1 / 45

Monitoring of endocrine disruption in different milieu matrices

Monitoring of endocrine disruption in different milieu matrices. W. Dhooge , F.H. Comhaire, A. Mahmoud, F. Eertmans, J.M. Kaufman Endocrinology/Andrology, University Hospital Ghent, Belgium  FlandersBio, Belgium. Introduction. A few facts.

liona
Download Presentation

Monitoring of endocrine disruption in different milieu matrices

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Monitoring of endocrine disruption in different milieu matrices W. Dhooge, F.H. Comhaire, A. Mahmoud, F. Eertmans, J.M. Kaufman Endocrinology/Andrology, University Hospital Ghent, Belgium  FlandersBio, Belgium

  2. Introduction

  3. A few facts • Man made chemicals are found everywhere on the planet • Many of these xeno-biotics may interfere with the endocrine system • Mainly with (anti-)estrogenic action • These include PCBs, pesticides, plastics, heavy metals

  4. “Possible” effects • Cancers • Obesity, diabetes • Genital tract anomalies • Pubertal disturbances • Infertility

  5. The spectrum of Testicular dysgenesis syndrome Skakkebaek et al (2001), Hum Reprod 16: 972–978

  6. Problems of analytical testing • Number of chemicals is growing • It is costly & difficult to test each separately • Frequently, no standard method is available • Analytical tests do not detect mixture effects

  7. Biological tests • Receptor-based assays • Sensitive (signal amplification), detect mixture effects • Receptor activation  Signal (color change etc) • Cells expressing receptor (yeast, liver, ..)

  8. Biological tests • Cell-based assays  possible false negative results (cell toxicity) in heavily polluted environmental samples • Receptor test without a cell !!!

  9. Objectives Develop screening tools: • affordable, • sensitive, rapid • biologically relevant Allow screening: • environmental samples • Humans: exogenous, endogenous substances • Low doses of highly active substances (natural estrogens)

  10. The Yeast assay (YES)

  11. Hsp Hsp Adapted from Routledge et al., 1996 ER ERE Lac-Z Luc b-Galactosidase Nucleus Absorbance read at 540 nm Hsp Hsp Estrogen inducible expression system in yeast

  12. 3 2.5 Estradiol Estradiol Methoxychlor Bisphenol A Dicofol Benzylbutylphthalate Paraquat Lindane Chloropicrin Endosulfan 2.0 Blanc Blanc 2 Absorbance 1.5 1.0 1 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 log(Conc.) (g/L) log(Conc.) (g/L) Yeast assay as developed by Routledge and Sumpter (1996)

  13. Validation of the Yeast assay

  14. 1000 ** 100 * ** 10 * ** * 1 0.1 2 5 7 9 15 Detection limit ethanol / DMSO Ethanol Ethanol Dimethylsulfoxide Dimethyl sulfoxide ** * 17b-estradiol (ng/l) ** * ** ** ** ** ** ** ** * Days of incubation *Significantly different from previous measurement, p<0.005 ** Significantly different from day 2 measurement, p<0.01

  15. Relative potency * * * * * *not tested in lab 1 *not detected in lab 3 Ringtest • The YES was performed according to Routledge and Sumpter (1996). Test plates were incubated for 10 days and absorbances (540 / 620 nm) were measured at regular intervals. 17β-estradiol (E2) was used as a positive control. • Relative Potency (RP) = EC50 (E2) /EC50 (test compound). • Relative Induction Efficiency (RIE) = Amax (test compound) / Amax (E2), with Amax = maximal absorbance. Variability (expressed as coefficient of variation) Intra-lab: 0.52 % - 8.2 % Intra-lab: 1.0 % - 7.3 % Inter-lab: 0.84 % - 7.9 % Inter-lab: 0.6 % - 17 % (except for DDE & lindane) (except for endosulfan)

  16. Receptor test: rationale • Problems with the Yeast assay • Toxicity (also with other tests using living organisms) • Cell wall permeability • Time consuming • Development of a receptor-based test system • Based on competitive binding of compounds to the ER alpha • Receptor production: truncated human estrogen receptor coupled to glutathione sulphotransferase (GST) for purification • Large scale production of the protein

  17. The Estrogen Receptor Based Assay (ERBA)

  18. E2 E E2 ER ER ER Principle of the ERBA competitive binding test Anti-GST GST-ER

  19. 140 120 100 80 Estradiol Coumestrol Genisteine 60 Bisfenol-A Bifenyl % Cortisol 40 % binding 20 0 -20 -12 -10 -8 -6 -4 -2 0 log conc (E2 equiv M) Competition of (xeno-) estrogens with 17b-Estradiol in ERBA

  20. Estradiol curve 140 120 100 80 cpm 60 40 20 IC50 0 -13 -12 -11 -10 -9 -8 -7 log conc (M) 17b-Estradiol curve for ERBA

  21. Relative induction efficiencies (RIE) of tested compounds in the ERBA and YES (n>3 independent experiments) EC50: 50% effect concentration; RIE: relative induction efficiency; GM: Geometric mean, AM. Arethmatic mean

  22. Receptor Test vs YES • Similar results • Negative tests are negative in all systems • Positives are positive including: • Anti-estrogens • Methoxychlor and permethrin (not shown) • Absolute sensitivity (EC50 values) are 3-10x lower than YES • Possible toxic effects in cell systems • Substances with low binding affinity in the YES & ERBA yield similar results

  23. Code Sample ERBA YES MVLN 01J 143 S water 9.32 3.47 3.48 01J 142 S water 0.97 0.46 0.67 01J 140 S water 1.51 13.72 14.99 01J 141 S water 1.57 2.42 1.9 01J 145 S water 6.46 6.21 6.72 01J 144 S water out of range 40.61 34.7 02B015-2 Industry 93.64 0.33 Toxic 02C045 S water 0.93 1.46 1.42 02C169 S water 2.14 0.63 0.19 02C172 S water 10.78 16.21 5.28 02B011-2 Industry 165.20 3.38 Toxic 02C046 S water 1.45 1.76 0.82 02C171 S water 107.70 69.73 28.51 02B011-3 Industry 0.50 <LOD <LOD 02C044 S water 11.56 2.12 3.18 02B015-3 Industry 0.83 <LOD <LOD Environmental Samples in Different Test Systems

  24. Competition of environmental sample with 17b-Estradiol for TER-GST 180.00 ERBA 160.00 YES 140.00 120.00 MVLN 100.00 80.00 60.00 40.00 20.00 0.00 01J 143 01J 142 01J 140 01J 141 01J 145 01J 144 02C045 02C169 02C172 02C046 02C171 02C044 02B015-2 02B011-2 02B011-3 02B015-3

  25. Environmental samples in the ERBA test: conclusions • ERBA-test can be used for pure substances AND environmental samples • Test results are mostly in the same order of magnitude as the YES and MVLN • For some samples discripancies may be due to: • Cell toxicity • Mixture of estrogens & anti-estrogens • Non-specific binding in ERBA: less likely in view of shape of binding curves

  26. Toxicity-guided fractionations

  27. Fractionation procedure protocol Environmental sample filtration Particulate material dissolved phase SPE Extract: 250 µl YES Identification of estrogens in active fractions via LC-MS/MS YES Investigate relationship between concentration of compounds and estrogen activity in different fractions

  28. A B 120 120 9 10 7 100 100 9 16 10 18 8 16 17 80 80 11 15 % estrogen activity relative to max E2 standard curve 13 60 60 7 14 12 40 40 6 17 18 8 27 26 11 25 20 20 5 19 15 4 24 13 28 14 21 23 12 6 6 29 26 27 20 4 5 30 22 0 0 1 1 5 5 10 10 15 15 20 20 25 25 30 30 Fraction number Fraction number Fractionation of environmental samples

  29. Fractionation of environmental samples LC-MS/MS fr4-6: Polar fraction? fr 7&8: Methyl, ethyl & propylparaben fr9&10: Estron, E2, EE2, Propylparaben fr16-19: 4-n-octylphenol, 4-n-nonylphenol, 4-tertiair octylphenol fr 22-29: apolar substances ? 100 A 9 9 10 10 80 60 % estrogen activity relative to max E2 standard curve 40 7 8 4 20 5 1 26 26 27 27 6 29 29 2 28 28 30 30 3 0 1 5 5 10 15 20 25 30 Fraction number

  30. 105 105 104 104 103 103 102 102 101 101 100 100 10-1 10-1 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 1 10 100 Correlation between estrogen activity in fractions & chemical concentration A B pg E2/L in fr 7&8 pg E2/L in fr 17&18 conc octyl phenol (as pg E2/L) conc methyl parabene (ng/L)

  31. 120 100 80 60 40 20 0 1 5 10 15 20 25 30 Fractionation of Environmental samples Relation between estrogen activity in fraction 7&8 & fr 17&18 with substances present in these fractions A 9 10 16 % estrogen activity relative to max E2 standard curve 7 Results YES correlates with methyl parabene & octyl phenol 17 18 8 11 15 13 14 12 6 6 26 27 4 5 Fraction number

  32. Toxicity-guided fractionations • Industrial samples: alkyl phenols up to 54 % of the total estrogenic activity • This is performed on 250µl of the extract • Parabens & alkyl phenols related to surface water estrogenic activity (has never been demonstrated before)

  33. Summary fractionation • The developed methods are sensitive, reproducible & effectively detect the cause of estrogen activity (EA). • The most active fractions: fr9&10: natural & synthetic estrogens. No quantitative relation • Interesting: Significant relation between estrogen activity in fr 7&8 & methyl paraben; & fr 17&18 & octyl phenol • The concentrations measured explain 50% of the EA maximum • Further research: other substances? Matrix effects?

  34. Studies on Human serum

  35. The aromatase study • Placebo-controlled study • Aromatase inhibitor (letrozole) • Testosterone  estradiol • Hormones (classical methods) • Total estrogen load (YES)

  36. The aromatase study

  37. The adolescents’ study • 550 adolescent males • Hormones (classical methods) • Total estrogen load (YES)

  38. The adolescents’ study a: p<0.00001, b: p<0.01

  39. Prediction of mixture effects

  40. Prediction of mixture effects • Data from actual combination experiments were compared to theoretical curves assuming additive combination effects (1+1=2) • Deviation from additivity suggests interaction between compounds (1+1=3, synergism)

  41. 120 2.5 100 2 80 1.5 60 1 40 0.5 20 0 0 Estradiol o,p-DDT Summation Mixture Effect summation • Only applicable with linear dose response relationships Arbitrary units Cell count Observed effect 0.2 mM Expected effect 0.2 mM Effect 0.1 mM 0.01 0.1 1 10 Conc. (mM)

  42. 1 0.9 0.8 0.7 0.6 0.3 pM Background 0.5 0.4 0.3 0.2 72 nM 98 nM 0.1 32 nM 39 nM 72 nM 19 nM 16 nM 52 nM 0 E2 1 2 3 4 5 6 7 8 Mix After Kortenkamp et al., (1999) MCF7 (Br ca) cell growth with a mixture of low level chemicals

  43. 0.9 0.9 1.2 0.8 0.8 bisphenol bisphenol - - A A lindane lindane p,p’ p,p’ - - DDE DDE 0.7 0.7 RA RA 0.9 CA CA + E2 + E2 0.6 0.6 + E2 + E2 0.6 0.5 0.5 RA RA Corrected Absorbance Units Corrected Absorbance Units Corrected Absorbance Units Corrected Absorbance Units Y Axis 2 0.4 0.4 + E2 + E2 RA RA 0.3 0.0 0.0 no E2 no E2 0.0 no E2 no E2 no E2 no E2 10 10 10 10 10 10 10 10 10 10 10 -7 -6 -5 -4 -2 -1 0 1 2 3 4 Molar Concentration Observed response after 3 days of incubation compared to the predicted response For p,p’-DDE/E2 (41,7 pM) & lindane/E2 mixtures observed effect is higher than predicted But for bisphenol A

  44. Special thanks to: • The team of Milieu en Gezondheid (UGent, UIA, VUB, KUL, VITO, ....) • A. Bossier, W. Verstraete, LabMeT • S. Stuyvaert, Nick Hendryckx, labo Andrology UZ Gent • Hormonology lab UZ Gent • T. Benijts/ Prof. W. Lambert: Labo Toxicologie FFW Ugent • A. De Winter M. Van Oost VMM Gent

More Related