kinetics of accumulation and transformation of paralytic shellfish toxins in the blue mussel mytilus...

Kinetics of accumulation and transformation of paralytic shellfish

toxins in the blue mussel Mytilus galloprovincialis

Juan Blancoa,*, Ma Isabel Reyerob, Jose Francoc,b

aCentro de Investigacions Marinas, Procesos oceanograficos costeros, Pedras de Coron s/n. Apdo. 13. Vilanova de Arousa 36620, SpainbInstituto Espanol de Oceanografıa, Centro Costero de Vigo. Subida a Radiofaro, San Miguel de Oia, Vigo, Spain

cInstituto de Investigaciones Marinas. Eduardo Cabello s/n. Vigo, Spain

Received 12 June 2003; revised 10 July 2003; accepted 10 October 2003

Abstract

Mussels (Mytilus galloprovincialis) were fed cultures of the Paralytic Shellfish Poisoning agent Alexandrium minutum

(Strain AL1V) for a 15-day period and, for the next 12 days, they were fed the non-toxic species Tetraselmis suecica, in order to

monitor the intoxication/detoxification process. The toxin content in the bivalve was checked daily throughout the experiment.

During the time-course of the experiment, the toxin profile of the bivalves changed substantially, showing increasingly greater

differences from the proportions found in the toxigenic dinoflagellate used as food. The main processes involved in the

accumulation of toxins and in the variation of the toxic profiles were implemented in a series of numerical models and the

usefulness of those models to describe the actual intoxication/detoxification kinetics was assessed. Models that did not include

transformations between toxins were unable to describe the kinetics, even when different detoxification rates were allowed for

the toxins involved. The models including epimerization and reduction provided a good description of the kinetics whether or

not differential detoxification was allowed for the different toxins, suggesting that the differences in detoxification rates between

the toxins are not an important factor in regulating the change of the toxic profile. The implementation of Michaelis–Menten

kinetics to describe the two reductive transformations produced a model that had a poorer fit to the data observed than the model

that included only a first order kinetics. This suggests that, it is very unlikely that any enzymatic reaction is involved in the

reduction of the hydroxycarbamate (OH-GTXs) to carbamate (H-GTXs) gonyautoxins.

q 2003 Elsevier Ltd. All rights reserved.

Keywords: Paralytic shellfish poisoning; Paralytic shellfish toxins; Kinetics; Accumulation; Ddetoxification; Biotransformation; Models

1. Introduction

Paralytic shellfish toxins (PSP toxins) are a group of

substances related to Saxitoxin (Fig. 1) produced, among

others, by some species of phytoplanktonic dinoflagel-

lates. As the bivalves ingest the producer organisms,

these toxins are accumulated—mainly in the digestive

gland—, becoming a serious risk to any mammal,

including man, that consumes them. The toxins contained

in the dinoflagellate cells are taken up by the bivalves,

then initially stored in the digestive gland and later

transferred in part to other organs or tissues through the

bloodstream. The toxins bind to receptors present in the

organs/tissues (Louzao et al., 1992) but a fraction is lost

or degraded at an organ/tissue specific rate (Bricelj and

Cembella, 1995). This occurrence often produces detox-

ification kinetics which is, in appearance, biphasic

(Lassus et al., 1989, 1993) and which must be described

by means of two- or multi-compartmental models (Silvert

and Cembella, 1995; Blanco et al., 1997; Silvert et al.,

1998a). The relative proportions between PSP toxins

inside the bivalves are different from those in the

producer dinoflagellate, which can only be explained by

means of toxin-specific uptake or elimination, or by

0041-0101/$ - see front matter q 2003 Elsevier Ltd. All rights reserved.

doi:10.1016/j.toxicon.2003.10.007

Toxicon 42 (2003) 777–784

www.elsevier.com/locate/toxicon

* Corresponding author. Tel.: þ34-986-500155; fax: þ34-986-

506788.

E-mail address: [email protected] (J. Blanco).

http://www.elsevier.com/locate/toxicon

transformations between toxin types. Differential uptake

has not been found (Bricelj and Shumway, 1998) and

only one experiment with Spisula solidissima suggested a

real differential elimination (Silvert et al., 1998b).

Several kinds of transformations have been documented

for PSP toxins. Epimerization between a and b epimers

appears to take place easily and it is not believed to be

enzymatically mediated. Reduction, acid hydrolysis or

enzymatic hydrolysis have also been demonstrated

(Cembella et al., 1993, 1994; Oshima, 1995; Murakami

et al., 1999a,b), but in some cases at different velocities

in different species, as well as in different organs of the

same organism.

Considering that these processes take place simul-

taneously and that they are difficult or even impossible to

measure directly, it becomes clear that predicting the

accumulation of these toxins is a difficult task which

requires the use of an indirect approach such as dynamic

modelling. This approach has been used with several

species and toxin groups, both taking the transformations

between toxins into account (Fernandez et al., 1998;

Silvert et al., 1998a) and not considering these trans-

formations (Silvert and Cembella, 1995; Blanco et al.,

1995, 1997, 1999).

In this work, we have used the modelling approach to

estimate the rates of all the processes mentioned above,

employing Mytilus galloprovincialis as the bivalve species,

because of its economic and ecological importance.

Alexandrium minutum (strain AL1V) was used as the source

of PSP toxins owing to its economic importance (it

frequently blooms in Galicia and other geographical

areas), and its relatively simple toxin profile (mainly

gonyautoxins, Franco et al., 1994), which greatly simplifies

both the analytical procedures and the models.

2. Material and methods

2.1. Biological material and procedures

Mussels M. galloprovincialis (3–4 cm long) were

collected from the Rıa de Vigo (Galicia, NW Spain), and

checked for the absence of PSP toxins by means of HPLC-

FD analysis. A. minutum (AL1V) was obtained from the

culture collection of the Centro Costero de Vigo of the

Instituto Espanol de Oceanografıa and cultured in K

medium (Keller and Guillard, 1987) in 2 l flasks under

fluorescent lighting. Tetraselmis suecica was cultured in 50 l

polypropylene bags using Walne’s medium (Lavens and

Sorgeloos, 1996) and fluorescent lightning. A new flask was

inoculated every 2 days in order to keep the cultures in a

homogeneous physiological state when needed to feed the

mussels. The mussels were placed in a 5 l tank, which

underwent cleaning and a change of water daily. Over the

course of 15 days, the animals were fed, at regular intervals,

by adding the amount of culture needed to reach an initial

concentration in the tank of roughly 1000 cells of A.

minutum ml21. Small aliquots of the culture used as food

were taken just prior feeding, to quantify the concentration

of Alexandrium and the toxin. After day 15, the Alexan-

drium cells in the diet were replaced with the non-toxic

species T. suecica. Each day three mussels were randomly

taken from the tank, weighed, their soft tissues homogenized

and the toxins they contained extracted following the AOAC

procedure (AOAC, 1990). Small aliquots were taken to

quantify the toxin concentration of the extracts by HPLC.

2.2. PSP toxin quantification

Toxins were identified and quantified by comparing their

retention times and fluorescent response with standard

Fig. 1. Structure and toxic power of saxitoxin and its main analogs (MU ¼ Mouse Unit, the amount of toxin required to kill a mouse weighing

20 g in 15 min upon intra-peritoneal injection).

J. Blanco et al. / Toxicon 42 (2003) 777–784778

PSP1-B solutions obtained from the National Research

Council (Canada). No standard of decarbamoyl-gonyautox-

ins was available. However, in view of the fluorescent

response of these toxins, as compared to the others found the

mussels, they always appeared in low quantities. This fact as

well as the difficulties involved in attempting to obtain an

accurate quantification of these types of toxins in the

absence of standards, prompted us to exclude them from the

analyses. The identification/quantification of the toxins was

carried out following the HPLC-FD technique of Franco and

Fernandez-Vila (1993).

2.3. Models

The models were implemented using Matlab and Matlab

Simulink. The fit was carried out by least square

minimization using the routines in the Matlab Optimization

Toolbox.

All the statistical procedures were performed using the

Minitab 13.1 statistical package, and following the general

methods given in Bates and Watts (1988).

3. Results

The first model implemented (Model 1) assumes the

simplest situation (Table 1): (a) there is no transformation

between toxins; (b) the uptake and detoxification rates are

the same for all toxins and (c) the detoxification follows a

first-order kinetics. In this case, the model can be formulated

as a simple system of differential equations

dGTX1=dt ¼ F½GTX1�mediumAE 2 KGTX1 ð1Þ

dGTX2=dt ¼ F½GTX2�mediumAE 2 KGTX2



where GTXn and ½GTXn� denote the concentration of each

gonyautoxin in mussels and in the maintenance medium,

respectively, F is the clearance rate and K is the

detoxification rate. The equation for each toxin has two

parts: uptake and loss. The uptake portion includes the

amount of toxin cleared by the mussels from the medium,

that is the F½GTX�medium and the fraction of it that is really

absorbed, AE (the absorption efficiency). The loss term is

assumed to be a fixed percentage, K (the detoxification rate)

of the amount of toxin inside the mussel, GTXn:

This model was not able to describe the experimental data

of most toxins (Fig. 2), and only GTX4, the most abundant,

was reasonably well described. Nevertheless, even in this

toxin, the peak values expected from the model were far from

the actual ones and detoxification seemed to proceed too

quickly. The filtration rate, the absorption efficiency and the

detoxification rate, with which the best fit was obtained, were

4.6 l h21, 67% and 0.15 day21, respectively.

The next model implemented (Model 2) assumes the

same filtration rate and absorption efficiency as in the

previous model but allows for a different detoxification rate

for each toxin instead of assuming a common detoxification

rate for all of them. The previous system of Eq. (1) was,

therefore, only modified by the substitution of each K by a

Kn (the detoxification rate for each particular toxin).

Although, the new model fit the data better than the

previous one (Fig. 3), it was totally unsuitable for two

ðGTX2 and GTX3Þ out of the four toxins. The estimated

detoxification rates of the four toxins were very different

from each other, ranging from 0 to 0.28 day1—a wide range

that would seem to be unlikely, considering the structural

similarity between the toxins.

The third model implemented (Model 3) differs from the

first in that some transformations between toxins were

allowed to take place. The transformations allowed were

those that appeared to be most likely, in view of the changes

detected in the proportions between toxins in other

mollusks: (a) epimerization between the a ðGTX1 and

GTX2Þ and b ðGTX3 and GTX4Þ forms, in both directions

and (b) reduction of the two OH-GTXs (4, 1) to their

corresponding H-GTXs (3, 2, respectively). The equations

describing the model are therefore

dGTX1=dt¼F½GTX1�mediumAE2KGTX1 þE4–1GTX4

2R1–2GTX1 ð2Þ

dGTX2=dt ¼ F½GTX2�mediumAE 2 KGTX2 þ E3–2GTX3

þ R1–2GTX1

Table 1

Differences between the models implemented

Model Detoxification rate Epimerization Reduction Compartments

Model 1 Common for all toxins No No 1

Model 2 Different for each toxin No No 1

Model 3 Common for all toxins Yes, first order kinetics Yes, first order kinetics 1

Model 4 Different for each toxin Yes, first order kinetics Yes, first order kinetics 1

Model 5 Common for all toxins Yes, first order kinetics Yes, Michaelis–Menten kinetics 1

Model 6 Common for all toxins Yes, first order kinetics Yes, first order kinetics 2

All models share common filtration rate and absorption efficiency for all toxins.

J. Blanco et al. / Toxicon 42 (2003) 777–784 779


þ R4–3GTX2


2 R4–3GTX4

where the equations defining first model are complemented

with the different transformations that were assumed to be

proportional to the amount of transformed toxin. Epimer-

izations were described by En–mGTXn and reductions by

Rn–mGTXn; where En–m are the rates of epimerization

between the toxins indicated in the sub-index, and Rn–m; the

reduction rates.

Fig. 2. Output of Model 1 (traces) and observed concentrations (symbols), of the four toxins studied in the experiment. The model assumes the

same incorporation and detoxification rate for the all the toxins; no transformation between toxins; and that the detoxification follows a first

order kinetics.


same incorporation for the all the toxins; no transformation between toxins; a first order kinetics for detoxification; but a different detoxification

rate for each toxin.


This model fit the data substantially better that the two

previous ones, adequately describing the main features

observed during the time-course of the experiment (Fig. 4).

In this case, the estimated detoxification rate for all

toxins was 0.06 day21. The estimated values for the

remaining parameters are given in Table 2. The model

output mirrors the general trend of the experimental data,

but obviously with the limitations imposed by their

dispersion. An analysis of the residual deviations of the

model (Fig. 5) showed that it was suitable for the two OH-

GTXs (4, 1), giving normal distributions and no detectable

trend. For the two H-GTXs (3, 2), however, an upward trend

was seen at the beginning of the experiment, while it shifted

downward towards the end. The distributions were not

normal either, indicating that the model did not provide an

accurate description of the kinetics of these two toxins from

a functional point of view.

Modifying the model to allow a different detoxification

rate for each toxin (Model 4) did not improve the fit, as the

variance explained was only marginally larger and the

residuals behaved in the same way as in the previous model.

The estimated values of the parameters are given in Table 2.

The estimated detoxification rates of the four toxins were

similar, ranging from 0.053 day21 (GTX3 and GTX1) to

0.070 day21 (GTX2). Epimerization occurred at a faster rate

between the two H-GTX toxins than between the OH-GTXs

and reduction was also estimated to be faster between the b-

forms than between the a ones.

The use of a Michaelis–Menten (Model 5), instead of

a first-order kinetics model, for the reduction from

the OH-GTXs to the H-GTXs degraded the fit, both

quantitatively and qualitatively. The model implemented

differed from Eq. (2) in which the reduction terms ðR4–3GTX4

and R1–2GTX1Þ were replaced with their corresponding

Table 2

Parameters estimated by fitting three of the models implemented:

Model 2 (differential detoxification without transformations),

Model 3 (common detoxification with transformations) and Model

4 (differential detoxification with transformations)

Models Model 2 Model 3 Model 4

Clearance rate (F; l h21) 4.6 4.6 4.6

Absorption efficiency (AE, %) 67 67 67

Detoxification rates

Common (K; day21) 0.06

GTX1 (K1; day21) 0.00 – 0.053

GTX2 (K2; day21) 0.28 – 0.070

GTX3 (K3; day21) 0.04 – 0.053

GTX4 (K4; day21) 0.13 – 0.063

Epimerization rates

GTX3 ! GTX2 (E3–2; day21) – 0.116 0.061

GTX2 ! GTX3 (E2–3; day21) – 0.008 0.003

GTX4 ! GTX1 (E4–1; day21) – 0.060 0.100

GTX1 ! GTX4 (E1–4; day21) – 0.000 0.014

Reduction rates

GTX1 ! GTX2 (R1–2; day21) – 0.0110 0.0038

GTX4 ! GTX3 (R4–3; day21) – 0.0001 0.0082


same incorporation and detoxification rate for the all the toxins; a first order kinetics for detoxification; but it also assumes the transformation

between toxins by epimerization and reduction.


Michaelis–Menten velocities ðVmax4–3½GTX4�Þ=ðKM4–3½

GTX4� and Vmax4–3½GTX4�Þ=ðKM4–3½GTX4�Þ; were the V

max are the maximal velocities of the reductions and the KM

are the Michaelis–Menten constants.

The inclusion of a second compartment in the model

(Model 6), to take into account the possibility of the

existence of two different pools of toxins with different

detoxification rates, did not effectively improve the fit of the

model to the actual data.

4. Discussion

Paralytic shellfish toxins produced by A. minutum

(AL1V) are transformed in the mussel M. galloprovincia-

lis, as in other bivalves (Shimizu and Yoshioka, 1981;

Sullivan et al., 1983; Cembella et al., 1994; Oshima, 1995;

Bricelj and Shumway, 1998; Silvert et al., 1998b). Two

transformations were identified—the epimerization and

reduction of the N1-OH groups. No evidence of decarba-

moylation or transformation of the GTX toxins to STX or

NeoSTX was found. Epimerization is a spontaneous

transformation that probably takes place in response to

the intracellular environment of the bivalve, which is

different from the environment inside the Alexandrium

cells. The reactions involved in the reductions from

OH-GTXs to H-GTXs are not known but there is no

evidence of their reversibility. The models built using

these considerations accurately described the time-course

of the accumulation/elimination of toxins in M. gallo-

provincialis. The models estimated greater epimerization

rates for the GTX4-1 pair than for GTX3-2, as well as

greater reduction rates between the b epimers than

between the a forms. The reactions involved in the

OH-GTX reductions are not known. Oshima (1995),

suggested that some natural reductants, such as gluta-

thione or cysteine, are the agents responsible for these

reductions, while according to Murakami et al. (1999a),

in the case of Pseudocardium sachalinensis, an enzyme

is involved, and Sakamoto et al. (2000) studying the

reductions produced by glutathione and mercaptoethanol,

suggested that these two compounds are not involved in

the reductions that we have considered in this exper-

iment. The models implementing a first-order reaction

kinetics for reduction slightly overestimated the amounts

of H-GTX during the early part of the experiment, but

the model that implemented a Michaelis–Menten kinetics

(typical of enzymatic reactions) resulted in much greater

overestimations. Although, none of the models is

completely satisfactory, better results were had with

those that used a first-order kinetics than with the one

that used the Michaelis–Menten kinetics, thus supporting

the suggestions made by Oshima (1995), that no enzyme

is involved.

Apart from transformations, the differential detoxifica-

tion is one of the possible mechanisms that may be able to

explain the changes in the proportions between the different

toxins in the bivalves as compared to those found in the algal

cells (Lassus et al., 1993). In this work, the models used

estimate only slight differences between the detoxification

rates of the four GTX toxins. Additionally, the inclusion of

these differences produced only a marginal (statistically

non-significant) increase in the fit, in relation to the

equivalent model that used a common detoxification rate

for all four GTX toxins. It would therefore seem that

differential detoxification does not play a significant role in

the change of the relative contributions of the GTX toxins

over time. (Silvert et al., 1998a), using a similar modelling

approach, found that GTX2 appeared to be depurated at

slower rate than the other toxins from the viscera of the

surfclam S. solidissima. In the mussel Mytilus edulis, GTX2

was found to increase its contribution relative to other toxins

during detoxification, and one possible mechanism to

explain this was reduced detoxification (Lassus et al.,

1993). Our results suggest that GTX2 depurates at the same

rate as the other GTX toxins or, if the minor difference found

in the model with differential detoxification is assumed to be

true, then GTX2 would depurate slightly faster than the

other toxins studied. The same lack of differences has been

found by Ichimi et al. (2001) with M. galloprovincialis and

by Sekiguchi et al. (2001) who analyzed the toxins excreted

Fig. 5. Residual deviations of Model 3 (observed–expected toxin

concentrations) for each of the toxins studied.


by Patinopecten yessoensis. Consequently, it would seem

that differential detoxification does not cause any major

changes in the toxin profile of bivalves, but the possibility

that this mechanism may affects certain species cannot be

ruled out.

Acknowledgements

This work was funded by the projects ‘Determinacion de

toxinas paralizantes en moluscos y cultivos de dinoflagela-

dos. Dinamica de intoxicacion y detoxificacion en mejil-

lones cultivados’ (CICYT ALI92-011-CO2-01) and

‘Acumulacion de toxinas de tipo paralıtico (PSP) e de tipo

amnesico (ASP) en moluscos bivalvos’ PGIDT99PXI50101

(Xunta de Galicia).

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