universidade federal do paraná thayanne lima barros estresse ...

UNIVERSIDADE FEDERAL DO PARANÁ

THAYANNE LIMA BARROS

ESTRESSE OXIDATIVO NO POLIQUETA LAEONEREIS CULVERI APÓS

CONTAMINAÇÃO E DESCONTAMINAÇÃO ABRUPTAS POR ESGOTO EM

UM ESTUÁRIO SUBTROPICAL

OXIDATIVE STRESS IN THE POLYCHAETE LAEONEREIS CULVERI AFTER

ABRUPT CONTAMINATION AND DECONTAMINATION BY SEWAGE IN A

SUBTROPICAL ESTUARY

CURITIBA

2016

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SUBTROPICAL ESTUARY

CURITIBA

2016

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SUBTROPICAL ESTUARY

Dissertação apresentada ao Curso de

Pós-Graduação em Zoologia, Setor de

Ciências Biológicas da Universidade

Federal do Paraná.

Orientador: Dr. Paulo da Cunha Lana

CURITIBA

2016

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AGRADECIMENTOS

Ao Paulo, pela dedicação, acessibilidade e principalmente pelo entusiasmo

durante esses dois anos.

Aos professores José Monserrat, Helena de Assis e Afonso Bainy, pela

disponibilidade e interesse em compor a banca avaliadora dessa dissertação.

Ao Centro de Estudos do Mar e à Universidade Federal do Paraná (UFPR),

pelo apoio logístico e infraestrutura para realização das atividades.

Ao Programa de Pós-Graduação em Zoologia da Universidade Federal do

Paraná, ao Conselho Nacional de Desenvolvimento Científico e Tecnológico

(CNPq) e à Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

(CAPES), pela concessão da bolsa de mestrado.

Ao professor Dr. Adalto Bianchini e à Dra. Roberta Klein do Instituto de

Ciências Biológicas FURG, pela recepção e atenção durante minha estadia na

FURG e pelo aprendizado das técnicas e procedimentos para determinação

dos biomarcadores utilizados neste trabalho.

À Mariana Holanda e ao Lucas Maltez, pela calorosa acolhida durante o

período das análises em Rio Grande.

Ao professor Dr. César Martins do Laboratório de Geoquímica Orgânica e

Poluição Marinha do CEM/UFPR pelas análises geoquímicas, à Ana Lucia

Lindroth Dauner pela extração das amostras e Ana Caroline Cabral pela

análise cromatográfica.

Ao professor Dr. Marcelo Lamour e à Msc. Pâmela Cattani do Laboratório de

Estudos Morfodinâmicos e Sedimentológicos do CEM/UFPR, pelas análises

granulométricas.

À professora Dra. Helena Cristina da Silva de Assis e à Dra. Izonete Guiloski

do Departamento de Farmacologia da UFPR, pelo armazenamento das

amostras.

Aos motoristas, vigilantes noturnos, marinheiros, telefonista, técnicos e demais

funcionários do Centro de Estudos do Mar por toda ajuda e parceria durante o

desenvolvimento do projeto. Um agradecimento especial ao Agnaldo,

Alexandre, Fumaça, Edinaldo, Pedro, Abraão, Felipe, Josias, Moisés, Ronei e

Sérgio.

Aos professores do Programa de Pós-Graduação em Zoologia e em Sistemas

Costeiros e Oceânicos da UFPR, pelos ensinamentos e contribuições

acadêmicas.

4

Aos integrantes do Laboratório de Bentos pelo companheirismo, “pitacos” e

ajuda durante os experimentos.

Aos voluntários que ajudaram nas inúmeras idas à campo, triagens, testes,

montagem de equipamento, instalação dos experimentos e organização das

coletas: Maria Emília Diez, Luiz Silva, Amanda Alvarez, Olalla Alonso, Adriana

Sardi, Cristiane de Matos, Rodolfo Rocha, Júlia Porto, Ariane Rodrigues, Flávia

de Souza, Christina Lazzarotto, Gustavo de Oliveira, Daniele da Conceição,

Madson de Melo, Ilara, Bruna Marcela, Nálita Scamparle, Bárbara Gimenez,

Mathilde Lemoine, Estela Pires, Orlando Ricetti, Inara Regina, Aline Cason,

Matheus Japur, Jessé Scapini, Bruno Escobar, Fernanda Souza, Eliandro

Gilbert, Bianca Possamai, Hectory Siuch, Kalina Brauko, Leonardo Sandrini,

Angel Gonzalez, Hugo, Ândrea Lemes, Rodrigo Pelanda, Taynara Pinheiro,

Renan Macedo, Julia Castro e Marina Sutili.

À minha família e amigos pelo constante apoio e incentivo. Apesar da distância,

sempre se fazem presentes nos momentos mais importantes.

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ABSTRACT

This study experimentally evaluated in situ responses of the polychaete

Laeonereis culveri to acute or chronic contamination/decontamination by

sewage in a subtropical estuary. We assessed levels of the total antioxidant

capacity (ACAP) and lipoperoxidation (LPO) through an experiment involving

reciprocal transplants between contaminated and uncontaminated intertidal

areas in acute/short term (24 to 96 hours) and chronic/medium term (7 to 14

days) time scales. In the acute assay, LPO levels significantly increased in

animals transplanted from an uncontaminated to a contaminated area.

However, there was no significant decrease in ACAP levels between

transplanted worms and those from origin areas. There was no significant

decrease of LPO levels in animals transplanted from contaminated to

uncontaminated areas, but ACAP levels surprisingly decreased over time. None

of the biochemical variables were affected in the chronic assay. Variations in

biochemical responses were more related to background variability over time

and heterogeneity among areas than to the experimental manipulation itself.

Our results strongly suggest that biochemical responses in L. culveri occur on

the time scale of hours to days after abrupt contamination or decontamination.

Keywords: sewage; oxidative stress; lipoperoxidation; manipulation; recovery

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RESUMO

Avaliamos experimentalmente respostas in situ do poliqueta Laeonereis

culveri à contaminação/descontaminação aguda e crônica por esgoto em um

estuário subtropical. Analisamos os níveis de capacidade antioxidante contra

radicais peroxil (ACAP) e de lipoperoxidação (LPO) com um experimento

envolvendo transplantes recíprocos entre áreas contaminadas e não

contaminadas em agudo/curto (24 à 96 horas) e crônico/médio (7 à 14 dias)

prazo. No experimento agudo, os níveis de LPO aumentaram

significativamente nos animais transplantados da área não contaminada para a

área contaminada. Contudo, não houve uma diminuição significativa nos níveis

de ACAP entre os animais transplantados e os da área de origem. Não houve

decréscimo significativo nos níveis de LPO nos animais transplantados da área

contaminada para a área não contaminada, mas os níveis de ACAP diminuíram

ao longo do tempo. Variações nas respostas bioquímicas no experimento

crônico estavam mais relacionadas à variabilidade de fundo ao longo do tempo

e à heterogeneidade entre áreas do que à manipulação experimental. Nossos

resultados indicam que as respostas bioquímicas em L. culveri ocorrem na

escala de horas a dias após contaminação ou descontaminação abruptas.

Palavras-chave: esgoto; estresse oxidativo; peroxidação lipídica; manipulação; recuperação

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TABLE OF CONTENTS

1. INTRODUCTION ................................................................................................................ 8

2.1. Study area ................................................................................................................. 10

2.2. Experimental design and field procedures ........................................................... 11

2.3. Sampling processing and laboratory procedures ................................................ 13

2.3.1. Tissue homogenization .................................................................................... 13

2.3.2. Antioxidant competence against peroxyl radicals determination .............. 13

2.3.3. LPO determination ............................................................................................ 14

2.3.4. Coprostanol ....................................................................................................... 14

2.3.5. Grain size and organic matter content .......................................................... 14

2.4. Data analysis ............................................................................................................. 15

3. RESULTS .......................................................................................................................... 15

3.1. Water and sediment variables ................................................................................ 15

3.2. Acute Experiment ..................................................................................................... 16

3.2.1. Transplant to the contaminated area (UC to C) ............................................... 18

3.2.2. Transplant to the uncontaminated area (C to UC) .......................................... 18

3.3. Chronic experiment .................................................................................................. 18

3.3.1. Transplant to the contaminated area (UC to C) ............................................... 18

3.3.2. Transplant to the uncontaminated area (C to UC) .......................................... 20

4. DISCUSSION .................................................................................................................... 20

5. CONCLUSIONS................................................................................................................ 23

6. REFERENCES ................................................................................................................. 23

SUPPLEMENTARY MATERIAL ............................................................................................ 30

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1. INTRODUCTION

Coastal zones are vulnerable to pollution from multiple sources, including

domestic and industrial discharges, agricultural runoff, and ship traffic (Islam

and Tanaka, 2004). Sewage discharges, made up by a complex mixture of

organic and inorganic components (Craig, 2012), are chronic sources of

pollution in developing countries, such as Brazil, with precarious sanitation

conditions, and inadequate facilities for the collection, treatment and disposal of

domestic wastewater (Martins et al., 2008). There is a need to assess the

sensitivity of coastal systems to sewage contamination and their recovery

potential from the impact of anthropogenic stresses, as a basis for adequate

management. Despite recovery time scales are expected to be dependent on

the particular community affected and the magnitude of the impacts (Duarte et

al., 2015), estuaries, which have naturally large populations of stress-tolerant

strategists, may recover relatively fast (Elliott and Whitfield, 2011). Ongoing

monitoring of human activities in coastal areas, particularly in developing

countries with basic sanitation problems, is necessary to ensure safer

operations and prevent or reduce damage to marine systems (Bevilacqua et al.,

2006)

Sewage pollution may affect the activity of multiple enzymes and

stimulate reactive oxygen species (ROS) production causing significant

oxidative damage (Livingstone, 2003; Bebianno et al., 2005; Bianchi et al.,

2014), given the capacity to generate reactive oxygen species (ROS), altering

the balance of pro-oxidants and antioxidants at the molecular and cellular level

(Baussant et al., 2009; Manduzio et al., 2005). Oxidative stress biomarkers are

widely used in environmental impact studies since they are considered a key

component of the response of organisms exposed to changing environmental

conditions and can be used to evaluate exposure to and effect of different

contaminants (Cajaraville et al., 2000; Douhri and Sayah, 2009; Gomes et al.,

2013; Lesser, 2006; Lushchak, 2011; Maranho et al., 2015; Martinez-Gomez et

al., 2010; Monserrat et al., 2007; Thain et al., 2008). For instance, exposure to

domestic sewage effluents causes an increase in lipid damage in marine worms

(Vlahogianni et al., 2007). Additionally, low capacity to face oxidative stress is

known for the polychaetes Laeonereis acuta and Perinereis gualpensis from

contaminated coastal areas (Díaz-Jaramillo et al., 2010; Geracitano et al.,

2004).

Classical oxidative stress studies usually measure a limited number of

antioxidants individually, such as SOD, catalase, GPX, and free radical

scavengers (Livingstone, 2003). However, determination of total antioxidant

capacity is essential to evaluate pollution effects and understand how oxidants

interact with the reactive oxygen species generated during oxidative stress

(Amado et al., 2009; Regoli et al., 2002). The analysis of total antioxidant

9

capacity may thus provide an overall assessment of the biological responses

against a particular type of ROS, such as peroxyl radicals (Bocchetti and

Regoli, 2006).

Lipid peroxidation (LPO) is the oxidation of cell membranes by ROS

which leads to the formation of secondary products (Reid and MacFarlane,

2003). The measurement of lipid peroxidation products represents an effect

biomarker besides being considered an index of peroxidation of membrane

phospholipids (Gorbi et al., 2005). Lipid peroxidation leads to loss of

permeability and integrity of cell membranes. Malondialdehyde (MDA) is an

end-product and has been widely used as an indicator of lipid injury caused by

ROS (Almeida et al., 2005).

Benthic organisms are considered reliable indicators of marine pollution

(Burton, 2013; Neto et al., 2010) and evaluation of their responses to

disturbance is essential for impact assessments (Dauvin et al., 2010).

Nevertheless, the use of oxidative stress responses for field monitoring in

estuarine benthic organisms is still scarce in the southern hemisphere (Díaz-

Jaramillo et al., 2013). Among macrofauna, polychaetes are often used in

environmental studies due to their high species and trophic diversity, sedentary

life-style, which ensures chronic exposure to any toxic materials in the

environment, resistance to different contamination levels, and abundance in

benthic communities (Dean, 2008).

Polychaetes belonging to the nereidid genus Laeonereis are among the

numerically dominant organisms in Paranaguá Bay, one of the largest and best

preserved subtropical estuaries in the South Atlantic (Souza et al., 2013).

Laeonereis most probably comprises a complex of cryptic species which occur

or co-occur from Florida to Argentina. Species of Laeonereis are considered

key species in SW Atlantic estuarine coastal environments for fish, shore birds

and carnivore invertebrates. The names Laeonereis culveri (which we favour till

a much needed phylogenetic review based on molecular data) and L. acuta are

largely interchanged both in the taxonomical and ecological literature in the

southwestern Atlantic. Laeonereis, usually under the name Laeonereis acuta, is

well known in terms of its antioxidant responses and oxidative damage induced

by pollutants, both under experimental and field conditions, in the Patos Lagoon

estuary, S Brazil (Geracitano et al. 2002, 2004a,b; Monserrat et al., 2007).

In this study we evaluated oxidative stress and antioxidant responses in

populations of Laeonereis culveri from a sewage-contaminated subtropical

estuary after abrupt recovery or disturbance, by carrying out reciprocal

sediment transplants between contaminated and uncontaminated areas at

acute and chronic time scales. We carried out two in situ assays to assess the

extent and velocity of biochemical responses of L. culveri to abrupt

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decontamination or contamination to sewage, by evaluating lipid peroxidation,

and total antioxidant capacity. We hypothesized that if organisms from

contaminated areas show higher MDA levels and a lower capacity to face

oxidative stress than those from uncontaminated areas, then their transplant to

uncontaminated areas will induce the reduction of MDA levels and the increase

of antioxidant competence against peroxyl radicals (ACAP) levels. Conversely,

animals transplanted from uncontaminated to contaminated areas will display

increased MDA levels and decreased ACAP levels both in short term/acute (24,

48 and 96 hours) and medium term/chronic (7 to 14 days) time scales.

Responses of Laeonereis culveri to sewage disturbance and subsequent

ecological recovery may provide a better tool to assess the putative effect of

these complex mixture of contaminants and to develop management policies.

2. MATERIALS AND METHODS

2.1. Study area

The Paranaguá Bay (25º30’ S, 48º25’ W), located in the coastal plain of

Paraná State, in Southern Brazil, is a semi-closed estuarine system, bordered

by extensive tidal plains and colonized by mangroves and marshes (Fig.1). The

bay has an average depth of 5.4 m, with a surface area of about 250 km² (Lana

et al., 2001). Estuarine hydrodynamics is mainly regulated by tidal currents, and

markedly seasonal fresh-water input (Marone et al., 2005). Macrobenthic

communities of local mangroves are numerically dominated by crabs and

polychaetes (Faraco and Lana, 2003).

Some sectors of the Paranaguá Bay are impacted by urban, industrial,

agricultural and harbour activities (Ribeiro et al., 2013). The lack of a sanitation

system is still a basic health problem. Levels of inorganic nutrients from

Paranagua city sewage exceed threshold limits determined by the Brazilian

environmental legislation (Mizerkowski et al., 2012). Most of the sewage from

Paranaguá city is discharged into Itiberê and Emboguaçú rivers (Kolm et al.,

2002), creating dispersion plumes and sedimentary environments with high

levels of organic matter, faecal coliforms and faecal steroid concentrations in

the vicinity of Paranaguá city (Abreu-Mota et al., 2014; Martins et al., 2010).

We selected two experimental areas in tidal plains at the mouth of Chumbo

river and at Cotinga Island, which are about 3 km apart from each other, and

display different levels of human pressure (Fig. 1). Both were previously

prospected for dense populational patches of Laeonereis. We selected the tidal

plain at the mouth of Chumbo river as an area contaminated by sewage.

Sewage is discharged directly into the estuary about 300 m from the

experimental area, without even primary treatment. Sewage discharge creates

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a sharp and compressed contamination gradient which is limited to areas near

the city of Paranaguá (Barboza et al., 2015; Brauko et al., 2015). In contrast,

the tidal plain of Cotinga Island is uncontaminated by sewage, as indicated by

the concentrations of faecal sterols (see section of results).

Figure 1. Study areas in the tidal plains near the Chumbo River (Contaminated – C) and

Cotinga Island (Uncontaminated – UC). Modified from Gern and Lana (2013).

2.2. Experimental design and field procedures

We carried out two in situ experiments to evaluate the response of

oxidative stress biomarkers of Laeonereis culveri after acute/short term (April

2015) and chronic/medium term (May 2015) exposure to sewage. Both field

experiments were licensed by SISBIO (license no. 36255, of the Brazilian

Ministry of Environment). In each field assay, we transplanted worms between

the contaminated and the uncontaminated area to simulate either abrupt

contamination or decontamination by sewage (transplant treatment). To assess

the effects of experimental artifacts (i.e, to discriminate between the effect of the

new environmental conditions and the effect of experimental handling), as

suggested by Crowe and Underwood (1999), worms were also translocated

within each of the origin areas (translocation treatment). Control treatments to

assess background variation included worms from each area, without any

manipulation.

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Two blocks were established 40 m apart from each other, in each area.

Each block included three experimental sites, 4 m apart from each other,

corresponding to the treatments (transplantation, translocation, and control)

(Fig. 2). Test organisms were transported in sediment blocks within an essay

chamber (Fig. 2), modified from Burton et al. (2005) and originally designed for

in situ assays with Hediste diversicolor, to reduce transportation stress. Each

chamber consisted of 10 cm inner diameter plastic pots with openings in the top

and two rectangular windows. To prevent the escape of the test organism and

allow the proper exchange of interstitial and overlying waters, the openings

were covered with a 40 µm nylon mesh.

We have taken three replicates for each treatment for each site over

three successive sampling times (24, 48, and 96 hours) for the acute

experiment and two successive sampling times (7 and 14 days) in the chronic

experiment. All samples were performed simultaneously in both tidal flats at

same time. Surface sediment samples were collected in each experimental site

to assess grain size, organic matter content and contamination levels using

coprostanol as a geochemical marker.

Figure 2. The schematic arrangement of the sampling sites in the contaminated (C) and

uncontaminated area (UC) and the essay chambers. B1 = block 1, B2 = block 2, Cuc = control

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for the uncontaminated area, Cc = control for the contaminated area, TL = translocate, TP =

transplant.

2.3. Sampling processing and laboratory procedures

Samples were screened through a 0.5 mm mesh. A pool of 6 to 9

polychaetes weighing between 35 and 55 mg were collected from each

replicate, cleaned and kept frozen at −80 °C until biochemical analysis. Only

complete, undamaged individuals were selected.

2.3.1. Tissue homogenization

For the biochemical measurements, organisms were homogenized (1:3

w:v) in buffer solution containing 0.5 M sucrose, 20 mMTris-base, 1 mM EDTA,

1 mMdithiothreitol (DTT) and 0.15 M KCL with pH adjusted to 7.6 and adding

protease inhibitor (0.1 mMphenylmethylsulfonyl fluoride, PMSF) (Geracitano et

al., 2004). Homogenates were centrifuged at 10.000g for 20 min at -4ºC.

Supernatants were collected, stored at -80 ºC and employed later to determine

total protein content, antioxidant capacity against peroxyl radical, and LPO

levels.

Protein concentration was determined using a commercial reagent kit

('ProteínasTotais', Doles Reagentes, Lagoa Santa, MG, Brazil), which is based

on the Biuret method. Absorbance readings (550 nm) were performed in

triplicate using a microplate reader (ELx808IU, BioTek Instruments, Winooski,

VT, USA).

2.3.2. Antioxidant competence against peroxyl radicals determination

Antioxidant competence against peroxyl radicals (ACAP) was measured

according to Amado et al. (2009). Briefly, homogenate supernatant obtained for

ACAP measurements had its protein content adjusted to 1.5 mg/ml. In a white

96-well microplate, we pipetted 10 µL of the supernatant, 127.5 µL of reaction

buffer (30 mM HEPES, 200 mMKCl, and 1 mM MgCl2,) with pH adjusted to 7.2,

and prepared a half of the wells with 7.5 µL ultrapure water and the other half

(with the same samples) 7.5 µL of 4 mM ABAP (2,2′-azobis 2

methylpropionamidinedihydrochloride, a ROS producer). Then, we put the

microplate into a fluorescence microplate reader (Victor 2, Perkin Elmer) and

added 10 µL of H2DCF-DA (2′,7′ dichlorofluorescein diacetate), a fluorescent

probe. The readings were taken every 5 min during 30 min at 37ºC. At this

temperature, thermal decomposition of ABAP produces ROS and the non-

fluorescent compound H2DCF is oxidized by ROS to the fluorescent compound

DCF, allowing to detect competence in neutralizing peroxyl radicals. Therefore,

we can measure the antioxidant capacity with the relative difference between

ROS area with and without ABAP and the data were expressed as 1/relative

area, where a smaller area means a lower antioxidant capacity.

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2.3.3. LPO determination

Lipid peroxidation was measured by thiobarbituric acid reactive

substances (TBARS) determination as described by Oakes & Van Der Kraak

(2003). Samples homogenates obtained for LPO determination had its protein

content adjusted to 3 mg/ml. We added 20 µL of tissue homogenate in test

tubes with the reaction mixture containing 67 mM BHT, 20 % acetic acid, 0,8%

thiobarbituric acid (TBA), ultrapure water and 8,1% sodium dodecyl sulfate

(SDS). Then, tubes were heated in a water bath at 95 °C for 30min. After

cooling, ultrapure water and n-butanol were added with thorough vortexing.

After centrifugation at 825 xg for 10 minutes at 15 °C, 150 µL of the supernatant

were put in a 96-well clear polystyrene plate and its fluorescence measured on

a fluorescence microplate reader (excitation: 515 nm; emission: 553 nm; Victor

2, Perkin Elmer). Under these conditions of high temperature and acidity,

malondialdehyde (MDA), an end product of lipid peroxidation, reacts with

thiobarbituric acid (TBA), allowing its measurement. Concentration of TBARS

was calculated employing a standard curve built with tetramethoxypropane

(TMP) and the results were expressed as nmol MDA/ mg of protein.

2.3.4. Coprostanol

The anthropogenic input of sedimentary organic matter, represented by

sewage contribution, was evaluated by fecal sterol concentrations, such as

coprostanol and epicoprostanol. Coprostanol is produced in the digestive tracts

of humans by microbial reduction of cholesterol (Venkatesan and Mirsadeghi,

1992) and epicoprostanol is formed during wastewater treatment and sewage

sludge digestion (Mudge and Lintern, 1999). These sterols are widely used as

tracers for human waste along coastal areas (Readman et al., 2005). The top 2

cm of surface sediment was collected with a spoon and placed in pre-cleaned

aluminum foil and stored at –20 ºC until determination. The identification and

quantification of sterols occurred by 2 µL of the resulting final extract injection

into a gas chromatograph (Agilent 7890A GC) coupled with a flame ionization

detector (GC-FID).

2.3.5. Grain size and organic matter content

Particle size analysis was conducted using the laser diffraction method

measured by the MICROTRAC Bluewave laser diffraction particle size analyzer.

Sediment parameters were estimated according to Folk and Ward, (1957)

method. The CO3 content and organic matter was calculated as the difference

between the initial and final weights of each sample after chemical attack, using

a solution of hydrochloric acid and hydrogen peroxide (Gross, 1971).

15

2.4. Data analysis

The statistical design demands that experiments involving animal

transplantation from uncontaminated to contaminated areas and from

contaminated to uncontaminated areas be analyzed separately.

Biomarker responses were individually tested using an analysis of

variance (ANOVA). The linear model employed to test the hypothesis consisted

of three factors: Treatments (fixed, four levels: transplantation, translocation,

contaminated control, and uncontaminated control), Time (acute experiment:

fixed, three levels: 24, 48, and 96 hours/ fixed; chronic experiment: two levels: 7

and 14 days), and Blocks (random, two levels: block 1 and block 2).

The homogeneity of variances was assessed by the Cochran’s C test. In

the absence of homogeneity, data were log-transformed prior to analysis of

variance (Underwood, 1997). For significant terms (P < 0.05), a posteriori test

was performed using Student–Newman–Keuls (SNK) test.

All statistical analyses and graphs were done into the R environment (R

Core Team, 2016) combined with GAD (Sandrini-Neto, L. & Camargo, 2014)

and sciplot (Morales, 2015) packages.

3. RESULTS

3.1. Water and sediment variables

Water regime varied from mesohaline to polyhaline (Tables 1 and 2).

Average temperatures were lower during the chronic than than during the acute

experiment. Sediment texture was similar between experimental areas, with

average grain diameter corresponding to fine sand. Organic matter content was

similar at all experimental blocks, varying from 1,69 to 2,2% (Table 3).

Table 1. Values of environmental parameters in experimental areas during the acute

experiment.

24h 48h 96h

Uncontaminated area

Salinity (%) 30 25 20

pH 8 7.9 7.9

Temperature (°C) 26.2 30.4 28.6

Dissolved oxygen (mg/L) 9.2 11.4 9.5

Contaminated area

Salinity (%) 20 15 15

pH 7.7 7.9 7.5

Temperature (°C) 25.2 27 27.7

Dissolved oxygen (mg/L) 6.8 5 6.3

Table 2. Values of environmental parameters in experimental areas during the chronic

experiment. T0 = field deployment.

16

T0 7 days 14 days

Uncontaminated area

Salinity (%) 25

Nd

20

pH 7.8 8.1

Temperature (°C) 22.8 22.9

Dissolved oxygen (mg/L) 5.0 6.9

Contaminated area

Salinity (%) 20 25 25

pH 7.7 7.4 7.7

Temperature (°C) 23 23.3 22.1

Dissolved oxygen (mg/L) 4.0 4.8 4.9

Nd= Not determined

Total sterol concentrations varied between 1.63 and 9.66 µg g-1, with

large variations between the sites of the contaminated area. Coprostanol

concentrations varied between 0.01 and 0.44 µg g–1. The highest concentration

of coprostanol (0.44 µg.g-1) was found at B1 of the contaminated area, which

was about 300 m from the sewage outfall. At the uncontaminated area, the

concentration of coprostanol was comparatively low and and epicoprostanol

was not detected (Table 3).

Table 3. Sediment parameters, sterols concentrations (in µg.g-1) and sterol diagnostic indices

in surface sediments from experimental blocks. nd = not detected.

Contaminated

area Uncontaminated

area

B1 B2 B1 B2

Particle size (µm) 172.70 205.90 225.6 213.4 250 - 125: fine sand

CO3 content 1.73 3.33 1.61 1.92 Organic matter (%) 1.69 1.32 1.84 2.20

Sterols

Coprostanol 0.44 0.09 0.03 0.01

Epicoprostanol 0.09 0.01 Nd Nd

Fecal sterol (cop+epic) 0.53 0.10 0.03 0.01

Total sterol 9.66 1.63 5.42 1.80

Sterol diagnostic indices Threshold levels

% of faecal sterols/total sterols

5.49 6.13 0.55 0.56 >50%: high sewage contamination

epicoprostanol/coprostanol

0.20 0.11 Nd Nd <0.20: untreated sewage input

3.2. Acute Experiment

ACAP levels varied significantly for the interaction among treatments,

times and blocks (interaction Tr x T x B) on both manipulations (UC to C and C

to UC), as demonstrated by the ANOVA test (supplementary material). A

posteriori analysis revealed that significant differences were only observed in

block 1. SNK tests revealed that the means of ACAP levels were higher in

17

control from contaminated than in control from uncontaminated areas.

Variations in MDA levels were significant between Treatment and Time (UC to

C) and between Treatment and Block (C to UC; Fig. 3). Nonetheless, in both

analyses, sampling times constituted a very large source of variation (note the

sizes of mean squares and F values for this term in supplementary material

Table 4).

Fig. 3 Acute experiment. Mean values of lipid peroxidation (MDA) and antioxidant competence

against peroxyl radicals (ACAP) in the polychaeta Laeonereis culveri in response to reciprocal

transplantation between a contaminated and uncontaminated estuaries. UC = uncontaminated

area, C= contaminated area, Cuc = control for the uncontaminated area, Cc = control for the

contaminated area, TLc = translocate in the contaminated area TPc = transplant to the

contaminated area, TLuc = translocate from the uncontaminated, TPuc = transplant to the

uncontaminated area, B1 = block 1, B2 = block 2. For Student–Newman–Keuls (SNK) tests, the

mean values are listed in ascending order. ‘‘>’’ indicates p < 0.05 and ‘‘=’’ indicates p > 0.05. "*"

denotes significant difference by SNK procedure. Lower values of ACAP data indicate lower

antioxidant capacity.

18

3.2.1. Transplant to the contaminated area (UC to C)

Variations in MDA levels were significantly affected by the interaction

between treatment and time (interaction Tr x T; F = 4.88; P < 0.05). The SNK

test and comparisons between the treatments revealed that MDA levels of

control from uncontaminated area were significantly lower than in the others

treatments at T3 (96 hours) (Cuc<TLc=Cc=TPc; Fig. 3).

Significant differences in ACAP levels resulted from the combined effect of

the treatments, time and sites (interaction Tr x T x B; F = 3.1576; P < 0.05).

ACAP levels on translocate treatment were significant higher than in the other

treatments (Cuc=Cc=Tpc<TLc) on time 2, block 1. At the same site on time 3

the ACAP levels were significantly higher in control from the contaminated area

(Cuc=TPc=TLc<Cc; Fig. 3).

3.2.2. Transplant to the uncontaminated area (C to UC)

The experimental manipulation did not cause detectable short-term changes

in the levels of MDA. Variations in MDA levels were significantly affected by the

combined effects of time and blocks (interaction T x B; F = 6.3974; P < 0.01 ).

On block 1, SNK a posteriori comparisons showed that MDA levels were

significantly lower at time 1 with not significant differences between T2 and T3

(T1<T3=T2) whereas on block 2, time 1 has once again the lower mean value

but time 2 shows higher MDA levels than T3 (T1<T3<T2; Fig. 3).

Variations in the mean values of ACAP radical levels resulted from the

combined effect of the treatments, time and sites (interaction Tr x T x B; F =

5.08; P < 0.001). ACAP levels of control from contaminated area were

significantly higher than the other treatments on times 2 and 3 in block 1

(Cuc=TLuc=Tpuc<Cc; TPuc=Cuc=TLuc<Cc; Fig. 3).

3.3. Chronic experiment

The mean values of total antioxidant capacity against peroxyl radical levels

were significantly affected by the combined effects of treatment, time and sites

(interaction Tr x T x B). Variations in MDA levels resulted from the combined

effect of the treatment and the blocks (interaction Tr x B), on both manipulations

(UC to C and C to UC) and sampling times constituted a very large source of

variation (note the sizes of mean squares and F values for this term in

supplementary material Table 5).

3.3.1. Transplant to the contaminated area (UC to C)

MDA levels varied significantly among treatments according to blocks and

time (Tr x B and Tr x T;F = 5.6325 and 12.973; P < 0.01 and P < 0.05,

respectively). SNK a posteriori comparisons showed that the MDA levels of

control from uncontaminated area was significantly higher on block 2

19

Fig. 4. Chronic experiment. Mean values of lipid peroxidation (MDA) and antioxidant

competence against peroxyl radicals (ACAP) in the polychaeta Laeonereis culveri in response

to reciprocal transplantation between a contaminated and uncontaminated estuaries. UC =

uncontaminated area, C= contaminated area, Cuc = control for the uncontaminated area, Cc =

control for the contaminated area, TLc = translocate in the contaminated area TPc = transplant

to the contaminated area, TLuc = translocate from the uncontaminated, TPuc = transplant to the

uncontaminated area, B1 =block 1, B2 = block 2. For Student–Newman–Keuls (SNK) tests, the

mean values are listed in ascending order. ‘‘>’’ indicates p < 0.05 and ‘‘=’’ indicates p > 0.05. "*"

denotes significant difference by SNK procedure. Lower values of ACAP data indicate lower

antioxidant capacity.

(TLc=Cc=TPc<Cuc; Fig. 4). There was no significant difference between

treatments on time 1 (TLc=Cc=TPc=Cuc). The MDA levels were higher in

control from uncontaminated area and transplant to the contaminated area than

in control from contaminated area and translocate of contaminated area

(TLc=Cc<Cuc=TPc) on time 2 (Fig. 4).

20

Variations on ACAP levels resulted from the combined effect of the

treatment, time and sites (interaction Tr x T x B; F = 10.8774; P < 0.001). The

SNK test and comparisons revealed that such variations occurred only in block

1. The mean values of ACAP were significantly lower in control from

contaminated area than in transplant to the contaminated area, and the mean

values of ACAP were significantly higher in control from uncontaminated area

than in translocated of contaminated area and transplant to the contaminated

area (Cc<TPc=TLc<Cuc; Fig. 4).

3.3.2. Transplant to the uncontaminated area (C to UC)

Variations in MDA levels resulted from the combined effects from the

treatment with the block and the time with the block (Tr x B and T x B, F =

4.3593 and 5.8405; P < 0.05, respectively). The SNK test and comparisons

showed that the mean values of MDA levels were significantly higher on time 2

than in time 1 on both blocks (T1<T2;Fig. 4).

Variations on ACAP were significantly affected by the combined effects of

treatment, time and sites (interaction Tr x T x B; F = 10.1675; P < 0.001). There

was no significant difference between the mean values of ACAP levels of

treatments on time 2 on both blocks. On time 1, the mean value of ACAP was

significantly higher in control from uncontaminated area than in the other

treatments on block 1 (Cc=TPuc=TLuc<Cuc) and significantly lower on block 2

(Cuc<Cc =TLuc=TPuc; Fig. 4).

4. DISCUSSION

We refuted the hypothesis that reciprocal experimental transplantation

induces acute or medium-term variation in oxidative stress responses of the

worm Laeonereis culveri. With the exception of a short-term response of MDA

levels after the abrupt exposure to sediment contaminated by domestic sewage

effluents, none of the biochemical responses were significantly affected by

reciprocal sediment transplants between contaminated and uncontaminated

areas

Differences in faecal and total sterol concentrations between blocks

indicate that the experimental blocks were not homogeneous, contrary to what

was expected. The local distribution of faecal sterols typically follows a gradient

pattern caused by the proximity to the sewage outfall (Barboza et al., 2015;

Martins et al., 2014). Barboza et al., (2015) showed a clear contamination

gradient at the kilometer scale at the study area. However, it is also known that

faecal sterol concentrations can dramatically decrease at small spatial scales

(Martins et al., 2002) or not necessarily be higher close to sewage outfalls, due

to dispersion processes (Mudge and Duce, 2005). In this context, our results

show that the 40 m distance between blocks at the contaminated area was

21

enough to considerably decrease sterol levels, probably as a consequence of

quick dispersion and dilution of the sewage-discharge plume. Discrepancy in

sterol distributions and concentrations can also be explained by small-scale

differences in sediment texture (Biache and Philp, 2013) . However, sediment

texture was similar between our experimental blocks. Thus, our results shows

significant variation in contamination conditions even at small spatial scales,

furthermore stressing the relevance of robust spatial replication for

ecotoxicological monitoring programs.

In the acute assay, as expected, the abrupt exposure to sediment

contaminated by domestic sewage effluents induced a short-term increase in

MDA levels. However, there was no significant decrease in ACAP levels

between transplanted worms and those from origin habitats. There was no

significant short-term decrease of MDA levels or increase of ACAP levels in the

transplant from a contaminated to an uncontaminated area. However, ACAP

levels of transplanted organisms decreased over time.

During the acute experiment, ACAP levels showed to significantly vary

only in block 1 for both transplants scenarios. Such a marked heterogeneity in

local contamination conditions may partially explain the unexpected response

patterns in the contaminated area, with significant short-term responses only

detected in block 1 for both transplant scenarios. Based on that, all the following

discussion on variations in ACAP refer only to the block 1.

Higher MDA levels in the control from contaminated area, transplanted

and translocated treatments (Cuc<TLc=Cc=TPc) on time 3 in transplants to the

contaminated area (UC to C) indicates that the antioxidant defense was not

sufficient to prevent oxidative damage at the lipid level. Four days of exposure

to sewage were enough to induce lipid peroxidation in transplanted organisms.

The lower mean values of antioxidant capacity in the transplanted, translocated

and control group from uncontaminated area (Cuc=TPc=TLc<Cc) on time 3,

indicate a potential higher susceptibility to oxidative damage by specific

oxyradicals. The pro-oxidant effect of sewage pollution promoting lipid

peroxidation has been previously reported for several other aquatic species

(Bianchi et al., 2014; López-López et al., 2006; Maranho et al., 2015; Soorya et

al., 2013; Vlahogianni et al., 2007).

Transplant to the uncontaminated area (C to UC) did not induce any

oxidative damage at the lipid level, as expected, since the organisms were

transplanted to an area with less anthropogenic pressure (Lukyanova, 2006;

Rocchetta et al., 2014). There were no significant difference between ACAP

levels of transplanted organisms and control of uncontaminated area after 48

hours. This indicates that organisms adapted to new environmental conditions

after an abrupt decontamination (less than 48-hours). Quick recovery responses

22

after abrupt sewage decontamination were also reported by Ferreira et al.,

(2005) and Liu et al. (2011) in fish and nematode community, respectively.

The ANOVA and SNK tests In the chronic assay indicated that variations

in biochemical responses were more related to background variability over time

and heterogeneity among areas than to the experimental manipulation itself. In

a previous experiment conducted with Perinereis gualpensis, at a same time

scale, the total antioxidant capacity and lipid peroxidation levels did not

consistently reflect differences between sites under different anthropogenic

pressure (Díaz-Jaramillo et al., 2013). The lack of differences between

treatments confirms that medium-term responses was attributed rather to the

high environmental variability than to experimental manipulation. This strongly

suggests that organism recovery after an abrupt contamination and

decontamination is a short-term process, which occurs on the scale of hours or

less than 4 days. However, Geracitano et al. (2004) showed different patterns

for biomarkers response in Laeonereis acuta after copper exposure, with

significant responses at medium but not short-time scales.

Variations on ACAP levels in 48 hours were probably a methodological

artefact, (note the high level in supplementary material and the standard error in

Figure 3).

Significant differences in ACAP levels between translocated and control

treatments, detected during the chronic experiment, were more related to

heterogeneity among experimental blocks than to methodological artefacts,

since there was a difference in faecal and total sterol concentrations between

blocks.

ACAP levels were higher in organisms from contaminated than in those

from uncontaminated areas in the acute experiment. An inverse pattern was

detected in the chronic experiment, where ACAP levels were lower in

organisms from contaminated than in those from uncontaminated areas (except

in block 2 time 1). This is unexpected, since the capacity to face oxidative stress

have previously proved to be lower in organisms from contaminated coastal

areas (Machado et al., 2014; Díaz-Jaramillo et al., 2010; Ferreira-Cravo et al.,

2007; Geracitano et al., 2004). Different response patterns for ACAP were also

recorded by Díaz-Jaramillo et al. (2011) and Díaz-Jaramillo et al. (2013).

Probably, ACAP response to xenobiotics does not follow a specific pattern,

especially when results of field and laboratory are compared. Therefore, such

comparisons should be made cautiously because organisms are subject to

variables and scales of variability that are quite different under each condition.

There is clearly a demand for more complex ecological assessments and

a further advance for ecotoxicology will dependent upon better integration of lab

toxicology with field experiments. For this, field, laboratory studies and long-

23

term monitoring combined with an advanced understanding of larger and more

complex variation along time and spatial scales are necessary to ensure that

the ecological complexity will be taken into account for better management

strategies and environmental monitoring programs.

5. CONCLUSIONS

There were no medium-term significant responses after the transplants

between contaminated and uncontaminated areas, as shown by the response

of oxidative stress and antioxidants biomarkers. With the exception of a short-

term response of MDA levels after the abrupt exposure to sediment

contaminated by domestic sewage effluents, none of the biochemical responses

were significantly altered by the impact. This result was attributed to the high

environmental variability between the experimental sites. Nevertheless, our

results strongly suggests that recovery in L. culveri after an abrupt

contamination and decontamination occurs on a very short term scale,

indicating the resilience or ability of fast recovery in estuarine species.

We also stress the importance of robust spatial replication for

ecotoxicological monitoring programs (as blocks were always interacting with

the other factors and showing significant differences), mainly when information

is scant about the local fauna and about the background variability of

biomarkers.

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SUPPLEMENTARY MATERIAL

Table 1. ACAP and MDA (nmol/mg) values of acute experiment.. CC = control for the

contaminated area, CUC = control for the uncontaminated area, TPC= transplant from the

uncontaminated to the contaminated area, TPUC= transplant from the contaminated to the

uncontaminated area, TLC= translocation for the contaminated area, TLUC= translocation for the

uncontaminated area.

Uncontaminated to contaminated Contaminated to uncontaminated

Treatment Exposure

time

ACAP (relative

area)

MDA nmol/mg protein

Treatment ACAP

(relative area)

MDA nmol/mg protein

TLC B1

T1 24h

0,471821552 0,019169771

TLUC B1

0,34808171 0,030746714

0,600737191 0,016853222 0,468383632 0,031091731

0,450291231 0,013408843 0,48118622 0,026826847

TPC B1

0,364441781 0,013249381

TPUC B1

0,539330067 0,032016611

0,514550807 0,00859309 0,476685603 0,028754888

0,486099108 0,02211257 0,304097241 0,026623895

CC B1

0,410182864 0,019883001

CUC B1

0,41333602 0,030372703

0,39619807 0,024429118 0,343937735 0,035762519

0,348747004 0,014609157 0,346275105 0,026809451

CUC B1

0,41333602 0,030372703

CC B1

0,410182864 0,019883001

0,343937735 0,035762519 0,39619807 0,024429118

0,346275105 0,026809451 0,348747004 0,014609157

TLC B2

0,540277053 0,011561982

TLUC B2

0,491063773 0,0245045

0,446308173 0,010784968 0,454038189 0,034040329

0,252367067 0,015858759 0,392296267 0,036783076

TPC B2

0,341530709 0,011222763

TPUC B2

0,470033271 0,039322871

0,328684487 0,014391709 0,3931528 0,034449132

0,324292616 0,029966799 0,570886255 0,035501581

CC B2

0,452821412 0,031471541

CUC B2

0,454275005 0,037783338

0,606151874 0,029615983 0,444114907 0,030793102

0,46346649 0,032437011 0,552367534 0,038009484

CUC B2

0,454275005 0,037783338

CC B2

0,452821412 0,031471541

0,444114907 0,030793102 0,606151874 0,029615983

0,552367534 0,038009484 0,46346649 0,032437011

TLC B1

T2 48h

1,091399397 0,055266174

TLUC B1

0,313491061 0,061438804

0,352123539 0,064923774 0,382358536 0,045683956

0,372420613 0,058290154 0,242819623 0,053111987

TPC B1

0,496101209 0,05091721

TPUC B1

0,287075632 0,054564541

0,488952601 0,058365536 0,308398081 0,042900619

0,37630465 0,054457267 0,402722164 0,055399542

CC B1

0,62446319 0,052016048

CUC B1

0,282592273 0,042874525

0,343597319 0,052813358 0,304095554 0,046617534

0,394682076 0,058142289 0,290169265 0,061885298

CUC B1

0,282592273 0,042874525

CC B1

0,62446319 0,052016048

0,304095554 0,046617534 0,343597319 0,052813358

0,290169265 0,061885298 0,394682076 0,058142289

TLC B2

0,283589263 0,060403751

TLUC B2

0,270819961 0,070635414

0,268543827 0,05477909 0,258792666 0,05864387

0,252307286 0,057417462 0,307438838 0,068701574

TPC B2

0,170827691 0,056405603

TPUC B2

0,276593841 0,069681541

0,193001323 0,057239637 0,256092041 0,0614562

0,265719062 0,057115934 0,26213796 0,065973324

CC B2

0,247439369 0,059806493

CUC B2

0,197959775 0,040413011

0,226393252 0,059383194 0,228354186 0,056414301

0,326376563 0,055579299 0,162908624 0,06326247

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CUC B2

0,197959775 0,040413011

CC B2

0,247439369 0,059806493

0,228354186 0,056414301 0,226393252 0,059383194

0,162908624 0,06326247 0,326376563 0,055579299

TLC B1

T3 96h

0,354250309 0,062157833

TLUC B1

0,3419795 0,064265631

0,41660613 0,050343147 0,373432969 0,058669963

0,461711679 0,070351281 0,275827833 0,027882196

TPC B1

0,206863167 0,064071377

TPUC B1

0,309943318 0,038737211

0,37717497 0,07220394 0,223048176 0,044683694

0,536300973 0,063827835 0,31054963 0,029555097

CC B1

1,156133173 0,067188135

CUC B1

0,241773633 0,04210041

0,629564038 0,072827292 0,398220728 0,052656796

0,714634223 0,08009876 0,250691747 0,03445493

CUC B1

0,241773633 0,04210041

CC B1

1,156133173 0,067188135

0,398220728 0,052656796 0,629564038 0,072827292

0,250691747 0,03445493 0,714634223 0,08009876

TLC B2

0,74206198 0,067191034

TLUC B2

0,243563881 0,039302576

0,370436007 0,064109068 0,189894157 0,026774659

0,310097924 0,051117262 0,300925971 0,031746975

TPC B2

0,456822134 0,072673628

TPUC B2

0,403275997 0,027809713

0,442244888 0,06510933 0,488361544 0,034727465

0,32338532 0,058814929 0,44374833 0,053633863

CC B2

0,433866504 0,06288266

CUC B2

0,373305934 0,056405603

0,303295227 0,063189987 0,345193503 0,041909055

0,330918095 0,037133892 0,732281973 0,043210845

CUC B2

0,373305934 0,056405603

CC B2

0,433866504 0,06288266

0,345193503 0,041909055 0,303295227 0,063189987

0,732281973 0,043210845 0,330918095 0,037133892

Table 2. ACAP and MDA (nmol/mg) values of chronic experiment. CC = control for the

contaminated area, CUC = control for the uncontaminated area, TPC= transplant from the

uncontaminated to the contaminated area, TPUC= transplant from the contaminated to the

uncontaminated area, TLC= translocation for the contaminated area, TLUC= translocation for

the uncontaminated área.

Exposure

time

Uncontaminated to Contaminated Contaminated to uncontaminated

Treatment ACAP

(relative area)

MDA nmol/mg protein

Treatment ACAP

(relative area)

MDA nmol/mg protein

T1 7 dias

TLC B1 0,711665 0,04099 TLUC B1 0,464844 0,034966

0,372835 0,044289

0,377924 0,049556

0,485432 0,047726

0,302121 0,040589

TPC B1 0,535231 0,035103 TPUC B1 0,228689 0,053153

0,384314 0,040472

0,349121 0,03011

0,272635 0,052835

0,25658 0,030265

CC B1 0,213492 0,0386 CUC B1 0,901127 0,029326

0,20291 0,064324

0,776922 0,033057

0,150191 0,040763

0,684896 0,021145

CUC B1 0,901127 0,029326 CC B1 0,213492 0,0386

0,776922 0,033057

0,20291 0,064324

0,684896 0,021145

0,150191 0,040763

TLC B2 0,347999 0,046288 TLUC B2 0,688432 0,028599

0,477098 0,039918

0,829736 0,042641

0,448704 0,04181

0,387617 0,041217

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TPC B2 0,342197 0,03957 TPUC B2 0,556107 0,063517

0,253194 0,04344

0,627461 0,056781

0,639318 0,043504

1,065994 0,057768

CC B2 0,590208 0,062502 CUC B2 2,052966 0,057651

0,498469 0,051355

0,528317 0,079784

0,466547 0,03163

0,275713 0,07308

CUC B2 2,052966 0,057651 CC B2 0,590208 0,062502

0,528317 0,079784

0,498469 0,051355

0,275713 0,07308

0,466547 0,03163

T2 14 dias

TLC B1 0,61003 0,060879 TLUC B1 0,387909 0,09353

0,681789 0,063365

0,397642 0,083222

0,718408 0,064743

0,66573 0,097955

TPC B1 0,252265 0,092813 TPUC B1 0,491727 0,126597

0,25338 0,109595

0,616704 0,109574

0,342104 0,06323

0,445622 0,077278

CC B1 0,26748 0,091045 CUC B1 1,895408 0,061643

0,319505 0,066926

0,339472 0,080438

0,237035 0,050002

0,243595 0,0795

CUC B1 1,895408 0,061643 CC B1 0,26748 0,091045

0,339472 0,080438

0,319505 0,066926

0,243595 0,0795

0,237035 0,050002

TLC B2 0,466821 0,063173 TLUC B2 0,290841 0,071401

0,277348 0,062903

0,316921 0,077828

0,390607 0,047765

0,208146 0,146642

TPC B2 0,525852 0,090817 TPUC B2 0,280574 0,081983

0,59869 0,081201

0,206827 0,089191

0,369857 0,078815

0,307914 0,052144

CC B2 0,331891 0,057921 CUC B2 0,104591 0,102805

0,269849 0,058798

0,164734 0,071074

0,131747 0,081127

0,147973 0,11963

CUC B2 0,104591 0,102805 CC B2 0,331891 0,057921

0,164734 0,071074

0,269849 0,058798

0,147973 0,11963

0,131747 0,081127

Table 3. Total sterol concentrations (in µg.g-1) and sterol diagnostic indices in surface

sediments from experimental blocks. nd = not detected.

Contaminated

area Uncontaminated

area

B1 B2 B1 B2

Sterols

Coprostanol 0,44 0,09 0,03 0,01

Epicoprostanol 0,09 0,01 nd nd

Colesterol 2,55 0,64 2,43 0,72

Cholestanol 0,69 0,09 0,59 0,09

Campesterol 1,51 0,10 1,06 0,11

Stigmasterol 0,87 0,34 0,28 0,50

Sitosterol 2,65 0,26 0,81 0,27

Sitostanol 0,48 0,05 0,14 0,06

Dinosterol 0,38 0,05 0,08 0,04

Fecal sterol (cop+epic) 0,53 0,10 0,03 0,01

Total sterol 9,66 1,63 5,42 1,80

Sterol diagnostic indices I Threshold levels

coprostanol/(coprostanol + 0,39 0,50 0,05 0,10 <0.30: pristine

33

cholestanol) environments

coprostanol/(coprostanol + cholesterol)

0,15 0,12 0,01 0,01 >0.50: sewage contamination

coprostanol/(coprostanol + dinosterol)

0,54 0,64 0,27 0,20 >0.50: sewage contamination

% of faecal sterols/total sterols 5,49 6,13 0,55 0,56 >50%: high sewage contamination

epicoprostanol/coprostanol 0,20 0,11 nc nc <0.20: untreated sewage input

Table 4. Acute experiment. Analysis of variance of lipid peroxidation levels and antioxidant

capacity against peroxyl on transplantations to the contaminated (UC to C) and

uncontaminated areas (C to UC). Significant terms of interest (α = 0.05) used in a posteriori

comparisons are highlighted in bold. For Student–Newman–Keuls (SNK) tests the mean values

are listed in ascending order. ‘‘>’’ indicates p < 0.05 and ‘‘=’’ indicates p > 0.05. UC =

uncontaminated area, C= contaminated area, Cuc = control for the uncontaminated area, Cc =

control for the contaminated area, TLc = translocate in the contaminated area TPc = transplant

to the contaminated area, TLuc = translocate from the uncontaminated, TPuc = transplant to the


UC to C C to UC

ACAP

Source of variation df MS F Pr(>F) MS F Pr(>F)

Treatment (Tr) 3 0.45475 35.333 0.16374

0.046893 1.8689 0.3101767

Time (T) 2 0.43329 0.5336 0.65208

0.122191 2.6329 0.2752616

Block (B) 1 131.365 24.6437 9.105e-06

0.012558 2.7228 0.1054568

Tr x T 6 0.12966 0.7703 0.62026

0.015662 0.6673 0.6821548

Tr x B 3 0.12870 2.4144 0.07803

0.025091 5.4402 0.0026576

T x B 2 0.81207 15.2342 7.535e-06

0.046409 10.0622 0.0002241

Tr x T x B 6 0.16832 3.1576 0.01084

0.023471 5.0888 0.0004114

Residuals 48 0.05331

0.004612 SNK test

T1.B1 Cuc=Cc=TPc=TLc

T1.B1 Cuc=Cc=TLuc=Tpuc

T1.B2 TPc=TLc=Cuc=Cc

T1.B2 TLuc=Tpuc=Cuc=Cc

T2.B1 Cuc=Cc=TPc<TLc

T2.B1 Cuc=TLuc=Tpuc<Cc

T2.B2 Cuc=TPc=Cc=TLc

T2.B2 Cuc=TPuc=Cc=TLuc

T3.B1 Cuc=TPc=TLc<Cc

T3.B1 TPuc=Cuc=TLuc<Cc

T3.B2 Cuc=Cc=TPc=TLc T3.B2 TLuc=Cuc=Cc=TPc

MDA

Source of variation df MS F Pr(>F) MS F Pr(>F)

Treatment (Tr) 3 0.0000866 2.7006 0.21810

0.01830 0.5989 0.658010

Time (T) 1 0.0097817 93.2917 0.01061

242.329 10.1085 0.090021

Block (B) 1 0.0000066 0.1330 0.71698

0.10057 2.6838 0.107914

Tr x T 3 0.0004713 4.8875 0.03737

0.22133 3.6592 0.069772

Tr x B 3 0.0000321 0.6480 0.58808

0.03056 0.8156 0.491611

T x B 1 0.0001049 2.1197 0.13117

0.23973 6.3974 0.003444

Tr x T x B 3 0.0000964 1.9495 0.09182

0.06049 1.6141 0.163751

Residuals 32 0.0000495 SNK test

T1 TLc=TPc=Cc=Cuc

B1 T1<T3=T2

34

T2 Cuc=TPc=Cc=TLc

B2 T1<T3<T2

T3 Cuc<TLc=Cc=TPc

Table 5. Chronic experiment. Analysis of variance of lipid peroxidation levels and antioxidant

capacity against peroxyl on transplant to the contaminated area (UC to C) and uncontaminated

area (C to UC). Significant terms of interest (α = 0.05) used in a posteriori comparisons are

highlighted in bold. For Student–Newman–Keuls (SNK) tests, the mean values are listed in

ascending order. ‘‘>’’ indicates p < 0.05 and ‘‘=’’ indicates p > 0.05. UC = uncontaminated area,

C= contaminated area, Cuc = control for the uncontaminated area, Cc = control for the

contaminated area, TLc = translocate in the contaminated area TPc = transplant to the

contaminated area, TLuc = translocate from the uncontaminated, TPuc = transplant to the


UC to C C to UC

ACAP

Source df MS F Pr(>F) MS F Pr(>F)

Treatment (Tr) 3 0.084206 0.6903 0.6160

0.077663 0.5534 0.680454

Time (T) 1 0.036069 6.5565 0.2370

0.081397 0.9696 0.504911

Block (B) 1 0.020537 1.8884 0.1789

0.037703 2.3313 0.136617

Tr x T 3 0.025572 0.2162 0.8798

0.018755 0.1141 0.946125

Tr x B 3 0.121992 11.2177 3.446e-05

0.140327 8.6771 0.000234

T x B 1 0.005501 0.5059 0.4821

0.083948 5.1909 0.029523

Tr x T x B 3 0.118291 10.8774 4.399e-05

0.164431 10.1675 7.406e-05


T1.B1 Cc<TPc=TLc<Cuc

T1.B1 Cc=TPuc=TLuc<Cuc

T1.B2 Cuc=TPc=TLc=Cc

T1.B2 Cuc<Cc=TLuc=Tpuc

T2.B1 Cc=TPc=Cuc<TLc

T2.B1 Cc=Cuc=TLuc=Tpuc

T2.B2 Cc=TLc=Cuc=TPc T2.B2 TLuc=Cc=Cuc=Tpuc

MDA

Source df MS F Pr(>F) MS F Pr(>F)

Treatment (Tr) 3 0.0005656 0.5917 0.661472

0.0350 0.1280 0.93737

Time (T) 1 0.0102389 60.6052 0.081330

46.164 12.6097 0.17475

Block (B) 1 0.0004925 2.9022 0.098154

0.2783 4.4392 0.04305

Tr x T 3 0.0005104 12.9730 0.031795

0.1320 0.7924 0.57356

Tr x B 3 0.0009559 5.6325 0.003236

0.2732 4.3593 0.01105

T x B 1 0.0001689 0.9955 0.325886

0.3661 5.8405 0.02154

Tr x T x B 3 0.0000393 0.2318 0.873536

0.1665 2.6570 0.06506


T1 TPc=TLc=Cc=Cuc

B1 Cuc=Cc=TPuc=Tluc

T2 TLc=Cc<Cuc=TPc

B2 Cc=TLuc=TPuc=Cuc

B1 Cuc=TLc=Cc=TPc

B1 T1<T2

B2 TLc=Cc=TPc<Cuc B2 T1<T2

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