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EMBO reports 5, 1, 66–70 (2004)
doi:10.1038/sj.embor.7400049
Published online: 12 December 2003
Adaptation to extreme environments: macromolecular dynamics in bacteria compared in vivo by neutron scattering
Moeava Tehei1, Bruno Franzetti1, Dominique Madern1, Margaret Ginzburg2, Ben Z Ginzburg2, Marie-Thérèse Giudici-Orticoni3, Mireille Bruschi3 & Giuseppe Zaccai1, 4
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1 Institut de Biologie Structurale,
CEA-CNRS-UJF, IBS, 41 rue Jules Horowitz, 38027 Grenoble
Cedex 1, France
2 Institute of Life Sciences, Hebrew
University, Jerusalem 24410, Israel
3 Bioénergétique et Ingéniene
des Protéines, CNRS, 31 Chemin Joseph Aiguier,
13402 Marseille Cedex 20, France
4 Institut Laue Langevin, B.P. 156X, 38042 Grenoble
Cedex 9, France
To whom correspondence should be addressed
Giuseppe Zaccai Tel: +33 4 38 78 95 73; Fax: +33 4 38 78 54 94;
E-mail: zaccai@ibs.fr
Received 11 June 2003; Accepted 13 October 2003; Published online 12 December 2003.
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Abstract
Mean macromolecular dynamics was quantified in vivo by neutron
scattering in psychrophile, mesophile, thermophile and hyperthermophile
bacteria. Root mean square atomic fluctuation amplitudes determining
macromolecular flexibility were found to be similar for each organism at its
physiological temperature ( 1 Å in the 0.1 ns timescale). Effective
force constants determining the mean macromolecular resilience were found to
increase with physiological temperature from 0.2 N/m for the psychrophiles,
which grow at 4°C, to 0.6 N/m for the hyperthermophiles (85°C),
indicating that the increase in stabilization free energy is dominated by
enthalpic rather than entropic terms. Larger resilience allows macromolecular
stability at high temperatures, while maintaining flexibility within acceptable
limits for biological activity.
EMBO reports 5, 1, 66–70 (2004)
doi:10.1038/sj.embor.7400049
Published online: 12 December 2003
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Introduction
Microbial life has adapted to temperatures below 0°C in glacial
waters to above 100°C and pressures of hundreds of atmospheres in deep
ocean hot springs (Price, 2000). What are the
mechanisms that allow proteins and nucleic acids to be stable and active under
extreme conditions? A comparison of three-dimensional structures revealed no
major differences in the folds of homologous psychrophilic, mesophilic,
thermophilic and hyperthermophilic proteins (e.g. Aghajari
et al, 1998; Auerbach et al,
1998; Bell et al, 2002). A
consensus has arisen that thermal adaptation is associated with amino-acid
substitutions modifying the balance of stabilization forces, and the concept of
resilience as a key factor in thermostability has been introduced by
Aguilar et al (1997). A hypothesis has been
formulated that thermoadaptation is associated with protein dynamics (e.g.
Zavodszky et al, 1998), in the sense that
the higher thermal stability of the thermophile proteins would arise from
increased rigidity and lower flexibility (Jaenicke,
2000), while increased flexibility in psychrophile protein molecules
would allow activity at low temperature (Lonhienne et
al, 2000; Petrescu et al,
2000; Russell, 2000; Arnold et al, 2001). A number of considerations come
in the way of fully testing by experiment the link between thermal adaptation
and macromolecular dynamics, mainly because there exists a spectrum of adaptive
strategies (Jaenicke, 2000), and because in
vitro protein dynamics strongly depends on solvent conditions (Tehei
et al, 2001). It is of particular interest, therefore, to
develop methods to characterize the mean thermal motions of the entire
macromolecular population in a cell, and we propose here a novel neutron
scattering approach. The forces (salt bridges, hydrogen bonds, hydration, van
der Waals, hydrophobic interactions) that maintain active structures and govern
atomic motions in macromolecules are 'weak' forces because their
associated energies are close to thermal energy. Fast atomic thermal motions on
the picosecond to nanosecond timescale act as a 'lubricant' for
larger conformational changes, such as those associated with enzyme or ion pump
activity, for example, occurring on slower, millisecond, timescales (Brooks et al, 1988; Lehnert et
al, 1998). Atomic motions are characterized by amplitudes (how
far does an atom move?) and frequencies (how often does it move?). Neutron
spectroscopy provides a unique tool to study atomic thermal motions in
macromolecules, because neutron wavelengths and energies, respectively, match
motion amplitudes and frequencies (Brooks et al,
1988; Smith, 1991; Gabel et al, 2002). Measured variables are the mean
square amplitudes in a given timescale, as a function of temperature, from
which an effective mean force constant, determining macromolecular resilience,
can be calculated (Zaccai, 2000). We applied the
method to compare the mean dynamics of macromolecules, in vivo, in
psychrophile, mesophile, thermophile and hyperthermophile bacteria.
Results and Discussion
Macromolecular flexibility and resilience in cells
Neutron scattering experiments were performed on washed pellet
samples of whole live cells of the psychrophile Aquaspirillum arcticum,
the mesophiles Escherichia coli and Proteus mirabilis, the
thermophile Thermus thermophilus and the hyperthermophile Aquifex
pyrofilus. Cells were harvested in the late mid-log phase, just before the
neutron experiments. The spectrometer was designed to examine a
space–time window of a few Ångstroms in 0.1 ns. At a given
temperature, the incoherent scattering from individual atoms moving inside this
window was observed and analysed to yield a value for their mean square
fluctuation amplitude. Previous neutron experiments on protein dynamics have
essentially been performed in D2O, which scatters neutrons much more
weakly than H2O, to avoid contamination by water scattering
(Doster et al, 1989; Fitter & Heberle, 2000; Zaccai et
al, 2000). We avoided the use of D2O, because it is
known to have an influence on protein stability and dynamics (Bonneté et al, 1994; Tehei
et al, 2001). It was possible to collect data in light water
solutions with negligible scattering from the water component, because the
space–time window essentially selected motions of atoms that are anchored
to macromolecules (proteins, nucleic acids and their complexes), and was not
sensitive to cytoplasmic bulk water (Trantham et al,
1984), small peptides or the smaller membrane components, for
example, which diffuse out of the window during the timescale of the
experiment. Strongly bound water will contribute as an internal part of the
macromolecules (Bon et al, 1999). The
overall macromolecular composition of the bacterial cells examined is not
expected to vary significantly from one cell type to another. Macromolecules
constitute 96% of the total dry weight of an E. coli cell. DNA
represents 3%, and lipids and polysaccharides about 17%; the
majority, more than 75% of the dry weight, consists of proteins and
ribosomes, themselves made up of about 50% protein and 50% RNA by
mass (Bicout & Field, 1996). Within a given
bacterium, differences in protein expression due to metabolic modifications in
unstressed cells affect a few hundred proteins out of about 5,000 (Rosen
& Ron, 2002). It is reasonable to assume, therefore, that the
neutron scattering data described in this paper are dominated by the dynamics
of the proteins, making up the cellular proteome, in association with their
natural environment.
The mean square fluctuation values
 u2 calculated as described in Methods were
plotted as a function of temperature, T (Figs 1,
2). The u2 values are
on an absolute scale and refer to thermal motions in the 0.1 ns time domain
defined by the energy resolution of the spectrometer. In order to validate the
comparison among different samples, intensity data were collected, normalized
and analysed in an identical manner. Effective mean force constants,
k', defining mean macromolecular resilience (Zaccai, 2000; Bicout & Zaccai,
2001), were calculated from u2
versus T, as described in Methods. A smaller slope corresponds to a
larger resilience and vice versa. The force constants, which are of the order
of 0.1 N/m, have also been related to measurements on single molecules by using
near-field microscopy or laser tweezers (Linke &
Granzier, 1998; Oesterhelt et al,
2000).
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Figure 1
Mean square amplitudes u2 were
plotted against temperature T for E. coli unstressed cells
(triangles), cells heated ('cooked') to 80°C (diamonds) and
cells that were heat shocked at 47°C (squares). The greater dispersion of
data points for the 'cooked' cells reflects larger errors due to
lower signal to noise. This is because there is less scattering material in the
instrumental space–time window under these conditions. Effective mean
force constants k', describing mean macromolecular
resilience, were calculated from the slopes of the straight-line fits as
described in Methods. They are 0.42 0.01, 0.080.03 and
0.300.01 N/m for the unstressed, 'cooked' and heat-shocked
cells, respectively.
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Figure 2
Mean square amplitudes u2 were
plotted against absolute temperature T for A. arcticum
(A), P. mirabilis (B), T. thermophilus (C)
and A. pyrofilus (D) samples. Effective mean force constants
k', describing mean macromolecular resilience, were
calculated from the slopes of the straight-line fits in the temperature region
where the bacteria proteins are stable, as described in Methods.
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Dynamic fluctuations and force constants
Different mean square amplitudes are expected for folded and
unfolded proteins (Receveur et al, 1997;
Bu et al, 2000, 2001). In order to check that measurements do in fact refer
to macromolecular dynamics in cells, we compared data from native samples and
from samples where various degrees of denaturation were expected. Experiments
were performed on three E. coli samples: freshly harvested live cells,
freshly harvested live cells heated at 80°C in the sample holder for 2 h
before data collection (the 'cooked' sample), and cells that had
been heat-shocked for 1.5 h at 47°C, then harvested and placed in the
sample holder for data collection (the 'stressed' sample). The
u2 values for the E. coli samples
plotted in Fig 1 increase linearly over the entire
temperature range. The significantly larger mean square amplitudes and lower
macromolecular resilience for the 'cooked' sample are indicative of
denatured protein systems, in agreement with previous neutron scattering
experiments on pure protein samples (the larger scatter of the data for the
denatured system reflects lower signal to noise due to very large fluctuation
amplitudes exiting in part from the measurement window). Interestingly, a small
difference also appeared for the heat-stressed sample. We concluded that the
method allows the measurement of values that are truly representative of the
folding status of macromolecules and therefore relevant to address the question
of thermoadaptation.
The u2 values for the unstressed
mesophile, thermophile and hyperthermophile cell samples increased linearly
with temperature, while the plot for A. arcticum showed a striking
transition above 20°C (Fig 2). We note that 17°C
is the maximum temperature at which A. arcticum can maintain net growth
(Butler et al, 1989). Following the
observations on denatured protein and 'stressed' and
'cooked' E. coli cells, it is reasonable to assume that the
transition from linear behaviour in the A. arcticum data reflects
macromolecular denaturation occurring during the time of data collection.
The same scan temperature range was examined for all the samples.
Lower temperatures were not measured because of ice formation and in order to
avoid the use of cryo-solvents. Due to technical limitations, it was not
possible to collect data at the physiological temperatures of the thermophiles
and hyperthermophiles. Based on the assumption supported by the mesophile and
psychrophile data that stable native systems show straight-line behaviour, the
amplitudes for the thermophiles and hyperthermophiles at their respective
physiological temperatures were calculated by extrapolation of the straight
lines fitted to the data. Similar values were found for the respective
 u2 values of the bacteria at their
physiological temperatures (Fig 3). Note that these
values are significantly smaller than the values associated with protein
denaturation seen in Figs 1, 2A.
Functional root mean square fluctuations, therefore, appear to be maintained
within narrow limits around 1.2 Å, independent of the adaptation
temperature (from 4 to 85°C) (Fig 3). This
experimental finding may be useful as a guide to force field calculations in
molecular dynamics simulations of proteins.
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Figure 3
Root mean square fluctuation
u2 values (flexibility) were
calculated at each adaptation temperature (from Figs 1,
2; by extrapolation for T. thermophilus and A.
pyrofilus) and plotted versus adaptation temperature T for the three
bacterial types: 4°C for A. arcticum (blank), 37°C for E.
coli (blank) and P. mirabilis (hatched), 75°C for T.
thermophilus (blank) and 85°C for A. pyrofilus (hatched). The
calculated uncertainty for the extrapolated values is 0.04 Å for
the thermophile and 0.01 Å for the hyperthermophile.
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Effective force constants (k') were
calculated from the temperature range where the macromolecules from the five
organisms remained native (Figs 1, 2). We named the k' value 'mean
resilience' in order to avoid 'rigidity', which has been used
broadly and in qualitative terms. The straight-line approximation for
u2 versus T was adequately supported
by the data with significantly different slopes for the different bacteria.
Using equation (2) (see Methods),
k' values of 0.210.03, 0.420.01,
0.390.01, 0.670.11 and 0.600.01 N/m were calculated for
A. arcticum, E. coli, P. mirabilis, T. thermophilus
and A. pyrofilus cells, respectively. For comparison, the resilience
values of hydrated myoglobin and myoglobon trapped in a hard trehalose glass
are 0.3 and 3 N/m, respectively (Zaccai et al,
2000). The correlation between mean resilience and physiological
growth temperature is shown in Fig 4. To the best of our
knowledge, the experiments described here provided the only quantification, so
far, of mean macromolecular resilience in a cellular environment.
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Figure 4
Mean macromolecular resilience k' for each
bacterial type, plotted versus adaptation temperature (histograms are as for
Fig 3).
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Protein and cellular adaptation
Our results suggested that macromolecular resilience is an important
parameter in adaptation to extreme temperatures in order to maintain functional
stability at physiological temperatures. The resilience values, which increased
with stabilization temperature, indicated the dominance of enthalpy terms in
the stabilization free energy differences. For proteins in which entropy terms
(such as the hydrophobic interaction) are dominant, a more flexible and less
resilient macromolecule will be more stable (Zidek et
al, 1999; Fitter & Heberle,
2000; Hernandez et al, 2000;
Arnold et al, 2001; Tehei
et al, 2001).
We note that the force constants analysed are mean values for all
the macromolecules in the cell. Can the molecular determinants associated to
these forces be identified by genomic or structural analysis?
Haney et al (1999) compared protein
sequences from mesophilic and extremely thermophilic Methanococcus
species. The observed replacements decrease the content of uncharged polar
residues, increase the content of charged residues, increase residue
hydrophobicity and increase residue volume in the extremely thermophilic
proteins. Cambillau & Claverie (2000) have
published a correlation between adaptation to high temperature and the average
charged minus polar amino-acid percentage (Ch-Pol) in mesophile and
hyperthermophile genomes. In general, an increase in the Ch-Pol percentage
would lead mainly to enthalpic (hydrogen bonds, hydration interactions, salt
bridges) contributions to the free energy landscape, as is reflected in our
data by the increase in k' values. A number of studies
have been published analysing structural differences among homologous
psychrophile, mesophile and thermophile proteins (Aghajari
et al, 1998; Bell et al,
2002; Gianese et al, 2002);
common trends include a decrease in the number of salt bridges and of
surface-exposed side chains in the psychrophiles as well as decreased
protein–protein and interdomain interactions within proteins. All these
effects would contribute to the decrease in resilience observed in the data
presented in this paper. Protein dynamics is strongly affected by solvent
effects (Tehei et al, 2001), however, and
adaptation of cytoplasm composition (e.g. through the presence of salt or
compatible solutes) may also contribute to the observed macromolecular
resilience differences.
Conclusion
The neutron experiments presented quantified the extent to which
macromolecular dynamics in bacterial cells is affected by adaptation to extreme
temperatures. The results support the hypothesis that a contribution to thermal
adaptation is through the evolutionary selection of appropriate resilience in
order to maintain macromolecular structure and flexibility within the narrow
limits required by biological activity.
Methods
Sample preparation. A. arcticum (ATCC 49402), E.
coli (MRE600), P. mirabilis and T. thermophilus (ATCC 579)
were grown aerobically in their respective complex media at 4, 37 and 75°C,
respectively, until the late mid-log phase. A. pyrofilus (DSM 6858) were
grown at 85°C in 2 l bottles under 1.4 bar of H2/CO2
in SME medium modified at pH 6.8. The cells were collected by centrifugation
and washed twice by suspending the pellets in a 50 mM Tris-HCl pH 8 buffer
containing 150 mM NaCl and 5 mM KCl. In all, 420 mg of the washed cell paste
was immediately sealed in the sample holder. Control experiments were carried
out in order to ensure that the cells were not damaged and were still viable
after about 20 h of total measuring time in the beam. To avoid cell damage, a
limited temperature range, 4–37°C (277–310 K), was examined in
the neutron scattering experiments.
Neutron scattering experiments. Experiments were performed on
the IN13 spectrometer at the Institut Laue Langevin (information on the
Institut Laue Langevin in Grenoble and its neutron spectrometers is available
at http://www.ill.fr). Aluminium sample holders had a 0.3 mm path
length. The samples showed a transmission of about 90% for the 2.23
Å neutron beam. Elastic incoherent scattering data were collected with an
energy resolution of 8  eV in a scattering vector range of 1.2
Å-1 Q2.2
Å-1, corresponding to a space–time measurement
'window' of a few Ångstroms in 0.1 ns. Intensity data were
corrected for sample holder and buffer scattering and normalized by vanadium
scattering to yield I (Q, elastic) as a function of
temperature for each sample, where elastic corresponds to zero energy
transfer. The scattering vector Q is given by
4 sin / , where 2 is the scattering
angle and is the incident neutron wavelength. For each sample
and temperature point, ln{I (Q, elastic)} was
plotted against Q2; the mean square fluctuation
u2 was calculated from the slope of the
straight-line fit to the experimental data according to the Gaussian
approximation (Zaccai, 2000):
The approximation is valid for Q values satisfying
Q2u2 2.
The mean square fluctuations were plotted as a function of absolute
temperature; effective force constants k' and their
errors were calculated from the slopes of the weighted straight-line fits
(using the Levenberg–Marquardt algorithm) to the data (Zaccai, 2000; Bicout & Zaccai,
2001) from
The numerical constants are to express k' in
N/m when u2 is in Ångstrom
squared and T is in Kelvin.
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Acknowledgements
M. T. was supported by a doctorate grant from the Région
Rhône-Alpes, France, and by the Istituto Nazionale Fisica della Materia,
Italy. The work was supported by the EC Improving Human Potential programme,
contract no. HPRI-CT-2001-50035, and the CNRS GEOMEX programme. We are happy to
acknowledge Marc Bee, Lawrence Cosenza, Lionel Costenaro, Christine Ebel, Frank
Gabel, Claude Pfister, Andrea Schmitt and Martin Weik for fruitful discussions,
advice with the experiments and critical readings of the manuscript, and Dr
Hélène Jouve for the P. mirabilis strain.
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