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Microbiology (2004), 150, 1609–1627
Review
DOI 10.1099/mic.0.26974-0
The replication-related organization of bacterial
genomes
Eduardo P. C. Rocha
Correspondence
[email protected]
Atelier de Bioinformatique, Université Pierre et Marie Curie, 12, Rue Cuvier, 75005 Paris, and
Unité Génétique des Génomes Bactériens, Institut Pasteur, 28 rue du Dr Roux, 75724 Paris
Cedex 15, France
The replication of the chromosome is among the most essential functions of the bacterial cell
and influences many other cellular mechanisms, from gene expression to cell division. Yet the
way it impacts on the bacterial chromosome was not fully acknowledged until the availability of
complete genomes allowed one to look upon genomes as more than bags of genes. Chromosomal
replication includes a set of asymmetric mechanisms, among which are a division in a lagging
and a leading strand and a gradient between early and late replicating regions. These differences
are the causes of many of the organizational features observed in bacterial genomes, in terms
of both gene distribution and sequence composition along the chromosome. When asymmetries
or gradients increase in some genomes, e.g. due to a different composition of the DNA
polymerase or to a higher growth rate, so do the corresponding biases. As some of the features
of the chromosome structure seem to be under strong selection, understanding such biases
is important for the understanding of chromosome organization and adaptation. Inversely,
understanding chromosome organization may shed further light on questions relating to
replication and cell division. Ultimately, the understanding of the interplay between these
different elements will allow a better understanding of bacterial genetics and evolution.
Background
The study of bacterial chromosome organization has
received little attention, at least when compared with the
focused research on the features of the eukaryotic chromosome. There are several historical reasons for this. First,
bacterial chromosomes are much more homogeneous than
most eukaryotic chromosomes in terms of sequence composition and gene density. Second, in the majority of
bacteria there are no large characteristically diverse regions,
such as isochores, telomeres and centromeres. Third, bacterial chromosomes vary between 500 kb and 10 Mb, which
is significant, but much less than the length variation
shown by eukaryotic chromosomes. Nonetheless, bacteria
can have more than one chromosome, which can be linear
or circular, or oscillate between the two (Casjens, 1998).
There is also extensive size variation within a species, with
strains of some species differing by more than 50 % in
genome size (Bergthorsson & Ochman, 1998; Carlson &
Kolsto, 1994). This, together with the results coming from
genome sequencing, sparked a new interest in this domain
(reviewed by Casjens, 1998; Kolsto, 1997). The abundance
of PFGE studies and especially the existence of more than
100 publicly available complete bacterial genomes have
Additional material with the description of genomes used for the
figures can be found in the online version of this review at http://
mic.sgmjournals.org
0002-6974 G 2004 SGM
rendered possible the build-up of comparative genomic
studies at very diverse levels of detail. A major result of such
studies was the demonstration that replication is at the
very basis of the organization of bacterial chromosomes.
By this, I denote that chromosome replication is a major
cause of the arrangement and interrelation of many of the
elements constituting the chromosomal organization.
In this article, I review the more recent developments in
the understanding of these trends and try to put them
together in a unifying framework. I start with a brief
outline of the mechanisms involved in bacterial replication,
with emphasis on the asymmetries it leads to within and
between bacterial genomes. I then discuss the major types
of replication-associated asymmetries: differences between
the leading and lagging strands and variations along the
replichores in relation to the distance from the origin of
replication. For each of these elements, biases at the level
of nucleotides, oligonucleotides and genes are discussed and
put into relation with current working hypotheses. This
review is not about replication mechanisms, replication
fidelity or the distribution of signals directly related to
replication or its regulation. Although these elements also
contribute to fashioning the bacterial chromosome, I
highlight the implications of replication on the chromosome at wider organizational levels and its implications on
mechanisms and structures other than replication itself.
The emphasis is on the elements that are structured by
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E. P. C. Rocha
replication without directly intervening in it. The argument
is that the intrinsic mechanistic asymmetries or gradients of
chromosome replication impose biases on sequence composition and gene distribution in the bacterial chromosome.
For further information on the mechanisms and regulation
of replication start, elongation and termination, the reader
is invited to consult the excellent reviews available (Bussiere
& Bastia, 1999; Giraldo, 2003; Kunkel & Bebenek, 2000;
Lobry & Louarn, 2003; Marians, 1992).
Replication in bacteria
In bacteria where replication has been thoroughly studied,
such as Escherichia coli and Bacillus subtilis, chromosome
replication starts at a single chromosome locus, the origin
(ori). The key regulation of chromosome replication takes
place at the start of the process and is tightly coupled to
cell mass (Boye et al., 1996). Initiation occurs once per cell
cycle during a short time interval at all origins within a
cell (Skarstad et al., 1986). Secondary initiations of the
newly replicated origins are then avoided by a transient,
temporally coordinated blockage in re-initiation at the
origin (Campbell & Kleckner, 1990). Replication proceeds
by the bidirectional progression of the replication forks
along the chromosome (Fig. 1). In each replication fork,
a complex with two DNA polymerases replicates the two
DNA strands. The pace of the replication fork varies
significantly between bacteria. For example, in E. coli the
fork progresses at ~1000 nt s21, in Pyrococcus abyssi at
~300 nt s21 (Myllykallio et al., 2000) and in Mycoplasma
capricolum at ~100 nt s21 (Seto & Miyata, 1998). Thus
although the M. capricolum genome is seven times smaller
than that of E. coli, it takes longer to be replicated. Short
DNA segments to which a replication terminator protein
binds (ter sites) arrest the movement of the replication forks
when these pass through the terminus region (Bussiere &
Bastia, 1999). The chromosome dimer is then resolved by
site-specific recombination mediated by XerC and XerD
recombinases at the dif sites (Blakely et al., 1993; Kuempel
et al., 1991). The system of replication fork arrest diverges
widely among bacteria, and deletion of ter sites is not lethal
in B. subtilis (Iismaa & Wake, 1987) or in E. coli (Henson &
Kuempel, 1985). On the contrary, the system of chromosome resolution is strongly conserved (Recchia & Sherratt,
1999).
The replication fork
Elongation of the newly synthesized strand involves the
displacement of the replication fork along the chromosome.
The replication fork is a holoenzyme with several components (Glover & McHenry, 2001), among which are a
helicase that unwinds the chromosome (DnaB in E. coli),
and two DNA polymerases III (DNAP) that replicate the
two strands (Fig. 1). The DNAP core is composed of a
heterodimer of the subunits a, e and h, and contains the
polymerase activity (a-subunit) and the proofreading 39R59
exonuclease activity (h-subunit). The t-subunit causes
DNAP to dimerize (Marians, 1992). Because DNA polymerization occurs in the 59R39 direction, one strand is
replicated continuously – the leading strand – whereas the
other strand is replicated in discrete steps – the lagging
strand – through the use of the Okazaki fragments. The
cycle of the synthesis of Okazaki fragments starts by the
Fig. 1. Replication of the bacterial chromosome proceeds bidirectionally from the origin to the terminus of replication. At each
replication fork, two DNAPs replicate the leading and lagging strands. Boxes indicate elements of asymmetry. See the text for
details.
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Replication and bacterial chromosome structure
synthesis of a new 10–12 nt RNA primer by a primase
(Kitani et al., 1985). Subsequently, the lagging strand
polymerase transits from the 39-OH terminus of the just
completed Okazaki fragment to the new primer terminus,
resuming DNA synthesis through 1000–2000 nt in E. coli
and around 100 nt in P. abyssi (Matsunaga et al., 2002). The
cycle ends by the removal of the previous RNA primer and
gap filling. Conversely, the synthesis of the leading strand is
essentially continuous, closely following the unwinding of
the DNA duplex, with processivities surpassing 500 kb and
eventually all the replichore (Marians, 1992).
Thus there are two polymerase cores within one holoenzyme particle, each replicating a different DNA strand. In
E. coli, the two core polymerases are not pre-dedicated to
one strand and can be interchanged without differences in
processivity (Yuzhakov et al., 1996). In B. subtilis and the
other Firmicutes there are two different genes encoding the
a-subunit of the DNA polymerase (Bruck & O’Donnell,
2000; Dervyn et al., 2001). One of these subunits is the
orthologue of the E. coli subunit (DnaE), whereas the other
shows weak sequence similarity (PolC) (Koonin & Bork,
1996). Recent evidence suggests complementary roles for
these proteins, with DnaE involved in lagging strand
synthesis and PolC involved in leading strand synthesis
(Dervyn et al., 2001). An important difference between the
two proteins is that PolC includes the exonuclease domain,
which is coded separately in E. coli (h-subunit, DnaQ)
(Huang & Ito, 1999). A third family of a-subunits resembling E. coli’s DnaE is present in cyanobacteria (Kaneko et al.,
1996). In this case the a-subunit is spliced in two genes (Ito
et al., 1998). Finally, some bacteria show a more mixed, and
less well-understood, picture. For example, in Thermotoga
maritima, there is one gene encoding a homologue of PolC,
but no obvious homologue of DnaE (Nelson et al., 1999).
Asymmetries and gradients in replication
The mechanistic asymmetries of bacterial replication result
in mutational or selective biases, differentiating the chromosome within replichores and between replicating strands
(Fig. 1).
Collisions between polymerases. Chromosomal replication
often takes place in moments of high transcription levels
and collisions between DNAP and RNA polymerase (RNAP)
are inevitable. Although the RNAP transcription rate varies
with the growth phase, it is usually in the range 40–
50 nt s21, thus is 20 times slower than that of DNAP in
E. coli (Bremer & Dennis, 1996). Because both polymerases
progress in the 59R39 direction, transcripts coded in the
lagging strand lead to head-on collisions whereas leading
strand transcripts lead to co-oriented collisions (Fig. 2).
There are two important consequences of this asymmetry.
When the replication fork arrives at an actively transcribed
operon, polymerases will inevitably collide if the operon is
in the lagging strand but occur with probability ~19/20
(i.e. 95 %) if the operon is in the leading strand (because
DNAP is 20 times faster than RNAP). Thus the probability
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of collision depends on the direction of transcription. But
so does the outcome of the collision. Studies of both E. coli
rRNA (French, 1992) and Saccharomyces cerevisiae tRNA
genes (Deshpande & Newlon, 1996) in vivo indicate that
only head-on collisions interfere significantly with the
progression of the replication fork. As a consequence,
differential probability and outcome of collisions between
polymerases lead to an asymmetric distribution of genes
between the two strands.
Compositional differences between replicating strands.
During the replication of the Okazaki fragments, the leading strand is kept single-stranded while the neo-formed
lagging strand is being synthesized. Yet the lagging strand
stays double-stranded when the neo-formed leading strand
is being synthesized. Single-stranded DNA (ssDNA) can
form secondary structures and these may lead to replication errors (Leach, 1994) and palindrome deletion (Trinh
& Sinden, 1991). Also, some types of substitutions
increase in ssDNA more than others, and thus the different replication of the two strands leads to compositional
differences between the replicating strands (Francino &
Ochman, 1997; Frank & Lobry, 1999).
Gene dosage effects. Fast-growing bacteria have growth
rates requiring replication re-initiation before the round
in progress is complete. In this way, E. coli can attain
growth rates of 2?5 doublings h21 (Bremer & Dennis,
1996). The replication fork moves at about 600–
1000 nt s21 (Marians, 1992), and to duplicate the average
5 Mb E. coli chromosome it takes from 40 to 67 min
(Bremer & Dennis, 1996). Hence E. coli cells under exponential growth show two to three simultaneous rounds of
replication, a new one starting every ~20 min. Under
these conditions, genes near the origin of replication are
overrepresented in the bacterial cell by a factor of 4 (22)
to 8 (23) relative to genes near the terminus of replication
(Chandler & Pritchard, 1975). Hence in fast-growing bacteria highly expressed genes tend to be positioned near
the origin of replication.
Gradients along the replichore. The directionality of
chromosome replication leads to a chronological asymmetry along the replichore. Since about 1 h separates the
beginning from the end of replication, the favourable conditions leading to replication start may no longer prevail
at the end of the process and this may result in different
mutation rates and compositional biases (Daubin &
Perriere, 2003). Dimer separation after full chromosome
replication requires site-specific or homologous recombination (Corre & Louarn, 2002). This may also result in
differential mutation and recombination biases near the
terminus of replication.
In the following sections, these different biases are discussed
in the framework of the major replication asymmetries.
Additional material with the description of genomes used
for the figures can be found in the online version of this
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Fig. 2. Differential outcome of DNAP and RNAP collisions, when operons are in the leading or the lagging strands. In
bacteria, translation is coupled to transcription, and this has important consequences in the model. In order not to complicate
excessively the figure, the translation machinery was not represented.
review at http://mic.sgmjournals.org, and also at http://
www.abi.snv.jussieu.fr/~erocha/replrev/.
Differences between leading and lagging
strands
Gene strand bias
The ‘polymerase collision avoidance’ model. The seven
rDNA operons in E. coli are all on the leading strand,
resulting in co-orientation of replication and transcription
(Ellwood & Nomura, 1982), which was speculated to
result from selection to prevent too frequent collisions
between DNAP and RNAP (Nomura & Morgan, 1977).
These and other works showing that RNAP movement
slows down DNA replication (Pato, 1975) led to the
proposition that the differential outcome of collisions
between DNAP and RNAP should result in a selective
pressure towards coding highly expressed genes in the
leading strand (Brewer, 1988). The lower collision rate
would carry two major advantages: (i) faster DNA replication; (ii) less transcript loss. It could also diminish the
number of replication arrests, which are dangerous for the
cell (Kuzminov, 2001). In fast-growing E. coli there are
~70 000 ribosomes per cell, corresponding to roughly
10 000 transcripts per rRNA operon per replication cycle
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(Bremer & Dennis, 1996). Under the same conditions,
there are about 70 RNAPs transcribing each of the seven
rRNA operons, implicating a potential for 490 collisions
per replication round, i.e. about 5 % of the rRNA transcription. This could significantly retard replication if collisions are head-on (Brewer, 1988). Indeed, highly expressed
translation-related genes, such as rRNA and ribosomal
protein genes, have been systematically found coded in
the leading strands of genomes for which replicating
strands can be identified (e.g. Blattner et al., 1997; Rocha,
2002; Zeigler & Dean, 1990). A rare exception concerns
the sequenced genome of Pasteurella multocida, which
exhibits two recent inversions near the origin of replication that shifted two of the six rDNA operons and several
ribosomal protein genes to the lagging strand (May et al.,
2001). The validity of the polymerase collision avoidance
model has never been thoroughly tested, due to obvious
experimental difficulties, and only recently has started to
be questioned.
Frequency of genes in the leading strand. The sequen-
cing of the regions surrounding replication origins of
both B. subtilis (Ogasawara & Yoshikawa, 1992) and E. coli
(Burland et al., 1993) showed that the genes are systematically coded in the leading strand. However, sequencing of
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Microbiology 150
Replication and bacterial chromosome structure
the two complete genomes resulted in very different
observations (Fig. 3). The frequency of leading strand
genes is ~75 % in B. subtilis (Kunst et al., 1997), but only
~55 % in E. coli (Blattner et al., 1997). A first systematic
survey of gene strand bias showed that genomes could
have from 55 to 80 % of genes in the leading strand,
although systematically more than 85 % of ribosomal proteins were coded in the leading strand of these genomes
(McLean et al., 1998). In fact, 78 % of the genes of
Firmicutes (including mycoplasmas) are in the leading
strand, compared with 58 % for the other genomes
(Rocha, 2002). Interestingly, the group with higher biases
coincides with the group of genomes containing two
different (and probably strand-dedicated; Dervyn et al.,
2001) DNAP a-subunits at the replication fork. The
causal association between these two observations, by considering that more asymmetric replication forks lead to
higher gene strand bias, is tempting but not trivial. One
could suppose that the additional structural asymmetry
at the fork would lead to increased asymmetry in its stability relative to different types of collisions (Rocha, 2002).
If this is so, genomes containing two different DNAP
a-subunits should be less sensitive to co-oriented collisions and/or more sensitive to head-on collisions. One
can think of several ways in which this could happen.
Collisions between polymerases can result in dangerous
replication arrests, which may be solved by the action
of homologous recombination (Lusetti & Cox, 2002). B.
subtilis has two different DNAPs and also different
mechanisms for homologous recombination where the
RecBCD system of E. coli is functionally replaced by the
AddAB system (Dubnau & Lovett, 2002). This might
render it more sensitive to replication arrests, which in
E. coli have been proposed to result only from head-on
collisions (French, 1992). Genomes containing two different
DNAP a-subunits lack the proofreading E. coli exonuclease
protein DnaQ. Although PolC contains a homologous
exonuclease motif, DnaE does not. Further, DnaQ performs
a structural role by increasing the stability of the DNAP
complex and thus processivity in E. coli (Maki & Kornberg,
1987; Studwell & O’Donnell, 1990). Genomes lacking DnaQ
could thus be more sensitive to collisions. Interestingly,
comparative works seem to indicate that B. subtilis RNAP is
more processive than that of E. coli (Artsimovitch et al.,
2000). The conjugation of these differences might render
B. subtilis DNAP more sensitive to collisions and thus
favour higher gene strand bias. However, collisions between
polymerases are expected to occur between RNAP and the
helicase (Fig. 2), probably by DNA knotting and without
direct contact (Olavarrieta et al., 2002). Although this does
not necessarily invalidate the possibility that differential
DNAP sensitivity could lead to higher overall biases,
further experimental work will be necessary to assess this
hypothesis.
Types of strand biased genes. Besides showing that com-
positionally different DNAPs are correlated with different
levels of gene strand bias, these works raise another
important point: high levels of gene expression can hardly
account for all the observed trends. The number of genes
that are highly expressed in bacteria is typically low
(Andersson & Kurland, 1990), and cannot justify the high
frequency of leading strand genes in Firmicutes. Furthermore, according to the polymerase collision model, gene
strand bias should be higher in fast-growing bacteria,
where transcription and replication (hence collisions) are
very frequent. However, one typically finds the inverse
(Rocha, 2002). That expression is not a determinant of
gene strand bias was recently demonstrated in B. subtilis
and E. coli (Rocha & Danchin, 2003a), where essentiality
seems to be the unexpected key to understanding this
bias. In B. subtilis, the frequency of leading strand essential genes (96 %) and non-essential genes (74 %) is radically different and is independent of expression levels.
Qualitatively similar results are found in E. coli when high
expression is defined using codon usage biases, or transcriptome or proteome data. Furthermore, these results
Fig. 3. Density of coding sequences (grey) and leading strand coding sequences (black) in model bacteria and highly biased
genomes of Firmicutes (B. subtilis and Thermoanaerobacter tengcongensis) and others (E. coli and Treponema pallidum). The
densities were computed in non-overlapping windows of 10 (T. tengcongensis and T. pallidum) and 20 (E. coli and B.
subtilis) kb.
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E. P. C. Rocha
seem to hold when essentiality is assigned by homology in
most other bacterial genomes (Rocha & Danchin, 2003b).
In all cases, essential genes are more biased than nonessential genes, and among non-essential genes there is
rarely a significant effect attributable to expression level.
Finally, when comparing the location of orthologues in
close genomes, essential genes are conserved in the leading
strand more often than the other genes.
Re-thinking the polymerase collision model. The poly-
merase collision model does not satisfactorily explain the
linkage between gene strand bias and essentiality. If the
major problem associated with collision between polymerases is replication slow-down, then one would expect
higher biases among the genes leading to higher collision
rates, i.e. among highly expressed genes. Yet among the
>3000 genes expressed during exponential growth in
E. coli (Tao et al., 1999), the essential genes, many of
which are expressed at low levels, are highly biased,
whereas the highly expressed genes that are not essential
are equally distributed between the replicating strands.
This suggests that the problem of collisions is not related
to the collision rate (i.e. with expression levels), but with
gene function. In co-oriented collisions, the transcript
may be finished, whereas head-on collisions result in
aborted transcripts (Fig. 2). The latter may be translated
into truncated non-functional peptides, which is particularly
deleterious for essential functions. Also, non-functional
peptides forming part of large complexes, as is often the
case of essential genes, are typically dominant negative
(Pakula & Sauer, 1989). As a result, the truncated peptide
may inactivate an entire complex. If this model proves
correct, it suggests that aborted transcripts may be more
deleterious than previously thought.
reciprocal substitutions are equal. The second parity rule
indicates that at equilibrium, and under PR1 conditions,
nG=nC and nA=nT in each DNA strand. In fact, under no
strand bias the second parity rule is the expected outcome
of the first (Lobry, 1995). However, the analysis of the first
bacterial genomes showed that nG=nC and nA=nT do not
hold when the genomes are divided into leading and lagging
replicating strands (Lobry, 1996a). The subsequent flood of
bacterial genomes confirmed the generality of this observation (Grigoriev, 1998; Lobry & Sueoka, 2002; Mackiewicz
et al., 1999; McLean et al., 1998; Mrázek & Karlin, 1998;
Rocha et al., 1999a). The analysis of the first 100 available
complete genomes in the bacterial branch of the tree of life
using conventional techniques indicates that less than a
dozen lack any type of compositional strand bias (Fig. 4).
Several reviews have been dedicated to compositional
strand bias (Francino & Ochman, 1997; Frank & Lobry,
1999; Karlin, 1999). Here I concentrate on the most recent
results. With the exception of Streptomyces coelicolor (see
below), the leading strand is richer in G relative to C, and
to a lesser degree richer in T relative to A (Lobry, 1996a).
Thus keto (leading strand) opposes amino (lagging strand)
in compositional strand bias. The C-richness of the leading strands of mycoplasmas (McLean et al., 1998) is due to
gene strand bias and biased composition of genes (Perrière
It is yet unclear if high levels of gene strand bias in genomes
containing two different DNAP a-subunits are related to a
higher frequency of essential genes in the leading strand.
One might consider that the problem of truncated peptides
associated with collisions between polymerases is common
to all expressed genes, but assumes a particular relevance
in the context of genes encoding essential functions. If
so, one could speculate that the asymmetry between the
two types of collisions, head-on and co-oriented, would
be qualitatively identical in all genomes, but have more
severe consequences in genomes having two different
DNAP a-subunits because they may be less robust to
collisions, as discussed above. Hence the overall bias would
be larger in these genomes.
Compositional strand bias
Early work suggested that the frequencies of G and C
and A and T (nG=nC and nA=nT) are roughly equal in
ssDNA (Rudner et al., 1968). These results were integrated
in the theoretical body of molecular evolution, under the
form of two parity rules (Sueoka, 1995). The first parity
rule (PR1) indicates that when mutation and selection are
symmetrical relative to both DNA strands, the rates of
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Fig. 4. Distribution of replication strand biases in the bacterial
tree (tree adapted from Brochier et al., 2002). Dark triangles
indicate the ubiquitous presence of compositional strand bias,
light triangles show groups containing some (usually few) genomes lacking compositional strand bias, and white indicates
that all genomes sequenced so far seem to lack a significant
bias. The hatched patterns distinguish the groups with particularly high levels of gene strand bias (on average more than
70 % of leading strand genes). The black circle indicates the
most commonly accepted position for the root of the tree.
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Microbiology 150
Replication and bacterial chromosome structure
et al., 1996), not compositional strand bias. Drawing GC
skews, defined as (G2C)/(G+C) in sliding windows, has
become a standard method to identify the origin and
terminus of replication in many bacteria, where experimental evidence is rarely available (Grigoriev, 1998; Lobry,
1996b). Compositional strand bias is relatively homogeneous in the genome and is especially strong at third
codon positions, as expected from a mutational bias
(Lobry, 1996a; McLean et al., 1998; Rocha et al., 1999a).
In highly biased genomes, strand bias is the major force
shaping codon usage (McInerney, 1998; Romero et al.,
2000). In these cases, one can easily discriminate the position of the genes relative to the replicating strand based on
their codon usage or amino acid content of the respective
proteins (Lafay et al., 1999; Mackiewicz et al., 1999; Rocha
et al., 1999a). In Borrelia burgdorferi, one can predict with
95 % accuracy the replicating strand positioning of the
gene based solely on its amino acid content (97 % using
nucleotide composition). The accuracy of such discrimination analysis is also significant, although less pronounced,
in the other genomes (Fig. 5). This is one of the most
striking examples of a mutational bias shaping protein
composition.
Strand bias is probably neutral and evolves fast. Genes
that switch off replicating strands following chromosomal
rearrangements evolve faster to adapt to the composition
of the new replicating strand. As a result they show lower
mean sequence similarity (Tillier & Collins, 2000b). The
ratio of synonymous/non-synonymous rates of switched
genes is similar to that of the average orthologues, in
agreement with a mutational driving force for this process
(Rocha & Danchin, 2001). As a consequence, strand
Fig. 5. Accuracy of the discrimination of the leading strand
genes and proteins based on their composition in nucleotides
and amino acids. Accuracy is defined as the percentage of correct predictions of 30 % of genes (the remaining 70 % being
used for learning) (Rocha et al., 1999a). Here, 58 genomes
corresponding to one strain per species were used.
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biases and fast sequence adaptation after strand switch
can lead to problems in estimating reliable phylogenies
based on sequence analysis (Szczepanik et al., 2001).
Mechanism(s) causing compositional strand bias. Hypo-
theses aiming at identifying the causes of compositional
strand bias must take into account the compositional
changes it creates, its apparently neutral basis, and its near
ubiquity.
Asymmetrical functioning and processivity of the two
DNAPs at each replication fork could result in different
mutation frequencies in the two strands, although there
are conflicting reports on this issue (see Frank & Lobry,
1999, for a discussion on this subject). The lagging strand
has been proposed to be less mutagenic based on the
analysis of mutations in lacZ (Fijalkowska et al., 1998).
The leading strand DNAP is highly processive staying on
the template throughout replication, while the lagging complex needs to allow rapid cycling and may thus dissociate
more easily from the template, leaving a mismatch for
correction. However, lacZ is a native lagging strand gene,
and adaptation to the leading strand composition is
expected to involve higher substitution rates (Szczepanik
et al., 2001). Radman (1998) proposed that the MutSHL
mismatch repair system would be more efficient in correcting errors in the lagging strand because it requires DNA
nicks to proceed and these are more readily available in the
lagging strand. However, some genomes without the mismatch repair system have strand biases (e.g. Actinobacteria),
and some genomes with MutSHL do not (e.g. Synechocystis
and Anabaena). More importantly, all the above hypotheses allow an explanation of the different mutation rates
between strands. However, the relevant variable regarding
compositional strand bias is the substitutions’ asymmetry
and different mutation rates per se do not lead to compositional asymmetry (Lobry & Lobry, 1999). Recent works
identified compositional strand bias in archaea (Lopez
et al., 1999), mitochondria (Mohr et al., 1999; Reyes et al.,
1998) and phages (Grigoriev, 1999; Miller et al., 2003;
Mrázek & Karlin, 1998). These elements possess different
DNAP and repair mechanisms, different G+C compositions (Sueoka, 1962) and different mutation rates (Drake
et al., 1998). Nevertheless, they all have a qualitatively
similar compositional strand bias. Thus the major source
of compositional asymmetry is probably to be found in a
fundamental property such as the chemical stability of DNA.
The cytosine deamination theory proposes that compositional strand bias is caused by the chemical instability of
cytosine in ssDNA (Frank & Lobry, 1999). Relative to
dsDNA, the rate of cytosine deamination increases by a
factor of 140 in ssDNA, and by a further factor of 4 when
cytosine is methylated (see Lutsenko & Bhagwat, 1999, for
a recent review). In the latter case, the deamination produces a T (instead of an U), which is not corrected by
the uracil-DNA glycosylase (Coulondre et al., 1978). The
leading strand is more exposed in the single-stranded state
(in order to serve as template for the synthesis of the new
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E. P. C. Rocha
lagging strand), and CRT mutations would lead to GC
and TA skews (and larger GC skews in G+C-poor
genomes). Still, GC skews are larger than expected, relative
to TA skews, under the cytosine deamination hypothesis
(McLean et al., 1998). Data on inverted genes of Chlamydia
and Bacillus were concordant with a major effect of cytosine
deamination in establishing the bias, but only when a
smaller contribution of asymmetric CRG substitutions
was considered (Rocha & Danchin, 2001). Caution is
necessary when interpreting the data of the latter analysis
because the substitutions could not be oriented, and
the genomes had accumulated multiple substitutions. Yet,
when the joint contributions of cytosine deamination and
CRG asymmetry were taken into consideration, there was
a satisfactory explanation of the association between GC
and TA skews in the available set of bacterial genomes
(Rocha & Danchin, 2001). As a result, cytosine deamination
of leading strand ssDNA is currently seen as the most
likely and important cause of compositional strand bias.
However, it may fail to describe the entire complexity of
this phenomenon since Streptomyces coelicolor leading
strands are G-poor and C-rich (Bentley et al., 2002). S.
coelicolor has the least biased genome displayed in Fig. 5
and GC skew is mostly present in the hypervariable arms,
not in the central most conserved regions. Further, the
closely related Streptomyces avermitilis shows no significant
compositional strand bias (Omura et al., 2001). It is still
unknown if the inverted bias of S. coelicolor is indeed
related directly to composition strand bias, to its extreme
GC composition (72 %) or to the frequent inversions,
fusions, deletions and insertions of large plasmids at these
chromosomal regions in Streptomyces (Chen et al., 2002).
Variation in the intensity of compositional strand bias.
As is clear from Fig. 5, compositional strand bias varies
significantly from genome to genome. This may be related
to the different stability of the genomes, as chromosome
shuffling will tend to level off the bias (Achaz et al., 2003;
Mackiewicz et al., 2001b; Rocha et al., 1999b; Tillier &
Collins, 2000b). The different length of the Okazaki fragments may also contribute to modulating the bias, since a
smaller exposure in the ssDNA state would lead to less
cytosine deamination (Mrázek & Karlin, 1998). Consistent
with this hypothesis, the intensity of compositional strand
bias is positively correlated with the duration of the
single-stranded state of the H-genes during mitochondrial
replication (Reyes et al., 1998). Eukaryotes have Okazaki
fragments that are 10 times smaller than those in E. coli,
and lack extensive replication strand bias (Gierlik et al.,
2000). P. abyssi and Sulfolobus acidocaldarius also have
small Okazaki fragments (Matsunaga et al., 2002), which
could explain the lower biases typically found in archaea
(Lopez & Philippe, 2001). Finally, some bacteria are more
exposed than others to DNA mutagenic agents. Obligately
intracellular bacteria may be particularly well protected
from this point of view, and this could partly explain why
they tend to exhibit higher biases.
1616
Oligonucleotide bias
Oligonucleotide frequency and distribution in chromosomes is far from random, even when the relative
frequencies of the sub-sequences they contain are taken
into account (Karlin & Brendel, 1992). Further, oligonucleotide usage differs between the two replicating strands
(Lopez et al., 1999; Mrázek & Karlin, 1998; Rocha et al.,
1998; Salzberg et al., 1998). This is the result of the
overlapping of different factors such as composition strand
bias, replication signals or the asymmetric distribution of
genes and corresponding regulatory signals in the two
replicating strands. If a genome has a high translationassociated codon usage bias, the differential distribution
of genes in the two strands may relate in a complicated
way to composition strand bias (Musto et al., 2003; Romero
et al., 2000). Therefore, oligonucleotide bias is the result
of conflicting biases associated with signals related to
different cellular processes (Trifonov, 1989). For example,
the sequence signalling the ribosome-binding site (RBS) is
very often found in the leading strand of B. subtilis. This
is partly because it is G-rich and C-poor, but most
fundamentally because 75 % of the genes of this genome
are in the leading strand. Similarly, stretches of T’s are often
related to the presence of rho-independent terminators
(d’Aubenton Carafa et al., 1990), and thus are more often
found in the leading strand.
Chi sequences are cis-acting DNA elements that enhance
recombination promoted by the RecBCD pathway in E. coli
(Smith, 1988). These sequences are overrepresented (75 %)
in the leading strand of E. coli (Blattner et al., 1997), which
allows collapsed or reversed replication forks to be protected against exonuclease degradation and to be preferentially used as a recombination substrate (Gruss & Michel,
2001). However, these sequences are GT-rich and include
triplets corresponding to frequent codons. Thus doubts
remain as to the biological significance of this overrepresentation in E. coli (Bell et al., 1998; Biaudet et al., 1998;
Uno et al., 2000). Furthermore, very different chi sequences
have been found in Haemophilus influenzae and B. subtilis,
where the leading strand bias is much less pronounced
(El Karoui et al., 1999). Such an overlapping of signals
and biases complicates the understanding of the biological
reasons behind most oligonucleotide avoidance or overrepresentation (Burge et al., 1992; Mrázek & Karlin, 1998;
Salzberg et al., 1998).
Gradients along the replichores
Gene distribution
Gene dosage effects. When the time required to repli-
cate the chromosome exceeds the duplication time, the
dosage of genes near the origin in the cell increases exponentially with the number of simultaneous replication
rounds. Fast-growing bacteria, such as E. coli or B. subtilis,
with multiple simultaneous replication rounds selectively
accumulate highly expressed genes near the replication
origin because of this effect (Fig. 6). The moderately
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Replication and bacterial chromosome structure
70
Ori
Frequency of genes (%)
60
50
50
40
40
30
30
20
20
10
0
Ter
10
rRNA
0
B. subtilis
E. coli
C. crescentus
M. tuberculosis
fast-growing Caulobacter crescentus has an optimal duplication time of 90 min, which is more than that necessary
to replicate its chromosome (i.e. ori/ter ¡2). Presumably
this does not carry sufficient selective advantage to constrain these genes to the vicinity of the origin, and in
slow-growing bacteria there is no appreciable bias in the
distribution of highly expressed genes along the replichore
(Fig. 6). Although gene dosage effects have rarely been
tested experimentally, they have been frequently invoked
to explain the deleterious effect of chromosomal rearrangements (Liu & Sanderson, 1996; Roth et al., 1996). Experimentally induced inversions in the E. coli chromosome
altering the distance of genes to the origin of replication
can lead to halving growth rates (Louarn et al., 1985).
Similarly, systematic translocations of an expressed gene
in the Salmonella enterica serovar Typhimurium chromosome indicate that its positioning closer to the origin
leads to higher expression levels (Schmid & Roth, 1987).
Essential genes are also not randomly placed along the
replichore, but this is not an intrinsic feature of essential
genes, being caused by the overrepresentation of highly
expressed genes in this subset (Fig. 7). Thus among the
constraints imposed by replication on the distribution of
genes in the bacterial chromosome, expression plays a role
in the distribution of genes as a function of the distance
to the origin of replication, whereas essentiality constrains
the replicating strand where genes are coded.
rRNA operons. In E. coli cells growing at exponential
rate, rRNA corresponds to 80 % of the total RNA and
50 % of all transcription taking place in the cell (Bremer
& Dennis, 1996). Although in slow-growing bacteria this
proportion is likely to be smaller, rRNA components
are arguably among the most highly expressed genes
in bacteria. As a result, many genomes show a strong
http://mic.sgmjournals.org
Fig. 6. Frequency in each third of the chromosome of rDNA operons in 68 bacterial
genomes (left) and of highly expressed
protein coding sequences in four genomes
(right). Highly expressed genes were defined
as the top 10 % highest CAI values in the
genome (Sharp & Li, 1987).
concentration of multiple rRNA operons near the origin
of replication (Fig. 6). The exceptions to this trend are
slow-growing bacteria such as Mycoplasma and Mycobacterium, which often have one single rRNA operon
closer to the terminus than to the origin of replication.
The compartmentalization of transcription and translation
studied through GFP fusions in B. subtilis shows that
RNAP is located within the nucleoid, whereas the ribosomes are located predominantly towards the cell poles
close to or in contact with the membrane (Lewis et al.,
2000). At higher growth rates transcription foci are close
to the origin of replication, presumably because most
highly expressed genes are located there. In B. subtilis the
10 rRNA operons are arranged in four groups (Kunst
et al., 1997). The largest one contains seven operons
placed very close to the origin of replication (<175 kb),
and recent data indicate that only these operons are
included in transcription foci, even though the other
operons are transcribed at significant rates (Davies &
Lewis, 2003). Because of gene dosage effects, the operons
most distant from ori account for less than 10 % of all
rRNA transcription at high growth rates in B. subtilis.
Significant expression and regulatory response heterogeneity is also found among the seven E. coli operons,
with operons further from the origin showing less expressiveness and/or smaller response to standard transcriptional activators (Condon et al., 1993). It is tempting,
then, to speculate that ribosomes closer to the origin are
dedicated to translating standard structural genes, such
as ribosomal proteins, whereas the other ribosomes are
dedicated to other types of transcripts. It has often been
suggested that phenotypic heterogeneity in the translation
machinery of bacteria could be selected to increase population adaptability (Mikkola & Kurland, 1991; Norris &
Madsen, 1995). In this case, a determinant variable for the
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E. P. C. Rocha
50
E. coli
40
30
20
No. of essential genes
10
10
20
30
40
Distance to the origin (% chromosome)
50
80
70
B. subtilis
60
positioning away from the origin. Second, local hyperrecombination at dif sites would favour the insertion of
horizontally transferred sequences. However, in B. subtilis
HGT at the terminus is mostly caused by the presence of
one single large SPb prophage (Kunst et al., 1997). Similarly,
in E. coli, lambdoid prophages tend to cluster closer to
the terminus of replication (Campbell, 1992), and it has
recently been suggested that hyper-recombination in the
E. coli ter region is mostly caused by these sites (Corre et al.,
2000). The availability of a large number of genomes from
bacteria closely related to E. coli, B. subtilis and Streptococcus
pneumoniae allows the reappraisal of these analyses by
identifying genes arising from HGT. The results suggest a
very small bias towards larger rates of HGT in the second
half of the chromosome for enterobacteria and Streptococcus, and smaller than expected HGT in the terminus of
Bacillus (Fig. 8). Although the regions immediately adjacent
to the origin seem to underrepresent HGT systematically,
there is no clear bias for an overrepresentation of HGT at
the terminus.
50
Heterogeneities in nucleotide composition
40
30
20
10
10
20
30
40
Distance to the origin (% chromosome)
50
Fig. 7. Distribution of essential genes as a function of the distance (%) to the origin of replication in E. coli and B. subtilis.
A black bar represents essential highly expressed genes,
whereas a white bar represents essential non-highly expressed
genes. Essential genes were retrieved from the literature for B.
subtilis (Kobayashi et al., 2003) and from the PEC database
for E. coli (http://www.shigen.nig.ac.jp/ecoli/pec/). Highly
expressed genes were defined as the top 10 % CAI values in
the genome (Sharp & Li, 1987).
assignment of ribosomes to their dedicated role would
be the distance of the respective operons to the origin of
replication.
Phage integration and gene transfer
The genomes of B. subtilis (Kunst et al., 1997) and E. coli
K-12 (Blattner et al., 1997) show A+T-rich ter regions
associated with the presence of prophages. Since recombination is involved in the resolution of the replicated
chromosomes and in the integration of horizontally transferred genes, it was tempting to relate the two. Horizontal
gene transfer (HGT) was suggested to cluster near the
terminus of replication because of two effects. First,
because horizontally transferred genes are typically weakly
(or not) expressed, gene dosage effects would lead to their
1618
Early analyses of nucleotide composition in bacterial
genomes showed high inter-genomic (Sueoka, 1962) but
low intra-genomic (Rolfe & Meselson, 1958) variability.
Further, each bacterial lineage has a characteristic pattern
of codon usage, which is determined by several factors
such as its G+C content, its tRNA set and gene expression levels (Grantham et al., 1980; Ikemura, 1981). These
observations led to the development of HGT detection
methods based on sequence composition (Lawrence &
Ochman, 1997; Médigue et al., 1991). These methods
assume that nucleotide composition is relatively uniform
along the chromosome. However, G+C content among
genes expressed at low levels is lower in late-replicating
regions of the E. coli genome (Deschavanne & Filipski,
1995). It also shows significant variations, although not in
function of replichore position, in Mycoplasma genitalium
(Kerr et al., 1997). This may lead to an overestimation of
HGT by methods based on nucleotide composition,
although real HGTs are most often found by these methods
(Daubin et al., 2003). These results have recently been
confirmed and extended by an analysis using several
complete genomes (Daubin & Perriere, 2003). Half of the
sequenced genomes show A+T-richness at the terminus
of replication, with a significant proportion of the others
showing significant heterogeneities along the chromosome
not coincident with the replication terminus. Tests done in
E. coli, Chlamydia and Helicobacter showed that HGT was
not the cause of these heterogeneities and one must then
conclude that the composition of bacterial chromosomes is
more heterogeneous than previously thought. Most of the
heterogeneity is correlated with the organization of the
chromosome relative to replication, although this leads to
smaller differences in nucleotide composition than compositional strand bias (Fig. 9).
The mechanisms establishing these replichore compositional
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Replication and bacterial chromosome structure
E. coli/S. enterica
750
500
250
250
200
150
100
50
Bacillus/Listeria
No. of HTGs
Streptococcus
750
500
250
0
10
20
30
40
Distance to the origin (%)
50
Fig. 8. Distribution of HGT elements in the replichore of three
bacterial groups. The E. coli group includes the strains K-12,
O157 : H7 and CFT073, Shigella flexneri, Salmonella enterica
serovar Typhimurium and Salmonella enterica serovar Typhi.
The Bacillus group includes B. subtilis, Bacillus halodurans,
Oceanobacillus iheyensis, Listeria monocytogenes and Listeria
innocua. The Streptococcus group includes two strains of
Streptococcus pyogenes, Streptococcus pneumoniae and
Streptococcus agalactiae and one strain of Streptococcus
mutans. In each group one counts as HGT every gene that
does not have an orthologue in any of the other genomes.
Orthologues were defined as in Rocha & Danchin (2001).
gradients are probably highly variable. The genome of
Corynebacterium diphtheriae shows a remarkably lower
G+C content at the terminus, but the closely related, and
largely co-linear, genome of Corynebacterium efficiens does
not show such a pattern (Cerdeno-Tarraga et al., 2003). The
mutation rates of TARGC transitions and transversions
in a lacZ revertant in four loci along the chromosome
of S. enterica serovar Typhimurium showed significant
heterogeneities, but not a clear gradient in the direction
origin to terminus (Hudson et al., 2002). However, ATrichness near the terminus is the result of the balance
between GCRAT and TARGC mutations, and this balance
has yet to be analysed. Two other possible causes for
replichore compositional gradients can be proposed. First,
the recombination at dif sites may induce a bias associated
with replication and/or repair of the end of both concatenates (see Daubin & Perriere, 2003, and references therein).
Second, if the end of replication is taking place in conditions
http://mic.sgmjournals.org
Fig. 9. Compositional bias is the difference in G and C
between genes in the lagging and leading strands of 87
genomes (mean values DG=”2?1 % and DC=1?9 %). G+Cpoorness at the terminus is the difference in G and C between
genes in the 90 % of the genome around the origin and the
10 % around the terminus of replication (mean values
DG=0?3 % and DC=0?2 %). When the chromosomes are
spliced 50 : 50 (%), the differences are smaller (mean values
DG=0?1 % and DC=0?1 %). The graphs represent box-plots,
where the boxes delimitate the 1st and 3rd quartiles. The
centre of the diamond indicates the mean, which is always
significantly different from zero (P<0?01).
of depleted nutrients, then A+T-richness at the terminus
could result from the relatively larger availability of these
nucleotides in bacterial cells (Rocha & Danchin, 2002; Sharp
et al., 1989). Exponentially growing bacteria are simultaneously replicating regions near the terminus and origin of
replication, and no base composition heterogeneity should
be observed under these circumstances. However, under low
growth rates, for which the condition of depleted nutrients
is more plausible, nucleotide scarcity may be important for
the late-replicating regions of the chromosome. Given the
underrepresentation of guanine and cytosine in the bacterial cytosol (Danchin et al., 1984), nucleotide scarcity
would lead to an A and T enrichment at the terminus
region. Since A+T-richness shows a significant increase
just at the vicinity of the terminus, this would suggest a
sudden decrease of the G+C nucleotide pool at the end of
chromosome replication.
Rate of sequence change
Sharp et al. (1989) found that genes near the origin of
replication of E. coli had synonymous substitution rates,
after accounting for codon usage bias, that were a half
smaller than those of genes near the terminus. This analysis
included the available 67 pairs of orthologues between E. coli
and S. enterica serovar Typhimurium, and the major effect
was observed in genes very close to the origin (which contain
many highly conserved genes). Recent analysis of closely
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E. P. C. Rocha
related complete genomes, including E. coli and S. enterica
serovar Typhimurium (Mira & Ochman, 2002), confirmed
the widespread existence of such bias. However, after
controlling for expression levels, using measures of codon
usage bias, the distance of the gene to the origin of replication accounts for only ~5 % of the variance in substitution rates along the replichore. More recent work has
shown that synonymous substitution rates are relatively
constant throughout the replichore, with the exception of
the G+C-poor regions immediately next to the terminus
of replication (Daubin & Perriere, 2003). Thus it is tempting to correlate the variation of substitution rates with
distance to the origin with the nucleotide bias along the
replichore that was mentioned in the previous section.
Open questions for research
The coupling of replication biases and segregation
Bacteria segregate their chromosomes without a mitotic
apparatus. Following replication start, the origins rapidly
move apart to opposite poles of the cell, whereas the
terminus of replication is located at the cell centre. The
remaining chromosome is between the pole and the cell
centre (for a recent review see Errington et al., 2003). Recent
work has suggested an important role of the chromosome
replication structure in chromosome segregation, both at
the origin and at the terminus of replication.
The intriguing rapid separation of replication origins
after replication led to the search for sequence signals that
might drive the process. Lin & Grossman (1998) identified
a degenerate 16 bp DNA signal, present 10 times in the
chromosome, always near the origin, eight instances of
which were found to bind to the partitioning protein
Spo0J in vivo. However, recent data show that these sites
are not necessary for segregation (Wu & Errington, 2002),
and the quest for such putative motifs continues. A very
different view of the partition process suggests that the
random diffusion of DNA is transiently constrained by the
process of co-transcriptional translation and translocation
(named transertion) of membrane proteins (Norris &
Madsen, 1995; Woldringh et al., 1995). After initiation of
DNA replication, the positioning of transertion areas near
the origin of replication might create a bidirectional expansion force leading to the separation of the chromosomes
(Woldringh, 2002). Recent evidence from genome analysis
suggests that highly expressed genes placed asymmetrically
relative to the origin of replication could also result in a
mechanism of chromosome segregation. This could result
from two different effects. First, the motor force of RNAP,
whose movements are restricted in the cell, could pull
the replication origins apart when transcribing the highly
expressed genes near the origin (Dworkin & Losick, 2002).
Second, highly expressed genes are distributed asymmetrically around the origin in both B. subtilis and E. coli, which
coupled with transcriptional effects and hemi-methylated
DNA could result in chromosome segregation and bacterial
differentiation (Rocha et al., 2003).
1620
The terminus region, being the last to be replicated and
segregated, is present at the cell centre during termination
(Errington et al., 2003). Site-specific recombination for
chromosome dimer resolution is coupled to cell division
by the presence of the FtsK protein at the dif site (Perals
et al., 2001). FtsK forms a ring-like structure at the cell
centre, and may be involved in guiding the regions flanking
the dif sites in dimeric chromosomes towards the septum,
so that synapsis and recombination can occur (Corre &
Louarn, 2002; Li et al., 2003). A model has been proposed
to explain the connection between segregation and dimer
resolution (Corre & Louarn, 2002). When the septum is
closing, the FtsK rings around the DNA threads mobilize
them to place the dif site exactly under the septum. The
recognition of the direction in which DNA should be
pumped by the translocase would be made by the asymmetric distribution of polar motifs in the chromosome
(Capiaux et al., 2001). Recent results suggest that such
motifs could be widespread in bacterial genomes, thus connecting the opposing composition of leading and lagging
strands with signals that are increasingly biased between the
strands near the terminus of replication (Lobry & Louarn,
2003). The regular polarized distribution of these motifs
could impose significant limitations to chromosome inversions and HGT (Lawrence & Hendrickson, 2003). All this
suggests a much closer integration between replication,
segregation, transcription and the chromosome structure
than previously thought.
Understanding replication from the organization it
induces
The analysis of replication biases in genomes has been
useful in the understanding of replication itself. A first
obvious use of this information resulted in the identification of putative replication origins in most bacterial
genomes. Composition strand bias also directed experimental work to the identification of replication origins in
the linear chromosome of B. burgdorferi (Picardeau et al.,
1999) and the first identification of an origin of replication in an archaeon (Myllykallio et al., 2000). Yet some
genomes lack all types of replication bias. These include
several cyanobacteria, Aquifex and Thermotoga (Fig. 4) as
well as most archaea. Could this be caused by different
replication mechanisms, e.g. lack of a unique origin of replication (Mrázek & Karlin, 1998)? Interestingly, two recently
sequenced genomes of closely related c-proteobacteria
obligate symbionts lack a gene encoding DnaA, opening
the possibility that they might lack a unique origin of
replication. However, whereas Wigglesworthia glossinidia
lacks significant compositional strand bias (Akman et al.,
2002), Blochmannia floridanus shows a very strong one
(Gil et al., 2003). Therefore, although W. glossinidia is the
only case of absence of significant compositional strand
bias among c-proteobacteria, this does not allow any
conclusions to be drawn regarding the association of the
loss of DnaA and strand biases. Recent experimental work
suggests that Methanocaldococcus jannaschii may have more
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Replication and bacterial chromosome structure
than one replication origin (Maisnier-Patin et al., 2002). A
genome with multiple potential replication origins would
lack strand biases because successive replication rounds
starting at different locations would be continuously
redefining the replication strand of each region. This
would level off any eventual biases.
Still, one wonders how genomes lacking replicationassociated biases can overcome the problems caused by
DNAP and RNAP collisions. Although many phages present
strand biases (Grigoriev, 1999), other phages, such as T4
and w29, have mechanisms to deal with head-on collisions.
In T4 the absence of the t-subunit of DNAP may prevent
the physical coupling of the two DNAPs in the replicating
fork (Alberts et al., 1983). Possibly as a result of this, it has
been found that T4 replication forks can bypass oppositely
oriented stalled transcription complexes in vitro (Liu &
Alberts, 1995). The linear B. subtilis phage w29 is replicated
from both extremities in such a way that it does not have
lagging strands and both transcription orientations result
in head-on and co-oriented collisions. In this phage cooriented collisions lead, as in E. coli, to replication slowdown, which is probably caused by the DNAP following
an actively transcribing RNAP (Elias-Arnanz & Salas, 1997).
On the other hand, head-on collisions are dealt with in
such a way that the DNAP by-passes RNAP without displacing it, in a mechanism that is probably different from
that of T4 (Elias-Arnanz & Salas, 1999). It remains to be
investigated whether bacteria lacking replication bias have
also found ways of dealing with the problem of collision
between polymerases.
Challenges to the chromosomal structure
The availability of more than 100 bacterial genomes allows
the comparative evolutionary analysis of genome structure
and bacterial lifestyle. The most significant compositional
strand biases have been found in obligately intracellular
bacteria (Fig. 5). The reasons for this are not quite clear.
Although these genomes have lost a significant part of
their repair mechanisms, so have the small genomes of
mycoplasmas, which do not have strong compositional
biases but do have strong gene strand bias. The association
between obligately intracellular niches and compositional
strand bias may be caused by the extreme stability of most
of these genomes (Tamas et al., 2002). Mycoplasmas, which
are less stable, show lower compositional strand bias.
Repeats induce frequent chromosomal rearrangements,
and may thus reduce strand biases (Rocha et al., 1999b).
Genomes depleted of repeats would then be more stable
and thus accumulate larger compositional strand bias
(Achaz et al., 2003; Frank et al., 2002). For example,
B. burgdorferi has the strongest compositional strand bias
and is nearly devoid of repeats. However, its plasmids
contain a significant number of repeats, and a much
smaller compositional strand bias (Picardeau et al., 2000).
GC skews have been used to infer patterns of rearrangements between chromosomes (Grigoriev, 2000; Zivanovic
et al., 2002), although the rapidity of strand adaptation
http://mic.sgmjournals.org
limits this analysis to close genomes. Gene strand biases
are relatively insensitive to different bacterial lifestyles
(Rocha, 2002), but as shown above, the distribution of
highly expressed genes along the replichore is highly biased
for fast-growing bacteria.
These biases impose constraints on chromosomal rearrangements. On the other hand, rearrangement rates accelerate
with the number of repeated elements in bacterial
chromosomes (Rocha, 2003), which are maintained by
either selfish systems (e.g. insertion sequences) or selection
for elements capable of generating genetic diversity (e.g. for
antigenic variation). It has been observed that repeats tend
to be placed in the chromosome in such a way that the
rearrangements they may induce provoke smaller disruptions to the chromosomal replication structure than
expected by chance (Achaz et al., 2003). Further, there is
an important negative correlation in bacteria between
the number of repeats and the replication strand bias. This
suggests a trade-off between the advantages associated with
chromosomes organized in function of replication and the
rearrangement events caused by repeats. Rearrangements
involving the change of the positioning of genes relative to
the origin of replication and from one replicating strand
to another lead to lower growth rates (Campo et al., 2004;
Louarn et al., 1985; Segall et al., 1988; Wu & Errington,
2002). The fitness impact of such rearrangements is correlated with the degree of replication-associated disorganization they induce in the chromosomal structure. In some
cases, inversions seem to be more deleterious than sequence
deletion. For example, E. coli strains show moderate fitness
loss upon loss of the region around the terminus (Henson
& Kuempel, 1985). However, many inversions near the
terminus of this chromosome are non-permissive, allegedly
because they disrupt the structure allowing correct termination and segregation of the chromosomes (Guijo et al.,
2001). Given the organization of genomes relative to replication, rearrangements strongly disrupting the chromosome
structure are naturally bound to be deleterious (Mackiewicz
et al., 2001a). Therefore, most fixed large chromosomal
rearrangements have led to small structural changes in the
chromosome relative to the replication (Eisen et al., 2000;
Suyama & Bork, 2001; Tillier & Collins, 2000c). The understanding of the interplay between organizing features of the
chromosome, such as replication, and elements inducing
sequence variation and chromosomal rearrangements will
allow an explanation of why different genomes show such
different levels of organization and how this relates with
their evolutionary history and ecology.
Conclusion
Bacterial genomes do not show the heterogeneity in coding
density and nucleotide composition characteristic of the
genomes of many eukaryotes. Still, they do show important
variations regarding several aspects of genome organization,
many of which relate to the asymmetries induced by the
mechanism of chromosome replication. Interestingly, one
single key asymmetry may lead to different biases. For
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E. P. C. Rocha
example, compositional strand bias and gene strand bias
both originate in the asymmetric nature of the replication
fork that divides the chromosome in leading and lagging
strands. Yet the two biases are poorly correlated (Rocha,
2002; Tillier & Collins, 2000a). This is because their direct
cause is different: in one case asymmetric exposure of
ssDNA creates asymmetric composition, whereas in the
other case the collision between polymerases favours leading strand genes. In Table 1, I summarize the different
types of bias that have been found and their mechanistic
basis. I also tentatively assign to each bias a mutational or
selective basis. In some cases, e.g. compositional strand
bias or gene strand bias, such assignment is relatively
straightforward, but in others it is not. It is also not unlikely
that in some cases mutational biases have been recruited
for other (eventually selective) purposes. In any case,
comparative genome analysis will have to take such biases
progressively into account in oligonucleotide frequency
or even phylogenetic studies, since the evolution of the
sequences clearly depends on their location in the chromosome. The current flood of bacterial genome data will
probably provide new information relating the subjects
discussed in this article. However, experimental work in
organisms other than E. coli will be of utmost importance
in understanding the diversity of biases associated with
bacterial replication. The wealth of expression data coming
from genomics and microbial cell biology may also allow
a better understanding of the associations between replication associated biases and other structuralizing variables
such as cell division, gene expression and compartmentalization of the cell.
Note added in proof
While this review was going to press, Le Chatelier et al.
(2004) provided further evidence for the asymmetric
nature of replication forks in B. subtilis. Massey et al.
(2004) show that the previously proposed RAG polarized
motifs (Capiaux et al., 2001; Lobry & Louarn, 2003) are not
implicated in the mobilization of DNA by FtsZ. It is yet
uncertain if another of these polarized motifs plays a role
in chromosome segregation. Furthermore, two papers
have been published demonstrating multiple origins of
replication in the archaeon Sulfolobus (Robinson et al.,
2004; Lundgren et al., 2004). Sulfolobus solfataricus and
Sulfolobus acidocaldarius have three synchronous replication
origins that are unevenly distributed in the chromosome.
All the forks progress at the rate of ~80–100 nt s21, leading
to asynchronous termination. It remains to be understood
how replication termination and chromosome segregation
take place under these circumstances, but this explains the
mixed patterns obtained in GC skew analyses of these
genomes. These results also show the mixed character of
archaeal replication, which shares resemblances with that
of prokaryotes and eukaryotes. It is thus most likely that
part of the replication-associated structure of bacterial
genomes described in this review is common to only some
of the archaeal genomes.
Table 1. Comparative analysis of the different biases arising in chromosomes from the asymmetric replication mechanisms
operating in bacterial cells
A ‘?’ indicates when there still seems to be a lack of a consensus in the community about the subject, or the available data are still scarce.
See comments and references in the text.
Replication bias
Selection/
mutation
Effect
Between strands
Nucleotide composition
Gene distribution I
M
S
Gene distribution II
S
Glead/Glag & Clead/Clag and Tlead/Tlag > Alead/Alag
Most essential genes are coded in the leading
strand
Most genes are coded in the leading strand
Palindrome deletion
M
S (?)
x sites
Along replichores
Gene distribution
Nucleotide composition
Rate of sequence evolution
Both
Polarized motifs
1622
S
M
M (?)
S (?)
Large palindromes are deleted
x sites are more abundant in the leading strand
Major basis of the bias
Chemical vulnerability of ssDNA
Collisions between DNAP and RNAP
Collisions between DNAP and RNAP;
DNAP composition
Slipped mispair in ssDNA
Recombination repair of stalled replication
forks
Highly expressed genes cluster near the origin
A+T-rich terminus
Gene dosage in fast-growing bacterial cells
Prophages, recombination (?), nucleotide
scarcity (?)
Sequence divergence increases along the replichore Recombination (?), nucleotide scarcity (?)
Some motifs are overrepresented in the leading
strand and near dif sites
Chromosome segregation and resolution (?)
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Microbiology 150
Replication and bacterial chromosome structure
Bruck, I. & O’Donnell, M. (2000). The DNA replication machine of a
Acknowledgements
I am much indebted to the persons with whom I’ve worked and
discussed the issues related to this review, and in particular to Antoine
Danchin, Alain Viari and Vic Norris. Antoine Danchin, Guillaume
Achaz and Vincent Daubin have given helpful criticisms and suggestions on earlier versions of this manuscript. Irina Artsimovitch
provided helpful comments on the differences between RNAP in
B. subtilis and E. coli.
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