DRs and a spacer may be considered as a maximal repeat where the repeated sequences are separated by a sequence of approximately the same length. The operation of the program can be divided into four main steps summarized in Figure 1: (Step 1) browsing the maximal repeats of length 2355 bp interspaced by sequences of 2560 bp, (Step 2) selecting the DR consensus according to a dened score taking into account the number of occurrences of the candidate DR in the whole genome and privileging internal mismatches between the DRs rather than mismatches in the rst or the last nucleotides, (Step 3) dening candidate CRISPRs after checking if they t CRISPR denition, (Step 4) eliminating residual tandem repeats. In the rst step, maximal repeats are found by the software Vmatch (http://www.vmatch.de/), the upgrade of REPuter (2224). Vmatch is based on a comprehensive implementation of enhanced sux arrays (27) which provides the power of sux trees with lower space requirements. A one nucleotide mismatch is allowed permitting minimal CRISPRs with a single nucleotide mutation between DRs to be found. Hereafter, the obtained maximal repeats are grouped to dene regions of possible CRISPRs with a display of consensus DR candidates related to each cluster. The second step is aimed at retrieving the DR consensus of each cluster. The diculty resides especially in the identication of boundaries, which is very important to extract the correct spacers and compare DRs. In fact, the consensus DR is selected as the maximal repeat which occurs the most in the whole underlying genome sequence with respect to the forward and the reverse complement directions (since two CRISPRs having the same DR consensus may be in opposite directions). Thus, ambiguity in the choice of a DR will be eliminated in the case of presence of similar DRs in other CRISPRs of the related genomic sequence. However, if occurrence numbers are equal, more than a single DR consensus candidate are kept and later compared. Given a candidate consensus DR, the pattern search program fuzznuc of the EMBOSS package (28) is applied to get DRs positions in the related cluster. As the rst or the last DR in a CRISPR may be diverged/truncated, a mismatch of one-third of the DR length is allowed between the anking DRs and the candidate consensus DR, whereas smaller nucleotide dierences are allowed between the other DRs to take into account possible single mutations. In case of multiple DR candidates, a score is computed and the best one (minimum) is picked. This score favours candidates which are encountered more frequently, rather than consensus DR showing less internal mismatches. Once the DR consensus is determined, the corresponding spacers (Step 3) are extracted according to the DR boundaries determined previously. The spacer length is not allowed to be shorter than 0.6 or longer than 2.5 times the DR length. These sizes are in the range of CRISPRs described in the literature. The last step consists in discarding false CRISPRs. Therefore, tandem repeats are eliminated by comparing the consensus DR with the spacer if there is only one spacer, or by comparing spacers between each other.

W54 Nucleic Acids Research, 2007, Vol. 35, Web Server issue
Figure 1. CRISPR Finder ow chart. (Step 1) Browsing the maximal repeats to get possible CRISPR localizations using the Vmatch program. (Step 2) Consensus DR selection according to candidate occurrences and a score computation: the score privileges internal mismatches between direct repeats of a cluster rather than boundary mismatches. (Step 3) DR and spacers size check. (Step 4) Tandem repeats elimination using ClustalW for aligning spacers.
The comparison is done with the CLUSTALW program (29) and the percentage of identity between spacers is not allowed to exceed 60%. Finally, candidates having at least three motifs and at least two exactly identical DRs are considered as conrmed CRISPRs. The remaining candidates are considered as questionable. These should be critically investigated by, for example, checking for intraspecies size variation of the locus. INPUT AND OPTIONS The query sequence must be in FASTA format. Ns characters are accepted, IUB/GCG letters (MRWSYKVHDBX) will be converted to Ns and considered as mismatches but any other characters will be deleted. One can either paste the genomic sequence into the input eld or upload it from a le on the local machine. Multisequence les are also allowed by the program and
will be treated independently. Users may use the default version or click on the advanced version link to set and modify all the program parameters, which may be especially useful for xing the DR size. OUTPUT After querying a genomic sequence by CRISPRFinder, results are summarized in a table with the number of conrmed and questionable CRISPRs (Figure 2A). A CRISPR locus is presented according to a colour code showing DRs in yellow and spacers in dierent colours. The respective positions are displayed, in addition to links to two les: a summary of the displayed properties (number of motifs, DR consensus, positions, etc.) and a fasta le containing the list of spacers. In addition, a PNG (Portable Network Graphics) gure displays the dierent candidates location in the analysed sequence.
Nucleic Acids Research, 2007, Vol. 35, Web Server issue W55
Figure 2. An example of CRISPRFinder output using the Aquifex aeolicus VF5 genomic sequence (Refseq: NC_000918). (Panel A) (1) Home page where the genomic sequence is submitted. (2) Table listing the detected CRISPRs candidates (questionable and conrmed) providing links to each one. (3) CRISPRs details, the DR is showed in yellow and the spacers in dierent colours. (4) A fasta le displaying the rst CRISPR spacers. (5) Figure showing the Aquifex circular chromosome with CRISPRs positions. (Panel B) One or several spacers may be blasted against NCBI databases by clicking on the blast_spacers button. (Panel C) The anking and the CRISPR sequences may be viewed by clicking on the Get sequences button. The sequences boundaries may be modied by the user. (Panel D) The list of consensus DRs for all CRISPRs is shown with a link to identical DRs in the CRISPR database.

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In the case of presence of CRISPR clusters, further analysis may be done through three hyperlinks in the left menu: (i) blast spacers against the Genbank databases with a cuto of 0.1 for the E-value and a matching length of at least 70% the queried spacer size (Figure 2B); (ii) obtain CRISPR and anking sequences which are especially useful to dene the leader sequence. As the size of the leader sequence depends on the species (it varies from 100 to 500 bp), the retrieved sequence may be manually modied by the user (Figure 2C) and (iii) display identical DRs in other known CRISPR loci (Figure 2D). This utility corresponds to a link to CRISPR database (Grissa et al. submitted for publication). DISCUSSION AND CONCLUSIONS CRISPRFinder is a program that allows the identication of structures with the principal characteristics of CRISPRs, the smaller being composed of a truncated or diverged DR, a spacer and a complete DR. In their analysis, Godde et al. (20) using Patscan had chosen to retain only CRISPRs with at least three exact repeats (eliminating CRISPRs constituted of a rst truncated repeat plus two exact repeats) thus ignoring most CRISPRs containing less than three spacers. Similarly in the work by Durand et al.(21), the PYGRAM program is mostly ecient in visually displaying large CRISPRs. Such stringent criteria were appropriate in order to avoid ambiguities in early investigations which were essentially describing these new structures. However, it is now important, in order to better understand the evolution and spreading of CRISPRs, to provide tools which will not eliminate the smallest CRISPRs. This is what we chose to achieve with CRISPFinder. The major drawback is that when looking for the shortest structures, such as those with a unique spacer, it is clear that the background of spurious candidates can be very high. The output of Patscan and CRT also contains a large quantity of noised data that needs a manual treatment. CRISPRFinder is accessible on the web and submission is very simple. We provide several samples on the website as demonstrators. Upon submission of the complete genome of Aquifex aeolicus VF5 (sample1), ve conrmed and ve possible CRISPRs are displayed in the following pages. On the contrary, while using the webservice for Patscan (http://www-unix.mcs.anl.gov/compbio/PatScan/), it is necessary to rst dene a pattern (which is not straightforward) and it is not possible to seek for CRISPRs in a single genomic sequence but rather in an entire predened database. In addition, Patscan requires a Sun machine for local implementation. Similarly, PYGRAM only runs on linux systems and its installation requires advanced skills. CRT requires either to install JRE (Java Runtime Environment) or compile the source les, and PILER-CR needs to be compiled before use. A comparison between layouts of available online programs (REPuter, Patscan, TRF) and of CRISPRFinder is provided in the Supplementary Data. To check that CRISPRFinder was ecient in recovering all the CRISPRs from a genome, we compared the

Published: 23 May 2007 BMC Bioinformatics 2007, 8:172 doi:10.1186/1471-2105-8-172
Received: 5 January 2007 Accepted: 23 May 2007
This article is available from: http://www.biomedcentral.com/1471-2105/8/Grissa et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background: In Archeae and Bacteria, the repeated elements called CRISPRs for "clustered regularly interspaced short palindromic repeats" are believed to participate in the defence against viruses. Short sequences called spacers are stored in-between repeated elements. In the current model, motifs comprising spacers and repeats may target an invading DNA and lead to its degradation through a proposed mechanism similar to RNA interference. Analysis of intra-species polymorphism shows that new motifs (one spacer and one repeated element) are added in a polarised fashion. Although their principal characteristics have been described, a lot remains to be discovered on the way CRISPRs are created and evolve. As new genome sequences become available it appears necessary to develop automated scanning tools to make available CRISPRs related information and to facilitate additional investigations. Description: We have produced a program, CRISPRFinder, which identifies CRISPRs and extracts the repeated and unique sequences. Using this software, a database is constructed which is automatically updated monthly from newly released genome sequences. Additional tools were created to allow the alignment of flanking sequences in search for similarities between different loci and to build dictionaries of unique sequences. To date, almost six hundred CRISPRs have been identified in 475 published genomes. Two Archeae out of thirty-seven and about half of Bacteria do not possess a CRISPR. Fine analysis of repeated sequences strongly supports the current view that new motifs are added at one end of the CRISPR adjacent to the putative promoter. Conclusion: It is hoped that availability of a public database, regularly updated and which can be queried on the web will help in further dissecting and understanding CRISPR structure and flanking sequences evolution. Subsequent analyses of the intra-species CRISPR polymorphism will be facilitated by CRISPRFinder and the dictionary creator. CRISPRdb is accessible at http://crispr.upsud.fr/crispr

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(page number not for citation purposes)
BMC Bioinformatics 2007, 8:172
http://www.biomedcentral.com/1471-2105/8/172

Background

Clustered regularly interspaced short palindromic repeats (CRISPRs) have been described in a wide range of prokaryotes, including the majority of Archaea and many Bacteria. They consist in the succession of 2447 bp repeated sequences (often called direct repeats or DR) separated by unique sequences of a similar length (spacers) [1-4]. Bona fide CRISPRs possess at one end a partial DR and at the other end after the last DR a sequence of about 200 bp called the leader [5]. The origin of the spacers is still largely unknown but several recent studies identified some of them as fragments of foreign DNA mostly of viral origin [6-9]. Analysis of a large number of Yersinia pestis isolates has shown that these elements are sequentially added in a polarised fashion next to the leader [8]. This suggestion was further confirmed by observations in Sulfolobus solfataricus and in Streptococcus thermophilus [9,10]. A cluster of genes called cas (CRISPR-associated) are often found in the vicinity of CRISPRs [5]. When several CRISPRs with the same DR are present, only one is associated with cas genes. The exact number of cas genes is not known and apparently varies from one strain to another. However, a core of 4 genes is regularly identified, which appears to encode proteins involved in DNA modification and repair [11]. Phylogenetic studies performed on the CAS proteins suggest that CRISPRs are acquired by horizontal transfer [12,13]. This is consistent with their presence on megaplasmids [12]. CRISPRs are non-coding regions but different observations suggest that they are transcribed into small RNAs (smRNA) possibly from the leader acting as a promoter, and that they might play a role as siRNA (small interfering RNA) to block the entry of foreign sequences [10,11,14]. In order to gain further insight into the organisation and behaviour of CRISPR loci it is necessary to perform extensive analyses of the available sequenced genomes. Several studies have been performed, the most extensive being that made on 370 prokaryotic genomes [12]. However, these studies are static and considering the amount of ongoing sequencing projects they are rapidly becoming obsolete. The TIGRFAM database [15] provides information on CAS associated CRISPR loci but it is not dedicated to CRISPR identification and will not report CRISPR structures devoid of neighbouring cas genes. For the algorithmic detection of CRISPR patterns, several methods were empirically applied previously, making use of REPuter [13,16], PatScan [12,17], TRF [8,18], LUNA [10], PYGRAM [19]. These programs are designed to find repeats and are not especially conceived for CRISPR patterns finding, so they may provide the CRISPR location but do not define accurately the consensus DR. The output of such tools requires significant manual discard to eliminate background, and post-processing to define the

consensus DR and the spacers. Recently, a CRISPR dedicated software tool called PILER-CR was described [20]. PILER-CR is based on an elegant algorithm that consists mainly in producing piles meeting the CRISPR properties from local alignments of the query sequence to itself. The software tool has the advantage of being rapidly executed but it sometimes misidentifies the DR boundaries and omits the truncated DR. Finally, using the available programs, "short" or "quite short" CRISPRs (defined as containing less than three, three or seven spacers [5,12,19]) are not considered. Since future insights into the evolution of CRISPRs may result from the investigation of these very small CRISPRs, some of which may be newly emerging structures, it is important to facilitate access to this enlarged, but much more difficult to define, group. We have developed tools to identify CRISPRs, select DR and store spacers into dictionaries, and a database which can be queried online at http://crispr.u-psud.fr/crispr. The CRISPRdb is automatically updated; in the May 2007 version, 475 published microbial genomes have been processed.

Construction and content

Database and software design and implementation CRISPRdb and associated web services are implemented in Perl version 5.8.8 [21] and take advantage of some BioPerl [22] modules for manipulating sequences. They run on an Apache 2.0 web server [23] with a Linux operating system (debian Sarge 3.1) [24]. The core application consists of two main programs: CRISPRFinder to detect CRISPRs and extract them from a genomic sequence, and Database Tools for downloading prokaryotic genomes from the NCBI ftp site [25], saving CRISPRs and making updates.
The first program is a full command line tool written inhouse in Perl. It is used to process published genome sequences and feed the CRISPR database. It can also be run interactively through the web interface for submission and analysis of users sequence data [26]. The second program is a set of Perl scripts. Downloading of genomic sequences, CRISPRs detection and motifs extraction are fully automated. A web resource is built on top of these programs via PHP [27] and Perl CGI scripts. This preserves platform independence across multiple operating systems and allows the user to interact with the different CRISPR tools programs without computer programming or (shell) scripting skills.

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The CRISPRs database (CRISPRdb) CRISPRdb is a relational database implemented using mysql 4.1 [28]. It utilizes the CRISPRFinder program to identify putative CRISPRs and additional tests to further screen for the smallest CRISPRs in a polyphasic approach. Indeed the CRISPRFinder program is conceived to authorize the largest number of possible CRISPRs, especially the shortest ones, containing one or two spacers. The main idea of the program is to first find possible CRISPR localizations in a genomic sequence and then check if these regions contain a cluster that possess the characteristics of "obvious" CRISPR, i.e. containing at least three repeats. Finding possible CRISPR localizations is achieved using the Vmatch package to detect maximal repeats [29], that is a repeat that cannot be extended in either direction without incurring a mismatch [16,30]. Reported matches must have a size within 23 to 55 bp with one possible mismatch, and the gap size between two instances of a repeat must be within 25 to 60 bp. The maximal repeats are clustered according to their position in the genome. In each "cluster", the maximal repeat which is the most frequent in the genome being processed is selected and "blasted" against the cluster. Such a maximal repeat is a candidate DR sequence, and when additional candidate DRs are identified, a score is computed to select the DR resulting in the minimum number of mismatches towards its boundaries. This step is probably instrumental to achieve a very precise identification of proper DR consensus compared to other programs. The related matches are then extracted and tested as putative DRs of a CRISPR, so that the first or the last match is allowed to be degenerated with a maximal number of errors equal to half the match length. This allows the efficient identification of the first, often truncated, DR. The other matches must be globally conserved at least to 80%. Finally two filters are added to check the CRISPR candidates' structure. The first one eliminates clusters for which spacers length are not within the range of 0.6 and 2.5 the DR length. In addition, CRISPR candidates with more than 60% of similarity between spacers (or between DR and spacer) are considered as tandem repeats and are eliminated by the second filter. The selected criteria described above imply that the minimal structure of a putative CRISPR detected by CRISPRFinder should consist in at least two successive direct repeats (one spacer) with a maximum of one mismatch. CRISPRs of more than 2 spacers with three or more perfect repeats are considered "confirmed CRISPR" whereas the shorter CRISPRs are considered "questionable".

Table 1: Summary of the characteristics and number of CRISPRs.

DR length

Number of CRISPRs (percentage %) Bacteria Archaea 14 (8.9) 9 (5.7) 1 (<1) 1 (<1) 2 (1.3) 46 (29.1) 9 (5.7) 7 (4.4) 2 (1.7) (23.4) 30 (19) Total 1 (<1) 3 (<1) 69 (13) 78 (14.7) 11 (2.6) 1 (<1) 4 (<1) 32 (6) 8 (1.5) 97 (18.2) 77 (14.4) 74 (13.9) 4 (<1) 1 (<1) 43 (8) 30 (5.7) 533 32

Total Number Mean Length

1 (<1) 3 (<1) 55 (14.7) 69 (18.4) 10 (2.7) 1 (<1) 4 (1) 31 (8.3) 6 (1.6) 51 (13.6) 68 (18.1) 67 (17.9) 2 (0.53) 1 (0.27) 6 (1.6) 32
Only confirmed CRISPRs are counted. The first column shows the DR length. In the second and the third columns are shown the number of clusters having the corresponding DR length in Bacteria and Archaea respectively (the percentage of CRISPR DR having this length is indicated). Only one strain per species is counted. In the last column, the two populations of CRISPRs are merged. The last two lines are respectively the total number of CRISPRs in each category, and the average DR length.
col. [5] further suggested that the secondary structure might play an essential biological role. A protein binding on one side of the repeat and producing an opening of the opposite side of the DNA structure was described in Sulfolobus solfataricus [38] and might be used in the processing of small RNAs [14]. A future development of our work will be the analysis of all the DRs in search for a common secondary structure that might help in understanding the role of the DR. Inside a species several strains can share a set of spacers, but in a given CRISPR spacers are generally unique except in a few cases where duplications of one to 7 motifs (a DR and a spacer) were observed [33]. Apparently, duplications are more frequently observed in Archaea as described in detail by Lillestol et al. [10]. It is important to note that the absence of CRISPR in one strain does not imply that CRISPRs are absent from all the members of the corresponding species. However in some species or genus no CRISPR has been identified yet although a number of strains have been fully sequenced. This is the case for example in Staphylococcus aureus and Burkholderia sp.

Table 1. Ancient DNA analysis challenges
Wish list: the appropriate target for aDNA analysis Because aDNA is: The appropriate genetic target should be: Fragmented Small Present in low amounts Present in multiple-copies, stable Contaminated With a high phylogenetic content Subject to erroneous nucleotide And interpretation not dependant upon incorporation sequence accuracy Y. pestis CRISPRs satisfy all these criteria data. There is no consensus so far on the choice of the genetic target in the case of Y. pestis. Plasmid targets are sometimes used, for their relatively high copy number. However, plasmids have a low phylogenetic value as they are usually acquired by horizontal transfer from different species. In a more recent investigation (Drancourt et al. 2004), a polymorphic tandem repeat (VNTR) was targeted but some of the weaknesses of this approach were subsequently demonstrated (Vergnaud 2005). The investigators were able to amplify a particular VNTR allele from ancient remains from the first two pandemics. Among the Y. pestis strains investigated so far, only strains from biovar Orientalis possess this VNTR allele. Consequently the authors concluded that all three pandemics were caused by Orientalis. However the phylogenetic evidence is too weak, because the strain collection investigated is by far not representative of the diversity of Y. pestis. Indeed studying an enlarged collection, the same Orientalis allele was observed in Antiqua and Medievalis strains as well (Yang and colleagues, unpublished data).
30.4 CRISPRs Diversity Within Y. pestis and Y. pseudotuberculosis
Y. pestis and Y. pseudotuberculosis contain three CRISPRs called YP1, YP2 and YP3 (Pourcel et al. 2005) (Fig. 3A). Since CRISPR loci can also be considered to some extent as polymorphic tandem repeats, they have been designated, respectively, ms06, ms76 and ms77 (Le Flche et al. 2001; Pourcel et al. 2005). The number of motifs (one DR and one spacer) in an allele is easily deduced from the size of the PCR product obtained by using flanking primers. These PCR products can be sequenced to identify the spacers (Fig. 3A-3B). It is this approach, applied to many very closely related isolates, some of which differed at the CRISPR loci, which led to the current model of evolution for CRISPR (Pourcel et al. 2005) (Fig. 4).
RS 28bp Sp 32-33bp VNTRyp2769ms06 CRISPR YP1 GTTACAAAATGCGCTTCCGCTCGCAATTTTGCTCCCCAAATAGCATCAGCACATGGCCCA tttgattatTGCCTGTGCGGCAGTGAACTCAGGGGACTGGCGAACAATGTCTTTCATGAT TTTCTAAGCTGCCTGTGCGGCAGTGAACGAAAAGGTAAGATGGGCAAGCTTCTAGTAGTT TTTCTAAGCTGCCTGTGCGGCAGTGAACATTATCTGAATGGCATTTTCTTTGGCGCAGAT TTTCTAAGCTGCCTGTGCGGCAGTGAACTCGCCATTCCGTGAACCTGAGCGCGTTCGCGA TTTCTAAGCTGCCTGTGCGGCAGTGAACATATTCTCGAGCGATAGCAATAGCCATTCCAC TTTCTAAGCTGCCTGTGCGGCAGTGAACTCGGTCAAACAAATTTAGGCGACGATTTAACA TTTCTAAGCTGCCTGTGCGGCAGTGAACAAAAAGAATTTGGGATTAAAGTTACCCATCAG TTTCTAAGCTGCCTGTGCGGCAGTGAACTCAATGCCTGAATCTCTGGCGTGATAGCTGCGG TTTCTAAGCTGCCTGTGCGGCAGTGAACAGTAAGATAATACGATAACATCCTGTTTGTAA AATACTTATTTCGCTAATGGGGAAAAAACCCTTTTTTTAGACCACCGATAACCACAATGT AAAATCAATGAGTTAGCAGTAGCTAAAAAAATAGGGTCAGAACATAACTCATAATAAAAC yp2895 CRISPR YP2 CAGGTAGATGCCTTCCGATCTCAATCAGCCACGCTCTGTCTAGTGCAGTCGCTGGTCGTG GCGTTGGCCTACCAGCAGGAGGCGCAGGCCGGGGCCGCGCTGGCGCACAGACAGTGACCC tctaTAAGCTGCCTGTGCGGCAGTGAACTCTGTACGCATACCGCCATCTTGCATCAGTCT TTTCTAAGCTGCCTGTGCGGCAGTGAACAGCAAAAATCTTAATTACATCTGATGATTTCGG TTTCTAAGCTGCCTGTGCGGCAGTGAACTTTACGGCACGGCGAAAGATTCGGTTCTTGTC TTTCTAAGCTGCCTGTGCGGCAGTGAACTTCTGGATAGGACAAATAGGATGATTGTATCAG TTTCTAAGCTGCCTGTGCGGCAGTGAACAACGAACCCACGTAGAATTGCCATCACCGCCGG TTTCTAAGCTGCCTGTGCGGCAGTGAACAGTAAGATAATACGGGTAACAGACTGTTTGTAA AATAATTCTTTCGCCAAAGGGTAAAAAATGATTTTTTTTAACCCTCGGTAAGCAGGATAT AAAATCAATGAGTTAGCCATAGCTAAAAAAATAGGGTCAAAAAATGATTCCCCTGATGCG

Focus B

Y. pestis pestis
Medievalis Focus A Foci C, D, E Focus F Orientalis

Antiqua

Fig. 5. Current view of relationships between some Y. pestis subspecies. Deletion analysis within Y. pestis pestis with respect to Y. pestis microtus lead to this current view of Y. pestis evolution. The relative position of African Antiqua strains is unknown. The naming of Chinese foci is as described in Zhou et al. (Zhou et al. 2004a).
A set of diverse strains from each of the main foci identified in China (Zhou et al. 2004a) and of some foci from the former Soviet Union (Anisimov et al. 2004) including strains from the different Y. pestis subspecies (with the exception of talassica) was selected accordingly for YP1 sequence analysis. More than 80 representative YP1 alleles were investigated and more than 40 new YP1 spacers were identified. The current total number of YP1 spacers is 71. Interestingly the number of new spacers is relatively low, given the very significant increase in the diversity of Y. pestis strains investigated. In particular, the non-pestis subspecies including the Angola strain share a number of previously identified spacers (spacers labeled a, b, c, d, e, f, 37). New lineages were uncovered in particular within the A and B Antiqua foci (Fig. 6). In Y. pseudotuberculosis the CRISPR polymorphism is very large with several hundred spacers identified to date (Gorge et al. unpublished). Spacers a, b, and c were observed in a couple of strains. In agreement with previous findings, the
CRISPR YP1 in Y. pestis : pestoides ( Angola ) a.c.d.37. caucasica (including pestoides F) a.b.c.d.e.m.n. altaica, hissarica, microtus a.d.f. pestis : Antiqua : a.b.c.d.e.f.37.38.39.40.41.50. a.b.c.d.e.f.37.38.39.40.41.50.51. a. c.d.e.f.37.38.39.40.41.42.43.44.45. a. c.d.e.f.37.38.39.40. 42.43.44.45. a.b.c.d. f.37. 39. 42.46. a. c.d. f.37. 39. 42.46.47.48. a. c.d. f.37. 39. 42.46.47.48.49. a.b.c.d.e.f.g. and a.b.c.d.e.f.g.+ Orientalis : a.b.c.d.e.f.g.h. and a.b.c.d.e.f.g.h.+ Medievalis : a.b.c. and a.b.c.+
Fig. 6. CRISPR YP1 alleles observed across Y. pestis. A few representative alleles are indicated. Allele codes are aligned to illustrate differences resulting from interstitial deletion or progressive addition of spacers from the right end. Spacer 37 is observed in the Angola strain which indicates that the combination a.b.c.d.e.f.37 was already present in the Y. pestis ancestor.
majority of the spacers for which an origin could be found corresponds to a prophage. This strengthens the hypothesis that the remaining spacers correspond to presently unknown viruses.

30.5 Conclusions

The present work provides a significantly enlarged view of the diversity of CRISPR spacers within Y. pestis intraspecies groups. Seventy CRISPR YP1 spacers have now been uncovered, and these are likely to represent the most frequently occurring spacers. Some very recently acquired and rare spacers present in only a few isolates will probably be identified in the future, but they would not significantly increase the validity of a future spoligotyping assay for Y. pestis. Consequently it will be possible to develop a very efficient typing assay when the other two (and less variable) CRISPR loci will have been similarly investigated. We anticipate that such an assay will help in deciphering the phylogeny of Y. pestis and in identifying closely related Y. pseudotuberculosis strains. In addition, the investigation of CRISPRs in aDNA should greatly improve our knowledge of the agent responsible for the different pandemics.

* Corresponding author: Tel.: 6915 3001; fax: 6915 6678. E-mail address: ibtissem.grissa@igmors.u-psud.fr (I. Grissa). 0300-9084/$ - see front matter 2007 Elsevier Masson SAS. All rights reserved. doi:10.1016/j.biochi.2007.07.014
literature to differentiate strains but not all methods are equally applicable to every species. In addition many techniques cannot provide a portable result and therefore the strain genetic prole cannot be easily coded and stored into databases that can be exchanged between laboratories. This is in particular the problem of methods relying on restriction enzyme polymorphism analysed by gel electrophoresis such as restriction fragment length polymorphism (RFLP) and pulsed eld gel electrophoresis (PFGE). Other pattern-producing techniques such as the random amplication of polymorphic DNA (RAPD) or amplied fragment-length polymorphism (AFLP) are respectively notably not reproducible enough or technically too demanding to allow accurate or convenient inter-laboratory comparisons of proles. Multiple loci sequence typing (MLST) is a highly accurate, reproducible
I. Grissa et al. / Biochimie 90 (2008) 660e668
and portable method but is not adapted to the typing of the most highly homogenous species such as Mycobacterium tuberculosis and its current cost prevents its systematic use. Multiple loci variable number of tandem repeats (VNTR) analysis (MLVA) is a typing technique based on the polymorphism of certain tandemly repeated DNA sequences. VNTRs consist in consecutive occurrences of a DNA repeat unit, and they are found in all organisms, prokaryotes as well as eukaryotes. Although their biological function and evolution mechanism is not fully understood, they have diverse practical applications including strain identication in bacterial epidemiology. In a typical MLVA assay, a few to more than twenty VNTRs, distributed over the entire bacterial genome, are analysed, and a code corresponding to the number of repeats at each locus is determined. This code is easily stored into databases and can be used for strain clustering and epidemiological studies. MLVA is nowadays increasingly replacing or at least completing traditional genotyping methods, providing a different or complementary point of view in M. tuberculosis, Bacillus anthracis, Yersinia pestis, Staphylococcus aureus, Pseudomonas aeruginosa, Legionella pneumophila investigations thanks to its design easiness, low cost and portability (see refs. [1,2] for reviews). MLVA is best applied within a highly homogeneous group of strains, typically with genomes showing an average similarity well above 98%. Some MLVA assays have been developed in species with an internal genome homogeneity in the 95%e98% range (as illustrated for instance in L. pneumophila [3]), but the design of primers, and the level of homoplasy at VNTR loci, introduce specic technical challenges. In parallel, the particular polymorphic structures called CRISPR (Clustered Regularly Interspaced Short Palindromic Repeat); or TREP (Tandem REPeat) [4], SRSR (short regularly spaced repeats) [5,6], DVRs (direct variant repeats) [7], LCTR (long clusters of tandem repeats) [8], SPIDR (spacers interspersed direct repeats) [9] have been used in some bacteria for genotyping (Fig. 1). They were rstly detected in Escherichia coli [10] and then in about 40% of bacterial genomes and almost all archaea. A CRISPR consists in exact

I. Grissa et al. / Biochimie 90 (2008) 660e668 [41] P. Le Fleche, I. Jacques, M. Grayon, S. Al Dahouk, P. Bouchon, F. Denoeud, K. Nockler, H. Neubauer, L.A. Guilloteau, G. Vergnaud, Evaluation and selection of tandem repeat loci for a Brucella MLVA typing assay, BMC Microbiol. 6 (2006) 9. [42] M. Fabre, J.L. Koeck, P. Le Fleche, F. Simon, V. Herve, G. Vergnaud, C. Pourcel, High genetic diversity revealed by variable-number tandem repeat genotyping and analysis of hsp65 gene polymorphism in a large collection of Mycobacterium canettii strains indicates that the M. tuberculosis complex is a recently emerged clone of M. canettii, J. Clin. Microbiol. 42 (2004) 3248e3255. [43] R. Barrangou, C. Fremaux, H. Deveau, M. Richards, P. Boyaval, S. Moineau, D.A. Romero, P. Horvath, CRISPR provides acquired resistance against viruses in prokaryotes, Science 315 (2007) 1709e 1712. [44] P. Durand, F. Mahe, A.S. Valin, J. Nicolas, Browsing repeats in genomes: Pygram and an application to non-coding region analysis, BMC Bioinformatics 7 (2006) 477. [45] R.C. Edgar, PILER-CR: fast and accurate identication of CRISPR repeats, BMC Bioinformatics 8 (2007) 18. [46] V. Kunin, R. Sorek, P. Hugenholtz, Evolutionary conservation of sequence and secondary structures in CRISPR repeats, Genome Biol. 8 (2007) R61. [47] M. Abouelhoda, S. Kurtz, E. Ohlebusch, Replacing sufx trees with enhanced sufx arrays, J. Discrete Algorithms 2 (2004) 53e86. [48] R. Lillestol, P. Redder, R. Garrett, K. Brugger, A putative viral defence mechanism in archaeal cells, Archaea 2 (2006) 59e72. [49] T. Boby, A.M. Patch, S.J. Aves, TRbase: a database relating tandem repeats to disease genes for the human genome, Bioinformatics 21 (2005) 811e816. [50] J.R. Collins, R.M. Stephens, B. Gold, B. Long, M. Dean, S.K. Burt, An exhaustive DNA micro-satellite map of the human genome using high performance computing, Genomics 82 (2003) 10e19. [51] J. Macas, T. Meszaros, M. Nouzova, PlantSat: a specialized database for plant satellite repeats, Bioinformatics 18 (2002) 28e35. [52] V.B. Sreenu, V. Alevoor, J. Nagaraju, H.A. Nagarajaram, MICdb: database of prokaryotic microsatellites, Nucleic Acids Res. 31 (2003) 106e108. [53] S. Subramanian, V.M. Madgula, R. George, R.K. Mishra, M.W. Pandit, C.S. Kumar, L. Singh, MRD: a microsatellite repeats database for prokaryotic and eukaryotic genomes, Genome Biol. 3 (2002) PREPRINT0011. [54] C.H. Chang, Y.C. Chang, A. Underwood, C.S. Chiou, C.Y. Kao, VNTRDB: a bacterial variable number tandem repeat locus database, Nucleic Acids Res. 35 (2007) D416eD421. [55] Y. Gelfand, A. Rodriguez, G. Benson, TRDBdthe Tandem Repeats Database, Nucleic Acids Res. 35 (2007) D80eD87. [56] D.H. Haft, J. Selengut, E.F. Mongodin, K.E. Nelson, A guild of 45 CRISPR-associated (Cas) protein families and multiple CRISPR/Cas subtypes exist in prokaryotic genomes, PLoS Comput. Biol. 1 (2005) e60.

has been mainly used in Mycobacterium tuberculosis (18). Indeed, the so called DR locus in M. tuberculosis is in fact a CRISPR element which diversity inside the species is analysed with the spoligotyping method (see dedicated chapter in this book). Spoligotyping only investigates the presence/absence of known spacers by hybridisation and is well suited for a DR locus which is not acquiring new motifs (such as in M. tuberculosis) or when an extensive survey of the CRISPR diversity inside a species has been performed. In species with one or several rapidly evolving CRISPRs, PCR analysis and sequencing of these loci remain the best approach to investigate their diversity.

2. Materials

2.1. DNA Purification Good quality DNA should be available as CRISPRs may sometimes be large and long-range PCR amplification is required. 1. The Qiagen DNeasy Tissue kit was successfully used for different bacterial species.
2. The quality and concentration of DNA was measured using a ND-1000 Spectrophotometer (NanoDrop, Labtech, France).
2.2. PCR Amplification 1. Standard Taq polymerase (Qiagen, Roche, Promega or Invitrogen). 2. The Qiagen kit provides the Q solution and corresponding buffer for amplification of GC-rich DNA. Alternatively, 0.5M betain (Sigma) can be used in the PCR reaction.
3. dNTPs (Eurogentec or MWG Biotech). 4. Reaction buffer is as recommended by the Taq polymerase manufacturer.The concentration of MgCl2 in the reaction is 1.5M. 5. Oligonucleotides are dissolved at 100 M, in 10 mM Tris-HCl, 1 mM EDTA, pH 7.8.
2.3. Agarose Gel Electrophoresis 1. Standard molecular biology grade agarose (from Invitrogen, Sigma, or QBIOgene). 2. Tris Borate EDTA (TBE) buffer: the 10X stock solution is 890mM Tris-borate and 20mM EDTA pH 8.3 (Sigma). 3. The DNA size marker is the 100-bp ladder (from Bio-Rad, MBI Fermentas, or Euromedex). 4. Ethidium bromide stock solution 10mg/ml (Sigma)
2.4. Sequencing 1. PCR products are purified using the QIAquick PCR purification kit (Qiagen) or precipitated with a solution of PEG8000 20% (w/v), 2.5 M NaCl (see Note 1) (19). 2. Sequencing is performed using the primers used for PCR.

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