It was suggested that this is due to a lower average concentration of reactive oxygen species in the oscillatory state compared to the steady state.. In all cases we found that, irrespec
Trang 1Mechanism of protection of peroxidase activity by oscillatory
dynamics
Lars F Olsen1,2, Marcus J B Hauser3and Ursula Kummer1
1
European Media Laboratory, Heidelberg, Germany;2CelCom, Institute of Biochemistry and Molecular Biology,
Syddansk Universitet, Odense, Denmark;3Institut fu¨r Experimentelle Physik, Abteilung Biophysik,
Otto-von-Guericke Universita¨t, Magdeburg, Germany
The peroxidase–oxidase reaction is known to involve
react-ive oxygen species as intermediates These intermediates
inactivate many types of biomolecules, including peroxidase
itself Previously, we have shown that oscillatory dynamics in
the peroxidase–oxidase reaction seem to protect the enzyme
from inactivation It was suggested that this is due to a lower
average concentration of reactive oxygen species in the
oscillatory state compared to the steady state Here, we
studied the peroxidase–oxidase reaction with either
4-hydroxybenzoic acid or melatonin as cofactors We show
that the protective effect of oscillatory dynamics is present
in both cases We also found that the enzyme degradation
depends on the concentration of the cofactor and on the pH
of the reaction mixture We simulated the oscillatory
beha-viour, including the oscillation/steady state bistability observed experimentally, using a detailed reaction scheme The computational results confirm the hypothesis that pro-tection is due to lower average concentrations of superoxide radical during oscillations They also show that the shape of the oscillations changes with increasing cofactor concentra-tion resulting in a further decrease in the average concen-tration of radicals We therefore hypothesize that the protective effect of oscillatory dynamics is a general effect in this system
Keywords: peroxidase; superoxide radical; hydrogen per-oxide; oscillations; enzyme degradation
Within the last 30 years the number of reports on oscillating
biochemical processes has grown considerably [1] From the
first observations of oscillations in glycolysis in yeast and
muscle cells [2,3] through measurements of oscillations in
secondary messengers such as cyclic AMP[4] and cytosolic
Ca2+[5] to recent observations of oscillations in
intracel-lular NAD(P)H, pH, hydrogen peroxide, and superoxide in
migrating neutrophils [6,7] we are beginning to understand
that temporal behaviours, that is dynamics, play important
roles in cell metabolism Thus, it might be appropriate to
suggest that in addition to its genome and proteome a given
cell should also be characterized by the diversity of its
dynamic behaviours
In spite of their universal occurrence the functions of
metabolic oscillations in cells are still not well understood It
is not certain whether some biochemical oscillations occur
as harmless side-effects of the nonlinear properties of
metabolic enzymes or whether they always serve one or
more important functions Over the years many different
roles have been proposed for oscillations It has been
suggested that they provide metabolism with an increased
thermodynamic efficiency [8] Furthermore, oscillations, e.g those of second messengers such as calcium ions, are believed to have information stored in their frequency [9] Roles as biological time-keepers [1] and encoders of transmembrane signalling have also been proposed [10] Presumably, oscillations serve many functions in cell metabolism Here we wish to explore further another potential role of oscillating biochemical processes, namely the protection of proteins against otherwise harmful substances such as reactive oxygen species that are produced during cell metabolism or cell signalling This idea is not new; it has already been speculated that oscillations in cytosolic calcium were originally meant to prevent the precipitation of calcium phosphates in cytoplasm [11] However, this hypothesis has, to our knowledge, never been verified experimentally Nevertheless, in a recent article [12]
we have demonstrated experimentally and by computer simulations that oscillations may protect an enzyme from catalyzing its self-destruction by free radicals produced during the catalytic cycle
The peroxidase–oxidase reaction entails the oxidation of
an organic electron donor (typically NADH) by molecular oxygen [13]:
2 NADHþ O2þ 2 Hþ! 2 NADþþ 2 H2O ð1Þ catalyzed by peroxidase When NADH and O2 are supplied continuously to a stirred aqueous solution with
a pH between 5 and 6.5 containing peroxidase, a suitable aromatic compound and methylene blue, the reaction starts to oscillate [14,15] During the reaction hydrogen peroxide and superoxide are formed as intermediates [13]
Correspondence to L F Olsen, CelCom, Institute of Biochemistry and
Molecular Biology, Syddansk Universitet, Campusvej 55, DK5230
Odense M, Denmark Fax: + 45 65502467, Tel.: + 45 65502482,
E-mail: lfo@bmb.sdu.dk
Enzyme: horseradish peroxidase (EC 1.11.1.7)
Note: The mathematical model described here has been submitted to
the Online Cellular Systems Modelling Database and can be accessed
free of charge at http://jjj.biochem.sun.ac.za/database/olsen/index.html
(Received 6 February 2003, accepted 8 May 2003)
Trang 2These reactive oxygen species were considered as
unde-sired in cellular metabolism, because of their ability to
oxidize a number of biochemical substances, such as
enzymes and membrane lipids For example, it has been
shown that high concentrations of hydrogen peroxide can
lead to the inactivation of peroxidase through reactions of
H2O2 with peroxidase compound I [16,17] On the other
hand, reactive oxygen species may also be useful to the
organism They are used by neutrophils and other
phagocytic white blood cells to eliminate invading
path-ogens, such as bacteria [18Ờ20] Recently, it has been
shown that reactive oxygen species also seem to function
as secondary messengers in certain cell signalling processes
[7,21] Thus, the cell faces the problem of handling a
substance with both a beneficial and a harmful effect
While our previous study [12] was aimed at demonstrating
the protective role of oscillatory dynamics, the present
work concentrates on the mechanism of inactivation of
the enzyme by free radical intermediates and the role of
aromatic species in this mechanism
The mathematical model described here has been
submitted to the Online Cellular Systems Modelling
Database and can be accessed free of charge at http://
jjj.biochem.sun.ac.za/database/olsen/index.html
Experimental procedures
Experiments were conducted as described previously [22,23]
at 28 (ổ 0.1)C in a 2.0 ở 2.0 ở 4.3 cm3 quartz cuvette
fitted with a thermostating jacket The cuvette was
connec-ted to a Zeiss S10 diode array spectrophotometer through
optical fibers Oxygen in the solution was measured with a
Clark-type oxygen electrode (Microelectrodes Inc.) The
reaction mixture consisted of an 8-mL well-stirred
homo-genous aqueous solution containing 0.1Msodium acetate,
pH 4.5Ờ5.8, 1.1Ờ1.3 lMhorseradish peroxidase (Boehringer
Mannheim), 0.1 lM methylene blue (Merck), and 600Ờ
900 lM 4-hydroxybenzoic acid or 50Ờ300 lM melatonin
(Aldrich, 99.5%) Entry of O2to the reaction mixture was
from a 1.05% (v/v) O2/N2 gas mixture supplied to
the approximately 9 mL gas head space above the liquid
The rate of oxygen diffusion vO
2into the liquid is given by the equation:
vO 2Ử KđơO2eq ơO2ỡ đ2ỡ where [O2] and [O2]eqare the actual oxygen concentration in
the liquid and the oxygen concentration at equilibrium
between the gas and the liquid, respectively The oxygen
transfer constant K depends on the surface area, the energy
dissipation by the stirrer, and hence on the stirring rate
Kwas typically 3.5)6.0 ở 10)3s)1corresponding to stirring
rates of 800Ờ1000 r.p.m NADH (Boehringer Mannheim)
was supplied by infusion of a 0.1MNADH solution into
the reaction mixture through a capillary whose tip was
below the surface of the liquid The infusion was mediated
by a Harvard Apparatus, model 22, syringe pump, and the
infusion rate was typically 35 lLẳh)1
We recorded the time series of the absorbencies in the
range 350Ờ600 nm (1 nm resolution) and the O2
concentra-tion every 2 s, and stored the data on a computer for later
analysis Specifically, the absorbencies at wavelengths
cor-responding to NADH (360 nm), ferric peroxidase (403 nm),
compound III (418 nm), and ferrous peroxidase (439 nm) were used for spectral deconvolution of the absorbance measurements to concentrations of these four species [24] Their concentrations were determined by solving the system of linear equations:
where A is a vector containing the absorbencies at wave-lengths 360 nm, 403 nm, 418 nm and 439 nm, l is the length
of the light path through the sample, e is a 4ở 4 matrix containing the molar extinction coefficients of NADH, ferric peroxidase, ferrous peroxidase, and compound III at the four wavelengths and c is the vector of the concentrations of these four species The molar extinction coefficients e used in the calculations of c have been measured previously [24]
Results
The peroxidaseỜoxidase reaction shows a variety of dynamic behaviours depending on the reaction conditions [25] The dynamics include stationary (nonoscillatory) and oscillatory states In addition, the peroxidaseỜoxidase system is known
to display bistability, that is, two different coexisting dynamic states are simultaneously stable for the same experimental parameters Which of these dynamic states is approached depends on the history of the reaction system Depending on how the experimental parameters inside a bistable domain are approached, the reaction may settle on either one of the two coexisting stable dynamic states Experimentally this means that for exactly the same experimental parameters and very similar initial conditions the reaction may converge on either one of the two stable dynamic regimes Examples are (a) two coexisting steady states [26] and (b) a steady state coexisting with periodic oscillations [27]
Here we study the dynamics of the peroxidaseỜoxidase reaction under experimental conditions where the system settles either on an oscillatory or on a stationary (non-oscillatory) state [27] This allows us to explore the inactivation of the enzyme when the reaction is either oscillating or stationary, while all other parameters, such as oxygen and NADH inflow, pH, temperature, etc., are the same The graphs in Fig 1A,B show time series of the concentration of O2 for a typical experiment where the peroxidaseỜoxidase reaction is either in a stationary state or
in an oscillatory state The experiment is started by infusion
of NADH into a solution equilibrated with O2in the gas phase and containing the enzyme and the two modifiers, 4-hydroxybenzoic acid and methylene blue In Fig 1A the oxygen concentration in the liquid reaches a stationary value of approximately 2.5 lMcorresponding to a constant rate of oxidation of NADH This rate remains essentially the same throughout the experiment, i.e for more than
10 000 s In Fig 1B we show the time series of [O2] for an experiment where the peroxidaseỜoxidase reaction is in an oscillatory state It is worth emphasizing that the two experiments only differ in the dynamics shown by the peroxidaseỜoxidase reaction The average rates of oxidation
of NADH were shown to be the same [12] We recorded the spectra of the enzyme during the nonoscillatory and the oscillatory states and some examples are shown in Fig 1C,D, respectively In Fig 1C we show the spectra of the enzyme before the onset of the NADH inflow and 750 s
FEBS 2003 Protection of peroxidase activity (Eur J Biochem 270) 2797
Trang 3after starting the NADH inflow The first spectrum has a
peak at 403 nm and is typical for ferric peroxidase, while the
latter is typical for compound III (oxyferrous peroxidase)
Inspection of the spectra in the visible region (500–600 nm)
showed no evidence for enzyme intermediates other than
ferric peroxidase, ferrous peroxidase, and compound III
Figure 1D shows spectra of the enzyme at various phases
of the oscillatory cycle Again we observe no evidence for
enzyme intermediates other than ferric peroxidase, ferrous
peroxidase, and compound III Furthermore, a phase plot
where the concentration of ferric peroxidase is plotted
against compound III defined an almost straight line,
indicating that compound III and ferric peroxidase are by
far the dominant species during the oscillations Thus, we
conclude that these three intermediates represent more than
90% of the total amount of enzyme present in the reaction
mixture In Fig 1E we have plotted the sum of the
concentrations of the three enzyme intermediates calculated
from Fig 1A,B The sum of concentrations from the experiment showing steady state kinetics decreases at an almost constant rate The rate of inactivation of the enzyme is calculated as 44.6 pMÆs)1 The sum of concentrations from the experiment showing oscillatory kinetics also decreases, but at a much lower rate compared to the steady state experiment The small periodic deviations from a smooth decline in concentrations, especially in the trace for oscilla-tory dynamics, is either an artifact due to inaccurate estimates
of the extinction coefficients or they represent the oscillations
in concentrations of compound I and compound II [24], which are two enzyme intermediates that are also believed to participate in the reaction The rate of inactivation of the enzyme in the oscillatory state is calculated as 14.2 pMÆs)1
We have conducted approximately 50 experiments showing oscillations and 50 experiments showing nonoscil-latory behaviour using different infusion rates of NADH and different stirring rates, corresponding to different oxygen transfer constants, to compare the rates of inacti-vation of the enzyme during oscillatory and nonoscillatory states In all cases we found that, irrespective of the average concentrations of O2, NADH, and enzyme intermediates, the rate of inactivation of the enzyme is always significantly lower in an oscillatory state than in the corresponding nonoscillatory state Previously we have shown that in experiments similar to those in Fig 1 in which the peroxidase–oxidase reaction starts in a stationary state, but following a small random perturbation switches to an oscillatory state, the degradation of the enzyme slows down after the transition from the nonoscillatory to the oscillatory state [12] Thus, oscillatory kinetics seem to protect the enzyme against degradation Moreover, during experiments
in which no reaction took place due to the absence of NADH, the enzyme did not degrade at all The same applies
if we block the peroxidase–oxidase reaction by the addition
of a small amount of hydroquinone [28] In this case we observe an abrupt termination of the degradation of the enzyme [12], because the inhibition of the reaction also blocks the formation of free radicals [28] Thus, the inactivation of the enzyme can be ascribed to the presence
of reactive intermediates such as superoxide radical, hydro-gen peroxide and hydroxyl radical, which are hydro-generated during the reaction [13,29,30]
A further understanding of the mechanism for inactiva-tion of the enzyme may come from measurement of the effect of the concentration of the aromatic cofactor responsible for the onset of oscillations Here we use the fact that melatonin (N-acetyl-5-methoxytryptamine), a hormone synthesized by the pineal gland, may also induce oscillatory behaviour in the peroxidase–oxidase reaction [31] However, so far we have not been able to demonstrate the same oscillation/steady state bistability with melatonin
as a cofactor Figure 2 shows time series of NADH, O2, ferric peroxidase and compound III in the presence of
50 lM melatonin We note that the oscillations stop after about 10 000 s Further addition of melatonin to the reaction mixture did not result in a resumption of oscillatory dynamics However, the addition of more enzyme did restart the oscillations Increasing the initial amount of melatonin has the effect of prolonging the time over which oscillations are observed [31] In addition, the rate of inactivation is slowed down by increasing the concentration
Fig 1 Bistability between a stationary state and oscillations in the
peroxidase–oxidase reaction (A,B) Time series of the concentration of
oxygen during a stationary state and an oscillatory state, respectively.
(C) Absorption spectra at time zero (dashed line) and at time 750 s
(solid line) after the start of the experiment in (A) (D) Spectra at time
zero (dashed line), at time 544 s (solid line), and at time 558 s (dotted
line) after the start of the experiment in (B) (E) Total enzyme
con-centration plotted against time The sum of the concon-centrations of ferric
peroxidase (Per3+), ferrous peroxidase (Per2+), and compound III
from the experiments in (A and B) are plotted against time Stationary
state, ( ); oscillatory state, (.) The reaction mixture contained
1.2 l M peroxidase, 900 l M 4-hydroxybenzoic acid, and 0.2 l M
methylene blue in 8 mL of a 0.1 M sodium acetate buffer, pH 5.1.
Oxygen in the solution was in equilibrium with a 1.05% (v/v) O 2 /N 2
gas phase The experiment was started by infusion of 0.1 M NADH
into the reaction mixture at a rate of 35 lLÆh)1 The oxygen transfer
constant was 5.5 · 10)3s)1.
Trang 4of melatonin, as illustrated in Fig 3 Figure 3A shows time
series of the total enzyme concentration in the presence of
different concentrations of melatonin, while Fig 3B shows
a plot of the rate of enzyme inactivation against the
melatonin concentration It has been shown previously that
melatonin is a powerful scavenger of oxygen and
nitrogen-based reactive species such as hypochlorous acid [32],
hydroxyl radical [33] and peroxynitrite [34] Increasing the
concentration of 4-hydroxybenzoic acid also resulted in a
decrease in the rate of enzyme inactivation However, when
the reaction is in a stationary state, the concentration of the aromatic cofactor does not seem to have any effect on the rate of inactivation, i.e the rate of inactivation is the same when the steady state rate of NADH consumption is the same, irrespective of the concentration of either melatonin
or 4-hydroxybenzoic acid
We also investigated the effect of the pH on the enzyme inactivation Figure 4 shows a plot of the rate of enzyme inactivation against pH We note that the rate of inactiva-tion increases with decreasing pH We were not able to measure the rate of inactivation by further decreases in pH, because other factors, such as increased autooxidation of NADH and other acid degradation of this substance [35], seemed to prevent the observation of long time intervals of oscillatory dynamics
Numerical simulations
In order to understand the mechanism of protection better and to be able to depict the role of the aromatic cofactor in this scheme we performed numerical simulations using a new variant of a detailed model [36], which was shown to describe the peroxidase–oxidase reaction reasonably well Unlike the original model [36], this variant considers the role
of the aromatic cofactor in detail In a previous study [12]
we used the original model to simulate the peroxidase– oxidase system and showed that the average concentration
Fig 2 Time series of the concentrations of NADH, ferric peroxidase
(Per3+), compound III, and oxygen during an oscillatory state induced
by melatonin The reaction was performed in 0.1 M acetate buffer,
pH 5.1 The reaction was started by infusion of NADH (flow rate
34 lLÆh)1) to a solution containing 1.2 l M peroxidase, 0.1 l M
methylene blue and 50 l M melatonin The oxygen transfer constant
was 4.4 · 10)3s)1.
Fig 3 Effect of the concentration of melatonin
on the rate of enzyme decay during oscillatory
states (A) Time series of total enzyme
con-centration in the presence of 50 l M , 100 l M
and 200 l M melatonin as indicated in the
fig-ure (B) Rate of enzyme decay plotted against
the concentration of melatonin Other
experi-mental conditions were as in the legend to
Fig 2.
Fig 4 Effect of pH on the rate of enzyme decay during an oscillatory state The experiments were conducted in the presence of 300 l M
melatonin Other experimental conditions, except for the pH of the reaction mixture, were as in the legend to Fig 2.
FEBS 2003 Protection of peroxidase activity (Eur J Biochem 270) 2799
Trang 5of superoxide radical was smaller in the oscillatory
compared to the steady state The modified model involves
12 different chemical species, including five enzyme
inter-mediates, hydrogen peroxide and superoxide, as well as the
aromatic cofactor and its radical form [37] Thus, the
complete model yields 11 nonlinear first order differential
equations (because the aromatic cofactor is not consumed in
the reaction [28,31] we need only one differential equation to
describe the temporal change of both the reduced and the
radical form) The elementary reactions of the model are
listed in Table 1 Most of the rate constants listed in Table 1
have been determined experimentally [13] For a proper set
of rate constants, which correspond to the present
experi-mental conditions, our model shows bistability similar to that of the experimental system, i.e depending on the initial conditions the system either settles on a steady state (Fig 1A) or on a periodic oscillation (Fig 1B) Steady state concentrations as well as average and maximum concentrations of O2during oscillations as functions of the NADH inflow rate are presented in Fig 5 Similar to our results with the original model [12], the simulations reveal that although the maximum concentration of superoxide during oscillations is much higher than the values observed
in a steady state, the average concentration of this species is several times lower during oscillations than during steady state conditions In Fig 6 we show the dependence of the
Table 1 Detailed model of the peroxidase–oxidase reaction Per3+and Per2+indicate iron(III) and iron(II) peroxidase, respectively Enzyme intermediates compound I, compound II and compound III are represented as coI, coII and coIII, with ArH and Ar indicating the aromatic compound (4-hydroxybenzoic acid or melatonin) and its free radical, respectively.
1 NADH + O 2 + H +
7 2 O 2 + 2 H +
10 Per3++ NAD fi Per 2+
a
In M )1 Æs)1.bIn s)1.cThe value of [O 2 ] eq is 1.2 · 10)5M
Fig 5 Predicted effect of the inflow rate of NADH (k 12 ) on the
maxi-mum and the average superoxide concentration during oscillatory
dynamics and the steady state concentration calculated using the model
presented in Table 1 The initial concentration of oxygen was 12 l M
and the total enzyme concentration was 1.4 l M , while the
concentra-tion of the aromatic cofactor was 200 l M All other initial
concen-trations were zero, except for the initial concentration of H 2 O 2 which
was either 0.7 l M (resulting in steady state behaviour) or 0 l M
(resulting in oscillatory behaviour).
Fig 6 Predicted effect of the concentration of the aromatic cofactor
on the average superoxide concentration during oscillatory dynamics and the steady state concentration calculated using the model in Table 1 The initial concentration of oxygen was 12 l M and the total enzyme concentration was 1.4 l M , while the flow rate of NADH (k 12 ) was 0.08 l M Æs)1 All other initial concentrations were zero, except for the initial concentration of H 2 O 2 which was either 0.7 l M
(resulting in steady state behaviour) or 0 l M (resulting in oscillatory behaviour).
Trang 6average concentration of superoxide during oscillations and
the steady state concentration on increasing the
concentra-tion of the aromatic cofactor Note that the steady state
concentration of superoxide is essentially independent of the
concentration of the cofactor The difference in steady state
and mean oscillatory concentrations is more pronounced with increasing cofactor concentration because the shape of the oscillations changes and the peaks of superoxide radical concentration become higher and narrower (Fig 7)
In order to depict the origin of the lowered average concentration of superoxide during oscillations, we calcula-ted the average concentrations of all intermediates during oscillations and compared those with the respective steady state concentrations (Table 2) With the new detailed model and the parameters displayed in Table 1, the rate of production of NAD+is somewhat smaller during oscilla-tions compared to the steady state Therefore, for a better comparison with the experimental data, we increased the infusion rate of NADH to obtain a higher rate of production
of NAD+(Table 2, osc*) Comparing the two oscillatory states (Table 2, osc and osc*) to the steady state reveals that most of the average concentrations of the intermediates differ Again, it can be seen that the average concentration of superoxide (the likely reason for the stability of the enzyme during oscillations) is several fold lower during oscillations, even if the production of NAD+is the same It is also worth pointing out here that the concentrations of hydrogen peroxide and compound I are very similar in the oscillatory states and the steady state, suggesting that the inactivation of the enzyme cannot occur through reaction of hydrogen peroxide with compound I [16,17]
Trying to depict the reason for the decreased superoxide concentration, a somewhat naive approach would be to analyse the rates for the formation and decomposition of superoxide in the system Superoxide is formed via reaction
5 and decomposed via reactions 6 and 7 The rate of formation depends on the concentration of NAD and oxygen and it is clear that this should be somewhat higher during oscillations because of the increased concentration of NAD On the other hand the rate of superoxide decom-position via reaction 7 only depends on the superoxide concentration, and the rate of decomposition via reaction 6 will be much higher during oscillations due to the higher concentration of the native enzyme (Per3+) So, one could conclude that the increased concentration of native enzyme
is the reason for the decrease in superoxide concentration during oscillations
Now, of course, one would have to continue with this analysis and look for the reasons for the increased concen-tration of Per3+ This enzyme species is formed via reaction
4 The rate of this reaction hardly changes (when comparing oscillatory to steady state dynamics) due to the very similar concentrations of compound II and the aromate The consumption of Per3+ occurs via reactions 2, 6, and 10 The rates of reactions 2 and 6 should be smaller during oscillations, while the rate of reaction 10 should be somewhat higher Reaction 6 shows the strongest change and therefore, should be mainly responsible for the observed effect The rate of this reaction is determined by the concentrations of superoxide and the enzyme peroxidase Therefore, this kind
of analysis takes us back to the beginning, namely the reduced concentration of superoxide radical
It is obvious that this analysis does not really help in understanding the origin of the phenomenon The reason is
of course that the changes in concentrations are inherent to the reaction system (i.e they depend on the entire network
of elementary reactions) rather than properties of the
Fig 7 Time series of the concentration of superoxide computed using
the model in Table 1 The initial concentration of oxygen was 12 l M
and the total enzyme concentration was 1.4 l M , while the
concentra-tion of the aromatic cofactor was (A) 100 l M and (B) 500 l M All
other initial concentrations were zero The flow rate of NADH (k 12 )
was 0.08 l M Æs)1.
Table 2 Average concentrations of the reactants in lmolÆL -1 The
values were computed for a time series of 7000 s ss, Steady state
solution; osc, oscillatory solution For the products NAD+and NAD 2
dimers, end concentrations instead of average concentrations were
computed The inital concentration of melatonin was 300 l M , k 12 was
0.08 l M Æs)1for the entries ss and osc, while it was set to 0.12 l M Æs)1for
osc* This was done to obtain a similar rate of production of NAD + in
the ss and osc* sets.
Per 2+ 1.0 · 10)4 0.012 0.019
NAD 5.0 · 10)4 9.0 · 10)4 1.4 · 10)3
O 2 0.026 8.6 · 10)4 9.5 · 10)3
co I 8.9 · 10)4 7.1 · 10)4 9.1 · 10)4
FEBS 2003 Protection of peroxidase activity (Eur J Biochem 270) 2801
Trang 7individual reactions In other words, this systemic property
cannot be reduced to the effect of a single reaction (or to a
subset of the reaction network)
One interesting result of this analysis is the observation of
an approximately 100-fold increase in the production of the
NAD dimer (NAD2) during an oscillatory reaction as
compared to a reaction in steady state (Table 2) There are
only three other species in the system which change their
concentrations in a similar dramatic way, two of which are
the intermediates Ar and Per2+ The 100-fold increased
production of a certain minor product in a reaction
pathway corresponds to a switching between different
production lines This can be very useful in responding to
different environmental conditions within seconds, rather
than waiting for different gene expression, for example
In summary, the bistability allows the system to switch
between two states which have similar production rates of
the main product NAD+while maintaining, for example,
two completely different levels of NADH (although this
effect is much more pronounced in the simulations
compared to experiments) Furthermore, the production
of side products can be switched on while intermediates like
the superoxide radical are maintained at very low
concen-trations stabilizing the enzyme
Thus, our simulations strongly support our initial
hypo-thesis that the explanation for the increased degradation of
the enzyme in the steady state is the higher average
concentration of toxic reaction intermediates
Discussion
We have demonstrated experimentally that oscillatory
dynamics seem to protect peroxidases from inactivation
Our simulations corroborate our earlier suggestion [12] that
this is because the average concentrations of reactive oxygen
species are much lower during oscillatory conditions than
during steady state conditions The inactivation of
peroxi-dase does not seem to involve P670 [29,38] as we were
unable to find spectral evidence for the formation of this
species Therefore, we suggest that the inactivation occurs
through unspecific reactions of reactive oxygen species with
amino acid side chains and possible also sugar residues of
peroxidase [39]
The exact species responsible for the inactivation cannot
be determined here It may be either superoxide (or rather its
protonated form) or it could be the hydroxyl radical The
decrease in inactivation following increases in the
concen-tration of melatonin, when the system is in an oscillatory
state, could favour the hydroxyl radical, as melatonin is
known to be a powerful scavenger of this radical species
[33] However, our numerical results suggest that the effect
of an increase in melatonin concentration is simply due to
a further reduction in the average concentration of
super-oxide and other radical species This result also explains the
experimental observation that the concentration of the
aro-matic cofactor does not seem to have an effect on the rate of
inactivation when the system is in a steady state
The pH dependence of the inactivation does not reveal
much more about the mechanism of the inactivation
Nevertheless, the fact that the inactivation rate increases
rapidly below pH 5 is consistent with the above-described
mechanism The protonated form of superoxide radical has
a pK of 4.8 [40] and forms hydroxyl radicals according to the following equation [20,40]:
HO2þ H2O2! OH þ H2Oþ O2 ð4Þ Therefore, a decrease in pH will lead to more hydroxyl radicals and more inactivation due to those This observation
is also consistent with previous results [41], showing that the production of OH, catalyzed by peroxidase in the presence
of NADH, increases with decreasing pH The mechanism responsible for the production of hydroxyl radical is believed
to involve compound III [41] Hydroxyl radicals are normally not assumed to play a crucial role in the dynamics
of the peroxidase–oxidase reaction [13], and therefore they
do not appear in most detailed models of the reaction The pronounced dependence of the stability of the enzyme against inactivation on the type of dynamics (i.e whether the reaction system shows oscillatory or steady state behaviour) is mainly due to the lower superoxide concentrations found in the oscillatory state The search for the source of such differences in the superoxide concentra-tion levels have shown that the value of the concentraconcentra-tion of superoxide (as well as that of other intermediates) is clearly determined by the entire reaction network rather than by some individual reactions of the network Hence, the mechanism responsible for the differences in the concentra-tion of this key intermediate is a systemic property that is encoded in the underlying reaction network
We believe that our finding that oscillatory dynamics seem to protect enzymes from inactivation by toxic reaction intermediates is important for the function of peroxidases
in vivo An example is the killing of microorganisms in pathogen-defence mechanisms of neutrophils and other phagocytic white blood cells The dominating protein in neutrophils is myeloperoxidase [42] and several of these cells also synthesize melatonin [43] Furthermore, the pH inside the phagocytic vacuole (phagosome) is between 4 and 6 [44], which should favour an oscillating peroxidase–oxidase reaction Computer simulations of a model of the peroxi-dase–oxidase reaction involving myeloperoxidase predict oscillations in NADPH, oxygen, and reactive oxygen species in neutrophils [45] This model is a two-compart-ment model and uses the fact that NADPH is formed in the cytosol through the pentose phosphate shunt, while peroxi-dase is situated in the phagosome Other reactants diffuse across the phagosome membrane
One potential function of such oscillations could be to protect the machinery producing reactive oxygen species against self-destruction For example, hydroxyl radicals react very fast with certain lipids, proteins and DNA [39,46] Peroxidases, on the other hand, do not react very fast with the free radicals whose formation they catalyze, and hence the enzyme will decay very slowly under oscillatory conditions Contrary to this, lipid oxidation and structural changes in DNA may require only brief time intervals of high concentrations of reactive oxygen species As we have shown here by experiments and simulations oscillatory dynamics offer exactly such conditions
Oscillations in enzymatic systems may also serve another biological function, provided that the dynamic system allows for a bistable regime Here, the system can switch on or off the production of minor products (in this case the dimeric NAD) without delay, therefore
Trang 8responding immediately to changes in the environmental
conditions
To summarize, we have shown that oscillatory dynamics
in the peroxidase–oxidase system may serve different
physiological purposes, in addition to a role in being
associated with signal transduction pathways These new
roles are firstly the protection of the peroxidase activity
against inactivation by reactive reaction intermediates, and
secondly the possibility to act as a tool for rapid adaptation
to changing conditions by inducing immediate changes
between two reaction pathways, without requiring any
involvement of changes in the genetic expression
Acknowledgements
LFO and UK wish to acknowledge the Klaus Tschira Foundation and
the Danish Natural Science Research Council, while MJBH thanks the
Deutsche Forschungsgemeinschaft, for financial support The authors
should like to thank Anita Lunding, Torben Christensen, and Søren
Knudsen for valuable technical assistance and Mario Allegra of the
University of Palermo for stimulating discussions.
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