DoriC: a database of oriC regions in bacterial genomes

Replication origins (oriCs) of bacterial genomes currently available in GenBank have been predicted by using a systematic method comprising the Z-curve analysis for nucleotide distribution asymmetry, DnaA box distribution, genes adjacent to candidate oriCs and phylogenetic relationships. These oriCs are organized into a MySQL database, DoriC, which provides extensive information and graphical views of the oriC regions. In addition, users can Blast a query sequence or even a whole genome against DoriC to find a homologous one. DoriC will be updated timely and the latest version is DoriC 1.8, in which oriCs of 425 genomes (468 chromosomes) are identified. AVAILABILITY: DoriC can be accessed from http://tubic.tju.edu.cn/doric/. SUPPLEMENTARY INFORMATION: Supplementary data are available at http://tubic.tju.edu.cn/doric/supplementary.htm.     

Identification of replication origins in prokaryotic genomes

The availability of hundreds of complete bacterial genomes has created new challenges and simultaneously opportunities for bioinformatics. In the area of statistical analysis of genomic sequences, the studies of nucleotide compositional bias and gene bias between strands and replichores paved way to the development of tools for prediction of bacterial replication origins. Only a few (about 20) origin regions for eubacteria and archaea have been proven experimentally. One reason for that may be that this is now considered as an essentially bioinformatics problem, where predictions are sufficiently reliable not to run labor-intensive experiments, unless specifically needed. Here we describe the main existing approaches to the identification of replication origin (oriC) and termination (terC) loci in prokaryotic chromosomes and characterize a number of computational tools based on various skew types and other types of evidence. We also classify the eubacterial and archaeal chromosomes by predictability of their replication origins using skew plots. Finally, we discuss possible combined approaches to the identification of the oriC sites that may be used to improve the prediction tools, in particular, the analysis of DnaA binding sites using the comparative genomic methods.     

Identification of replication origins in archaeal genomes based on the Z-curve method

The Z-curve is a three-dimensional curve that constitutes a unique representation of a DNA sequence, i.e., both the Z-curve and the given DNA sequence can be uniquely reconstructed from the other. We employed Z-curve analysis to identify one replication origin in the Methanocaldococcus jannaschii genome, two replication origins in the Halobacterium species NRC-1 genome and one replication origin in the Methanosarcina mazei genome. One of the predicted replication origins of Halobacterium species NRC-1 is the same as a replication origin later identified by in vivo experiments. The Z-curve analysis of the Sulfolobus solfataricus P2 genome suggested the existence of three replication origins, which is also consistent with later experimental results. This review aims to summarize applications of the Z-curve in identifying replication origins of archaeal genomes, and to provide clues about the locations of as yet unidentified replication origins of the Aeropyrum pernix K1, Methanococcus maripaludis S2, Picrophilus torridus DSM 9790 and Pyrobaculum aerophilum str. IM2 genomes.     

Multiple origins of replication in archaea

Until recently, the only archaeon for which a bona fide origin of replication was reported was Pyrococcus abyssi, where a single origin was identified. Although several in silico analyses have suggested that some archaeal species might contain more than one origin, this has only been demonstrated recently. Two studies have shown that multiple origins of replication function in two archaeal species. One study identified two origins of replication in the archaeon Sulfolobus solfataricus, whereas a second study used a different technique to show that both S. solfataricus and Sulfolobus acidocaldarius have three functional origins. These are the first reports of archaea having multiple origins. This finding has implications for research on the mechanisms of DNA replication and evolution.     

Origins of Replication in Sorangium cellulosum and Microcystis aeruginosa.

The genome of Sorangium cellulosum has recently been completely sequenced, and it is the largest bacterial genome sequenced so far. In their report, Schneiker et al. (in Complete genome sequence of the myxobacterium Sorangium cellulosum, Nat. Biotechnol., 2007, 25, 1281-1289) concluded that 'In the absence of the GC-skew inversion typically seen at the replication origin of bacterial chromosomes, it was not possible to discern the location of oriC'. In addition, the complete genome of Microcystis aeruginosa NIES-843 has also been recently sequenced, and in this report, Kaneko et al. (in Complete genomic structure of the bloom-forming toxic cyanobacterium Microcystis aeruginosa NIES-843, DNA Res., 2007, 14, 247-256) concluded that 'there was no characteristic pattern, according to GC skew analysis'. Therefore, oriC locations of the above genomes remain unsolved. Using Ori-Finder, a recently developed computer program, in both genomes, we have identified candidate oriC regions that have almost all sequence hallmarks of bacterial oriCs, such as asymmetrical nucleotide distributions, being adjacent to the dnaN gene, and containing DnaA boxes and repeat elements.     

Multiple replication origins of the archaeon Halobacterium species NRC-1

The genomic sequence of the halophilic archaeon Halobacterium NRC-1 has been analyzed by the Z curve method. The Z curve is a three-dimensional curve that uniquely represents a given DNA sequence. Based on the known behaviors of the Z curves for the archaea whose replication origins have been identified, the analysis of the Z curve for the genome of Halobacterium NRC-1 strongly suggests that the large genome has two replication origins, oriC1 (921,863-922,014) and oriC2 (1,806,444-1,807,229), which are located at two sharp peaks of the Z curve. These two regions are next to the cdc6 genes and contain multiple copies of stretches of G and C, i.e., ggggtgggg and ccccacccc, which may also be regarded as direct and inverted repeats. Based on the above analysis, a model of replication of Halobacterium NRC-1 with two replication origins and two termini has been proposed. The experimental confirmation of this model would constitute the first example of multiple replication origins of archaea, which will finally provide much insight into the understanding of replication mechanisms of eukaryotic organisms, including human. In addition, the potential multiple replication origins of the archaeon Sulfolobus solfataricus are suggested by the analysis based on the Z curve method.     

Recognition of Protein-coding Genes Based on Z-curve Algorithms

Recognition of protein-coding genes, a classical bioinformatics issue, is an absolutely needed step for annotating newly sequenced genomes. The Z-curve algorithm, as one of the most effective methods on this issue, has been successfully applied in annotating or re-annotating many genomes, including those of bacteria, archaea and viruses. Two Z-curve based ab initio gene-finding programs have been developed: ZCURVE (for bacteria and archaea) and ZCURVE_V (for viruses and phages). ZCURVE_C (for 57 bacteria) and Zfisher (for any bacterium) are web servers for re-annotation of bacterial and archaeal genomes. The above four tools can be used for genome annotation or re-annotation, either independently or combined with the other gene-finding programs. In addition to recognizing protein-coding genes and exons, Z-curve algorithms are also effective in recognizing promoters and translation start sites. Here, we summarize the applications of Z-curve algorithms in gene finding and genome annotation.     

The Z curve database: a graphic representation of genome sequences

MOTIVATION: Genome projects for many prokaryotic and eukaryotic species have been completed and more new genome projects are being underway currently. The availability of a large number of genomic sequences for researchers creates a need to find graphic tools to study genomes in a perceivable form. The Z curve is one of such tools available for visualizing genomes. The Z curve is a unique three-dimensional curve representation for a given DNA sequence in the sense that each can be uniquely reconstructed given the other. The Z curve database for more than 1000 genomes have been established here. RESULTS: The database contains the Z curves for archaea, bacteria, eukaryota, organelles, phages, plasmids, viroids and viruses, whose genomic sequences are currently available. All the 3-dimensional Z curves and their three component curves are stored in the database. The applications of the Z curve database on comparative genomics, gene prediction, computation of G+C content with a windowless technique, prediction of replication origins and terminations of bacterial and archaeal genomes and study of local deviations from the Chargaff Parity Rule 2 etc. are presented in detail. The Z curve database reported here is a treasure trove in which biologists could find useful biological knowledge.     

Genome DNA Sequence Variation, Evolution, and Function in Bacteria and Archaea

Comparative genomics has revealed that variations in bacterial and archaeal genome DNA sequences cannot be explained by only neutral mutations. Virus resistance and plasmid distribution systems have resulted in changes in bacterial and archaeal genome sequences during evolution. The restriction-modification system, a virus resistance system, leads to avoidance of palindromic DNA sequences in genomes. Clustered, regularly interspaced, short palindromic repeats (CRISPRs) found in genomes represent yet another virus resistance system. Comparative genomics has shown that bacteria and archaea have failed to gain any DNA with GC content higher than the GC content of their chromosomes. Thus, horizontally transferred DNA regions have lower GC content than the host chromosomal DNA does. Some nucleoid-associated proteins bind DNA regions with low GC content and inhibit the expression of genes contained in those regions. This form of gene repression is another type of virus resistance system. On the other hand, bacteria and archaea have used plasmids to gain additional genes. Virus resistance systems influence plasmid distribution. Interestingly, the restriction-modification system and nucleoid-associated protein genes have been distributed via plasmids. Thus, GC content and genomic signatures do not reflect bacterial and archaeal evolutionary relationships.     

Gene recognition from questionable ORFs in bacterial and archaeal genomes

The ORFs of microbial genomes in annotation files are usually classified into two groups: the first corresponds to known genes; whereas the second includes 'putative', 'probable', 'conserved hypothetical', 'hypothetical', 'unknown' and 'predicted' ORFs etc. Since the annotation is not 100% accurate, it is essential to confirm which ORF of the latter group is coding and which is not. Starting from known genes in the former, this paper describes an improved Z curve method to recognize genes in the latter. Ten-fold cross-validation tests show that the average accuracy of the algorithm is greater than 99% for recognizing the known genes in 57 bacterial and archaeal genomes. The method is then applied to recognize genes of the latter group. The likely non-coding ORFs in each of the 57 bacterial or archaeal genomes studied here are recognized and listed at the website http://tubic.tju.edu.cn/ZCURVE_C_html/noncoding.html. The working mechanism of the algorithm has been discussed in details. A computer program, called ZCURVE_C, was written to calculate a coding score called Z-curve score for ORFs in the above 57 bacterial and archaeal genomes. Coding/non-coding is simply determined by the criterion of Z-curve score > 0/ Z-curve score < 0. A website has been set up to provide the service to calculate the Z-curve score. A user may submit the DNA sequence of an ORF to the server at http://tubic.tju.edu.cn/ZCURVE_C/Default.cgi, and the Z-curve score of the ORF is calculated and returned to the user immediately.     

The sequence requirements for a functional Escherichia coli replication origin are different for the chromosome and a minichromosome

We have developed a simple three-step method for transferring oriC mutations from plasmids to the Escherichia coli chromosome. Ten oriC mutations were used to replace the wild-type chromosomal origin of a recBCsbcB host by recombination. The mutations were subsequently transferred to a wild-type host by transduction. oriC mutants with a mutated DnaA box R1 were not obtained, suggesting that R1 is essential for chromosomal origin function. The other mutant strains showed the same growth rates, DNA contents and cell mass as wild-type cells. Mutations in the left half of oriC, in DnaA boxes M, R2 or R3 or in the Fis or IHF binding sites caused moderate asynchrony of the initiation of chromosome replication, as measured by flow cytometry. In mutants with a scrambled DnaA box R4 or with a modified distance between DnaA boxes R3 and R4, initiations were severely asynchronous. Except for oriC14 and oriC21, mutated oriCs could not, or could only poorly, support minichromosome replication, whereas most of them supported chromosome replication, showing that the classical definition of a minimal oriC is not valid for chromosome replication. We present evidence that the functionality of certain mutated oriCs is far better on the chromosome than on a minichromosome.     

AT excursion: a new approach to predict replication origins in viral genomes by locating AT-rich regions

Background  

Replication origins are considered important sites for understanding the molecular mechanisms involved in DNA replication. Many computational methods have been developed for predicting their locations in archaeal, bacterial and eukaryotic genomes. However, a prediction method designed for a particular kind of genomes might not work well for another. In this paper, we propose the AT excursion method, which is a score-based approach, to quantify local AT abundance in genomic sequences and use the identified high scoring segments for predicting replication origins. This method has the advantages of requiring no preset window size and having rigorous criteria to evaluate statistical significance of high scoring segments.     

DNA replication in the archaea.

The archaeal DNA replication machinery bears striking similarity to that of eukaryotes and is clearly distinct from the bacterial apparatus. In recent years, considerable advances have been made in understanding the biochemistry of the archaeal replication proteins. Furthermore, a number of structures have now been obtained for individual components and higher-order assemblies of archaeal replication factors, yielding important insights into the mechanisms of DNA replication in both archaea and eukaryotes.     

DNA Replication in the Archaea

The archaeal DNA replication machinery bears striking similarity to that of eukaryotes and is clearly distinct from the bacterial apparatus. In recent years, considerable advances have been made in understanding the biochemistry of the archaeal replication proteins. Furthermore, a number of structures have now been obtained for individual components and higher-order assemblies of archaeal replication factors, yielding important insights into the mechanisms of DNA replication in both archaea and eukaryotes.     

The replicated ftsQAZ and minB chromosomal regions of Escherichia coli segregate on average in line with nucleoid movement

The average cellular positions of the ftsQAZ region (2 min) and the minB region (26.5 min) during the cell cycle was determined by fluorescent in situ hybridization using the position of oriC as a reference point. At the steady-state growth conditions used, newborn cells had replicated about 50% of the chromosome. By measuring the distances of the labelled oriCs with respect to mid-cell, we found two well-separated average oriC positions in cells of newborn length. These average oriC positions moved further apart along with cell elongation. The cellular position of the ftsQAZ gene region resembled the position of oriC, although its average position was closer to mid-cell. In contrast, a single minB focus was observed at cell birth. Separated minB foci appeared towards the end of DNA replication. The average positions of oriC, ftsQAZ and minB relative to each other fitted a model in which DNA replication takes place in the cell centre and subsequent gene regions pass sequentially through this centre. We have interpreted the polarized orientation of the studied gene regions as a consequence of the mode of DNA segregation.     

Multiple replication origins with diverse control mechanisms in Haloarcula hispanica

The use of multiple replication origins in archaea is not well understood. In particular, little is known about their specific control mechanisms. Here, we investigated the active replication origins in the three replicons of a halophilic archaeon, Haloarcula hispanica, by extensive gene deletion, DNA mutation and genome-wide marker frequency analyses. We revealed that individual origins are specifically dependent on their co-located cdc6 genes, and a single active origin/cdc6 pairing is essential and sufficient for each replicon. Notably, we demonstrated that the activities of oriC1 and oriC2, the two origins on the main chromosome, are differently controlled. A G-rich inverted repeat located in the internal region between the two inverted origin recognition boxes (ORBs) plays as an enhancer for oriC1, whereas the replication initiation at oriC2 is negatively regulated by an ORB-rich region located downstream of oriC2-cdc6E, likely via Cdc6E-titrating. The oriC2 placed on a plasmid is incompatible with the wild-type (but not the ΔoriC2) host strain, further indicating that strict control of the oriC2 activity is important for the cell. This is the first report revealing diverse control mechanisms of origins in haloarchaea, which has provided novel insights into the use and coordination of multiple replication origins in the domain of Archaea.     

Four chromosome replication origins in the archaeon Pyrobaculum calidifontis

Replication origins were mapped in hyperthermophilic crenarchaea, using high‐throughput sequencing‐based marker frequency analysis. We confirm previous origin mapping in Sulfolobus acidocaldarius, and demonstrate that the single chromosome of Pyrobaculum calidifontis contains four replication origins, the highest number detected in a prokaryotic organism. The relative positions of the origins in both organisms coincided with regions enriched in highly conserved (core) archaeal genes. We show that core gene distribution provides a useful tool for origin identification in archaea, and predict multiple replication origins in a range of species. One of the P. calidifontis origins was mapped in detail, and electrophoretic mobility shift assays demonstrated binding of the Cdc6/Orc1 replication initiator protein to a repeated sequence element, denoted Orb‐1, within the origin. The high‐throughput sequencing approach also allowed for an annotation update of both genomes, resulting in the restoration of open reading frames encoding proteins involved in, e.g., sugar, nitrate and energy metabolism, as well as in glycosylation and DNA repair.     

Re-replication from non-sequesterable origins generates three-nucleoid cells which divide asymmetrically

In rapidly growing Escherichia coli cells replication cycles overlap and initiation occurs at multiple replication origins (oriCs). All origins within a cell are initiated essentially in synchrony and only once per cell cycle. Immediate re-initiation of new origins is avoided by sequestration, a mechanism dependent on the SeqA protein and Dam methylation of GATC sites in oriC. Here, GATC sites in oriC were changed to GTTC. This reduced the sequestration to essentially the level found in SeqA-less cells. The mutant origins underwent re-initiation, showing that the GATC sites in oriC are required for sequestration. Each re-initiation eventually gave rise to a cell containing an extra nucleoid. The three-nucleoid cells displayed one asymmetrically placed FtsZ-ring and divided into a two-nucleoid cell and a one-nucleoid cell. The three nucleoid-cells thus divided into three daughters by two consecutive divisions. The results show that extra rounds of replication cause extra daughter cells to be formed prematurely. The fairly normal mutant growth rate and size distribution show, however, that premature rounds of replication, chromosome segregation, and cell division are flexibly accommodated by the existing cell cycle controls.     

Chromosome replication, nucleoid segregation and cell division in archaea

Recent progress in cell cycle analysis of archaea has included the identification of putative chromosome replication origins, novel DNA polymerases and an unusual mode of cell cycle organization featuring multiple copies of the chromosome and asymmetric cell divisions. Genome sequence data indicate that in crenarchaea, the 'ubiquitous' FtsZ/MinD-based prokaryotic cell division apparatus is absent and division therefore must occur by unique, as-yet-unidentified mechanisms. The evolutionary and functional relationships between the archaeal Cdc6 protein and bacterial and eukaryal replication initiation factors are discussed.     

Archaeal cell cycle progress

The discovery of multiple chromosome replication origins in Sulfolobus species has added yet another eukaryotic trait to the archaea, and brought new levels of complexity to the cell cycle in terms of initiation of chromosome replication, replication termination and chromosome decatenation. Conserved repeated DNA elements--origin recognition boxes--have been identified in the origins of replication, and shown to bind the Orc1/Cdc6 proteins involved in cell cycle control. The origin recognition boxes aid in the identification and characterization of new origins, and their conservation suggests that most archaea have a similar replication initiation mechanism. Cell-cycle-dependent variation in Orc1/Cdc6 levels has been demonstrated, reminiscent of variations in cyclin levels during the eukaryotic cell cycle. Information about archaeal chromosome segregation is also accumulating, including the identification of a protein that binds to short regularly spaced repeats that might constitute centromere-like elements. In addition, studies of cell-cycle-specific gene expression have potential to reveal, in the near future, missing components in crenarchaeal chromosome replication, genome segregation and cell division. Together with an increased number of physiological and cytological investigations of the overall organization of the cell cycle, rapid progress of the archaeal cell cycle field is evident, and archaea, in particular Sulfolobus species, are emerging as simple and powerful models for the eukaryotic cell cycle.