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1 Institut für Virologie und Immunbiologie, Universität Würzburg, Versbacher Straße 7, 97078 Würzburg, Germany
2 Lehrstuhl für Bioinformatik, Universität Würzburg, Versbacher Straße 7, 97078 Würzburg, Germany
3 Division of Experimental Hematology, Cincinnati Children's Hospital Research Foundation, Cincinnati, OH, USA
Correspondence
Axel Rethwilm
virologie{at}mail.uni-wuerzburg.de
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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The GenBank/EMBL/DDBJ accession numbers for the sequences described in this paper are DQ192669 [GenBank] –DQ193515 [GenBank] .
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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). The MLV vector was used to introduce the corrected gene into haematopoietic stem cells of boys with common 
-chain deficiency of the interleukin receptor (Hacein-Bey-Abina et al., 2002). In a minority of patients, a lymphoproliferative disease developed that was explained in part by the integration of the vector in the vicinity of cellular proto-oncogenes, including the LMO-2 proto-oncogene (Hacein-Bey-Abina et al., 2003). This is believed to have stimulated the proto-oncogene promoter by enhancer function of the vector virus U3 elements in the long terminal repeat (LTR) (Baum et al., 2003; von Kalle et al., 2004). Preferential integration of MLV into the promoter regions of actively transcribed genes is thought to be responsible, at least in part, for this gene activation (Wu et al., 2003).
Besides this applied aspect, there is an interest in understanding the retroviral integration pattern from a more basic scientific point of view. Investigating retroviral integration was, until recently, limited to in vitro assays using recombinant enzymes and oligonucleotides or in vivo assays using added target DNAs and cellular extracts (Brown, 1997; Bushman, 2002; Craigie, 2002; Goff, 1992). By these studies, insight into the complex mechanism of retroviral integration and some structural features of the target DNA that influence integration were obtained (Craigie, 2001; Müller & Varmus, 1994; Pruss et al., 1994a, b; Pryciak & Varmus, 1992). However, these assays do not fully reflect all aspects of retroviral integration into chromosomal DNA of a living cell.
The availability of most of the DNA sequence of the human genome and those of some other model organisms, together with the development of methods to amplify and sequence proviral integration sites on a large scale, have made it possible to investigate more closely the process of retroviral integration under in vivo conditions. This may eventually lead to the discovery of cellular and viral factors that influence the observed differences in integration-site selection by different retroviruses and to a better understanding of what directs retroviral latency and the transcriptional activity of proviruses.
The integration profiles of three genera from the subfamily Orthoretrovirinae of the family Retroviridae have been investigated so far, namely Lentivirus [human (HIV) and simian immunodeficiency viruses], Alpharetrovirus (avian sarcoma/leukosis virus) and Gammaretrovirus (MLV) (Hematti et al., 2004; Mitchell et al., 2004; Narezkina et al., 2004; Schröder et al., 2002; Wu et al., 2003). Here, we investigated the integration profile of the subfamily Spumaretrovirinae and compared it with those of HIV and MLV. The reasons for doing so were the fact that vectors derived from FVs have previously been shown to be good candidates for retroviral gene transfer into human haematopoietic stem cells (Leurs et al., 2003) and because of the unique position of these viruses among the family Retroviridae, which may also include special features of integration (Delelis et al., 2005; Enssle et al., 1999; Juretzek et al., 2004).
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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) and 293 were used for transfections and transductions, respectively. Cells were cultivated in Dulbecco's modified minimal essential medium supplemented with 10 % fetal calf serum and antibiotics.
Recombinant DNA.
The prototypic FV (PFV) plasmids pMH123 (Juretzek et al., 2004), pCgp1 (Fischer et al., 1998) and pCenv1 (Fischer et al., 1998), the HIV vector pGJ3/U3E (Leurs et al., 2003), the MLV plasmid pcAMS/U3E (Leurs et al., 2003) and the plasmid pczVSV-G (Pietschmann et al., 1999), which directs the expression of the vesicular stomatitis virus (VSV) G protein, have been described previously. The vector plasmid pMH123 contains the enhancer/promoter of human cytomegalovirus (CMV), the PFV start of transcription, full-length gag and pol genes, an internal cassette directing the expression of the gene for the enhanced green fluorescent protein (EGFP) under control of the spleen focus-forming virus U3 promoter and the 3' LTR of pHSRV2 (Schmidt & Rethwilm, 1995; Schmidt et al., 1997). The vector pMH124 was derived from pMH123 by deletion of a 1·83 kb PacI–SwaI gag–pol fragment and religation. The viral vectors are shown in Fig. 1.
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; Sambrook & Russell, 2001). PFV env was used to envelope PFV capsids and HIV and MLV vectors were pseudotyped with VSV-G. For the generation of pMH124 vector, 293T cells were also co-transfected with the pCpg1 packaging plasmid. The supernatant was passed through a 0·45 µm filter (Schleicher & Schuell) 48 h after transfection and used for the transduction of 293 cells that had been seeded the day before at a density of 2x105 cells per well in six-well plates. The transduction efficiency was determined by flow cytometry (FACS) 3 days later from an aliquot of the cells, whereas the remainder was cultivated for an additional 3 days before DNA was extracted by conventional methods (Ausubel et al., 1987; Sambrook & Russell, 2001). To avoid multiple integrations into one cellular genome, only cultures with transduction efficiencies below 40 % as determined by FACS, which approximates an m.o.i. of 1·0 (Fehse et al., 2004), were used for DNA extraction and further analysis.
Inverse PCR and sequencing of amplimers.
For amplification, 2·5 µg genomic DNA was digested overnight with 5 U HaeIII (PFV and HIV vector-transduced cells) or NlaIII (MLV vector-transduced cells). After heat inactivation of the restriction enzymes, 0·6 µg genomic DNA was religated overnight. T4 ligase was heat-inactivated and 0·12 µg DNA from PFV vector-transduced cells was relinearized with with AvrII, whilst cellular DNA from MLV and HIV vector-transduced cells was digested with AflII. Inverse PCR was done in a total volume of 25 µl containing 15 ng genomic DNA, 25 pmol each primer (as shown in Supplementary Table 1, available at http://www.uni-wuerzburg.de/virologie/Nowrouzi/PFVintegrationpattern.html), buffer with nucleotides and MgCl2 and 1 U Taq polymerase (Fermentas). The cycle conditions consisted of 30 repeats of 30 s at 94 °C, 1 min at 58 °C and 2 min at 72 °C. A final extension step of 10 min at 72 °C was included. When the amplimers of the first PCR were run on 1 % agarose-containing gel, no bands could be visualized after staining with ethidium bromide. A nested reaction with oligonucleotide primers listed in Supplementary Table 1 (available at http://www.uni-wuerzburg.de/virologie/Nowrouzi/PFVintegrationpattern.html) and 2·5 µl of the first-reaction product was required to see a DNA smear in the range of 500–1500 bp after gel electrophoresis. However, the products of the first reaction could be cloned and sequenced. To avoid any bias due to a second-round PCR and the characterization of multiple identical molecular clones, we followed the strategy of cloning the first-round PCR products without exception. To do this, 3 µl first-round PCR product was ligated into the pCRII-TOPO vector (Invitrogen). Recombinant PFV clones were identified by digestion of DNA with EcoRV and HIV and MLV sequence-containing clones with EcoRI. The clones were sequenced by using a BigDye Terminator Cycle Sequencing kit v1.1 (Applied Biosystems) and M13 forward or reverse primers, depending on the orientation of the insert. Sequences were determined automatically on an ABI 3700 sequencing device (Applied Biosystems).
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) by using the BLAT algorithm (Kent, 2002). Only hits with a sequence identity of >95 % starting at position 1 in the cellular sequence were counted as valid hits. Integration sites satisfying these criteria were selected for further analysis.
The RefSeq gene catalogue and the CpG-Island annotation were obtained from the UCSC ftp server (ftp://hgdownload.cse.ucsc.edu). After removal of redundant annotations, the relative coverage of genes (31·36 %) and CpG islands (0·68 %) was calculated for these catalogues. To examine the distribution along transcription units for insertion into RefSeq genes, each transcript was divided in ten segments of equal length as described by Mitchell et al. (2004). Further, the association of FV integration with transcription starts was studied by calculating the distance to the closest start of transcription for each integration event.
As a control, 10 000 random sites were created by computer simulation and characterized in the same way as the integration sites.
To analyse integration into proto-oncogenes, we used the Sanger Institute Cancer Gene Census Table (http://www.sanger.ac.uk/genetics/CGP/Census/), which contains 346 potential oncogenes. The genomic positions of these proto-oncogenes were obtained by mapping their Entrez Gene (formerly LocusLink) identifiers to the UCSC ‘known-gene’ catalogue. For each FV integrant, the distance and the relative orientation of the nearest proto-oncogene were determined.
For the analysis of characteristic sequence patterns of integrations, 1000 bases flanking the insertion sites in both directions were investigated. The bases of these sequences were numbered from –1000 to 1000 so that the insertion site is located between base –1 and 1, as described by Holman & Coffin (2005) and Wu et al. (2005). For each position, the specific base frequency was calculated and compared with global base frequencies of this assembly. Significant deviations (P values) from the global base compositions were detected by 
2 analysis.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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, is a replication-deficient FV vector with full-length gag and pol genes and integration-competent LTRs. Due to deletion of the FV Tas trans-activator gene, the LTRs are transcriptionally silent (Rethwilm, 1995). 293T cells were transfected with vector plasmid DNA and envelope construct, and cell-free supernatant was used for the transduction of 293 cells at a low m.o.i. that was estimated by FACS using green fluorescent protein as a marker. The transduced cells were cultivated for 6 days without selection prior to DNA extraction and amplification of junction sequences. The pMH123 vector was used to obtain 397 junction sequences by inverse PCR. Of these, 329 could be mapped to the human genome. The other sequences were either too short or the BLAT search yielded no match satisfying our selection criteria.
In the absence of env, PFV can perform an intracellular replication cycle, known as intracellular retrotransposition (IRT) (Heinkelein et al., 2000, 2003). PFV IRT has been shown to be particularly active in 293 cells (Heinkelein et al., 2000, 2003). Provided that the pMH123 vector would integrate downstream of a transcriptionally active cellular promoter, we could not exclude pMH123 IRT. Depending on how often this occurs, it could influence the outcome of the mapping study in an unpredictable way. We therefore generated pMH124 (Fig. 1), which has a large deletion in gag and pol and is, therefore, unable to perform IRT, even if a cellular promoter should give rise to gene expression from the integrated vector. The pMH124 vector was packaged after co-transfection of cells with pCgp1 and pCenv1. Three hundred and seventy-three junction sequences were obtained from transduced cells, of which 299 could be allocated specifically to the human genome. In further analyses, no significant differences were found between pMH123 and pMH124 integrants. Therefore, the results of both experiments were combined. Very few integration sites after PFV IRT have been sequenced previously (Heinkelein et al., 2000). Although, so far, we have no indication that the pattern of integration after IRT and extracellular infection differs, it would be interesting to examine this thoroughly on a larger scale.
For a comparison and to validate our methods with published data, we also generated 103 junction sequences after transduction of 293 cells with the pGJ3/U3E vector (HIV) and 175 junction sequences of the pcAMS/U3E vector (MLV). Of these, 87 and 141 sequences were mapped to the human genome, respectively. Altogether, 15–20 % of sequences that were obtained by inverse PCR could not be allocated to distinct regions of the human genome (see Supplementary Table 2, available at http://www.uni-wuerzburg.de/virologie/Nowrouzi/PFVintegrationpattern.html).
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, we found no particular preference of FV to target specific chromosomes. Analysis of the 293 cell karyotype revealed no major differences in the numbers of individual chromosomes per cell (data not shown). We detected significantly more than random integrations into chromosomes 16, 17, 19 and 22 for HIV. This has also been noted previously and is probably due to the high frequency of actively transcribed genes on these chromosomes (Schröder et al., 2002). The MLV vector targeted chromosome 17 specifically (Fig. 2). However, it should be noted that the HIV and MLV integration-site samples in this study are very small and do not readily allow statistically relevant conclusions.
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). We cannot exclude the possibility that the restriction enzyme used for cutting the genomic DNA resulted in some bias. However, a non-uniform integration on chromosomes was also reported for HIV (Schröder et al., 2002), in which case, a bias due to the choice of a specific restriction enzyme could be excluded (Mitchell et al., 2004). By analogy, it appears unlikely that the choice of the restriction enzyme was responsible for the uneven distribution of FV integrations.
Integration into genes and distance to promoter regions
To determine the integration into genes, we analysed the percentages of proviruses found in RefSeq sequences. As shown in Table 1, we detected slightly fewer FV integrants into RefSeq sequences than would be expected by random integration (27 vs 31 %), whilst MLV had a tendency to prefer transcribed regions of the genome (41 vs 31 %). Consistent with what has been reported previously, we found the highest incidence to target RefSeq genes for HIV (55 vs 31 %).
When the RefSeq regions were divided arbitrarily into 10 segments, which were then analysed for the presence of proviruses (Fig. 3), we found that FVs targeted the first two segments approximately twice as often as would be expected from random integration. MLV integrants preferred the first two segments even more. Consistent with previous studies, HIV integrants avoid the first two segments (Mitchell et al., 2004; Wu et al., 2003).
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, we found that FVs integrated at a rate approximately three- to fourfold of the expected random value 2·5 kb upstream or downstream of the TSS, whilst HIV avoided this region. For MLV, we found the vast majority of proviruses around the TSS, as reported previously (Wu et al., 2003) (Fig. 4).
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). To this end, the selection of integration sites by a given retrovirus is probably related to an optimum of transcriptional activity of the provirus. For HIV, heterochromatin and gene deserts, regions that appear to be underrepresented for integration, have been shown to be chromosomal features that can repress HIV transcription (Lewinski et al., 2005).
Obviously, virus-specific cellular factors that bind to the integration machinery are responsible for the selection of specific integration target sites (Cherepanov et al., 2003; Ciuffi et al., 2005; Turlure et al., 2004).
Integrations into proto-oncogenes
We also determined the frequency with which cellular proto-oncogenes were hit by FV integrants. As shown in Table 2, seven direct hits into proto-oncogenes were found. However, it has been reported recently that retroviral enhancers may act at distances of 0·5 Mb on cellular genes in a clinically relevant gene-transfer setting (Kustikova et al., 2005). Therefore, we analysed the distance of FV integrants to the nearest proto-oncogene up to a maximum of 0·5 Mb. By using the search modus, 108 hits were found in the database (see Supplementary Fig. 1 and Supplementary Table 3, available at http://www.uni-wuerzburg.de/virologie/Nowrouzi/OnlineMaterial.pdf).
It should be noted that the potential activation of cellular genes by a FV vector would also be determined by the activity of the internal promoter that must be used to drive transgene expression in these vectors, because of the inactivity of the FV LTR in the absence of the viral trans-activator (Rethwilm, 1995).
Integration into CpG islands
After analysing the integration frequency into RefSeq genes and evaluating the distances to TSS, we wanted to further investigate the proximity of integration sites to regulatory regions by a different criterion. To this aim, we evaluated the distance of FV integrations upstream and downstream of CpG islands (Mitchell et al., 2004; Wu et al., 2003). CpG islands are often associated with promoter regions of housekeeping genes (Gardiner-Garden & Frommer, 1987; Larsen et al., 1992; Yamashita et al., 2005). For the regulation of gene expression of downstream genes, transcription factors bind to CpG sequences, a feature that depends on their methylation status (Costello et al., 2000; Cross & Bird, 1995).
As shown in Fig. 5, we detected no significant difference between PFV and HIV in integration into CpG islands; both target these sequences approximately twice as often as would be expected from random integration. The highest number of integrations into CpG islands was found for MLV, which is consistent with previous reports (Mitchell et al., 2004; Wu et al., 2003).
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; Wu et al., 2005). Similar to MLV, FV integration generates a duplication of 4 nt at the cellular genome target site (Enssle et al., 1999). When the nucleotide composition at integration sites was compared with the overall base composition of the human genome (30 % A, 20 % C, 20 % G, 30 % T; Wu et al., 2005), we found a highly significant preference for G and C nucleotides at positions –1 and –4, whereas A at position –4 and T at position –1 are highly disfavoured (Fig. 6 and Supplementary Fig. 2, available at http://www.uni-wuerzburg.de/virologie/Nowrouzi/OnlineMaterial.pdf). Integration-site preferences were found at even greater distances (up to position 4 or –8 of the site of integration). The ideal PFV site of integration appears to be a palindrome of the sequence C–8C–7(A)–6C–5C/G–4N–3N–2C–1G/C1(T)2N3G4, indicating that there are local sequence constraints that, in addition to more global preferences, determine the sites used by PFV to integrate into the genome on a more local scale. However, we never found a sequence with an identical base composition to the depicted site at each position, suggesting that there are preferences for certain bases at specific positions, without necessarily resulting in the ideal sequence. Interestingly, the strongest preferences or avoidances for specific bases at FV integration sites were found at the positions of the DNA-strand transfer (Fig. 6). This was also noted for other retroviruses that have been investigated in this respect (Holman & Coffin, 2005; Wu et al., 2005).
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; Schröder et al., 2002; Wu et al., 2003). We used an inverse PCR to obtain PFV proviral-junction sequences. The limited numbers of HIV and MLV sequences that were identified for control purposes were in good agreement with the previous studies on these retroviruses, which demonstrated the usefulness of our method in generating a map of PFV integrations.
As shown previously and in this study, HIV integration prefers actively transcribed genes and avoids promoter regions (Mitchell et al., 2004; Schröder et al., 2002; Wu et al., 2003). To the contrary, MLV has a strong preference for promoter regions (Mitchell et al., 2004; Schröder et al., 2002; Wu et al., 2003). This was also demonstrated for MLV by targeting CpG islands. We show here that PFV has an integration pattern different from those of HIV and MLV. PFV clearly does not favour transcribed regions of the genome. However, when it comes to an integration in such regions, it integrates close to the start of transcription and is, therefore, more similar to MLV than to HIV. A more detailed discussion of the different integration patterns between various retroviruses must wait until the viral and cellular factors that promote this kind of wide-range selectivity for integration sites have been identified. The same holds true for the more local-range selectivity that was described for the different integration reactions (Holman & Coffin, 2005; Wu et al., 2005). However, with respect to the latter, it may turn out that they can be attributed to different specificities of the individual integrase enzymes for nucleosome-bound target DNA, which in turn is strongly determined by the base composition of the DNA (Wu et al., 2005).
Definite conclusions with respect to the risk of retroviral vectors derived from HIV, MLV or PFV to lead to insertional mutagenesis also cannot be drawn from our study. Such a risk is determined less by the integration profile of a given vector, but more by the number of transduced cells reinfused into the patient (von Kalle et al., 2004). In addition, the nature of the transgene and the kind of disease to be cured have a major impact on the clinical outcome of gene therapy (Baum et al., 2003; von Kalle et al., 2004). The determination of the risk of proto-oncogene activation is further complicated by the recent demonstration in the mouse model that proto-oncogene activation via MLV vector integration into haematopoietic cells can occur over distances as long as 0·5 Mb (Kustikova et al., 2005). Furthermore, the activation of growth-promoting genes by retroviral vector insertion is, as such, not necessarily deleterious. Depending on the individual constellation, a stimulation of in vivo growth of the gene-corrected cells can be helpful in the treatment of diseases where an in vivo selective advantage does not exist.
Different strategies, such as the use of self-inactivating (SIN) vectors or insulators, have been suggested to reduce the risk of proto-oncogene activation by MLV-derived vectors (Baum & Fehse, 2003; von Kalle et al., 2004). In this respect, it is noteworthy that PFV-derived vectors are naturally of a SIN type because they lack the viral Tas transactivator, which is required for transcription from the LTR (Rethwilm, 1995). Furthermore, PFV vectors have been shown to be ideal in transducing unstimulated CD34-positive human cells by a simple overnight transduction protocol (Josephson et al., 2002; Leurs et al., 2003). This may turn out to be the greatest advantage of using these vectors in clinical trials, because it would allow for a significant reduction in the number of gene-corrected cells that must be reinfused into a patient.
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ACKNOWLEDGEMENTS |
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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Received 23 September 2005;
accepted 9 January 2006.
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