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Originally published In Press as doi:10.1074/jbc.C000497200 on August 11, 2000
J. Biol. Chem., Vol. 275, Issue 42, 32383-32386, October 20, 2000
ACCELERATED PUBLICATION
Structural and Genomic Correlates of Hyperthermostability*
Christian
Cambillau§ and
Jean-Michel
Claverie¶
From the § Architecture et Fonction des
Macromolécules Biologiques, CNRS UPR9039, and the
¶ Information Génétique et Structurale, CNRS UMR 1889, 31 chemin Joseph Aiguier, 13402 Marseille cedex 20, France
Received for publication, July 26, 2000, and in revised form, August 10, 2000
 |
ABSTRACT |
While most organisms grow at temperatures ranging
between 20 and 50 °C, many archaea and a few bacteria have been
found capable of withstanding temperatures close to 100 °C, or
beyond, such as Pyrococcus or Aquifex. Here we
report the results of two independent large scale unbiased approaches
to identify global protein properties correlating with an extreme
thermophile lifestyle. First, we performed a comparative proteome
analyses using 30 complete genome sequences from the three kingdoms. A
large difference between the proportions of charged versus
polar (noncharged) amino acids was found to be a signature of all
hyperthermophilic organisms. Second, we analyzed the water accessible
surfaces of 189 protein structures belonging to mesophiles or
hyperthermophiles. We found that the surfaces of hyperthermophilic
proteins exhibited the shift already observed at the genomic level,
i.e. a proportion of solvent accessible charged residues
strongly increased at the expense of polar residues. The biophysical
requirements for the presence of charged residues at the protein
surface, allowing protein stabilization through ion bonds, is therefore
clearly imprinted and detectable in all genome sequences available to date.
 |
INTRODUCTION |
The number of solved protein structures from hyperthermophiles is
increasing at a fast pace (Refs. 1-13 and references therein), due in
part to structural genomics approaches. Based on comparisons between
mesophiles and hyperthermophiles, two main factors have been suggested
as responsible for thermostability: (i) the presence of large networks
of ion pairs at the protein surface (1, 8-12), (ii) protein loop
shortening (7), and (iii) an increase of protein compactness (7, 12).
About a dozen additional determinants have also been mentioned, but do
not appear relevant to all the structures elucidated (3-6, 8, 13).
Recently, it as been proposed that adaptation to high temperature might
involve different mechanisms in moderate thermophiles versus
extreme thermophiles (12). This follows from a markedly different
temperature dependence of the hydrophobic interactions, optimal around
70 °C (14), compared with coulombic interactions, optimum at higher
temperatures, up to 100 °C (9). Moderate thermophiles and extreme
thermophiles should therefore be treated separately for the analysis of
high temperature adaptation factors. Apparent discrepancies in the results of previous works might originate in a failure to do so.
The availability of an increasing number of complete genomic sequences
makes global proteome analysis a powerful tool for establishing genome-function relationships. In this respect, some differences were already noted between the amino acid compositions of
subsets of ORFs1 from
mesophiles and hyperthermophiles (15-18). However, previous approaches
used comparisons of orthologous sequences or of structures of proteins
belonging to a same family (5-8). The x-ray structures were also
selected according to quality criteria. Applying these two criteria
lead to a reduced number of structures analyzed and might yield to a
statistically less satisfactory approach. Here, we postulated that the
most basic features of protein structures, amino acid composition and
localization, should be imprinted in the genome of organisms with very
different lifestyles. We therefore expected that global differences
should be readily detectable from a coarse but comprehensive and
unbiased analysis. Here, we computed the amino acid compositions in the
ORFs of all complete genome sequences available to date (30)
as well as on the protein surfaces (water-accessible surface
(WAS), Ref. 19) of a large set of protein structures.
Although these analysis were unbiased, since no prior selection of
sequences or structures was performed, they exhibit a remarkable
correlation, suggesting that the replacement of polar noncharged
residues by charged ones constitutes a major stabilization
mechanism in the proteins of hyperthermophilic organisms.
 |
MATERIALS AND METHODS |
Data on the amino acid composition of the fully sequenced
genomes were taken from the web site of Fred Tekaia, Pasteur Institute (Paris). Organisms have been classified according to the three major domains of life and using the following abbreviations (which are
used in Figs. 1 and 2A). Mesophiles (total
of 22): (i) Eukaryotes, Saccharomyces cerevisiae
(SC), C. elegans (CE), Schizosaccharomyces pombe
(SP; 68% of total proteome), Drosophila melanogaster (DM), Arabidopsis thaliana (ATH; not complete), Plasmodium
falciparum (PF; not complete); (ii) Bacteria, Mycoplasma
genitalium (MG), Mycoplasma pneumoniae (MP),
Synechocystis sp. (Ssp.), hemeophilus influenzae
(HI), Escherichia coli (EC), Helicobacter pylori
(HP), Bacillus subtilis (BS), Borrelia burgdorfi
(BB), Mycobacterium tuberculosis (MT), Treponema
pallidum (TP), Chlamydia trachomatis (CT),
Chlamydia pneumoniae (CP), Rickettsia prowazekii
(RP), Campylobacter jejuni (CJ), Deinococcus
radiodurans (DR), Neisseria meningitidis (NM).
Thermophile (total of 1): Archaea, Methanothermobacter
thermoautotrophicum (MTH). Hyperthermophiles (total of 7):
(i) Bacteria, Aquifex aeolicus (AE), Thermotoga
maritima (TM); (ii) Archaea, Pyrococcus horikoshii OT3
(PH), Pyrococcus abyssii (PA), Methanococcus
jannaschii (MJ), Archaeoglobus fulgidus (AF),
Aeropyrum pernix K1 (APE).
The three-dimensional structures come from the Protein Data Bank at
RCSB. Water-accessible surface calculations were performed with
the program DSSP (22). The number of Protein Data Bank structures used for surface calculations are as follows. (i)
Mesophiles: E. coli, 50; B. subtilis, 34;
S. cerevisiae, 47. (ii) Hyperthermophiles (total of
58): Pyrococcus furiosus, 11; wosei, 3;
kodakaraensis, 2; T. maritima, 10;
neapolitana, 1; Aquifex pyrophilus, 2;
aeolicus, 1; Sulfolobus solfataricus, 6;
acidocaldarius, 5; M. jannaschii, 9;
Thermococcus littoralis, 2; celer, 1;
gorgonarius, 1; Methanopyrus kandleri, 2; Pyrobaculum
aerophilum, 2.
 |
RESULTS AND DISCUSSION |
Amino Acid Composition of the Proteomes--
Our data set consists
of the amino acid compositions of the entire proteomes of 22 mesophiles, 1 thermophile, and 7 hyperthermophiles. We calculated the
average proportion of each amino acid in all mesophiles
(30-50 °C) on one hand and in all
hyperthermophiles (>80 °C, Table I) on the other hand. The
only moderately thermophile organism genome available, that of M. thermoautotrophicum (Table I), was
excluded from the comparisons for the reasons mentioned above (except
for Figs 1 and 2A). We then
grouped the results for each amino acid in classes such as charged,
polar noncharged, aliphatics, and aromatics, a procedure based on
biophysical characters and already used in this kind of approach (5,
12). A benefit of this procedure is also to correct the bias in the
proportion of certain amino acids induced by the strong variation in (G + C) content across the compared genomes (Fig. 1). For instance, arginine content was found to be strongly correlated with the (G + C) percentage, while the lysine content is strongly
anticorrelated (Fig. 1). The use of Lys or Arg by a given
organism does not depend on specific chemical properties of Arg
versus Lys, but only depends on the (G + C)
content, as indicated by Fig. 1. Therefore, grouping Lys + Arg makes it
possible to overcome the (G + C) content bias. As a consequence,
the variations observed for the positively charged residues (Lys + Arg)
stay within 50%, while up to 5-fold variations are observed for the
individual amino acids (Fig. 1). It is worth to notice that the (G + C) content is not correlated to the optimal growth temperature
of the organisms (Fig. 1).
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Table I
Optimal growth temperature of the thermophile and the different
hyperthermophiles used in this work
Data were taken from the DSMZ data base of organisms (Braunschweg,
Germany).
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Fig. 1.
Plot of the correlated variations the
percentage of arginine (R, light
blue) with the (G + C) content (divided
by 10; G+C/10, red) of the 30 genomes
under study (see "Materials and Methods"). The amount of
lysines is anticorrelated with that of arginines (K,
green), and therefore varies with the (A + T) content. The
large variations of Arg and Lys taken separately are buffered when
considering the sum Arg + Lys (POS, dark blue).
This suggests that the choice of positively charged residues, Arg or
Lys, is only dictated by the (G + C) content of the
organism.
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Fig. 2.
Amino acid content variations within the 30 genomes under study (see Fig. 1). A, plot of
the sum of the percentages of charged amino acids (Lys, Arg, Asp, Glu;
CHA, blue), polar noncharged amino acids (Asn,
Gln, Ser, Thr; POL, green), and of the difference
of the two values (CH-POL, red). The mesophiles
and hyperthermophiles are identified by MESO and
HYPER, respectively. The eukaryotes are identified. All the
other mesophiles are bacteria, while most hyperthermophiles are archaea
except the two bacteria (ae and tm) identified by
black circles. The sole moderate thermophile is the archaea
M. thermoautotrophicum (mth, isolated red
square). B, plot of the percentages of the various
amino acids in mesophiles (blue) and hyperthermophiles
(red), also identified in their class. C, plot of
the sum of percentages of the various amino acid classes in mesophiles
(blue) and hyperthermophiles (red).
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|
The proteome analysis in amino acid classes indicated that
hyperthermophilicity is characterized by a sharp increase of charged residues, Lys and Glu, at the expense of polar noncharged residues, mainly Gln (Fig. 2A). This correlation with growth
temperature is verified across the three kingdoms (Fig. 2A).
A slight increase in medium and large aliphatics is also observed,
while the percentage of the short aliphatic alanine is lower (Fig.
2B). No significant variations are observed in aromatics or
in other residues such as His, Pro, Gly, or Cys. In summary, the
difference between charged and polar noncharged amino acids (Ch-Po) is
the best indicator of the organism's lifestyle (Fig. 2,
A-C). A threshold is observed around 10% for the extreme
thermophiles Ch-Po values, while a higher limit of 5%
characterizes the mesophiles. The moderate thermophile M. thermoautotrophicum is situated in between these two values (Fig.
2A).
The Case of A. pernix and P. horikoshii--
Our initial analysis
of the A. pernix proteome revealed a discrepancy: a Ch-Po
value of only 5.2% was computed for this organism, thus in the
mesophile range and much below the 10% lower limit inferred from the
other true hyperthermophiles (Table I). This conflicting result
prompted us to reassess the quality of the ORF annotation originally
proposed for this genome. According to the original publication (20)
A. pernix was found to exhibit 2694 ORFs for a total genome
length of 1,669,695 base pairs, thus corresponding to 1 ORF for 620 nucleotides in average. This theoretical gene density is almost twice
as much as previously reported for any other micro-organism sequenced
so far. The fact that this organism was also claimed to exhibit the
largest proportion of ORFs without data base similarity (57.1%)
suggested an anomaly in the genome annotation. The whole A. permix ORF data set was then downloaded from the official site at
the Japan National Institute for Technology Evaluation for
further study. It soon appeared that the total number of nucleotides
included in the protein coding fraction of the genome (1,916,052) was
much greater than the total number of nucleotides (1,669,695). This
anomaly is mostly due to the annotation of overlapping ORFs in
different reading frames, resulting in a significant overprediction of
genes and the pollution of our computations by illegitimate protein sequences.
We first corrected this problem by limiting our amino acid composition
analyses to the subset of 628 predicted ORFs for which clear homologues
have been recognized in other organisms ("Annotable ORFs,"
according to Ref. 20). This subset is less likely to contain
illegitimate ORFs. Independently, we also reannotated A
pernix genomic sequence using the iterative Markov model method SelfID (21) and recomputed the amino acid composition on the predicted
coding regions longer than 300 nucleotides. The amino acid compositions
obtained by these two independent ways are virtually identical, and as
expected, very different from the composition computed on the original
data set. Using the two corrected amino acid compositions, our
previously defined indicator of thermophilicity Ch-Po was 10.6%,
compatible with the values observed for the other hyperthermophilic organisms.
After the above correction for A. pernix, P. horkoshii became the hyperthermophile organism associated with the
lowest Ch-Po value (10.2%), far from the other Pyrococcus,
P. abyssii (13.2%). It turns out that the P. horkoshii genome sequence was determined in the same Institute as
that of A. pernix and annotated according to a similar
protocol (23). P. horkoshii is also characterized by
a very large fraction of ORFs without data base similarity (44.4%) and
a unusually high gene density with predicted protein coding nucleotides
representing 98.5% of the total genome. We thus suspected that the
same overprediction plaguing A. pernix could affect P. horikoshii, although to a lesser extent. As expected, restraining
the amino acid composition analysis to the subset of 557 predicted ORFs
with recognized homologs resulted in a corrected C-P value of 13.6%,
almost identical to that of P. abyssii. The average values
presented in the plots of Fig. 2 include these corrections.
In the paper by Audic and Claverie (21) 10 bacterial genomes were
checked using the described method. There were very small differences
between the published data and the reanalyzed one. After the discovery
of the wrong annotations of the Japanese institute, we reanalyzed the
13 remaining genomes, and we found, as in the first 10, small
differences or none.
The Water-accessible Surfaces of Amino Acid Classes--
The
proportion of polar noncharged amino acids is greatly decreased in the
extreme thermophile organisms and partially compensated by charged
amino acids (Fig. 2A). Where are these amino acids located
in the proteins structures? Are the variations observed in the genomes
correlated with differences at the protein surfaces? To address these
questions, we calculated the WAS of the various amino acids for 131 proteins from three mesophilic bacteria and for 58 proteins from
hyperthermophilic bacteria or archaea (Fig. 3). The WAS values were then grouped by
classes of amino acids, as defined above for the genomic analyses. The
most striking difference between the WAS values was again found between
charged and polar noncharged amino acids (Fig. 3A). The WAS
percentage of charged amino acids increased from 22.5 in mesophiles to
27 in hyperthermophiles (+20%), mainly due to lysines and glutamic
acids. This difference (+4.5%) was almost fully compensated for by the
decrease of the WAS percentage ( 3.5%) of polar residues in
mesophiles (Fig. 3B). Glutamine exhibited the largest
variation among all residues, with a WAS decreased by more than 2-fold.
WAS values for the other polar residues exhibited the same trend, to a
lesser magnitude. The WAS percentage for aliphatic residues showed
little change at 6.0-6.5% of the total surface area. In contrast,
alanines are decreased by 2-fold, and histidines by 1.5-fold (Fig.
3A). Finally, the exposed area of Gly, Cys, and aromatic
residues was found to be unchanged between mesophiles and
hyperthermophiles. The differences observed in the above average values
are comparable with those computed between individual sets of proteins
from the three mesophilic or the three hyperthermophilic organisms,
reinforcing their significance (Fig. 3B). Thus, our results
indicate that the large differences in surface accessibilities of amino
acid classes are correlated with the large variations observed in the overall proteome abundance between the two sets of organisms.

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Fig. 3.
Amino acid water-accessible surface area
within the 189 protein structures under study. A,
percentages of the various amino acids WAS (relative to the total
surface area calculated for each Protein Data Bank file) belonging to
mesophiles (blue) and hyperthermophiles (red)
plotted versus the 20 amino acids. B, percentages
of the WAS of the different classes of amino acids for three mesophiles
(yeast, B. subtilis, and E. coli) and their
average (blue) compared with three hyperthermophiles
(Thermococcus, Pyrococcus, and Methanococcus) and
their average (red) (see "Materials and Methods").
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Concluding Remarks--
Coarse but extensive approaches at the
genome or structure level are thus able to identify discriminant
factors between mesophiles and extreme thermophiles. This implies the
existence of global structural features associated with
hyperthermostability common to thermophilic bacteria and archaea. The
equal increase of subclasses of oppositely charged residues (mostly
Lys, Arg, and Glu) in hyperthermophiles most likely derives from the
increased amount of ion pairs observed at the surface of their
proteins. This is the genomic signature of a thermodynamic advantage
resulting from the increased stability of coulombic interactions with
temperature (itself due to the decrease of water dielectric constant,
Ref. 9). Furthermore, in most structures of hyperthermophilic proteins,
the existence of long chains of ion pairs providing cooperative
stabilization has been demonstrated (1-3).
Interestingly, the residues the proportion of which exhibit the largest
relative decreases in the genomes of hyperthermophiles are Asn and Gln,
already known to be the most temperature sensitive. It is tempting to
relate the observed Glu/Gln balance to a peculiarity in the metabolism
of hyperthermophiles. For instance, the Gln tRNA synthetase gene is
missing in the bacteria A. aeolicus (18) and the archaea
M. janaschii (24). In both organisms, Gln originates from
the amidation of glutamic acid loaded on the Gln tRNA. Conversely, a
completely different class of Lys tRNA synthetase gene has been found
to exist in some hyperthermophiles, where the proportion of lysine is
much increased. Missing, different, or more efficient aminoacyl tRNA
synthetases may contribute to various adaptive mechanisms and play a
crucial and general role in the pathway to hyperthermostability.
 |
ACKNOWLEDGEMENTS |
The computing assistance of Stephane Audic
and Eric Blanc is greatly acknowledged.
 |
FOOTNOTES |
*
The costs of publication of this
article were defrayed in part by the
payment of page charges. The article
must therefore be hereby marked
"advertisement" in
accordance with 18 U.S.C. Section
1734 solely to indicate this fact.
§
To whom correspondence should be addressed. Fax: 33-491-16-45-36;
E-mail: cambillau@afmb.cnrs-mrs.fr.
Published, JBC Papers in Press, August 11, 2000, DOI 10.1074/jbc.C000497200
 |
ABBREVIATIONS |
The abbreviations used are:
ORF, open reading
frame;
WAS, water-accessible surface;
Ch-Po, the difference between
charged and polar noncharged amino acids.
 |
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R. Friedman, J. W. Drake, and A. L. Hughes
Genome-Wide Patterns of Nucleotide Substitution Reveal Stringent Functional Constraints on the Protein Sequences of Thermophiles
Genetics,
July 1, 2004;
167(3):
1507 - 1512.
[Abstract]
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J. Eichler
Facing extremes: archaeal surface-layer (glyco)proteins
Microbiology,
December 1, 2003;
149(12):
3347 - 3351.
[Abstract]
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C. L. Nesbo and W. F. Doolittle
Active self-splicing group I introns in 23S rRNA genes of hyperthermophilic bacteria, derived from introns in eukaryotic organelles
PNAS,
September 16, 2003;
100(19):
10806 - 10811.
[Abstract]
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S. Bartolucci, G. De Simone, S. Galdiero, R. Improta, V. Menchise, C. Pedone, E. Pedone, and M. Saviano
An Integrated Structural and Computational Study of the Thermostability of Two Thioredoxin Mutants from Alicyclobacillus acidocaldarius
J. Bacteriol.,
July 15, 2003;
185(14):
4285 - 4289.
[Abstract]
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N. F.W. Saunders, T. Thomas, P. M.G. Curmi, J. S. Mattick, E. Kuczek, R. Slade, J. Davis, P. D. Franzmann, D. Boone, K. Rusterholtz, et al.
Mechanisms of Thermal Adaptation Revealed From the Genomes of the Antarctic Archaea Methanogenium frigidum and Methanococcoides burtonii
Genome Res.,
July 1, 2003;
13(7):
1580 - 1588.
[Abstract]
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K. Suhre and J.-M. Claverie
Genomic Correlates of Hyperthermostability, an Update
J. Biol. Chem.,
May 2, 2003;
278(19):
17198 - 17202.
[Abstract]
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N. Declerck, M. Machius, P. Joyet, G. Wiegand, R. Huber, and C. Gaillardin
Hyperthermostabilization of Bacillus licheniformis{alpha}-amylase and modulation of its stability over a 50{degrees}C temperature range
Protein Eng. Des. Sel.,
April 1, 2003;
16(4):
287 - 293.
[Abstract]
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J. K. Yano, F. Blasco, H. Li, R. D. Schmid, A. Henne, and T. L. Poulos
Preliminary Characterization and Crystal Structure of a Thermostable Cytochrome P450 from Thermus thermophilus
J. Biol. Chem.,
January 3, 2003;
278(1):
608 - 616.
[Abstract]
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A. Jaramillo, L. Wernisch, S. Hery, and S. J. Wodak
Folding free energy function selects native-like protein sequences in the core but not on the surface
PNAS,
October 15, 2002;
99(21):
13554 - 13559.
[Abstract]
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R. A. Somerville, R. C. Oberthur, U. Havekost, F. MacDonald, D. M. Taylor, and A. G. Dickinson
Characterization of Thermodynamic Diversity between Transmissible Spongiform Encephalopathy Agent Strains and Its Theoretical Implications
J. Biol. Chem.,
March 22, 2002;
277(13):
11084 - 11089.
[Abstract]
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S. D'Amico, C. Gerday, and G. Feller
Structural Determinants of Cold Adaptation and Stability in a Large Protein
J. Biol. Chem.,
July 6, 2001;
276(28):
25791 - 25796.
[Abstract]
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G. Manco, L. Mandrich, and M. Rossi
Residues at the Active Site of the Esterase 2 from Alicyclobacillus acidocaldarius Involved in Substrate Specificity and Catalytic Activity at High Temperature
J. Biol. Chem.,
September 28, 2001;
276(40):
37482 - 37490.
[Abstract]
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B. Snel, P. Bork, and M. A. Huynen
Genomes in Flux: The Evolution of Archaeal and Proteobacterial Gene Content
Genome Res.,
January 1, 2002;
12(1):
17 - 25.
[Abstract]
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