Hierarchical Bionanotubes Formed by the Self Assembly of Microtubules with Cationic Membranes or Polypeptides
Original Entry by Holly McIlwee, AP225 Fall 09
Uri Raviv, Daniel J, Needleman, Kai Ewert, Cyrus R. Safinya, Hierarchical Bionanotubes Formed by the Self Assembly of Microtubules with Cationic Membranes or Polypeptides Journal of Applied Crystallography. 2007, 40, s83-s87.
Self-assembly, Microtubules, Nanotubes
This paper focuses on the interactions between cellular proteins and associated biomolecules and supramolecular structures leading to the relationship between structure and function of the nerve cell. Currently the structure-function relationship in nerve cells is still poorly understood. But their high order specialized functions make nerve cells an extremely fascinating structure to understand. Needleman et al. present synchrotron X-ray diffraction and electron microscopy data of reconstituted protein systems from the bovine central nervous system. From these experiments bionanotubes composed of a three component structure: microtubules coated in lipid bilayers, coated with tubulin oligomers forming rings or spirals are discovered. Next, their structure is further investigated and possible applications are discussed.
Needleman et al. describes a generally accepted perspective for lipid self-assembly leading to nanotubule formation in mixed charged systems. An interaction between negatively charged microtubules and positively charged lipid membranes, under appropriate conditions gives rise to spontaneously forming lipid protein nanotubules.
Following are examples of lipid-biopolymer interactions previosuly studied:
1. The mixing of cationic lipids and DNA complexes are formed that bring genes into cells (Koltover, 1998)
Polyelectrolyte lipid complexes:
2. Pinched multilamellar PLCs from PGA complexed with cationic membranes (Subramanian, 2000)
3. Flat, thermally functioning, multilamellar PLCs from lambda DNA complexed with cationic membranes (Radler, 1997)
4. Swollen multilamllar PLCs from filamentous actin (F-actin) is complexed with cationic membranes (Wong, 2000)
The structures listed above are templated by the original multilamellar phase of the lipid bilayers and the biopolymers absorb on and between the membranes. Polyelectrolyte layers that form on cationic lipid membranes increase in order as polymer diameter and ridity are increased.
Microtubules (MTs) are negatively charged supramolecular polymers, which self-assemble from tubulin protein subunits into hollow cylinders. MTs are critical in many functions in eukaryotic cells: for instance, as pathways for neurotransmitter precursors and enzymes to synaptic junctions in nerve cells.
Needleman et al. study the interactions between MTs and cationic lipid bilayers to understand the interplay between electrostatic and elastic interactions governing lipids and biopolymers. It was found that in this case the electrostatic interactions of MTs dominate and MTs form the template for the complex structure.
Analysis of these structures with SAXRD and TEM realized 2 novel structures (Raviv 2005, 2006): At low membrance charge density, vesicles adsorb onto the MT and appear as 'beads on a rod' (BOR). This state appears to be kinetically trapped. At low and intermediate rigidity, cationic liposomes spread and coat the MTs and the external lipid layer is decorated by tubulin oligomers, forming a novel LPN. By controlling stoichiometry the ends can be opened and closed with lipid caps for possible drug delivery applications.
Later MT and poly L-lysine interactions were studied. Poly L-lysine coats the MT and is then coated by a third layer of tubulin oligomers, forming peptide-protein nanotubes. BOR is formed at low cationic lipid mole fractions (Xcl=0.1). The MT wall is negative. The state is kinetically trapped and over 60hrs, lipid-protein nanotubes form. At Xcl>0.1, LPNs form immediately after mixing. LPN is essentially 3 layers: MTs, coated with a lipid bilayer, coated by tubulin oligomers forming rings or spirals. This showed that formation of the third layer is not specific to the 2nd layer chemistry, but is drive by electrostatic interaction optimization.
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