HIV recombination in the development of drug resistance

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1 HIV recombination in the development of drug resistance A. Schultz T. Tänzer Department of Virology J. Reiter University of the Saarland T. Breinig A. Meyerhans J-P. Vartanian Unité de Rétrovirologie Moléculaire S. Wain-Hobson Institut Pasteur G. Bocharov Institute of Numerical Mathematics Russian Academy of Science

2 HIV recombination in the development of drug resistance Ingrid Stahmer Hans-Jürgen Stellbrink Center of Internal Medicine University Clinic Eppendorf Hamburg Paul Racz Klara Tenner-Racz Department of Pathology Bernhardt-Nocht Institute Hamburg

3 Variation mechanisms HIV dynamics Point mutation ~ 0.25 / genome / round up to 700 / genome / round HIV error mechanisms ~ 3-30 / genome / round Hypermutation Recombination Error catastrophy Mosaic structures

HIV484 HIV497 HIV493 HIV465 HIV482 HIV500 HIV506 HIV510 HIV504 HIV499 HIV503

4 To analyse the generation of HIV recombinants multiple HIV proviruses co-packaging of viralrna recombinant HIVprovirus HIV496 HIV488 HIV494 HIV472 HIV484 HIV497 HIV493 HIV465 HIV482 HIV500 HIV506 HIV510 HIV504 HIV499 HIV503 HIV498 Jung et al. (2002), Nature 418 p144 Wain-Hobson et al. (2003), J. Gen. Virol. 84 p885-95

5 Multiinfection and recombination can accelerate fitness-dependent fixation of advantageous mutants Random assortment + HIV budding HIV transcription (expansion) Infection of uninfected cells Distinct stagesof a single replication round Multiple HIV integration Reverse transcription ->point mutation ->recombination Population fitness Initial population: [0 (1),É,0 (10),É,0 (49),0 (50),0 (51),É,0 (90),É,0 (100) ], fitness =0.01 Specific 1-point mutants population: [0 (1),É,* (10),É,0 (49), * (50),0 (51),É,* (90),É,0 (100) ], fitness =0.33 Specific 2-point mutants population: [0 (1),É,* (10),É,0 (49), * (50),0 (51),É,* (90),É,0 (100) ], fitness =0.67 Specific 3-point mutants population:, [0 (1),É,1 (10),É,0 (49), 1 (50),0 (51),É,1 (90),É,0 (100) ], fitness = pv + recomb 1 pv Bocharov et al. (2005), J.Gen.Virol. 86 p

6 Questions What is the consequence of multiinfection and recombination for HIV evolution? i.e. evolution of multidrug resistant viruses? How does multi-infection occur? i.e. cell-cell transmission or via free virus? How many viruses have to enter a single cell to generate 3-4 proviruses? i.e. to overcome intracellular defence mechanism? Are the different HIV proviruses within a single infected cell transcriptionally active?

7 Aim Detection of transcriptionally active HIV-1 variants within single cell

8 Experimental Design Virus reactivation from infected cells via IL-2, IL-6 and TNFα Inhibition of HIV spread after reactivation via T20 Identification of transcriptionally active cells via RNA-FISH Isolation of FISH + cells via laser microdissection RT-PCR and sequence analysis

9 Zur Anzeige wird der QuickTime Dekompressor TIFF (Unkomprimiert) benötigt. are needed to see this picture. QuickTime and a TIFF (LZW) decompressor are needed to see this picture. QuickTime and a TIFF (LZW) decompressor are needed to see this picture. Sensitive detection of HIV RNA by RNA-FISH in PMA-stimulated ACH2 cells A 3.01 ACH2 (hrs post stimulation) QuickTime and a TIFF (LZW) decompressor

10 IL-2, IL-6 and TNFα is an efficient cocktail to reactivate HIV-1 provirus transcription A3.01 ACH2 (hrs post stimulation) Stimulation cocktail: Fauci et al. J. Ex. Med. Vol. 188 No. 1, 1998

11 T20 efficient inhibits HIV infection and spread in PBLs ex vivo + T20 50 µg/ml 10 µg/ml 5 µg/ml without T 20

12 PBLs: from patient to analysis ~ 2,5 x 10 5 PBLs ~ 1 x 10 5 PBLs ~ 1 x 10 4 PBLs for analysis reactivation +T20 fixation RNA-FISH procedure fluorescence microscopy

13 Isolation of FISH + cells via laser microdissection cells after FISH on PE-coated slides adhesive cap selection of single cells for isolation laser slides after isolation of the cells via LPC Principle of Laser Pressure Catapulting (LPC):

14 Summary Virus reactivation from infected cells via IL-2, IL-6 and TNFα Inhibition of HIV spread after reactivation via T20 Identification of transcriptionally active cells via RNA-FISH Isolation of FISH + cells via laser microdissection RT-PCR and sequence analysis, experiments are ongoing

15 Outlook Modelling of recombination effects on the evolution of HIV drug resistance in patients Analysis of patient material for transcribed drug resistant variants within single cells

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