agricultural workers included in this study were exposed to complex mixtures of pesticides, such as herbicides (25.9%), fungicides (22.4%), and mainly insecticides (51.7%). Regarding the haematological markers: leukocytes (banded neutrophils, segmented neutrophils, eosinophils, basophils, lymphocytes and monocytes), erythrocytes, hematocrit, hemoglobin, mean corpuscular volume, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, red blood cell distribution width and platelets, both study groups presented normal values, according to Naoum and Naoum (33,34), and no significant differences were observed between exposed and unexposed group (Table 2). Table 2. Haematological parameters (mean ± standard deviation) of unexposed controls and exposed groups Haematological parameters Unexposed group Exposed group Reference values Erythrogram Erythrocytes (millions/µl) 4.9 ± 0.4 5.1 ± 0.4 4.0–5.6 million/µl Haemoglobin (g/dl) 14.5 ± 0.9 15.2 ± 1.2 11.3–14.5 g/dl Haematocrit (%) 42.4 ± 2.6 39.9 ± 11.3 36–48% Mean corpuscular volume (fl) 86.8 ± 2.7 87.4 ± 3.7 77–92 fl Mean corpuscular haemoglobin (pg) 29.7 ± 1.2 29.8 ± 1.5 27–29 pg Mean corpuscular haemoglobin concentration (g/dl) 34.2 ± 0.9 34.1 ± 0.9 30–35 g/dl Red blood cell distribution width (%) 12.9 ± 0.8 12.9 ± 0.9 10–15% Platelets (mm3) 229 800 ± 59.5 219 900 ± 47.7 150 000–450 000/mm3 Leukogram Leukocytes/µl 6000 ± 1.7 6200 ± 1.5 4000–11 000/µl Banded neutrophils/µl 146 ± 59.1 153 ± 90.5 45–330/µl Segmented neutrophils/µl 3605 ± 1.2 3668 ± 1.1 2500–7500/µl Eosinophils/µl 138 ± 98.6 183 ± 23.7 40–330/µl Basophils/µl 3.7 ± 3.6 4.5 ± 6.0 1–100/µl Lymphocytes/µl 1939 ± 0.7 1971 ± 0.5 1500–4000/µl Monocytes 221 ± 86.9 225 ± 34.3 200–800/µl Haematological parameters Unexposed group Exposed group Reference values Erythrogram Erythrocytes (millions/µl) 4.9 ± 0.4 5.1 ± 0.4 4.0–5.6 million/µl Haemoglobin (g/dl) 14.5 ± 0.9 15.2 ± 1.2 11.3–14.5 g/dl Haematocrit (%) 42.4 ± 2.6 39.9 ± 11.3 36–48% Mean corpuscular volume (fl) 86.8 ± 2.7 87.4 ± 3.7 77–92 fl Mean corpuscular haemoglobin (pg) 29.7 ± 1.2 29.8 ± 1.5 27–29 pg Mean corpuscular haemoglobin concentration (g/dl) 34.2 ± 0.9 34.1 ± 0.9 30–35 g/dl Red blood cell distribution width (%) 12.9 ± 0.8 12.9 ± 0.9 10–15% Platelets (mm3) 229 800 ± 59.5 219 900 ± 47.7 150 000–450 000/mm3 Leukogram Leukocytes/µl 6000 ± 1.7 6200 ± 1.5 4000–11 000/µl Banded neutrophils/µl 146 ± 59.1 153 ± 90.5 45–330/µl Segmented neutrophils/µl 3605 ± 1.2 3668 ± 1.1 2500–7500/µl Eosinophils/µl 138 ± 98.6 183 ± 23.7 40–330/µl Basophils/µl 3.7 ± 3.6 4.5 ± 6.0 1–100/µl Lymphocytes/µl 1939 ± 0.7 1971 ± 0.5 1500–4000/µl Monocytes 221 ± 86.9 225 ± 34.3 200–800/µl View Large Table 3 shows the results of GGT, SGOT, SGPT and total serum protein. No significant difference was found in any of the biochemical parameters from unexposed and exposed groups analysed, and the values were within the normal range. Additionally, to determine the exposure to organophosphorus and carbamates the activities of BChE were assessed in unexposed and exposed groups and no significant difference was found; the results were within the normal range (Table 3). Table 3. Biochemical analyses, serum glutamic oxaloacetic transaminase (SGOT), serum glutamic pyruvic transaminase (SGPT), gamma-glutamyl-transferase (GGT) and butyrylcholinesterase (BChE), obtained from unexposed and exposed groups Biochemical analyses Unexposed group Exposed group SGOT (U/l) 39.3 ± 15.4 32.6 ± 12.2 SGPT (U/l) 22.6 ± 15.3 23.3 ± 13.8 GGT (U/l) 28.2 ± 12.6 26.7 ± 19.3 Total protein (g/l) 7.8 ± 1.5 8.7 ± 2.9 BChE (U/l) 7539 ± 1863 7521 ± 2284 Biochemical analyses Unexposed group Exposed group SGOT (U/l) 39.3 ± 15.4 32.6 ± 12.2 SGPT (U/l) 22.6 ± 15.3 23.3 ± 13.8 GGT (U/l) 28.2 ± 12.6 26.7 ± 19.3 Total protein (g/l) 7.8 ± 1.5 8.7 ± 2.9 BChE (U/l) 7539 ± 1863 7521 ± 2284 Data presented as mean ± standard deviation. View Large The results of comet assay in unexposed and exposed groups are presented in Figure 1. A significant increase of DI was observed for the exposed group relative to unexposed group (P < 0.01; Mann–Whitney test). In addition, the enzyme-modified comet assay (with hOGG1) demonstrated for exposed group a significantly higher levels of oxidised guanine relative to the unexposed group (P < 0.001; Mann–Whitney test). In order to monitor the ongoing process of the assay, a positive control for strand breaks (cells treated with a solution H2O2) were included. Mean result of positive control exposed to enzyme showed a significant increase of DI (290.0 ± 60.4; with hOGG1) when compared with positive control without enzyme (166.7 ± 16.4; without hOGG1) (P < 0.01; Mann–Whitney test). Figure 1. View largeDownload slide DNA damage using the comet assay was measured as DNA strand breaks (white bars) or oxidative damage, expressed as net hOGG1ss (ss: sensitive sites; gray bars), in whole blood cells of unexposed and exposed groups. DNA damage was measured in arbitrary units (0–400). **Significant at P < 0.01 in relation to unexposed group (strand breaks); and ***Significant at P < 0.001 in relation to unexposed group (net hOGG1ss) (Mann–Whitney test). DNA strand breaks were detected with the standard alkaline comet assay, and net hOGG1ss obtained by subtraction of strand breaks from hOGG1ss, which gives a measure of oxidised guanine (primarily 8-oxoGua). Figure 1. View largeDownload slide DNA damage using the comet assay was measured as DNA strand breaks (white bars) or oxidative damage, expressed as net hOGG1ss (ss: sensitive sites; gray bars), in whole blood cells of unexposed and exposed groups. DNA damage was measured in arbitrary units (0–400). **Significant at P < 0.01 in relation to unexposed group (strand breaks); and ***Significant at P < 0.001 in relation to unexposed group (net hOGG1ss) (Mann–Whitney test). DNA strand breaks were detected with the standard alkaline comet assay, and net hOGG1ss obtained by subtraction of strand breaks from hOGG1ss, which gives a measure of oxidised guanine (primarily 8-oxoGua). In this study, we determined the mutagenic and cell death potential of pesticides through the increased frequency of micronuclei (chromosomal mutations), nuclear bud (elimination of nuclear material by budding), binucleated cells (defective cytokinesis) and cell death (condensed chromatin, karyorrhectic, pyknotic and karyolytic cells) (Table 4). The BMNCyt assay showed a significant increase of micronuclei, nuclear bud and broken eggs, binucleated cells, karyorrhectic, pyknotic and karyolytic cells among the exposed group when compared with the unexposed group. Table 4. BMCyt assay for cells collected from the unexposed and exposed groups Parameters Unexposed group Exposed group DNA damage MN 0.6 ± 1.0 2.8 ± 2.2*** Nuclear buds 1.0 ± 0.2 4.3 ± 0.3*** Binucleated cells 3.5 ± 4.7 7.6 ± 5.6*** Cell death Condensed chromatin 9.3 ± 5.6 11.3 ± 7.9 Karyorrhectic cells 9.0 ± 5.3 13.6 ± 9.0*** Pyknotic cells 1.3 ± 1.8 3.5 ± 3.5 *** Karyolytic cells 5.3 ± 4.3 9.8 ± 7.1*** Parameters Unexposed group Exposed group DNA damage MN 0.6 ± 1.0 2.8 ± 2.2*** Nuclear buds 1.0 ± 0.2 4.3 ± 0.3*** Binucleated cells 3.5 ± 4.7 7.6 ± 5.6*** Cell death Condensed chromatin 9.3 ± 5.6 11.3 ± 7.9 Karyorrhectic cells 9.0 ± 5.3 13.6 ± 9.0*** Pyknotic cells 1.3 ± 1.8 3.5 ± 3.5 *** Karyolytic cells 5.3 ± 4.3 9.8 ± 7.1*** Data presented as mean ± standard deviation from 2000 cells per subject. ***Significant at P < 0.001 in relation to unexposed group (Mann–Whitney Test). View Large Table 5 shows results obtained in the comet assay and BMNCyt assay for two modes of spraying pesticides and use of personal protection equipment (PPE). The results did not indicate significant differences between groups for both the comet assay and the BMNCyt assay. Table 5. Parameters on DNA damage in the exposed group: BMNCyt assay and alkaline comet assay results in relation to use or not use of personal protection equipment (PPE) and form of exposure (tractor or tractor plus hand pump) Parameters Personal protection equipment Form of exposure Not use of PPE Use of PPE Tractor Tractor plus Hand pump Comet assay Damage index (0–400) 42.8 ± 24.1 36.6 ± 19.7 39.4 ± 25.3 43.1 ± 20.7 BMNCyt DNA damage Micronuclei 2.5 ± 2.1 3.2 ± 2.5 3.2 ± 2.3 2.5 ± 2.2 Nuclear buds 4.7 ± 4.9 3.7 ± 3.5 3.9 ± 3.5 4.5 ± 5.0 Binucleated cells 7.5 ± 5.5 7.9 ± 5.8 9.1 ± 6.9 6.6 ± 4.3 Cell death Condensed chromatin 10.2 ± 7.7 12.8 ± 8.4 10.2 ± 8.6 12.1 ± 7.5 Karyorrhectic cells 12.3 ± 7.6 15.5 ± 10.0 11.7 ± 8.2 15.0 ± 9.5 Pyknotic cells 3.6 ± 3.7 3.5 ± 2.9 3.7 ± 3.5 3.3 ± 3.5 Karyolytic cells 9.8 ± 7.0 8.9 ± 5.4 9.7 ± 7.4 9.9 ± 6.6 Parameters Personal protection equipment Form of exposure Not use of PPE Use of PPE Tractor Tractor plus Hand pump Comet assay Damage index (0–400) 42.8 ± 24.1 36.6 ± 19.7 39.4 ± 25.3 43.1 ± 20.7 BMNCyt DNA damage Micronuclei 2.5 ± 2.1 3.2 ± 2.5 3.2 ± 2.3 2.5 ± 2.2 Nuclear buds 4.7 ± 4.9 3.7 ± 3.5 3.9 ± 3.5 4.5 ± 5.0 Binucleated cells 7.5 ± 5.5 7.9 ± 5.8 9.1 ± 6.9 6.6 ± 4.3 Cell death Condensed chromatin 10.2 ± 7.7 12.8 ± 8.4 10.2 ± 8.6 12.1 ± 7.5 Karyorrhectic cells 12.3 ± 7.6 15.5 ± 10.0 11.7 ± 8.2 15.0 ± 9.5 Pyknotic cells 3.6 ± 3.7 3.5 ± 2.9 3.7 ± 3.5 3.3 ± 3.5 Karyolytic cells 9.8 ± 7.0 8.9 ± 5.4 9.7 ± 7.4 9.9 ± 6.6 Data presented as mean ± standard deviation. View Large Mean values of % of global DNA methylation, and minimum and maximum values, are shown in Figure 2. A significant difference was observed between exposed and unexposed groups (P = 0.0157). Figure 2. View largeDownload slide % Global DNA methylation of unexposed and exposed groups. Data presented as mean ± standard deviation, minimum and maximum values. *Significant at P < 0.05 in relation to unexposed (Mann–Whitney test). Figure 2. View largeDownload slide % Global DNA methylation of unexposed and exposed groups. Data presented as mean ± standard deviation, minimum and maximum values. *Significant at P < 0.05 in relation to unexposed (Mann–Whitney test). No correlations were demonstrated between DNA damage (comet assay and BMNCyt test) and age and exposure time for both groups (data not shown), except for nuclear bud cells and age in the unexposed group (rs = 0.3891; P = 0.0305). A significant correlation was demonstrated between micronucleated cells and others parameters in the exposed group: % DNA methylation (rs = 0.3843; P = 0.0009); nuclear bud (rs = 0.5646; P < 0.0001); binucleated cells (rs = 0.3462; P = 0.0033). Cells with micronuclei were also correlated with nuclear bud (rs = 0.4706; P = 0.0075) and binucleated cells (rs = 0.4205; P = 0.0185) in the unexposed group. Analyses of trace element (ng/cm2; mean ± standard error) content in urine samples of the unexposed and exposed groups through PIXE are shown in Table 6, and higher concentrations of aluminium (Al) and phosphorus (P) were observed in urine of exposed individuals than that of unexposed individuals. Table 6. Inorganic elements content in the urine samples using the particle-induced X-ray emission (PIXE) technique from unexposed and exposed groups Elements Unexposed group (ng/cm2) Exposed group (ng/cm2) Aluminium (Al) 2.7 ± 5.4 44.1 ± 44.5** Silicon (Si) 21.8 ± 24.4 48.6 ± 40.7 Phosphorus (P) 20.1 ± 12.9 544.6 ± 305.1*** Chlorine (Cl) 151.7 ± 194.5 232 ± 112.6 Potassium (K) 224.7 ± 197.5 271.0 ± 84.0 Calcium (Ca) 397.6 ± 58.7 301.1 ± 110.5 Titanium (Ti) 7.1 ± 5.5 9.1 ± 3.1 Manganese (Mn) 5.6 ± 1.9 8.3 ± 2.8 Nickel (Ni) 56.1 ± 16.4 49.1 ± 17.2 Copper (Cu) 35.1 ± 15.5 50.3 ± 16.6 Elements Unexposed group (ng/cm2) Exposed group (ng/cm2) Aluminium (Al) 2.7 ± 5.4 44.1 ± 44.5** Silicon (Si) 21.8 ± 24.4 48.6 ± 40.7 Phosphorus (P) 20.1 ± 12.9 544.6 ± 305.1*** Chlorine (Cl) 151.7 ± 194.5 232 ± 112.6 Potassium (K) 224.7 ± 197.5 271.0 ± 84.0 Calcium (Ca) 397.6 ± 58.7 301.1 ± 110.5 Titanium (Ti) 7.1 ± 5.5 9.1 ± 3.1 Manganese (Mn) 5.6 ± 1.9 8.3 ± 2.8 Nickel (Ni) 56.1 ± 16.4 49.1 ± 17.2 Copper (Cu) 35.1 ± 15.5 50.3 ± 16.6 **Significant at P < 0.01 and *** Significant at P < 0.001 in relation to unexposed group (Student’s t-test). View Large Discussion This study showed through interviews and questionnaires a combination use of herbicides, fungicides and insecticides. Glyphosate-based formulations were the herbicides most used by soybean farmers in this study. The consumption of fungicides and insecticides has increased, especially propriconazole, epoxiconazole, carbendazim, azoxystrobin, which are used for example to control Asian Soybean Rust, a disease caused by fungus, and acephate to control infestation by Helicoverpaarmigera caterpillars. Supplementary Table 1, available at Mutagenesis Online, shows the pesticides used in soybean crops considered by both ANVISA (Brazilian Drug Administration) and WHO as moderately and highly toxic to humans. According to IARC, most pesticides used in soybean crops have not been evaluated and are not listed (86%), 7% are not classified as carcinogenic, 5% are considered possibly carcinogenic, and only 3% as probably carcinogenic to humans. However, pesticides formulations are complex mixtures; they can be produced from active ingredients, plus inert substances and impurities and in general are used in combinations. These chemical compounds can favour interaction and combination, triggering synergistic and additive effects that are potentially adverse to the health of populations exposed to them (1,35,36). Further, regarding Supplementary Table 1, available at Mutagenesis Online, it can be observed that 18% of the pesticides used on soybeans (tested alone) can cause DNA strand breaks and CAs, 12% induce the formation of micronuclei, 8% form DNA adducts and 5% cause SCE. Although the risks to human health due to multiple exposures are known, the combined use of pesticides still generates uncertainties (17). Therefore, studies to evaluate exposure to multiple genotoxic agents present in the composition of pesticides should be considered in relation to human health (11,17). Considering a prospection of a network of interactions between pesticides used in soybeans (listed in Supplementary Table 1, available at Mutagenesis Online) and human proteins, it was possible to observe interference of the mixture of pesticides in different cell regulation processes, such as signalling, cell communication, cell differentiation, mitotic cycles and apoptosis, organisation of mitochondria and chromatin, among others (data not shown). Alterations of these cell regulation mechanisms may promote the development of chronic diseases among the soybean farmers. The liver, brain, lung and many other tissues are known to be responsible for the bioactivation and biodegradation of pesticides, and for this reason, the toxic effects exerted through these substances vary greatly. Therefore, the purpose of this study was to find nonspecific and specific biomarkers used in the clinical routine that could evaluate the effects of exposure to pesticides, including the evaluation of the activity of serum cholinesterase, foreseen in labour laws to biomonitor occupational exposure. Although cases established by acute intoxication support clear clinical and laboratory evidence, this study showed results on BChE, GGT, SPOT, SGOT, total proteins and haematological parameters do not provide evidence of intoxication among the soybean farmers. Similar results were also produced by other authors, where repeated exposures over the long-term reproduce conflicting results (11–14,22,37–47). Cumulative effects through excessive exposures are related to the chronic toxicity mechanisms, and may suggest the induction of a compensatory and gradual synthesis generated over the course of many exposures (1,22,42). Therefore, it is necessary to review the use of AChE and/or BChE activity levels. In our study, it was observed that the pesticides to which the soybean farmers are exposed could be associated with the induction of DNA damage, which was observed in peripheral blood and buccal cells using the comet assay and MN test. In order to understand the action mechanism of the pesticides used in soybean farming we used the enzyme-modified comet assay (hOGG1). Based on this assay it was observed that the complete mixture of pesticides used during soybean cultivation was able to induce oxidation of purine nucleobases, including 8-oxoguanine (8-oxoGua) (Figure 1). 8-oxoGua can be formed in DNA by two main mechanisms: (i) oxidation of a guanine base in DNA; and/or (ii) incorporation of an oxidised dGTP (8-oxo-dGTP) during DNA synthesis (43). The enzyme-modified comet assay makes the comet assay more sensitive, specific and confirmatory regarding the oxidative damage mechanisms (44). Exposure to pesticides may induce oxidative stress, increasing lipid peroxidation and reducing the antioxidant defenses (22). This oxidative damage triggers a number of molecular responses that activate the repair path by base excision (BER), such as oxidised bases. This repair mechanism generates apurinic and/or apyrimidic (AP) sites that serve as an action substrate for DNA glycosylases responsible for the removal of purine or pyrimidine bases or both. One of the biomarkers of oxidative damage in DNA is 8-oxoGua, which is one of the main oxidised bases (26,27,45). It can accumulate in nuclear and mitochondrial DNA and this may be associated with changes in the gene expression triggered through mutagenic processes involved in early aging and several diseases, including tumourigenesis (43,46). It is known that oxidised bases and AP sites alter the DNA structure and begin a complex mechanism of cell and molecular reactions that can induce mutagenic processes, cell death, cell cycle alterations, DNA remodelling and DNA repair (47). Some of these effects were verified by the BMNCyt assay, through the significant increase of micronuclei, nuclear buds and binucleated cells, as well as cell death, which are related to genetic instability. The presence of the micronuclei means a loss of chromatin as a consequence of structure chromosomal damage or disorder in the mitotic apparatus (24,48–50). On the other hand the nuclear buds are possibly formed by gene amplification; and the binucleated cells are related to a cytokinetic defect (which may be related to aneuploidy) (24,49,51). A significant positive correlation was demonstrated between nuclear buds and age for unexposed individuals. Other authors, comparing young and older controls (49,50), did not demonstrate this relationship between nuclear buds and aging in human buccal cells. Despite this, Ivanov et al. (52) observed that cellular senescence involves extensive cellular remodelling, including chromatin structure loss of histones in senescent human cells and more relaxed chromatin structure. The increase frequency of nuclear buds related with age (control group) in our results could suggest chromatin loops formation in the peripheral nucleus region, once chromatin has to be relaxed for efficient lesion detection and to make DNA lesions accessible for repair. It was also observed that the epithelial cell death process was increased through nuclear abnormalities recognised by cells: karyorrhetic (nuclear fragmentation), pyknotic (extreme condensation of the chromatin, which may reduce the nucleus substantially) and karyolytic (nuclear material completely lost or also known as ‘ghost cells’). The latter may be associated with cell death by necrosis (24,49,50). Cell death by apoptosis is a genetically controlled process that is essential to normal cell growth, development, immunoregulation and homeostasis. The increase of apoptotic and necrotic cells also provides guidance about the degree of genotoxicity, since they are related to the defense mechanisms to eliminate genetically damaged cells and ensure that the genetic information is complete. Different studies have in some way shown results similar to ours, in relation to DNA damage induced in populations exposed to the complex mixtures of pesticides (10,12–17,37). In addition, Bonassi et al. (49) observed a relationship between exposure to pesticides and increased values of micronuclei, nuclear buds, binucleated cells and karyorrhectic cells, using a database of 5424 subjects with buccal MN values obtained from 30 laboratories worldwide. Bolognesi and Holland (17) and Pastor et al. (53) highlight the way that pesticides are applied as a major factor in increasing genetic damage associated with the practice of spraying and dispersing pesticides during occupational exposure. Despite this, the results presented in this study did not show any influence of using PPE and the form of spraying on the genotoxic damage. Accuracy in workers’ answers or the fact that workers do not use all equipment should be taken into consideration, as well as both forms of spraying (only tractor or tractor plus hand pump). DNA damage and the relationship with oxidative damage observed in this study may be related to the inorganic elements present in pesticides. Among the inorganic elements detected by PIXE, significantly higher concentrations of Al and P were observed in the urine of the soybean farmers. These elements are generally present in the chemical composition of different pesticides and fertilizers to which the farmers are exposed. The increase of Al in biological systems is related to the formation of free radicals and oxidative stress that interfere in various biochemical processes, especially of the cholinesterases, and is involved in the onset of Parkinson’s and Alzheimer diseases (54,55). Moreover, Benedetti et al. (12) and Da Silva et al. (13) associated the increase of Al with genetic damage. Increased P can be associated to the intense use of organophosphorus compounds. Similarly to this result, in a previous study P was found increased in oral mucosa cells among the soy farmers exposed to pesticides (12). In addition to the genotoxicity mechanisms of the inorganic elements associated with the presence of reactive oxygen species, associations with inhibition of the repair systems, genome instability and accumulation of mutations are reported in the literature (56,57). In fact, the results of the enzyme-modified comet assay suggest an oxidation of guanine in DNA generated by pesticide exposure. In addition to genetic damage observed in farmers from this study, epigenetic alteration was observed. DNA methylation is the most studied epigenetic tool since it allows verifying cellular alterations caused by modifications in the gene expression without involving mutations (58). Besides, methylation regulates important cellular processes such as transcription, mismatch repair and maintenance of genomic stability during the cell cycle (20,59). Studies have shown that some pesticides may be associated with the silencing of important genes in the cell cycle through hypermethylation (60). Our results show increased methylation in the DNA of the individuals exposed to the pesticides, besides a positive correlation between methylation and MN formation. Probably hypermethylation is involved with MN formation due to inactivation of DNA repair genes or to difficulty of accessing DNA damage in chromatin (61–63). DNA methylation in DNA repair genes participates in the DNA damage regulation. Gene silencing and depletion of important proteins involved in maintaining genetic stability during replication and cell cycle, especially during chromosome segregation, spindle elongation and cytokinesis can induce DNA damage events (61–63). Taspinar et al. (64) suggested that methylation status under Al exposure might be a part of the defense mechanism in stress. In addition, Alvarado-Cruz et al. (65) demonstrated that increased methylation is associated with oxidative damage in children from an industrial environment (exposed to metals and polycyclic aromatic hydrocarbons). Although the use of pesticides is a great advance for soy crops, considered one of the main Brazilian commodities, it should be mentioned that the indiscriminate use of pesticides can harm human health by DNA damage mechanisms (7–8,10–11,17,66–74). It is important to emphasise that in order to reduce the risks associated with the development of diseases among the occupationally exposed individuals to pesticides it is necessary to carry out epidemiological investigations investigating genotoxic, mutagenic and epigenetic effects in order to guide education programmes and safety policies. Supplementary data Supplementary data are available at Mutagenesis Online. Funding This work was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo a Pesquisa no Estado do Rio Grande do Sul (FAPERGS), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), and Lutheran University of Brazil (ULBRA). Conflict of interest statement: None declared. 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Published: Jan 1, 2018
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