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Virus discovery-454 sequencing

Virus discovery-454 sequencing. Michel de Vries. Laboratory of Experimental Virology. Introduction. In 5-40 % of hospitalized patients with suspected respiratory viral infection no agent is identified. Possible problem: New or unusual subtype.

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Virus discovery-454 sequencing

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  1. Virus discovery-454 sequencing Michel de Vries Laboratory of Experimental Virology

  2. Introduction • In 5-40 % of hospitalized patients with suspected respiratory viral infection no agent is identified. • Possible problem: • New or unusual subtype. • Virus Discovery cDNA-AFLP (VIDISCA) was developed in 2004. * • VIDISCA can amplify both RNA and DNA viruses without prior knowledge of the target • sequence. • Based on restriction enzyme cleavage sites + ligation of adaptors + PCR. * van der Hoek et al, Nature medicine 2004

  3. Selective PCR (16 primer combin.) Fragment separation and isolation Cloning in TA vector Colony-PCR Sequencing of colony-PCR products VIDISCA

  4. Problems • VIDISCA amplifies background ribosomal RNA (rRNA) and chromosomal DNA together with viral sequences. • This background amplification interferes with VIDISCA by acting as competitors. • VIDISCA can only amplify high viral load samples and/or low background samples. • Clinical samples such as nose washing are full with background rRNA and chromosomal DNA.

  5. Clinical samples • 12 clinical samples (nose washings) supplied by clinical virology. • Virus in the samples were identified via multiplex PCR but given double blind. • Samples containing high/medium/low viral load of known viruses. • For 1 out of 12 samples a viral sequences was obtained (HCoV-229E). • In most samples only background rRNA and DNA was identified

  6. Solution If a high number of fragments are randomly sequenced, a minority population can be identified.

  7. Primer A MID DNA fragment Primer B Next Generation Sequencing • One of NGS is the 454 sequencer of Roche, which is present in the AMC. • Per run a maximum of 1.5 E6 beads can be used resulting in about 400.000 quality sequences. • Multiplex identifiers (MID) are 10 nucleotides long barcodes that are recognized by our software. • The MID can be incorporated into samples allowing multiple samples to be pooled.

  8. Selective PCR (16 primer combin.) Fragment separation and isolation Cloning in TA vector Colony-PCR Sequencing of colony-PCR products VIDISCA- 454 454 sequencing

  9. VIDISCA-454 • Can we sequence viruses with VIDISCA-454 ? • Can we use 12 MIDs in one run ?

  10. Test with human coxsackievirus B4 • 12 times coxsackievirus B4 supernatant (2.0 E8 copies/ml) as input. • Each with a specific MID-primer A anchor. • Sequences were separated per MID, aligned and compared to GenBank database.

  11. Result

  12. Result 2

  13. Conclusion • VIDSICA-454 works!! • 12 MIDs can be used, so 12 samples can be pooled in a sequence run.

  14. Conclusion • VIDSICA-454 works!! • 12 MIDs can be used, so 12 samples can be pooled in a sequence run Are we ready for clinical samples??

  15. Result 3 • Again the12 clinical samples tested with VIDSICA-454 1 2 3 4 5 6 7 8 9 10 11 12

  16. Result 4 In 6 out of 12 samples a virus could be identified.

  17. Conclusion • With VIDISCA-454 6 out of 12 clinical samples could be identified compared to 1 out of 12 with normal VIDISCA. • An increase of sequence data by 454 sequencing results in a high chance of viral detection in clinical samples. • We are ready for clinical samples!!

  18. Advantage VIDISCA-454 • Cheaper per sample. • More samples per time unit. • More sequence information per sample. • Less interference by background amplification. • More sensitive.

  19. Problems • One of the critical steps is measuring/calculating the amount of DNA. • DNA is measured in ng/µl via fluormeter and DNA size is estimated via agarose gel. • Analyses takes 1 month. • Codoncode (aligning program) can not handle > 2000 sequences. Therefore you have to align in batches. • For analyses via Blast sequences have to be exported in batches of 100 and then submitted.

  20. Acknowledgements • Laboratory of experimental virology Nuno Faria Marta Canuti Martin Deijs Maarten F. Jebbink Lia van der Hoek • Department of Neurogenetics Marja jakobs Frank Baas • Deparment of clinical virology Richard Molenkamp • Klinische Epidemiologie, Biostatistiek en Bioinformatica Barbera van Schaik Angela Luijf micheldevries@high-throughput-sequencing.com

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