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Stochastic Models of Microdomain Formation in Biological Membranes Anne Kenworthy Lab: Maria Byrne, Kimberly Drake, Shawn Goodwin, Minchul Kang, Carl Rogers Research Problem The micro-organization of lipids and proteins within the cell membrane is an open question. It is hypothesized that many proteins organize within glycosphingolipid and cholesterol-enriched “lipid- raft” domains. We investigate: (1) Clustering mechanisms which would result in distinct protein organizations within lipid rafts and (2) Ways in which FRET could be used to distinguish among these possibilities in native cell membranes. Conclusions Evidence for Lipid Rafts In Cell Membranes Models for Lipid Raft Formation A Discrete Stochastic Model For FRET Results Distinguishing 3 Different Models for Raft Formation With FRET The Fluid-Mosaic Model With Microdomains The fluid-mosaic model of Singer and Nicholson, in which the plasma membrane is a phospholipid bilayer embedded with proteins, includes lipid membrane domains within the “mosaic”. Protein clustering occurs as proteins form complexes or preferentially partition into different membrane domains: the protein caveolin clusters in flask-shaped structures called caveolae and GPI-anchored proteins cluster in the apical ends of epithelial cells. Drawn by P. Kinnunen, CEO of Kibron, Inc Heetderks and Weiss Lipid-Lipid Interactions FRET: Fluorescence Resonance Energy Transfer FRET Rate and Förster Distance Dipole-dipole interaction is highly dependent upon distance. In 1948, T.M. Förster calculated that the rate of resonance energy transfer between two fluorophores would depend on the inverse of the sixth power of their separation. Ro =distance when transfer rate equals decay rate A fluorophore with an excited electron may transfer its electronic energy to another fluorophore (by resonance) if: 1. the second fluorophore is near and 2. the emission energy of the first molecule matches the excitation energy of the second. This occurs by dipole-dipole interaction. Due to the sensitive dependence of FRET on inter-molecular separation, FRET has been used as an amazingly accurate “spectroscopic ruler” [Stryer, 1967]. Donors excite with constant rate k E., which models constant illumination. Modeling: Fluorophore Excitation States Transfer occurs between every unexcited acceptor and every excited donor at rate k T, which depends upon their molecular separation r : Excited fluorophores decay with constant rate K D, which models exponential decay. Y = Y 0 e -k D t k t = k D * (R 0 /r) 6 The lifetime of the fluorophore Is 1/K D = . 0Un-excited0 → 1Excitation 1Excited1 → 0 Decay or Transfer The coupling energy (e.g., partition coefficient) between any two lipid species i and j is i i. The total energy of the system is defined as the sum of the coupling energies of all adjacent nodes on the lattice. Lipid Species Each lipid species is assigned an indice and each node of a square lattice is occupied by exactly one lipid species. Lipids diffuse by stochastic random walk in a way which decreases system energy by the Metropolis algorithm: Neighboring lipids switch locations if switching decreases the energy of the system. Otherwise, the switch is permitted depending on the temperature of the system. Lipid Diffusion Lattice Energy These rules cause lipid species to sort from a random distribution into clusters Rule: “like” lipids have lower coupling energies than unlike. Random Initial ConditionsSorting After 100 Timesteps Lattice Energy Over Time Example A Lipid 3 Partitions Within Lipid 2 Example B Lipid3 Partitions Slightly Within Lipid2: L2-L2 coupling energy is less than L2-L3 coupling energy Low Intermediate High Example C Lipid3 Doesn’t Partition Within Lipid2 Low Intermediate High Labeling Lipid 3 with 50% acceptors and 50% donors: The three models cannot be distinguished. Labeling Lipid 3 with donors (100%) and Lipid 2 with acceptors (25%):: The most extreme model C can be distinguished. Labeling Lipid 3 with donors (100%) and Lipid 1 with acceptors (25%):: All models can be distinguished. All figures show FRET efficiency verses concentration of Lipid 3 for Example A (blue), Example B (violet) and Example C (pink). [Low=1%, Medium=10%, High=30%] General Results For FRET When Lipid3 is Randomly Distributed Within Lipid2 FRET Efficiency = (# Actual Transfers) / (# Possible Transfers) = (Acceptor Fluorescence) / (Acceptor + Donor Fluorescence) For a wide range of experimental conditions in which lipid 3 is labeled (varying acceptor to donor ratio, percent labeling) and any cluster mechanism resulting in a random distribution of lipid3 within regions of lipid2, FRET efficiency shows very regular behavior. For cluster mechanisms which are known to result in a random distribution of a lipid (or protein) within another lipid domain, FRET reports unambiguously on the concentration of the lipid (or protein) within the domain. For more complex cluster mechanisms (e.g., ones which do not result in random distributions within subdomains) FRET can distinguish between models. Modeling can be used to determine the most sensitive experimental approach. In simple lipid mixtures, phospholipids with long, ordered chains sort into gel domains and those with short, disordered chains sort into fluid domains. The addition of cholesterol to gel domains forms a liquid ordered phase, the proposed state of lipid rafts. Putative Lipid Rafts Isolated by Detergent Extraction Cholesterol and glycosphingolipids, along with putative raft proteins, are resistant to cold Triton X- 100 extraction. However, the “raft proteins” can be extracted from cholesterol-depleted membranes. Low Intermediate High Examples of A 3-Lipid Mixture: Lipid 1 and Lipid 2 occur in 1:1 ratio. Lipid 1 and Lipid 2 do not mix. Lipid 3 increases in concentration from low to high. Lipid 1: lighter color Lipid 2: darker color Lipid 3: white pixels The Lipid Raft Hypothesis It is hypothesized that separation of discrete liquid-ordered and liquid-disordered phase domains occurs in membranes containing sufficient amounts of sphingolipid and sterol. The proposed liquid-ordered lipid “rafts” would be involved in signal transduction, protein sorting and membrane transport.
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