Journal of Plankton Research Vol.18 no.10 pp.1819-1835, 1996
Oxygen consumption in the marine bacterium Pseudomonas
nautica predicted from ETS activity and bisubstrate enzyme
kinetics
T.T.Packard, E.Berdalet 1 , D.Blasco2, S.O.Roy, L.St-Amand, B.Lagace\ K.Lee and
J.-P.Gagn63
Institut Maurice-Lamontagne, CP1000, Mont-Joli Quebec, G5H 3Z4, Canada,
'Institut de Ciencias Marinas, Passeig Juan Borbd c/n, 08030 Barcelona, Spain,
2
329 Rte 298 Sud, St-Donat de Rimouski, Quibec, GOK1L0 and 3Dipartement
d'Ocianologie, Universite du Quibec a Rimouski, 300 allie des Ursulines,
Rimouski, Quibec, G5L 3A1, Canada
Abstract The respiratory O2 consumption in aerobic bacterial cultures has been modeled from the
time profiles of the in vitro activity of the respiratory electron transfer system (ETS), the bacterial
protein and the concentration of the carbon source in the cultures. The model was based on the concept
of bisubstrate kinetic control of the ETS throughout the exponential, steady-state and senescent
phases of the cultures. In the exponential phase, the measured rates of O2 consumption and the in vitro
ETS activity were closely coupled, but in the senescent phase, they were uncoupled. The in vitro ETS
activity remained high even after the culture's carbon source was exhausted, while the O2 consumption fell to low levels. Based on the hypothesis that this uncoupling was caused by limitation of the
intracellular ETS substrates (NADH and NADPH), a semi-empirical model incorporating a bisubstrate enzyme kinetics algorithm was formulated and fitted to the observations of the experiments. The
model predicted the rate of O2 consumption throughout the different phases of the cultures with an r2
> 0.92 (n = 9, P < 0.001) using physiologically realistic Michaelis and dissociation constants. These
results suggest that plankton respiration in thefieldcould be assessed more accurately than before by
measuring the intracellular ETS substrates (NADH and NADPH), in addition to ETS activity, in
plankton.
Introduction
Interest in plankton respiration has stimulated exploration of the use of electron
transfer system (ETS) activity in oceanography and limnology (Vosjan and
Olanczuk-Neyman, 1991; del Giorgio, 1992; Martinez and Estrada, 1992; Naqvi
and Shailaja, 1993; Savenkoff et al., 1993; Dortch et al., 1994; Arfstegui and
Montero, 1995;Takahashi et al., 1995; Ikeda, 1996). Reasons for this interest stem
from the strong theoretical link between the function of the ETS and the physiological rate of oxygen consumption (Chance and Williams, 1956; Lehninger et al.,
1993). This interest persists in spite of fears of interference from (i) photosynthetic
electron transfer activity in phytoplankton, (ii) competing alternate oxidases in
both algae and bacteria, (iii) size or body weight problems in zooplankton, or (iv)
variability in the ratio of respiration to ETS activity (R/ETS) associated with
changes in species and physiology. The interest in ETS endures because an oceanic
ETS survey provides the fastest, simplest and least expensive way to assess
mesoscale variations in plankton potential respiration (Packard, 1985). Nevertheless, the problem of interpretation is serious and should be addressed.
The current way of calculating microplankton respiration in the euphotic zone
from ETS activity is to use a calibration study, such as that of Arfstegui and
Montero (1995) or del Giorgio (1992) in the fashion demonstrated by Savenkoff
© Oxford University Press
1819
T.T.Pidcard el at
et al. (1995c). In the deep sea, the current way is outlined by Savenkoff et al. (1993)
and by Naqvi and Shailaja (1993). Deep-ocean respiration is estimated by assuming that deep-sea plankton are dominated by bacteria in a dormant, starved or
senescent state. The findings of Morita et al. (1972), Morita (1980,1985) and Tabor
et al. (1981a,b) support this assumption. Accordingly, studies of the relationship
between ETS activity, energy charge and respiration in senescent-phase marine
bacteria (Christensen et al., 1980) are used to interpret the deep-sea activity
measurements. Applying this approach to deep-ocean ETS measurements led to
a calculation of global new production of 22 Gt C year 1 (Packard et al., 1988) that
provided the upper boundary condition on new production in the global carbon
cycling model of Siegenthaler and Sarmiento (1993); applying it to surface
upwelled waters led to calculations of phytoplankton and zooplankton respiration
(Packard, 1979), and applying it to estuaries led to carbon flux calculations (Relexans and Etcheber, 1985; Savenkoff et al., 1995a,c). del Gorgio (1992) has shown
that the errors associated with these applications are similar to the errors in other
standard ecological procedures used in plankton carbon flow studies (14C technique, thymidine uptake). Nevertheless, improvement is needed.
The problem
There is little question that the respiratory oxygen consumption is the product of
the enzyme-catalyzed reactions in the respiratory ETS, that respiratory physiological and enzymatic rates are affected by temperature in the same way, and that
the control of respiratory oxygen consumption at the physiological level is based
on the control of the rates of the component enzyme reactions in the respiratory
ETS. However, there is question about how respiration, at the level of the intact
organism, is related stoichiometrically to an in vitro measurement at the
enzymatic level. Most studies in the literature stop at a qualitative or statistical
understanding of the relationship between physiological respiration and the biochemical consumption of oxygen at the enzyme reaction level. Rare is a study like
that of Walsh and Koshland (1984) where reconstruction of the physiological respiration rate from the activities of the component enzymes is attempted. To
improve our ability to assess plankton respiration in the sea, laboratory studies
like that of Walsh and Koshland (1984), but focused on marine organisms, are
needed.
This is a laboratory study focused on the relationship between respiration and
ETS activity in a marine bacterium. A bacterium was chosen, rather than a phytoplankter, dliate or metazoan, to eliminate problems that photosynthetic electron
transport, organelle organization or behavior might have introduced [see
C.LevinthaPs argument in Platt (1964)].
Respiratory control hypotheses
In order to understand physiological oxygen consumption, one must investigate
respiratory ETS enzymatic control. Regulation of the respiratory ETS can be
accomplished by changing the concentration of the ETS enzymes or by changing
1820
Respiration and ETS activity in P. naulica
the activities of these enzymes. The activity can be changed by several mechanisms: (i) substrate availability; (ii) reversible (non-covalent) allosteric modification by enzyme modulators; (iii) chemical factors (i.e. pH and ionic strength),
and physical factors (i.e. temperature and pressure).
The first regulatory mechanism, regulation by a change in enzyme concentration, can be achieved by dehydrogenase synthesis or repression. It would
permit slow, coarse tuning of respiration. Evidence for this mechanism would
consist of a high degree of correlation (r2), as measured by least squares analysis,
between in vitro ETS activity (.AETSX a measure of concentration, and respiration
at the whole-cell level (i?^). This relationship would have to hold throughout
different growth phases of a bacterial culture.
The second regulatory mechanism, regulation by a change in enzyme activity,
is rapid and permits fine tuning of respiration in response to rapidly changing
environmental or intracellular conditions. It is achieved by changing the in vivo
activity of the ETS activity ( VETS). Regulation by chemical and physical factors
is non-specific; many other enzyme reactions would be impacted at the same time.
So this type of regulation is unlikely. Regulation by allosteric modification, e.g.
the way isocitrate dehydrogenase is inactivated by phosphorylation (Dean and
Koshland, 1990), is a possibility. It could function in conjunction with substrate
availability to regulate the ETS. However, regulation by substrate availability is
the most obvious potential mechanism and should be investigated first. In any of
these three cases, indirect evidence for regulation by a change in enzyme activity
would consist of the absence of parallelism between J4ETS ar| d #02 throughout
different growth phases of a bacterial culture. Stronger evidence for this group of
mechanisms would be a prediction of variations in R^ from modeled or
measured variations in ETS substrates, pH, ionic strength and enzyme modulators (ATP and ADP) throughout different growth stages of a bacterial culture.
In this paper, we will investigate by direct observation the role that concentration
changes in the ETS (i.e. A^^) have on R^. In addition, and more importantly,
we will investigate the effect that ETS-substrate availability has on R^ by modeling VETS-
The laboratory experiments here show time profiles of ^02 anc* ^ETS throughout the exponential, steady-state and senescent phases of cultures of the marine
bacterium Pseudomonas nautica. They will demonstrate the difference in the
relationships between the /4ETS and R^ in the exponential and senescent phases
of the bacterial culture, and suggest that respiratory control is achieved through
changes in the VETS rather than through changes in -AETS- Th e model presented in
this paper is a heuristic investigation of substrate control. This model is based (i)
on the concept that the concentration of the ETS substrates (NADH and
NADPH) can be calculated from the carbon source in the culture medium and the
biomass of the population, and (ii) on the assumption of bisubstrate kinetic
control of the in vivo ETS activity in the bacterial population. The model is evaluated qualitatively by comparing the model-calculated respiration (VETS) time
profile with the measured R^ time profile [sensu Warburg (1930) and Varma and
Palsson (1994)]; it is evaluated quantitatively by least squares regression analysis
on the modeled and measured time profiles.
1821
T.T.Packard el al
Method
Experimental design
In order to demonstrate the degree of association between >1ETS a n d ^02 ' n different stages of bacterial growth, time-profile experiments (1 or 14 days) were run
on batch cultures that were maintained on pyruvate at 22°C. In the 1 day experiments, samples were taken every 2 h for pyruvate, protein, A^^ and R^, while the
cultures passed through exponential growth, steady state and senescence. Pyruvate exhaustion occurred between 13 and 18 h (Figure 1). The 1 day time profiles
of experiments A and B are presented in Figure 1A and B. The 14 day experiment
(C) is presented in Figure 2. These three experiments are the culmination of many
preliminary experiments that were focused on one variable or another to solve
methodological problems.
Bacterial cultures
Pseudomonas nautica (strain 617), an oil-degrading bacterium isolated from the
sediments of the Gulf of Fos, France (Bonin, 1986; Bonin et al., 1987), was cultivated aerobically at 22°C in a phosphate-buffered medium (0.33 mM,pH 7.5) containing 400 mM NaCl, 10 mM MgSO4-7H2O,10 mM CaCl2-2H2O,10 mM KC1,25
mM NH4CI, 0.01 mM FeSO4-7H2O and 20 mM pyruvate. The original culture was
kindly given to us by Dr P.Bonin of the University of Aix-Marseille. Growth was
monitored from absorbance at 550 nm (OD 550). OD 550 and protein (A/) were
related by the regression equation M = 221.8 (OD 550) - 19.9 (n = 21). This
relationship held for all culture phases with an r2 of 0.987 (P < 0.001).
Respiration measurements
In this paper, our experimentally determined Rc^ refers to O2 consumed by the
P.nautica culture. The units of RQJ are umol O 2 min"1 I"1. A respirometer (MicroOxymax, Columbus Instruments International Corporation, OH) was used tc
make these measurements. The apparatus was a closed-system respirometer that
monitored changes in CO 2 and O 2 in the head space of the respirometer chamber.
The O 2 detector was a Pb-O 2 fuel cell (Hobbs et al., 1991). The instrument featured a multiple sample intake manifold (for up to 20 channels), a reference
chamber and software to control the system. Varma and Palsson (1994) used this
type of instrument in their study of R^ time profiles in Escherichia coli, and
Berdalet et al. (1995) used it in a study of isocitrate dehydrogenase and CO 2
production in the marine bacterium Vibrio natriegens. During the R^ measurements, the cultures were continuously shaken to optimize gas exchange. Oxygen
levels in the head space were monitored by the Micro-oxymax and held above
19.3% by periodic replenishment with air. The oxygen detector was calibrated
with high-precision gas standards. Each R^ measurement represents the mean of
duplicate analyses. The range of the duplicates was 10.0% of the mean (SD 9.4%,
n = 20).
1822
Respiration and ETS activity in P. nautlca
350
A
40
pfOteln____--©
^30
r
300
e-1—
9>
250
/
s
f\
in vitro ETS
200 |
fc
c5
3.
&
|
o UJ 20<
§
y§»
1
1°
»^_^^ respiration
*S>\ pyruvate
, >9
r-—
10
15
20
TIME (hours)
.
100
50
rO .
25
30
350
300
Bui)
200
J
z ;5 <
150 uj
100
L
temli
250 L
8
0.
g
3
g
- 50
10
15
TIME (hours)
20
25
30
Fig. L Replicate 1-day time-course experiments (A and B) showing observations of >4ETS. " O , protein
and pyruvate. The analytical errors are given in Method.
50
100
150
200
250
300
TIME (hours)
Fig. 2. Fourteen day time-course observations of /IETS. ^c>2> protein and pyruvate (experiment C).
1823
T.T.Packard et al
Biochemical sampling
Five to 10 ml samples from the bacterial cultures were centrifuged for 15 min at
10 000 g at 4°C. A sample of the supernatant fluid was immediately transferred to
an acid-rinsed cryovial and stored in liquid nitrogen for pyruvate analysis. Pellets
of concentrated bacteria were resuspended in 2 ml of the extraction buffer for
ETS analyses, and in 2-4 ml 1 N NaOH (at 20°C) for protein analyses. All samples
were stored in liquid nitrogen according to Ahmed et al. (1976).
Pyruvate measurements
Pymvate was extracted from the supernatent fluid and measured in its acid form
at 210 nm by HPLC as described by Berdalet et al. (1995). Sodium pyruvate (99%
pure, Sigma Chemical Company) served as a standard. Measurements were made
in duplicate. Their range around the average of these duplicates decreased from
14% at 1 mmol pyruvate I"1 of culture to 2% at 20 mmol"1. The mean of these
ranges averaged 4.1%.
In vitro ETS activity (Af^g) measurements
A ETS w a s measured with a modification of the method described by Packard and
Williams (1981). The changes consisted of reducing the reagent volumes to 0.2 of
the volumes described in their protocol and following continuously the absorbance increase of the formazan at 490 nm. The latter change enabled the reaction
to be monitored continuously in less time, and facilitated determination of the
initial velocity of the reaction. This kinetic assay saved time and generated higher
quality data. It should be noted here that this ETS assay, when performed on
P.nautica, measures the oxidation of NADH and NADPH, and not the oxidation
of succinate (Savenkoff et al., 1995b). The ETS assay was performed in cuvettes
(1 cm path length, 1 ml capacity) at 22°C. The frozen samples at (-196°C) were
thawed and kept on ice (0-4°C). Blanks were run without the ETS substrates.
Readings at 490 nm were corrected for turbidity at 750 nm. The regression line
of absorption versus time was used in the calculation of A^ys- Results are
reported as (xmol O2 min"1 I"1 of culture. A^JS in u.mol e~ min"1 I"1 can be
obtained by multiplying by four. To be consistent with Lehninger et at (1993), we
use the term transfer, rather than transport, when discussing the ETS in this
paper.
Protein measurements
Protein in the bacterial pellet was analyzed by the Lowry method (Lowry et al.,
1951) and reported as milligrams of protein per liter of culture. Bovine serum
albumin (BSA) was used as a standard. Each data point represents the mean of
quadruplicate analyses. The average standard deviation for experiments A and B
(expressed as a percent of the mean of the four replicates) was 6.5 ± 3.8 (n - 21).
This variability decreased from 8.4% at 50 mg protein I"1 to 3.4% at 300 mg I"1.
1824
Respiration and ETS activity in P. nautica
Modeling computation
Modeling was done on a Macintosh HSi computer using the software Data
Desk®, version 4.2 from Data Description Inc., Ithaca, New York. Using this software, one has the capability of: (i) entering a function with the parameters set as
adjustable sliders; (ii) comparing the output of the function with experimental
observations; (iii) viewing simultaneously the regression of the output on the
observations; (iv) viewing simultaneously the statistics of the regression analysis
(r2, regression equation, degrees of freedom, etc.) and, most importantly, adjusting the value of the parameters while viewing all of the above on the computer
screen. Parameter sliders are adjusted by mouse manipulation. With this capability, one can manually and rapidly experiment with different parameter values
in each equation of the model. This procedure is referred to as optimization in this
paper. It is analogous to adjusting a potentiometer on an oscilloscope tofita wave
function to experimental observations. This approach was necessitated by the
scarcity of kinetic data on the ETS in marine bacteria.
The merit of the algorithms of NADH and NADPH was judged on their ability
to generate declining time profiles of NADH and NADPH within the boundary
conditions of 1-60 uM (White et al, 1964; Lehninger, 1970). The merit of the
algorithm for V^^ was judged on its ability to predict the form and the magnitude
of /?Q2 l^me profiles in the experiments. Quantitatively, the evaluation was based
on least squares regression analysis of R^ measurements and R^ predictions
throughout the different growth phases of cultures A and B.
Results
Time profiles of A ^j^, protein and pyruvate in P.nautica batch cultures
The experimental results describe the time-profile observations of the bacterial
cultures during experiments A, B and C (Figures 1 and 2). The pyruvate in the
culture media in the three experiments decreased from an initial level of 20 mmol
I"1 to nearly zero within 24 h. Protein increased as a mirror image of the pyruvate
decline (Figure 1). Pyruvate was converted to cellular protein in a ratio of 15.40
mg protein mmol-1 pyruvate (Table I).
The Rty time profiles did not follow the same pattern over the lifespan of the
cultures (Table I, Figures 1 and 2) as did the time profiles offers and protein.
During the exponential growth phase, /IETS a °d ^02 were in parallel and highly
Table L /^OZ-^ETS, flo:-Prote'n and /lETS-Pr°tem relationships by linear regression analysis on the
exponential phase data from experiments A and B. The protein-pyruvate regression analysis was run
on the data from all three growth phases of experiments A and B. The data are shown in Figure 1. The
slope of the regression equation (m) and its intercept (b) are given with their standard errors. All
relationships are significant at P < 0.001
Function
Ko7 = MITTS)
floj = f(protein)
AETS = f(protein)
Protein = f(pyruvate)
m
b
n
r2
0.24 ±0.01
1.61 ±0.75
11
0.988
0.20 ±0.01
0.84 ±0.02
-15.40 ±0.79
-036 ±0.57
-7.73 ±2.18
315.8 ±9.60
11
11
21
0.994
0.995
0.958
1825
T.T.PKkard el al
correlated (Table I), but in senescence during pyruvate limitation, A^^ and R^
diverged from their parallel course. This divergence is clearly seen in the later half
of experiments A and B (Figure 1). It is also apparent in experiment C, where even
after 15 days of nutrient depletion /^ETS maintained at least 50% of its maximum
activity, whereas RQ^ had fallen to <5% of its maximum value (Figure 2).
The respiration model
The experimental results indicate that regulation of R^ by changes in the enzyme
concentration does not explain the data from experiments A, B and C. If changing ETS concentrations were an important regulatory mechanism for R^ in
P.nautica, then /Igrs would decline along with R^ in senescence. In our experiments, -AETS did not decline as R^ did (Figures 1 and 2), suggesting that respiration was being regulated through changes in the in vivo ETS activity (VETS). If
these changes were caused by a decline in the intracellular NADH and NADPH
pools as the extracellular pyruvate declined, then the degree to which the
enzymatic potential 04ETS) was expressed would have been lower in senescence
than during growth. In other words, the ratio of VETS» o r 'ts physiological expression, Rty, to /4ETS would be lower in senescence than in exponential growth.
("O2'-^ETs)$eDescence < ("O/-"ETs)exponential growth
Indeed, in our experiments, 7?O2//1ETS was 0.004 during senescence, while during
exponential growth it was 0.25 (Table I). Thus, the observations support this
hypothesis. Stronger support would consist of measurements of the declining
intracellular pools of NADH and NADPH during nutrient depletion. Since this
model was developed after the experiments were run, and since intracellular
NADH and NADPH were not measured, we will model them from the data available. With the modeled substrates we will demonstrate, by a respiration model,
how one can use the hypothesis of substrate limitation of /4ETS t o predict the R^
time profiles in experiments A and B.
Initially, the mathematical model of R^ uses a bisubstrate enzyme kinetics
equation and measurements of /4ETS> protein, and pyruvate from experiment A.
Later it will be applied to experiment B. In this model, the R^ of the bacterial
culture is represented by VQJ with units of umol O 2 min"1 H. For the case where
^02 = ^ETS. a r | d ^ETS is t r i e substrate-limited expression of A^s (i.e. ABTS limited
by declining intracellular levels of NADH and NADPH), one can develop a predictive algorithm for V ^ by applying enzyme kinetics to calculate V^s from
Agjs. If all the internal complexities of the respiratory ETS are ignored and if succinate can be neglected as an ETS substrate, as Savenkoff el al. (1995b) have
shown, then for the heuristic exercise here, the ETS can be considered as a single
enzyme that catalyzes the reaction:
NADH + NADPH + O2 + 2H+ -» NAD+ + NADP+ + 2H2O
In this case, the tools of multisubstrate kinetics (Qeland, 1967; Mahler and Cordes,
1826
Respiration and ETS activity in P. nautica
1971; Ricard, 1973; Kuby, 1991), rather than single-substrate kinetics (Michaelis
and Menten, 1913; Lehninger et ai, 1993), are more appropriate to calculate VETS
from AEJS. However, in this work, where O2 and H+ are not limiting throughout
the experiment, one can simplify the kinetics to the bisubstrate case. They cannot
be simplified further to the single-substrate situation until it is demonstrated that
a single substrate limits the ETS throughout the experiment. The rationale for
using bisubstrate kinetics in cases like this one is discussed in Cleland (1967) and
paper cited therein. The mathematics and the methodology for experimentally
determining the kinetic constants for bisubstrate kinetics are discussed by Mahler
and Cordes (1971), Engasser and Hisland (1979) and Kuby (1991). This rationale
argues that VETS = f^ers. [NADH], [NADPH]). Accordingly, we propose to
apply the following bisubstrate kinetics expression to calculate VETS from >4ETS:
VETS = ^ETS[NADH][NADPH]/(A:p
where Kp = (KNADH)(KJ
+ [NADH][NADPH])
(1)
+ (ATNADPH)[NADH] + (KNADH)[NADPH]
Here, K^ADH and XNADPH a r e bisubstrate Michaelis constants for NADH and
NADPH. Kia is the dissociation constant for the enzyme-NADPH complex, and
[NADH] and [NADPH] are the intracellular ETS substrate concentrations
(Savenkoff et ai, 1995b). Since our purpose is to simulate the observed Z?^ time
profiles, as shown in Figure 1, the enzyme activities in this paper ( VETS, ^ETS) a r e
normalized by culture volume, not by protein. Note that although >1ETS m equation (1) is analogous to V ^ , indeed it equals M X Vm^, it is not a constant as is
Vmax. Such usage does not invalidate equation (1). Furthermore, our use of A^rs
and Rty, by themselves, minimizes experimental errors by confining the analysis
to single measured variables rather than compound ones such as A^j^M and
R(yJM (see Packard and Boardman, 1988).
From our conceptual model that VETS can be calculated from equation (1) and
that V02 = VETS. a model of O2 consumption can be constructed. To do this from
the experimental data in Figure 1A, one has to express intracellular NADH and
NADPH as functions of the pyruvate levels in the culture media (P) and the bacterial protein of the culture (A/), i.e. NADH = f(P,M) and NADPH = t(P,M)Accordingly:
NADPH = kP + -nM
(2)
NADH = 8P + (oA/
(3)
and
The values of P and M in these expressions represent the mean levels of pyruvate
and protein in the culture during the previous intersampling period. They were
calculated by interpolation between the sample measurements (Figure 1). The
first term in these equations is based on the assumption that the intracellular
levels of NADH and NADPH will be proportional to the external substrate levels
until the external substrate falls to some low value. The second term puts a minimum value on these intracellular pyridine nucleotides even during carbon-source
1827
T.T.Packard el al
starvation. It does this by making them proportional to the bacterial biomass (M).
The parameters in equations (2) and (3), expressed in the units of the protein and
pyruvate measurements, are given in Table II. These parameters were originally
set to constrain the NADH and NADPH between boundary conditions of 1-60
uM,a biologically reasonable range (White et al., 1964; Lehninger, 1970; Walsh and
Koshland, 1984; Lehninger et al., 1993). They were then adjusted so that the
NADH and NADPH time profiles resembled the pyruvate time profile, and the
VETS time profile resembled the R^ time profile for experiment A (Figure 1). The
substrate levels were constrained from falling below 1 uM by adjusting T| and w.
The time profiles generated by equations (2) and (3) for experiments A and B are
shown in Figure 3. The substrates decrease from -50 uM NADH and -18 uM
NADPH at the beginning of the experiments to -18 uM NADH and -1 uM
NADPH at the end of the experiments. The relatively greater abundance of
NADH to NADPH (Figure 3) is consistent with observations in other organisms
(White et al., 1964; Lehninger, 1970), but direct measurements have not been made
in P.nautica.
For simulating the R^ time profiles (Figures 4 and 5), kinetic parameters that
ranged between 7 and 14 uM for Kia, 26 and 45 uM for KNADH, and 9 and 15 uM
for .KNADPH yielded the best correlations with the measured values of R^. The
values of these parameters that were used to produce the time profiles shown in
Figures 4 and 5 are given in Table II.
Predicting respiration
From the A^TS, pyruvate and protein measurements (Figure 1), and from equations
(l)-(3), a prediction of VETS can be made for each sampling period. The lower part
of Figure 4 shows the time profile of the predicted V^s for experiment A. VETS
ranges from 1.8 umol mur 1 I"1 at the beginning to a maximum of 28.4 umol min~'
I"1 at 11.4 h; by the end of the experiment, VETS has fallen to 4.7 umol min"11"1. From
the lower part of Figure 4, one can see that throughout the exponential, steady-state
and senescent phases of the bacterial culture, the VETS t i m e profile resembles the
/?O2 tmie profile much better than does the AETS time profile (Figure 4, upper). The
regression equation for RQ^ versus VETS is RQ^ = I.OOVETS + 0.478 (r2 = 0.961). For
Table H. Kinetic parameters that were used to calculate the in vivo ETS activity (VETS) fr°m equation (1), and the intracellular NADH and NADPH concentrations from equations (2) and (3)
Parameter
Experiment A
For equation (1)
Ka
13.5 (iM
KNADPH
For equations (2) and (3)
X
8.82 x
Tl
5.90 x
8
2.60 x
(i)
5.20 x
1828
10- 4 u.mol
10"7 pjnol
10"3 jimol
10~5 pjnol
Experiment B
6.7 »iM
14.5 |iM
9.0 uM
45.0 |iM
26.0 jiM
N A D P H mrnol-' pyruvate
N A D P H mgr 1 protein
N A D H mrnoh 1 pyruvate
N A D H mgr 1 protein
Same
Same
Same
Same
Respiration and ETS actiriry in P. nautica
10
15
TIME (hours)
20
25
30
60
20
50
15
401
10
30
NADH
20
NADPH \ _ _
B
10
1
i
15
TIME (hours)
20
25
30
10
Fig. 3. Simulated intracellular NADH and NADPH for experiments A and B. These time profiles were
calculated from equations (2) and (3), and the protein and pynivate measurements shown in Figure 1.
#02 versus /IETS. it is ^02 = 0.05.4ETS + 7-57 (r2 = 0.167). These results illustrate the
improvement that calculations of VETS bring to the prediction of RO2 in experiment A. The standard error for the RO^-VETS r a t i ° (100) is ±8%.
For experiment B, a prediction of V^^ using the same equations and kinetic
constants as were used for experiment A underestimates R^, but gives a similar
time profile. Regression analysis yields the equation R^ - 2.11VETS + 3.23 (r2 =
0.820). Given the dependence of VETS o n t n e protein-pyruvate relationship
[equations (l)-{3)], the difference in the initial pynivate concentration in the two
experiments (Figure 1) and their different protein-pyruvate ratios are the likely
causes of the underestimate of R^ in this experiment. In experiment A, the initial
pynivate concentration was 20 mM (Figure 1) and the protein-pyruvate ratio was
15.2 ± 0.9. In experiment B, the initial (measured) pynivate concentration was 18
mM (Figure 1) and the protein-pyruvate ratio was 16.7 ± 0.3. However, if the
kinetic constants are adjusted to 6.6 uM for K^, 26 uM for ANADPH a n d 9 uM for
(Table II), VETS closely estimates RQ^, quantitatively and qualitatively
1829
T.T.Packard el al
250
40h
in vitro ETS
L
200 r
J15O|
- 100 W
I501
10
15
TIME (hours)
20
25
—'o
30
40 In vivo ETS
30
20
10
10
15
TIME (hours)
20
30
Fig. 4. Experimental observations and modeling results from experiment A. Upper panel: the coupling
of i4ETS and R^ in the exponential phase of growth, and the absence of coupling in the senescent
phase. Lower panel: The coupling of V^j^, [as modeled from equations (1) (3)] and RQ^ in both exponential growth and senescence.
(Figure 5, lower). Regression analysis yields the equation R^ = LOOK^rs - 1.16
(r2 = 0.921). The standard error for the ^?O2~^ETS r a t io in this case is ±10%.
Discussion
ETS activity
The behavior of A^j^ in P.nautica throughout different bacterial growth phases
was unknown prior to this investigation. Would starvation cause the culture to
decrease the concentration of the ETS, would ETS be inactivated and kept in
reserve, or would it be kept active but substrate limited? The data from this study
answer the first question. In vitro ETS activity (AEJS), a measure of the concentration of the ETS, was maintained at a high level for at least 6 days after nutrient
exhaustion (Figure 2). During this period, the respiration rate fell to 4% of its
peak value even though the cell biomass (protein) remained near its peak value
1830
Respiration and ETS activity in P. nautlca
250
50r
10
15
20
TIME (hours)
25
30
150
40^
20
10
10
15
20
TIME (hours)
25
30
Fig. 5. ExperimentaJ observations and modeling results from experiment B. Upper panel: The coupling
of /Igrs and R^ in the exponential phase of growth, and the absence of coupling in the senescent
phase. Lower panel The coupling of Vg^j [as modeled from equations (l)-(3)] and Rol in both exponential growth and senescence.
over the same period (Figure 2). Thus, P.nautica conserves cellular resources
(respiratory capacity, structural proteins, enzymes, etc.) during nutrient starvation
by reducing R^. Such a characteristic would benefit marine microbes, especially
deep-sea bacteria (Morita et ai, 1972; Morita, 1980,1985;Tabor et al., 1981a,b). The
deep sea is characterized by low, but highly variable availability of organic nutrients. So, in that environment, the ability to reduce R^ while maintaining a reserve
of substrate-limited enzymes would be advantageous. Although P.nautica was isolated from shallow sediments in the Mediterranean Sea, it nevertheless displays
these characteristics (Figures 1 and 2).
Respiration simulation
The reactions responsible for cellular respiratory metabolism are well identified
in E.coli (Poole and Ingledew, 1987) and in other well-studied organisms
1831
T.T.Pactard el at
(Lehninger et al., 1993), but the control and the kinetics of these reactions are not
well enough understood to allow quantitative reconstruction of the physiological
respiration rate. There are no accounts in the literature where R^of whole cells
or cultures is calculated from biochemical principles and measurements of
enzyme activities, substrate concentrations and biomass levels. This paper is an
attempt to do this through modeling. By using equations (l)-(3), the A^^, pyruvate and protein data from experiments A and B, and reasonable kinetic constants, we were able to predict the time course of R^ in a bacterial culture. Our
objective was heuristic, we wanted to demonstrate the potential of using calculated in vivo ETS activity (VETS) rather than measured in vitro ETS activity
e
(^ETS)I by itself, in estimating i?or Th degree of success in using VETS is evident
2
from the high r values when VETS is compared to the measured R^ (Figures 4
and 5, lower panels). It is clear that the kinetic constants used in experiment A did
not predict R^ in experiment B with equal success. The r2 was only 0.82. However,
we suspect that the cause of this problem was associated with the low levels of
pymvate measured in the earlier stages of experiment B. The culture was started
on 20 mM pyruvate, as observed in experiment A. Yet, in experiment B only 18
raM pyruvate was measured. Such a difference affects the modeled time functions
of the pyridine nucleotides. In spite of this, a comparison of the upper and lower
parts of Figures 4 and 5 demonstrates that a calculation of VETS from bisubstrate
enzyme kinetics has more potential for predicting R^ than does a measurement
of AETS alone. That was one of the objectives of this paper.
Challenges for this hypothesis
First, we have presented substrate limitation of VETS as a hypothesis to explain the
fall in Rfy during starvation. This hypothesis is supported (i) by the maintenance
of high levels of A^^ during starvation (Figures 1 and 2) and (ii) by the successful
prediction of R^ from calculations of VETS from bisubstrate kinetics (lower parts
of Figures 4 and 5). As with any hypothesis, this one should be challenged. It could
be disproved if the intracellular levels of NADH and NADPH in the bacteria
remain constant or increase as the culture passes into starvation. Measured time
profiles resembling Figure 3 would be supportive. If one substrate time course were
found to be constant, equation (1) would be reduced to simple Michaelis-Menten
kinetics The hypothesis would still be sound, but simpler to apply.
Second, since this hypothesis is based on the assumption that the kinetic constants remain invariant through the lifetime of the bacterial culture, measurements demonstrating their variability, although not proof of fallacy, would require
additional expressions of K^, ATNADH and KNADPH as functions of time. Demonstrating this variability would retard applications of this approach.
Thirdly, since the constructions of equations (2) and (3) were intuited from an
understanding of metabolic biochemistry, a demonstration that internal substrate
concentration is not dependent on available carbon sources and biomass would
invalidate the use of these two equations. However, the basic hypothesis of
internal substrate limitation would still remain standing. A demonstration that
internal substrate concentration is dependent on available carbon sources and
1832
Respiration and ETS activity in P. nautica
biomass would strengthen the foundation of equations (2) and (3). Furthermore,
such a positive demonstration would suggest a field test of this hypothesis based
on dissolved organic carbon measurements and microbial biomass measurements.
Impact onfieldstudies
The shift from strong coupling between R^ and .AETS m t n e exponential phase to
weak coupling in senescence, as shown in the upper parts of Figures 4 and 5,
resulted in a decrease in the i ? ^ to A^JS ratio from 0.24 (Table I) to 0.004. In the
exponential phase, this ratio indicated that the bacteria were functioning at 1/4
their respiratory capacity or that 75% of their capacity was available to respond
to some cellular demand. In senescence, only 1/250 of their respiratory capacity
was being used. The implication of this variability in the R^ to /4ETS ratio indicates that an understanding of the nutritional state of the microbial population is
important to the interpretation of ETS measurements in the ocean.
ETS activity is also used to assess nitrate reduction and denitrification in the
anoxic or oxygen-deficient oceanic water column (i.e. Naqvi and Shailaja, 1993).
It is used to assess fish, zooplankton and phytoplankton respiration (Packard,
1979; Setchell and Packard, 1979; Ikeda, 1996; Savenkoff et al., 1996). This work
does not address these problems, but the conceptual ideas expressed here could
be suitably applied to them.
For the present, the best way to interpret ETS measurements made on samples
from the oxic water column is exemplified by the work of del Giorgio (1992),
Arfstegui and Montero (1995) and Savenkoff et al. (1995a). However, if the
hypotheses presented here could be supported by direct measurements of NADH
and NADPH depletion in senescent bacteria and other types of marine organisms,
and if calculations of in vivo ETS served to predict R^ in cultures of different bacteria and other organisms, then the next step would be to explore the estimation
of Rty from measurements of NADH and NADPH and ETS in the plankton. To
be more direct, these results suggest that plankton respiration in the field could
be assessed more accurately than before by measuring the ETS substrates
(NADH and NADPH), in addition to ETS activity, in plankton samples.
Summary
Our modeling results demonstrate the feasibility of using a single algorithm and
standard biochemical measurements of enzyme activity, protein and substrate
concentration to reconstruct the time profile of respiration throughout all phases
of a bacterial culture. They also serve as an example of a novel application of
bisubstrate enzyme kinetics to the general problem of rate prediction in marine
organisms. Our experimental results demonstrate a strong correlation between in
vitro ETS activity and respiration in bacteria growing exponentially, but a weak
correlation in their senescence. Our experimental results also present unique data
on the respiration and ETS activity in a relatively newly described oil-degrading
bacterium, P.nautica. The respiration data themselves, are examples of the utility
of a new respirometer that has recently been used in the marine microbiological
study by Berdalet et al. (1995).
1833
T.T.Packard el al.
Acknowledgements
We thank the Spanish Ministry of Science for granting the post-doctoral fellowship to E.Berdalet, A.V6zina for his helpful discussions and constructive criticism
of the manuscript, J.Piuze, B.Sundby and J.C.Therriault for their support and
encouragement, L.Devine-Castonguay for the figures and proofing, J.Cullen for
introducing TTP to Data Desk®, and L.Codispoti, CSavenkoff, R.L.Smith and
T.Yoshinari for careful reviews of the manuscript.
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Received on January 17,1996; accepted on May 2,1996
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