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binding to negatively curved membranes

binding to negatively curved membranes. Cell biology with bacteria?. 5 µm. Localization of cell division proteins. Rut Carballido-López. GFP-MinD. How do proteins localize to cell poles ? (DivIVA as model system). DivIVA-GFP. (lack of) Information from secondary structure prediction.

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binding to negatively curved membranes

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  1. binding to negatively curved membranes

  2. Cell biology with bacteria? 5 µm

  3. Localization of cell division proteins

  4. Rut Carballido-López

  5. GFP-MinD

  6. How do proteins localize to cell poles ?(DivIVA as model system) DivIVA-GFP

  7. (lack of) Information from secondary structure prediction 164 amino acids, mostly helical secondary structure prediction by PSIPRED coiled coil prediction by LUPAS multimerization via coiled coil regions

  8. Possible mechanisms: 1) binding to another (cell division) protein 2) binding to a specific lipid species 3) affinity for curved membranes

  9. 20 % membrane vesicles 30 % 70 % Binding to another (membrane) protein? DG = DivIVA-GFP V = membrane vesicles Lip = liposomes D = DivIVA G = GFP

  10. amphipathic helix of N-terminus (60 aa) Biacore (surface plasmon resonance) with L1-chip T = min

  11. Possible mechanisms: 1) binding to another (cell division) protein 2) binding to a specific lipid species 3) affinity for curved membranes Edwards, 2000, EMBO

  12. Cardiolipin Domains in Bacillus subtilis Kawai, 2003, J. Bac.

  13. DivIVA localization in B. subtilis strains lacking certain lipids wt - PG -PE - CL

  14. Possible mechanisms: 1) binding to another (cell division) protein 2) binding to a specific lipid species 3) affinity for curved membranes

  15. Affinity for curvature = induces curvature ‘BAR domains as sensors or membrane curvature’ Peter et al., 2004, Science

  16. Affinity for curvature = induces curvature ‘BAR domains as sensors or membrane curvature’ Peter et al., 2004, Science

  17. DivIVA D D D D D D D D D liposomes Induction of curved membranes ? liposomes + DivIVA liposomes 200 nm

  18. Induction of curved membranes ? 200 nm

  19. 100 nm

  20. Possible mechanisms: 1) binding to another (cell division) protein 2) binding to a specific lipid species 3) affinity for curved membranes ?

  21. Does curvature really not play a role? B. subtilis E. coli

  22. E. coli division mutant MHD63

  23. Possible mechanisms: 1) binding to another (cell division) protein 2) binding to a specific lipid species 3) affinity for curved membranes….., but not as we know it

  24. Ø ~ 25 nm Higher order DivIVA structures ‘Doggy bones’ Stahlberg, 2004, Mol. Mic. ( Cryo-negative stain EM )

  25. ? ~ 25 nm ? Ø ~ 100 nm Conceptual simplification:

  26. ‘Molecular Bridging’ 1) self interaction (clustering) of subunits 2) subunits should be large (relative to curvature) 3) membrane interaction (weak) - no other proteins / lipids / or curved proteins necessary -

  27. Monte Carlo simulation

  28. Monte Carlo simulation • Rules: • - cylinder 1 x 4 µm • - DivIVA oligomers (green) = spheres of 25 nm diameter • - curvature of membranes at transition from lateral wall to sides = diameter of 100 nm • - spheres can make max 8 contacts (doggy bone contains at least 8 DivIVA molecules) • 2 membrane contacts maximal (based on our EM data) • Epp and Epm in the range 1.5-6 k bT • (equivalent to 1-4 kcal/mol) ~in range of typical weak protein-protein attractions

  29. - spheres can make 8 contacts - 2 membrane contacts maximal - spheres can make 4 contacts - no limitations in membrane contacts

  30. d = 50 nm d =100 nm - No restrictions in nr. of interactions Epp = 2 k bT Epm = 6 k bT - 4 pp bonds - membrane contact = 1 pp contact Epp = 2.5 k bT Epm = 5.5 k bT

  31. d = 50 nm d =100 nm • - max 4 pp bonds • - membrane contact • = 2 pp contact • Epp = 3 k bT • Emp = 5.5 k bT • max 6 pp bonds • membrane contact • = 3 pp contacts • Epp = 3.5 k bT • Epm = 5.5 k bT

  32. Max 8 pp bonds • membrane contact • = 4 pp contacts • Epp = 3.5 k bT • Epm = 5.5 k bT d = 50 nm d =100 nm

  33. Modelling of doggy bones

  34. CBCB - Newcastle University Rok Lenarcic Ling Wu Jeff Errington Sven Halbedel University of Oxford Wouter de Jong LoekVisser Michael Shaw University of Edinburgh Davide Marenduzzo

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