Impact of pollution on the marine environment Bio monitoring and Biomarkers : Advantages and limits

Transcription

1 Impact of pollution on the marine environment Bio monitoring and Biomarkers : Advantages and limits Pr Hamza-Chaffai Amel Toxicologie Marine et Environnemental, UR 09-03, IPEIS, Bp SFAX-Tunisia <amel.chaffai@tunet.tn>

2 SFAX University Created in Members (2Pr, 4 Ass Pr, 8PhD students, 2 masters, 1admin) National (local) network (6 labs) International network (8 labs)

3 PROJETS & FINANCIAL SUPPORT Ministry of Higher Education International Foundation of science (Sweden) UNEP/MEDPOL 4 Prg AUF 5 Prg Tuniso-français 1 Prg Tuniso-portugais Japon Groupe Chimique de Tunisie Taparura

4 Local Network (Sfax University) CBS (Bio Mol) Labo Médecine Nucléaire ( P/T/E) LARSEN ENIS (Métaux) INSTM Sfax (lépido/réseau) CHU (métaux et cancer) F.M.Sfax (Histologie)

5 Réseau International Turquie Universitéd Izmir Japon Université d Akita Université de Soukouba Université de Toyama France Université de Caen Université du Havre Université du Maine Espagne CSIC Maroc Université de Rabat Portugal Universitéd Algarve

6 Preserving the marine environment quality is a priority To provide an optimal use of marine resources To preserve marine organisms To protect human health What are the possibilities?? to distinguish between a polluted and a clean site?? That should be preserved or in which some aquaculture activities could be developed

7 What are the possibilities for bio monitoring marine pollution? Sea water fluctuations Low concentrations => analytical difficulties Sediments Long term integrator for contamination Concentrations are higher than those of sea water Heterogeneity (granule size, organic matter) Pollutants are not available owing to their ρχ form Living Organisms BIOMONITORS Reflect the bio available fraction of contaminant Ecological and human health interest

8 Good Candidates for monitoring = Bivalves BIOMONITORS OR BIOINDICATOR ORGANISMS International monitoring programs RNO (France) Use Mussels and Oysters Mussel watch (USA) In Tunisia These species are available only in the northern coast Use of other bivalve species

9 Modèles Biologiques Cerastoderma glaucum Ruditapes decussatus Posidonia oceanica

10 Approaches used 1. Laboratory experiments Studying the effect of contamination on the organism s response, Allow the control of many parameters, We can not simulate the field conditions 2. Field (in situ) sampling Reflect the contamination state of one site, Possibilities to carry analysis during time (months, years) Difficulties to control natural factors 3. Field Transplantation This approach goes between 1 and 2 Possibilities to control population 4. Lab Transplantation This approach goes between 1 and3 Possibilities to control population and conditions Limited in size and volumes

11 How to choose a Bio monitor Some important criteria h The capacity of accumulating pollutant, htheir sedentary habit which could reflect the pollution state of one site h Availability in the studied sites, h A reasonable size allowing dissection and analysis, h possibility to undertake laboratory experiments.

12 Detect pollution at different Biological levels POPULATION Damage Years ORGANISM Months ORGAN Hours Minutes CELL Seconds Early warning system!!!! MOLECULE

13 Biomarker : definition Definition A biomarker is a xenobiotically induced variation in cellular or biochemical component or processes, structures, or functions that is measurable in a biological system or sample (US academy of Science (in Connel at al., 1999) They constitute early warning systems able to detect the effect of pollution even at low concentrations.

14 Criteria for biomarker choice Simplicity, sensitivity and reproducibility of the technique, We should know basal levels of the biomarker, We should study biotic and abiotic variations, We should evidence the relationship dose/ effect between the pollutant and the biomarker, The ratio signal to noise should be high (Cairns, 1992).

15 BIOMARKERS : Metallothioneins h Cytosolic proteins h Low MW (6-7 KDa) h high cystein content (20-35%) hheat stability haffinity for metals hproposed as biomarker β α Spatial representation of Metallothionein (Kägi, 1993)

16 Synapses Acetylcholinesterase * Enzyme necessary for the correct nervous transmission * A main target for insecticide organophosphorous and carbamates, inhibition by metals *Acetylcholinesterase inhibited by pollutants accumulation of acetylcholine excitation/tetany/death Représentation spatiale d une AChE (d après Mora, 1998)

17 OTHER BIOMARKERS MDA lipid peroxidation Glycogen energy reserves Stress on Stress general health status Endocrine disruption reproduction

18 Le test «YES» Composé œstrogénique Récepteur aux estrogènes 3 2 Promoteur PGK ERE Lac-Z 4 Récepteur activé β-galactosidase 5 CPRG jaune cytoplasme 1 CPRG rouge milieu her noyau Structure du génome de la levure modifiée. Le gène du récepteur aux oestrogènes est intégré dans le génome et s exprime (1) sous une forme capable de se lier à l élément de réponse aux oestrogènes au niveau du plasmide (2). L activation du récepteur par fixation d un ligand (3) entraîne l expression du gène Lac-Z (4) qui produit la β-galactosidase. L enzyme sécrétée dans le milieu (5) métabolise le CPRG en un produit rouge (6), dont l absorbance est mesurée. D après Routledge & Sumpter (1996).

19 How to validate a biomarker? Response (Figure -A) Stress Time Response (Figure -B) Stress Temps iif the ration signal/noise is high=> the response linked to the pollution is higer than the response due to natural and biotic factors (Figure -A). Good biomarker i If the ration signal/noise is low=>it is difficult to distinguish between the response provoked by pollution and the response due to natural and biotic factors (Figure -B). bad biomarker

20 Some Results

21 Mediterranean Sea OUR CONTRIBUTION TUNISIA Effluent The gulf of Gabès region Shallow waters, tides 8 SFAX Borj Ungha 2-Kerkenah 3-Zarb El Ain 4-El Hofra 5-Chott Nakhla 6-Mahras 7-Ras Yungha 8-Skhira 9-El Akarit 10-S mansour 2 N Weak currents 9 High salinity and T S Spawning and refuge area Important resources

22 Box-Cox transformation The relationship between MTLP levels and the studied factors (Cd, Cu, Zn, size and sex) can be expressed in some cases by a linear model (I) MTLP = β + α 1 Cd + α 2 Cu + α 3 Zn + α 4 Sex + α 5 Size (I) X λ 1 Y (λ) i=n λ) = α + Σβ ι Xi ( λ ) (II) With X( λ), = α = 0, when we take the standardised coefficients In our case, model (II) can be written λ i=1 MTLP ( λ ) = α + β 1 Cd ( λ ) + β 2 Cu ( λ ) + β 3 Zn ( λ ) + β 4 Sex ( λ ) + β 5 Size ( λ ) Sacaht que α, β 1, β 2, β 3, β 4 and β 5 (β i ) sont les paramètres de la regression, λ est un scalair définissant la transformation. For λ=1, the linear form for λ > 0, it becomes linear in the logarithms We estimated α, β i, the standard error of estimate σ and λ in two stages. In a first stage, we obtained the least squares estimates of α, β i and σ for fixed value of λ. In a second stage we searched for the value of λ, say λ 0, which maximises the log Likelihood function, say L max (λ), and thus produces the optimal transformation

23 Correlations metals/metallothionein: non linear multiple model λ λ λ λ MTs = 0,64 Cd - 1,18 Cu + 0,23 Zn λ = -0,73 (t=4.36) (t=-1,52) (t= -2,10) MTs Area A Cd Area B Zn M T Area C 8 4 Area D C u C d

24 In situ Transplantation Experiment Unités arbitraires Unités arbitraires 0,5 0,4 0,3 MTs Cd Cu Zn 0,4 0,3 0,2 0,2 0,1 0,1 T=0 T=62 T=132 T=0 T=62 T=132 DAYS 0,0 Site de Gargour Site de Sidi Mansour Evolution des MTs et des métaux (unités arbitraires) au cours de la transplantation.

25 Identification des composés par HPLC 2,5 oestradiol Estrogenicity (ng) 2 1,5 estrone 1 0, Time (minutes)

26 Endocrine disruption Some Measurable effects?

27 Simultaneous hermaphrodism (Smaoui-Damak et al, 2007)

28 Simultaneous hermaphrodism (Smaoui-Damak et al, 2007) Sz 40 µm 100 µm

29 Accidental hermaphrodism (Smaoui-Damak et al, 2007)

30 Sites concerned by hermaphroditism Site /STEP % Hermaph Month STWT 2 ZE/ 8 km sud 10 June 2004 STWT 1 R decussatus BU/40km Sud 6.66 May 2002 June 2002 EH/ 6.66 Bayadha 14 km Ker/20km au large Decembre 2001 June Juin Août 2004 C glaucum RU 40 km 5 Août 2004

31 Observed effects In situ studies The cockle Cerastoderma glaucum Characteristics havailable along the Tunisian coasts hbio monitor Organism hlive in the superficial sediment

32 Sex ratios (Cockle) STEP pollution mx male female (N) R Ungha 68,3 260 Bayadha 63, percentage (%)

33 Cerastoderma glaucum 63,43 males 36,55 females

34 Cerastoderma glaucum (Ajimi, 2008) More males 65% than females 35% Mâles Femelles Herm Pourcentage (%) ju1 JUL Aout SEP OCT NV DEC JV FV MRS AV Mai Ju2 Sex-ratio chez les coques mâles et femelles de juin 2004 (ju1) jusqu au juin 2005 (Ju2). Herm: specimens hermaphrodites.

35 Des cas d hermaphrodisme d observés s Chez Cerastoderma glaucum

36 Les parasites chez C. glaucum

37 Exemple de parasites colonisant la gonade de Cerastoderma glaucum Tubule gonadique Parasite

38 Conclusions The gulf of Gabès area is exposed to both Toxic metals and xeno estrogenic compounds Correlation between pollutants and biomarkers was evidenced HPLC, evidenced two main ED: oestradiol et estrone. These ED are accumulated by bivalves gonads constitute the target organ Some effects are observed (sex ratio values, histological effects, hermaphrodites, parasites.. The Ecotoxicological significance is still uncertain. Further investigations are needed. In spite of differences, the ED effects are conserved We will focus on some important aspects : Combined effect of in vivo contamination by ED and in situ transplantation of bivalves will clarify the effects on the reproductive cycle. Vtg gene expression,

39 Thank you

40

41 Niveau de contamination par le Cd R decussatus Sites Cd in toto ug/g PS BU/40km Sud 0.6 Accidentel Et simultané EH/ 3.5 Accidentel Et simultané ZE/ 8 km sud 2.4 Accidentel et simultané STEP STEP 2 C glaucum Ker/20km au large RU 40 km 0.75 accidentel? accidentel

42 Sex ratios de quelques espèces présentes en estuaire de Seine Number of fish observed Flounder 39,6 663 Gobby 34,2 73 Eel 0 27 male female Roach 35, percentage (% )

43 Effluents STEP et les sites de prélèvement : Etude in situ STEP 2 STEP 120 effluent Activité (ngee2/l) Entrée STEP Sortie STEP sédiment dvstep effluent ,8 3,69

44 Les sites concernés s par cas d hermaphrodismed Site /STEP % Hermaph Mois STEP 2 ZE/ 8 km sud 10 Juin 2004 STEP R decussatus BU/40km Sud 6.66 Mai 2002 Juin 2002 EH/ 6.66 Bayadha 14 km Ker/20km au large Décembre 2001 Juin Juin Août 2004 C glaucum RU 40 km 5 Août 2004

45 Indice de gamètogénèse (Dammak, 2005) IG differnces in females IG differnces in males 7 6 IM EH fem EH F IM BU fem BU F IM BU male IM EH male 0 J1 J A S O D J F M A M J2 Mois J1 J A S O D J F M A M J2

46 IM (Ketata, 2008)

47 Remerciements à toute l él équipe

48 Bivalves étudiés APPROCHES Etudes in situ Etudes in vivo Transplantation in situ Transplantation in vivo Hg Chaînes trophiques HISTOLOGIE Qualitative quantitative POLLUANTS Cd, Cu, Zn, Pb, Hg xéno estrogènes BIOMARQUEURS MTs/AChE/MDA/ Glyco/Stress on stress PERTURBATEURS YES P/T/E ETUDE MOLECULAIRE Différentiation génétique C glaucum/c edule Clonage du cdna MTs Quantification de l exp du gène

49 THEMES DE RECHERCHE DE L UNITE Validation in situ et in vivo de la bio accumulation des métaux par la palourde et la coque Identifier via ces organismes les sites le plus pollués et les sites «témoins Evaluer dans le site «témoin» l effet des facteurs biotiques? Etudier les variations des biomarqueurs en fonction du cycle reproducteur Valider in situ les biomarqueurs et évaluer leurs niveaux de base? Le cadmium affecte-t-il le cycle reproducteur chez les palourdes? Effet In situ des polluants sur les taux d hormones (T, E, P) chez la palourde Structure expression du gène métallothioneine chez les espèces étudiées. Transfert du mercure le long des chaîne trophiques et incidences sur la santé de l homme Etude du potentiel oestrogénique des effluents de la station d épuration de Sfax. Effet de l exposition aux métaux toxiques sur des neuropathologies fréquentes dans la ville de Sfax L exposition professionnelle aux métaux et le cancer

50 Savoir faire du labo Contamination in vivo Transplantation in situ Transplantation in vivo Analyse des métaux Cd, Pb, Hg, Ag Analyse histologique->histologie quantitative Dosage d hormones T / E / P Métallothioneines AChE Réserves énergétiques (Glycogène, Lipides, protéines) MDA Stress on Stress test Histologie quantitative

51 Niveau de contamination par le Cd R decussatus Sites Cd in toto ug/g PS BU/40km Sud 0.6 Accidentel Et simultané EH/ 3.5 Accidentel Et simultané ZE/ 8 km sud 2.4 Accidentel et simultané STEP STEP 2 C glaucum Ker/20km au large RU 40 km 0.75 accidentel? accidentel

52 Questions??? What are the main polluted and clean sites? In clean sites what is the effect of biotic factors? What are the useful biomarkers and their basal levels? Did cadmium affect the reproductive cycle of the Clam? Is there any endocrine disruption linked to pollution by metals and synthetic hormones? What is the structure and gene expression of metallothionein of the studies species? (fundamental approach)

53 Some Results About Field Studies

54 Tunisia Mediterranean Sea Sfax The gulf of Gabès region Shallow waters, tides Weak currents High salinity and temperatures Spawning and refuge area Important resources Industrial effluents

55 4 3 Hot Spot! 2 ( Cd 1 0 S.M El.H G.S G.B R.Y Sk Kr Sites South 1 1,5 (Mt) mg/g (Br) 0,9 0,8 0,7 Mt mg/g (GD) 1,3 1,1 0,9 0,7 0,6 0,5 SITES 0,5 S.Mansour EL.Hofra G.Soui R.You Skhira Kerkanah SITES S.Mansour EL.Hofra G.Soui R young Skhira Kerkan South

56 Variations des MTs en fonction du mois et du sexe MTs (mg/g) ** n.s * * Juin Juillet Août Septembre Mâles Femelles Juin Juillet Août Septembre MTs * ** n.s ** Cd n.s n.s n.s n.s Cu n.s n.s n.s n.s Zn n.s n.s n.s n.s *significatif à 90% ** significatif à 95% n.s non significatif

57 Multiple model MTs = f(cd, Cu, Zn, taille, sexe) Linear model (OLS) Non linear model (Box-Cox) R2= 0.53 R2= 0.65 Variables Coefficients Coefficients Lambda (αi) (βi) (λ) Cd (n.s) 0.22 (1.75)** Cu (n.s) (n.s) Zn 0.50 (2.72)*** 0.39 (2.82)*** Size 0.23 (2.84)*** 0.13 (3.20)*** Sex (n.s) (-1.70)** (***) significant at 99% (**) significant at 95%. ( ) t ratios 54 df, (OLS) : ordinary least squares Functional relationship between MTs and the studied variables using both linear and non linear models, MTs=f(Cd, Cu, Zn, Sex, Size).

58 What are the main affected and clean sites? ( Cd 1 0 S.M El.H G.S G.B R.Y Sk Kr Sites South (Cd) µg/g 3,5 3 (Mt) mg/g GD 1,4 1,2 2, ,5 1 0,8 0,6 0,4 Mt mg/g GD MTs mg/g Cd µg/g 0,5 0,2 0 S M EL H G S RY Sk Kr SITES 0

59 Simple Correlationsmetals/metallothionein Correlation MT- Cd Soluble Correlation MT- Zn Soluble 4 Quantity of MT (mg) Quantity of Cd (ng) Quantity of MT (mg) Quantity of Zn (ng) Correlation MT- Cu Soluble Correlation Metals - MT 4 4 Quantity of MT (mg) Quantity of Cu (ng) Quantity of MT (mg) Metals (Cd+Cu+Zn natomgram)

60 What is the effect of biotic factors? Modèle multiple MTs = f(cd, Cu, Zn, taille, sexe) V a r ia b le s C d C u C o e ffic ie n ts (β i) (1.7 5 )* * (n.s ) L a m b d a ( λ ) Z n S iz e (2.8 2 )* * * (3.2 0 )* * * S e x ( )* * (* * * ) s ig n if ic a n t a t 9 9 % (* * ) s ig n if ic a n t a t 9 5 %. ( ) t ra tio s 5 4 d f, (O L S ) : o rd in a ry le a s t s q u a re s F u n c tio n a l re la tio n s h ip b e tw e e n M T s a n d th e s tu d ie d v a ria b le s u s in g b o th lin e a r a n d n o n lin e a r m o d e ls, M T s = f(c d, C u, Z n, S e x, S iz e ). E ffe t s u r le s M T s Z n > C d > ta ille, s e x e

61 What is the effect of biotic and abiotic factors? MDA = 641, ,48 Temps - 34,47 Site - 11,57 Taille (t=2,28) (t=-1,7) (t= -2,74) Glycogène = 10,4 + 6,63 Temps - 3,95 Site - 1,45 Zn (t=5,66) (t=-3,11) (t= -2,3)

62 Differences between sites El Hofra 5 ( µg/gPS) 4 3 EH/BU= Cd Cd "in toto" BU EH J1 J A S O D J F M A M J Bordj d'ungha ( µg/gPS) Cd J1 J A S O D J F M A M J Cd J1 J A S O D J F M A M J2

63 Differences between organs : Bu GD/Br 4; Eh GD/Br 3.16 Branchies 1.2 * BU EH Cd (µg/g PF) * * * * * * * * 0.2 Cd (µg/g PF) 0 J1 J A S O D J F M A M J2 Glande digestive * * * * BU EH J1 J A S O D J F M A M J2 * * * * * *

64 Some Results About Lab Studies

65 In vivo Contamination of Ruditapes decussatus Cu (75 µg/l) Lindane (34 µg/l) Cu+Lindane Control 1,15 µm 0,12 µm Studied Biomarkers Metallothionein Acétylcholinestérase "Stress on stress" ( digestive gland) (Gills and mantle) 30 clams from each contamination anoxy at 15 C, LT50

66 Results about AChE Control Cuivre Lindane Cu + Lindane Manteaux Branchies AChE 0- activity (U/mg de protéines) in the studied organs ( ) Différence significative (p<0,005). Results of MTs No significant difference was observed for MT levels

67 What is the structure and gene expression of metallothionein of the studies species? (fundamental approach) In vivo contamination experiment Cerastoderma glaucum were collected from Mahras (site located at 40 Km in the south of Sfax) 20 days of contamination. Controls 50 µg/l (CdCl 2 ) 75 µg/l (CdCl 2 ) 100 µg/l (CdCl 2 ) 150 µg/l (CdCl 2 ) 5days 10 days 15 days 20 days Optimal conditions of MTs induction Purification RNA Extraction, Study of MT gene

68 Variation of MTs concentration with the time and the CdCl 2 concentration [MTs] (mg/g of gills) 1 Gills * C 50 µg/l 75 µg/l 100 µg/l 150 µg/l t (days) Induction MTs DG>Gills Maximum of induction in the digestive gland and Gills 150ug/l, 10 days 50ug/l, 15 days [MTs] (mg/g of DG) DG * C 50 µg/l 75 µg/l 100 µg/l 150 µg/l

69 Health status Results of «Stress on Stress» test % of mortality /time Better health status More resistant days t10 Day µg/l 100µg/l 75µg/l 50 µg/l C % days Day 15 t t(days) 150 µg/l 100 µg/l 75 µg/l 50 µg/l C t (days) Choose 50ug/l (15 days)

70 240 calibrated clams (29-37mm) from Gargour site Gargour (n=120) Sidi Mansour (n =120) 2-Sampling from the 2 sites, n=40) T = 0 T = 62 jours T = 132 jours 3- Analysis MTs MDA Glycogène metals (Cd, Cu et Zn)

71 Unités arbitraires Unités arbitraires 0,5 0,4 0,3 MTs Cd Cu Zn 0,4 0,3 0,2 0,2 0,1 0,1 T=0 T=62 T=132 T=0 T=62 T=132 DAYS 0,0 Site de Gargour Site de Sidi Mansour Evolution des MTs et des métaux (unités arbitraires) au cours de la transplantation.

72 Glycoge n mg/g MTLP mg/g MDA mmol/g Go G1 Sm1 0 MDA = 641, ,48 Time - 34,47 Site - 11,57 Size (t=2,28) (t=-1,7) (t= -2,74) Glycogene = 10,4 + 6,63 Times - 3,95 Site - 1,45 Zn (t=5,66) (t=-3,11) (t= -2,3)

73 Main Results Validation of Ruditapes decussatus and Cerastoderma glaucum as bio monitor useful for monitoring pollution along the Tunisian coast Validation of some specific biomarkers (MTs, AChE) and non specific biomarkers (Stress on stress, glycogen, MDA). The use of multi parametric approach taking into account biotic and abiotic factors Biomarker= fonction (contamination factors, size, time, sex, site) The hisological study showed that Cadmium affects the reproductive cycle of Ruditapes decussatus The endocrine disruption is evidenced in the polluted site. DNA extraction, PCR, Direct sequencing : The ITS 1 sequences of Cerastoderma species showed: Genetic identification of C. glaucum from Tunisia (Yellow and orange foot) Low genetic divergence between C. glaucum (Tunisia) and C. edule (France)

74 PERSPECTIVES Effect of TBT on endocrine disruption and Imposex Genetic identification and taxonomic position of Cerastoderma glaucum. Molecular quantification of MTs transcription in Cerastoderma glaucum and Ruditapes decussatus. Identification of sequences of MTs cdna of Cerastoderma glaucum and Ruditapes decussatus Spatial distribution of contamination (interpolation)

75 The structure of MT domains β domain α domain 9 Cys 11 Cys Cys-X-Cys 3 metallic ions (Cu+, Ag+) less reactive domain Cys-Cys 4 metallic ions (Zn++, Cd++) most reactive domain

76 Studied Bio monitors Characteristics h Good geographic distribution h representation of the site hfilter feeding habit Cerastoderma galucum Ruditapes decussatus h94% of the total production is from the gulf of Gabès. h economic interest (8000workers, exportation) h in situ study h in situ transplantation h laboratory Contamination

77 Bivalves étudiés APPROCHES Etudes in situ Etudes in vivo Transplantation in situ Transplantation in vivo Hg Chaînes trophiques HISTOLOGIE Qualitative quantitative POLLUANTS Cd, Cu, Zn, Pb, Hg xéno estrogènes BIOMARQUEURS MTs/AChE/MDA/ Glyco/Stress on stress PERTURBATEURS YES P/T/E ETUDE MOLECULAIRE Différentiation génétique C glaucum/c edule Clonage du cdna MTs Quantification de l exp du gène