Embed Size (px)
Citation preview
University of Calgary
PRISM: University of Calgary's Digital Repository
Graduate Studies The Vault: Electronic Theses and Dissertations
2015-09-18
Observations in Lipid Membrane Systems
Munro, Fay
Munro, F. (2015). Observations in Lipid Membrane Systems (Unpublished master's thesis).
University of Calgary, Calgary, AB. doi:10.11575/PRISM/27158
http://hdl.handle.net/11023/2468
master thesis
University of Calgary graduate students retain copyright ownership and moral rights for their
thesis. You may use this material in any way that is permitted by the Copyright Act or through
licensing that has been assigned to the document. For uses that are not allowable under
copyright legislation or licensing, you are required to seek permission.
Downloaded from PRISM: https://prism.ucalgary.ca
UNIVERSITY OF CALGARY
Observations in Lipid Membrane Systems by
Fay Elizabeth Munro
A THESIS
SUBMITTED TO THE FACULTY OF GRADUATE STUDIES
IN PARTIAL FULFILMENT OF THE REQUIRMENTS FOR THE INTERDISCIPLINARY
DEGREE OF MASTER OF SCIENCE
GRADUATE PROGRAM IN CARDIOVASCULAR AND RESPIRATORY SCIENCES
CALGARY, ALBERTA
SEPTEMBER, 2015
©FAY ELIZABETH MUNRO 2015
ii
Abstract The plasma membrane is phase separated into a fluid (Ld) phase and a more
ordered (Lo) phase. The latter exists as small “rafts” of specific lipid composition
containing a host of signaling proteins. Lipid raft theory links the aggregation of
rafts to a signaling event. In its current iteration, the theory is incomplete, as it does
not explain how rafts form and how they aggregate and disperse again. These
problems are addressed when the membrane is viewed as a critical system.
Previous work using giant plasma membrane vesicles (GPMVs) used this framework
to explain the dynamics of the rafts. We intended to show critical behavior as a
factor for cell signaling. Critical behavior was not easily ascertained and further
observations were made. We found a heterogeneous population with respect to the
behavior of the vesicles. We categorized these observations with respect to the
appearance of the lipid membrane to characterize the phenomenon.
iii
Acknowledgements I would like to thank my supervisor, Matthias Amrein, my family, the Amrein lab and my committee.
iv
Table of Contents Abstract ........................................................................................................................................................................ ii Acknowledgements ............................................................................................................................................... iii Table of Contents .................................................................................................................................................... iv List of Tables and Graphs .................................................................................................................................... v List of Figures ........................................................................................................................................................... vi List of Abbreviations ........................................................................................................................................... vii
1 Introduction ..................................................................................................................................... 1 1.1 Overview ............................................................................................................................................................. 1 1.2 Plasma Membrane: A historical background ................................................................................... 1 1.3 Lipid Rafts ......................................................................................................................................................... 2 1.4 Lipid raft theory .............................................................................................................................................. 6 1.5 Lipid raft theory: shortcomings ............................................................................................................... 8 1.6 A New Understanding of the Plasma Membrane ................................................................... 10 1.7 General hypothesis ...................................................................................................................................... 13
1.7.1 Specific Aim 1 .................................................................................................................................. 13 1.7.2 Specific Aim 2 .................................................................................................................................. 14 1.7.3 Specific Aim 3 .................................................................................................................................. 15
2 Materials and Methods ................................................................................................................. 17 2.1 Materials and Methods: ............................................................................................................................. 17 2.1.1 Cell Lines ........................................................................................................................................... 17 2.1.2 Reagents ............................................................................................................................................ 17 2.1.3 Collection of GPMVs: .................................................................................................................... 18 2.1.4 Imaging .............................................................................................................................................. 19 2.1.5 Light Microscopes ........................................................................................................................... 19 2.1.6 Spectrofluorometer ...................................................................................................................... 21
3 Results ............................................................................................................................................. 22 3.1 GPMV Production ...................................................................................................................................... 22 3.2 Phase Separation ...................................................................................................................................... 23 3.2.1 Static Phase Separation .............................................................................................................. 24 3.2.2 Dynamic Phase Separation ........................................................................................................ 25 3.2.3 Critical Phase Separation ........................................................................................................... 26
3.3 Observations of Blebbing ..................................................................................................................... 28 3.3.1 Observations of Blebbing – Results ....................................................................................... 28 3.3.2 Observations of Blebbing – Discussion ................................................................................ 29
3.4 Vibrations ..................................................................................................................................................... 33 3.4.1 Vibrations -‐ Results ...................................................................................................................... 33 3.4.2 Vibrations – Discussion .............................................................................................................. 35
3.5 Spectrofluorometer ................................................................................................................................. 37 4 Discussion ......................................................................................................................................... 39 Bibliography ......................................................................................................................................... 42 Appendices ................................................................................................................................................................ 47 Tables ........................................................................................................................................................................... 47 Figures ......................................................................................................................................................................... 50
v
List of Tables and Graphs Table 1.1 ………………………………………………………………………………………page 47 Graph 2.1 ………………………………………………………………………………………page 48 Graph 2.2 ………………………………………………………………………………………page 48 Graph 2.3 ………………………………………………………………………………………page 49 Graph 2.4 ………………………………………………………………………………………page 49
vi
List of Figures Figure 2.1 ………………………………………………………………………………………page 50 Figure 2.2 ………………………………………………………………………………………page 51 Figure 2.3 ………………………………………………………………………………………page 52 Figure 2.4 ………………………………………………………………………………………page 53 Figure 2.5 ………………………………………………………………………………………page 54 Figure 2.6 ………………………………………………………………………………………page 55 Figure 2.7 ………………………………………………………………………………………page 56 Figure 2.8 ………………………………………………………………………………………page 57 Figure 2.9 ………………………………………………………………………………………page 57 Figure 2.10 .……………………………………………………………………………………page 58 Figure 2.11 …………………………………………………………………………………….page 59
vii
List of Abbreviations BCR – B cell Receptor
CalDAG-GEF - Calcium and Diacylglycerol regulated Guanine Nucleotide Exchange
Factor
CTB -‐ Cholera toxin β
D.C. 2.4 -‐ Dendritic cell 2.4
DMSO -‐ Dimethyl sulfoxide
DPPC -‐ Dipalmitoylphosphatidylcholine
DRM -‐ Detergent resistant membrane
DTT -‐ Dithiothreitol
ENTH -‐ Epsin N-‐terminal domain
GM1 -‐ Glycosyl phosphatidylinositol
GPMV -‐ Giant plasma membrane vesicle
HEPES -‐ 4(2-‐hydroxyethyl)-‐1-‐piperazineethanesulfonic acid
Ld -‐ Liquid disordered
Lo -‐ Liquid ordered
LPC -‐ Lysophosphatidylcholine
MβCD -‐ Methyl-‐beta-‐cyclodextrin
MSU -‐ Monosodium urate crystal
PFA -‐ Paraformaldehyde
PI-‐4,5-‐P2 -‐ 1,2-‐Diacyl-‐sn-‐glycero-‐3-‐phospho-‐(1-‐D-‐myo-‐inositol 4,5-‐bisphosphate)
POPC -‐ 1-‐palmitoyl-‐2-‐oleoyl-‐sn-‐glycero-‐3-‐phosphocholine
POPE/PE -‐ phosphatidylethanolamine
Tc -‐ Critical temperature
TIRF – Total internal reflection fluorescence microscopy
TCR – T Cell Receptor
1
1 Introduction
1.1 Overview This thesis aims to establish a novel view for lipid raft based plasma membrane
signaling. Currently, lipid rafts are thought to be small lipid domains with associated
lipid-raft proteins that exist in the plasma membrane. The coalescence of these rafts has
been associated with signaling events. The accumulation of signaling proteins is
understood to result from the accumulation of lipid rafts. The current lipid raft theory
does not explain how rafts would form and self-assemble into structures of the right size
and contain the right assortment of proteins. It also leaves unexplained why and how rafts
would dispel again after the signaling event. In this thesis, we pursued an alternate theory
for cell signaling, namely that critical behavior is an underlying feature of the plasma
membrane that is required for signaling.
1.2 Plasma Membrane: A historical background The understanding of the plasma membrane has evolved greatly since its
discovery. Robert Hooke was the first to describe a cell in 1665, and along with
discovering the cell; Hooke observed that the cell was a protoplasm enclosed within some
form of membrane. At the time, the only known function of the membrane was
encasement. It was not until 1925 when Groter and Grendal (1925) discovered that the
membrane consisted of lipids in a bilayer. Singer and Nicolson (1972) changed the
previous plasma membrane concept where the plasma membrane proteins lined the
exterior (Danielli & Davson, 1935) by conceptualizing the proteins of the plasma
membrane as being embedded within the two-dimensional fluid of the lipids. This model
changed how we view the plasma membrane, and is still used today as a simplistic model
2
of basic membrane physiology. The proteins found in the plasma membrane are vital as
they provide a variety of functions for the cell, including providing membrane structure,
transporting specific molecules, and cell signaling. To understand this relationship
between lipid rafts and proteins, we must first assess the current understanding of the
lipid raft model.
1.3 Lipid Rafts Lipid rafts are dense regions on the outer leaflet on the plasma membrane
(Cooper, 2000). Lipid rafts are thought to be 50-100nm in diameter of highly ordered
and densely packed lipids and cholesterol. Rafts, known as the liquid ordered phase (Lo)
are floating in the fluid like ocean of disordered lipids (Ld) (Simons & Toomre, 2000).
The Lo phase contains a higher concentration of cholesterol and saturated fatty acid
lipid tails, whereas the Ld phase has a lower concentration of cholesterol and is
higher in unsaturated fatty acid lipid tails and reduced packing (Simons & Toomre,
2000).
Two separate parties independently observed the small domains on the plasma
membrane. The first observation came from Stier and Sackmann (1973), where they
described the cell membrane as a mosaic like structure where, ‘the enzyme system is
enclosed in a halo of rigid phospholipids’. The second important observation of
membrane domains was by Brown and Rose (Brown & Rose, 1992) where they observed
that certain membrane proteins were detergent resistant. Yu and colleagues (Yu,
Fischman, & Steck, 1973) had already established that when solubilizing cell membranes
with Triton X100, there was an insoluble fraction present, which was rich in
sphingolipids – known as the detergent resistant membrane (or DRM). Brown and Rose
3
(1992) observed how certain membrane proteins can become detergent insoluble by
associating with these lipid domains. Specifically glycosyl phosphatidylinositol (GP1)
anchored proteins are associated with the DRM’s (Brown & London, 1997). These two
independent observations strongly suggested the presence of quasi-crystalline regions
present on the cell membrane and that these regions are associated with particular
proteins.
Lipid domains form due to the differences in the morphology of lipid shapes.
Lipid species have a certain affinity for certain other lipid species, whilst having a lower
affinity for other specific types of lipid species. For example, lipids of cylindrical shape
will prefer to orient themselves next to other lipids of cylindrical shape and form a planer
membrane. Likewise, cone shaped lipids will prefer other cone shaped lipids, and form a
micellular structure. Another example is the charge on the lipid species. Sackmann
(1994) describes the segregation of charged lipids, which forms small domains. These
small domains exhibit different local curvatures than that of the surrounding greater
domain.
Phase separation will lead to domains that contain certain species of lipids,
opposed to the other domain that contains another lipid species. There are two known
contributors to the specific shape and size that lipid domains take on. Theses factors are
line tension, and dipole-dipole interactions. Brockman describes line tension (or
energy/unit length) and dipole interaction as responsible for the shape and distribution of
lipid domains, and it is the balance of two forces that creates these domains. There is a
line tension associated with the boundary line between the Lo and the Ld phases (Veatch
4
& Keller, 2005). If line tension were the sole factor in domain size, the two domains
would fuse into one large domain.
Lipid molecules are molecular dipoles; these dipoles will be aligned with
respect to each other due to the packing density. The dipole interaction arises within
the lipid raft due to amphipathic nature of the membrane lipids being forced to assume a
parallel arrangement (Brockman, 1994). Line tension opposes the dipolar repulsion
resulting in the domains assuming a smaller dimension. Current understanding of lipid
rafts explains the size and shape of the rafts with this framework.
Sackmann argues that domain formation is essential for the stabilization of the
heterogeneous organization of the membrane, and that complete segregation of the
membrane would result in decay of the vesicles (1994). We have in fact also observed
this segregation and the decay of a vesicle into two vesicles due to this phenomenon. It is
likely that in a cell, the cytoskeleton stabilizes the plasma membrane’s unstable lipid
composition. Evidence of local changes in domain curvature can be observed in our data
(See Figure 2.7). This view of the formation of phase separation and the formation of
domains underlies a clearer understanding of how rafts form.
Due to the minute size and high mobility of lipid rafts within the membrane, lipid
rafts are difficult to observe experimentally. A pertinent observation of the size and
dynamics of lipid rafts is an experiment done by Pralle (2000), to better describe the size
and dynamics of lipid rafts. A laser trap was used to limit the movement of a styrene
bead bound to a raft protein (Pralle, Keller, Simons, & Horber, 2000). The position of the
protein/bead complex within the cell membrane affected the vibrational movement of the
complex as well as the local diffusion of the single membrane proteins. Using this
5
technique, Pralle (2000), found that the lipid rafts were stable structures with
measurements of approximately 50 nm in size. The size of the domains could be
estimated from the viscous diffusion of a protein to get the diffusion constant. This
experiment also proved useful for giving a clear picture on the dynamics of the rafts and
the effect on raft proteins relative to the protein diffusion rate.
A hallmark of lipid rafts is their ability to include or exclude proteins based on
their affinity for the lipid raft area (Simons & Toomre, 2000). Both Brown and London
(1997) and Simons (Simons & Toomre, 2000) have observed that lipid rafts have the
ability to ‘sort’ proteins preferentially into the lipid rafts. Proteins are sorted in the lipid
rafts according to the size of the proteins hydrophobic region. Proteins with a larger
hydrophobic region will be preferentially sorted into the lipid raft area due to the
increased thickness of lipid rafts, to reduce hydrophobic mismatch (Cooper, 2000). There
are three different ways that proteins can be embedded in a lipid raft; proteins can have a
GP1 anchor into the raft, be directly inserted in the lipid raft via a hydrophobic α helix, or
by a palmitoyl anchor (Simons & Sampaio, 2000). Simons observed that
glycosylphosphatidylinositol (GP1) anchored proteins are favored in lipid rafts along
with, caveolins, flotillins, low molecular weight and heterotrimeric G proteins, src family
kinases, EGF receptors, platelet-derived growth factor receptors, endothelin receptors, the
phosphotyrosine phosphatase syp, Grb2, Shc, MAP kinase, protein kinase C and the P85
subunit of Phosphoinosoitol 3-kinase (Pike, 2003).
Tyrosine Kinases are an interesting case as their immediate function is explained
by their resonance within the lipid rafts. Tyrosine Kinases are lacking in catalytic activity
on their own, but upon ligand binding are induced to form a dimer, which is able to
6
interact with cytosolic protein kinases (Lodish, Berk, & Zipurksky, 2000). These
receptors (possessing intrinsic enzymatic activity) are activated by binding of a ligand
(typically a dimer), leading to the dimerization of the receptor, resulting in kinase
activation (Lodish, Berk, & Zipurksky, 2000).
1.4 Lipid raft theory Earlier observations and knowledge of lipid rafts led Simons to the lipid raft
theory (2000). Simons postulated that lipid rafts played a key role in the cells’ ability to
mount a signaling event due to the high amount of signaling proteins that are present
within lipid rafts. Simons and Toomre stated in their paper (2000), that lipid rafts are
crucial for the activation of many signal transduction pathways.
Based on the literature, Simons drew the conclusion that lipid rafts must somehow
aggregate on the surface of the membrane for a signaling event to occur, and that some
agent, which drives this aggregation of lipid rafts would be a crosslinking protein. Lipid
rafts are concentrating platforms for individual receptors that are activated by their
respective ligand binding (2000). In order for a signaling activation, a number of
signaling molecules in their respective lipid rafts must come together and fuse such that
the signaling molecules are in close proximity to on another.
It is not currently known how many molecules must be phosphorylated in a
certain region of the plasma membrane for signal transduction to take place however,
there is evidence to suggest that higher amounts of proteins within a small aggregate
increases the baseline level of tyrosine phosphorylation (Kornberg, Earp, Turner, &
Juliano, 1991).
It has been described in the literature that treatment of the plasma membrane with
methyl-beta-cyclodextrin (MβCD) sequesters cholesterol and inhibits signaling by
7
inhibiting the presence of lipid rafts (Ohtani, Irie, Uekama, Fukunaga, & Pitha, 1989)
(Simons & Toomre, 2000). We can conclude that for a successful signaling response, a
given region of the plasma membrane would have to possess a high concentration of the
targeted protein available for phosphorylation. Cell signaling events happen due to a
variety of different factors, but the signaling that occurs as a result of lipid raft activity
requiring a certain subset of proteins. When Simons formulated his lipid raft theory on
signaling, he was primarily interested in a mechanism, which explained the accumulation
of proteins that subsequently produced a signaling event in the cell.
Not all cell signaling is dependent on the phosphorylation of tyrosine kinases. In
recent years, it has been discovered that other proteins such as Calcium and
Diacylglycerol regulated Guanine Nucleotide Exchange Factor (CalDAG-GEF) have the
ability to act in a protein kinase fashion to recruit secondary messengers (Springett,
Kawasaki, & Springgs, 2004). Examples of this would be G protein signaling, integrin
binding, tyrosine kinase binding, and toll like receptor binding (See Table 1). Of these
signaling types, all require the presence of scaffolding, or a large accumulation of
proteins for the signaling to take place (Simons & Toomre, 2000) (Pike, 2003). It is
unknown how these signaling proteins accumulate, but Simons postulated that lipid rafts
would play a crucial role in the ferrying of these proteins to the required area on the cell
membrane for the signaling to take place.
This phenomenon was described in B-cell receptors. It has been shown that in
TCR (Harder & Kuhn, 2000) signaling and B-cell receptors (BCR) (Gupta & DeFranco,
2007) signaling that accumulation of membrane proteins can lead to a signaling event in
the cell. (See table 1 for a comprehensive list of signaling events where this occurs.) It
8
has been well established that lipid rafts are implicated in this process of aggregation
(Simons & Toomre, 2000) (Pike, 2003).
1.5 Lipid raft theory: shortcomings Domains were understood to be a solid phase section of plasma membrane, which
sits separately from the surrounding fluid membrane. These sections of plasma
membrane are unable to fuse together. This would mean that the lipid phases would be
unable to accumulate together due to the intra domain dipole interactions present in the
lipid domains.
The many opponents to lipid raft theory argue against several key points.
Specifically, it is not known, how rafts form, nor how they would aggregate to produce a
signaling event. There is no knowledge of what determines the size of lipid rafts. Why
must lipid rafts begin very small and slowly grow into to a larger raft instead of
originating as the larger size? Researchers have also tried to reproduce raft domains of
defined size and other properties consistent with known features of rafts in model
membranes. Indeed, when synthesizing model membranes in practice, the size of the lipid
raft domains are highly variable depending on the purity of the system, the temperature,
proteins present etc. (Munro, 2003). In model membranes, the lipid raft domains will
attempt to group together or shrink depending on temperature changes, akin to
crystallization. There are no robust mechanisms to be found to explain the production or
accumulation of lipid rafts when reproduced in model systems (Munro, 2003). There
have been suggestions of a possible scaffolding protein, which would induce the
formation of the lipid raft scaffolding. However, this has been found to only exist in
specialized raft structures of clathrin and caveolin (Pike, 2003).
9
A further criticism for lipid raft theory focuses on line tension. Line tension
should exist between the two Ld and the Lo phase domains. If there truly are two
different phases present, this should be observable and quantifiable in cells. As yet, line
tension has only been observed in model membranes. In Munro’s (2003) criticism of
lipid raft theory, he discusses how the domains disappear at physiological temperature in
vitro, and that lipid raft domain segregation has yet to be seen in vivo.
The accumulation of lipid rafts was postulated to occur via crosslinking proteins.
Lipid raft theory includes the mechanism of crosslinking (due to antibodies) as a
mechanism for the accumulation of lipid rafts (Simons & Toomre, 2000). However, cell
signaling can occur as a result of a variety of factors, not just the presence of an antibody
protein. In fact, most membrane receptor ligands are not antibodies, nor do they have
crosslinking abilities. An example of this is Monosodium Urate (MSU) crystals, which
are known for producing a signaling response from cells signaling linked to lipid raft
behavior (inhibited in the presence of MβCD) (Ng, et al., 2008). For this event there is
no known protein receptor, let alone crosslinking activity for MSU. Those opposed to, or
critical of lipid raft theory will point out that relying on crosslinking proteins as the sole
contributor to lipid raft accumulation is a major flaw in lipid raft theory. If the
accumulation of lipid rafts is only due to crosslinking proteins, then how can crystals
such as MSU induce a signaling event? Are there some undiscovered crosslinking
proteins that are causing signaling events? The answer is most likely no.
In summary, for cell signaling to take place, a mechanism must be in place that
does not require an exorbitant amount of energy for the signaling event to take place nor
should the mechanism depend on crosslinking. While the existence of liquid ordered
10
domains is firmly established, the current Simons theory does not explain convincingly
how these domains reliably form, collect associated proteins and then aggregate into
larger platform upon signaling. Lipid raft theory therefore remains an unconvincing
concept in the scientific community.
1.6 A New Understanding of the Plasma Membrane
While we do not dispute the presence of lipid rafts and their role in signaling, we
aim to refine the function and view of lipid rafts. The following sections explains a new
view of how lipid rafts evolve and how they dynamically change or adapt during
signaling, which reconciles the shortcomings of the lipid raft theory using experimental
observations. Ising devised a theory to describe two-dimensional critical systems.
Veatch and Keller employed this theory to assess whether the plasma membrane followed
the rules of a two-dimensional critical system. The two-dimensional Ising model (Ising,
1925) is based solely on intermolecular interactions. In our case, this model would be
referring to the adhesion among raft lipids, among non-raft lipids and among hetero-pairs,
and how these interactions are affected by temperature (Onsager, 1994). The Ising
formalism predicts small domains, the size of lipid rafts for the more condensed region
(Veatch, Cucuta, Honerkamp-Smith, D., & Baird, 2008).
In critical systems, different domains can coexist without line tension at the
critical temperature. Critical behavior is best known for materials such as water, CO2 or
O2. At their critical point (a material specific temperature and pressure) a distinct liquid
and gas phase no longer exist. As the substance approaches the critical point, densities of
its gas and liquid phases come closer and closer, and the interfacial energy between the
11
phases approaches zero, until eventually there is a mixture of both phases wherein there is
no energy requirement to move between them.
Veatch and Keller described the plasma membrane as a critical system by
observations of line tension, domain formation and membrane dynamics using
fluorescence light microscopy (Veatch, Cucuta, Honerkamp-Smith, D., & Baird, 2008) to
detect minute fluctuations in the plasma membrane. This provides an elegant theoretical
and experimental framework to explain the nano-sized liquid ordered domains
(Honerkamp-Smith, et al., 2008). All cells contain a critical composition of lipids and
possess a miscibility critical point at the transition temperature. As the critical
temperature is reached, the near neighbor interactions between like and unlike domains
require less and less energy. There are increased lipid fluctuations and the line tension
between the Ld and the Lo domains dissipates (Veatch, Cicuta, Sengupta, Honerkamp-
Smith, Holowka, & Baird, 2008).
Veatch (2008) then used these characteristics of critical behavior to definitively
characterize it in membrane vesicles. To determine a vesicle as a critical system, the
calculation of line tension can be used according to the 2D Ising model (Ising, 1925).
Line tensions can be extracted from images of GPMVs and fitting the power spectrum of
boundary fluctuations in accordance to methods shown by (Veatch, Cucuta, Honerkamp-
Smith, D., & Baird, 2008). As line tension is a linear function of temperature, line tension
will intersect 0 at the critical Temperature (Tc). [λ≈λ0(Tc-T)/Tc, where Tc is the critical
temperature in Kelvin (Veatch, Cucuta, Honerkamp-Smith, D., & Baird, 2008)].
12
With respect to signaling, we suggested that the significance of the critical
behavior is that even small perturbations in the plasma membrane can lead to local phase
segregation, without a large change in free energy encountered. The cell membrane is
operating at a temperature slightly above the Tc. When the cell membrane is locally
constrained in its movemen for example, this is akin to cooling the membrane locally
(due to environmental factors, such as MSU), the critical temperature is reached and
liquid ordered domain size increases. This is further explained by molecules within the
plasma membrane that move within the two-dimensional fluid as a product of thermal
motion. If the degree of freedom of the molecules now becomes limited, for example by
binding of a crystal or binding of a ligand to its receptor, the movement of the molecules
is limited akin to a local change in temperature. Lipid raft accumulation in an area could
thus be understood as a local cooling of the membrane leading to larger ordered domains.
Thus, one could easily imagine the formation of large signaling platforms as soon as the
membrane would be cooled to the Tc or below the Tc. By using the properties of the
critical system that Veatch and Keller have used, we had hoped to establish; what is a
critical system, and extrapolate this data such that we can observe changes in critical
behavior for cell signaling and observe a dependence of cell signaling on critical
behavior.
Raft proteins having an affinity for the higher density region of lipid rafts and
they become concentrated in this area, and thus, a signaling event would take place.
Because aggregates are able to form and dissipate easily in a critical system, such an
event is terminated rapidly as soon as the trigger is released.
13
Critical behavior could explain the problem of the size of lipid rafts. Once lipid
rafts are disturbed, they segregate into larger domains. Lipid rafts could then return to
their smaller size when above the critical temperature. Secondly, this model addresses the
issue of crosslinking. In the two-dimensional Ising model (Ising, 1925), crosslinking is
not required to ‘stick’ the rafts together or fuse them. The system does not require a
crosslinking molecule to associate like molecules as it does in the earlier lipid raft theory.
It is not to say that crosslinking does not occur in our model, but it is not the only reliant
method for raft affinity. Lastly, the phase separation of the lipids is addressed with this
model. With latent energy of the phase change from Ld to Lo high in a non-critical
mixture, aggregation would be too costly energetically. In the critical system, there is no
energy cost to move between Ld and Lo.
In summary it is attractive to link specific elements of cell signaling on the
plasma membrane to critical behavior, the critical temperature and the presence of
signaling proteins that have an affinity for lipid rafts. Given the exactitude of the theory
of critical behavior this can be rigorously tested.
1.7 General hypothesis In this study we plan to investigate lipid sorting as an integral mechanism for cell
signaling. Our general hypothesis is that lipid sorting occurs in response to a local
trigger, akin to the local cooling of the membrane. We further hypothesize that the
signaling is able to occur because of the critical behavior of the membrane.
1.7.1 Specific Aim 1 Produce a membrane system that will allowed us to visualize isolated membrane
behavior, similar to those observations obtained by Veatch and Keller (2008).
14
We created membrane blebs, GPMVs, which would then be used to observe
membrane behavior. These vesicles are blebbed off from Dendritic Cells (D.C. 2.4) and
thus are expected to be true representative of the plasma membrane that constitutes a
living cell.
Rational:
Model membranes can be produced to contain a vast array of lipid ratios. These
membranes can represent the membrane of a living cell, the surfactant of the lungs, or an
artificial membrane. Model membranes are useful in that they are able to represent a
mixture of lipids and cholesterol specified by the research work. For a membrane derived
from a real cell as used here, should allow one to study basic membrane function isolated
from the overall functions of the entire cell. The model membranes known as giant
plasma membrane vesicles (GPMVs) are created from blebs of D.C. 2.4 and are treated
with fluorescent membrane dyes. In the past, model membranes have been used to
examine lipid function and behavior, most notably by Israechvili (1980) in his landmark
paper on the structural properties and behaviors of lipid bilayers.
1.7.2 Specific Aim 2 We aimed to establish that the GPMVs created are critical systems. By
establishing that the membrane blebs are critical systems, we would be able to
demonstrate that the signaling events can be caused by the critical behavior of the lipids
and thereby build on and critique the current signaling theory.
Rational:
If we build on the knowledge already put forth by Veatch and Keller, cell-
signaling theory can stand on a new and robust set of well-established characteristics.
The model of a critical system explains the movements and evolutions of lipid rafts on
15
the cell membrane. Applying these principals to a new theory on lipid raft function, we
can put forth a new conceptual mechanism for cell signaling.
Critical behavior can be analyzed by using microscopy to observe membrane
domain fluctuations that are representative of the critical system. To do this, the GPMVs
will be dyed with differing fluorescent dyes, in an effort to show the phase separation
between the Ld and the Lo domains. This establishes the phase change over a range of
temperatures and allows for determining if the system is indeed critical. The GPMVs
will be observed to determine the phase domains in the vesicles and the absence of line
tension at the critical temperature. Video data will be collected, and analysis performed
building on the previous work of Veatch (2008) to determine if the GPMVs are critical
systems.
In a critical system, line tension (λ) decreases to zero at the critical temperature.
To determine line tension of a system as it approaches Tc, the line tension of domains on
a GPMV can be measured by a spectrum of deviations from the radius (Honerkamp-
Smith, et al., 2008). Line tension decreases linearly to zero as the critical temperature is
reached. As line tension data is gathered, it can be fit to a linear slope to ensure data is in
keeping with a critical system.
Alternatively correlation length within the fluorescence images (fluctuations at
small temperature far above the Tc) can also be determined for a critical system,
according to Honerkamp-Smith (2008).
1.7.3 Specific Aim 3 Demonstrate lipid sorting in response to an external trigger (for example, the impact of an
MSU crystal).
16
We hope to show that external triggers on the plasma membrane do not have to be
dependent on a receptor/ligand binding to induce cell signaling. We intend to prove that
the critical behavior of the plasma membrane is the crucial factor in a cell mounting a
signaling response, regardless of a specific receptor/ligand bond. We will test whether
changes in temperature can affect the ability of the plasma membrane to cluster lipid rafts
and signal, and thereby show that the plasma membrane behavior is the critical factor in
cell signaling.
Rational:
It has recently been observed that other non-ligand substances such as MSU are
able to induce a signaling response in cells via a lipid raft mediated mechanism (Ng, et
al., 2008). Although the mechanism for this signaling event is as of yet, unclear, it is our
aim to prove that this event, and all other lipid raft mediated events, are caused by the
aggregation of lipid rafts due to the critical nature of the lipid membrane. We intend to
build on this work by Veatch (2008), and demonstrate how lipid rafts are able to
accumulate and induce signaling not because of a crosslinking protein, but due to the
critical system nature of the plasma membrane.
The previous work of Ng (2008) is important in that it proves that signaling can
take place in the absence of a receptor ligand bond. We intend to take this concept one
step further and show a plausible mechanism for how such a signaling event could take
place, indeed how many signaling events can take place. Through experimentation we
intend to prove that signaling protein accumulation occurs due to minute changes in the
local environment of the plasma membrane, and not necessarily due to a receptor ligand
bond.
17
2 Materials and Methods 2.1 Materials and Methods:
2.1.1 Cell Lines D.C. 2.4 cell line was donated from Kenneth Rock of the University of
Massachusetts Medical School. D.C. 2.4 is an immortal cell line, which can
effectively adhere to the glass slides, and are efficient in the collection of blebs.
D.C. 2. 4 cells were cultured in 6 well plates with approximately 400,000 cells
per well in 5GM cell media. 24 hours after seeding the plates, cells were
prepared for GPMV collection.
2.1.2 Reagents
2.1.2.1 Fluorophores: Several different fluorophores were used throughout the course of our
experiments. For each fluorophore used we have outlined the preparation of the
fluorphore and the procedure used for dying the cells prior to GPMV collection.
2.1.2.2 Fast Dio: Fast Dilinoleyloxacarbocyanine (Dio) was purchased from Life Technologies.
Fast Dio is a fluorescent dye that labels the unsaturated fatty acid tails of membrane
lipids. Fast Dio was diluted in DMSO to 1mM. 1uL of Fast Dio for every milliliter of
media was added to the cells 10 minutes prior to GPMV collection.
2.1.2.3 Bodipy Cholesterol: Bodipy cholesterol is a fluorescently tagged cholesterol lipid (which occupies the
Lo phase). TopFluor Cholesterol (23-‐[dipyrrometheneboron difluoride]-‐24-‐
18
norcholesterol) was purchased from Avanti polar lipids. The bodipy fluorophore is
dissolved in dimethyl sulfoxide (DMSO) to a concentration of 1mM. 1uL/mL of
media is added and left for 10 minutes.
2.1.2.4 Alexa 647 Cholera toxin recombinant: The Alexa 647 fluorophore, conjugated with the cholera toxin β (CT-‐B) via an
anti CT-‐B antibody, was purchased from Life Technologies. The CT-‐B can be used as
a marker for lipid rafts as it binds preferentially to the GM1 ganglioside, associated
with lipid rafts. The Alexa 647 CT-‐B recombinant was prepared to a concentration of
1.0mg/mL of phosphate buffered saline (PBS) as per the manufactures
specifications. The 1uL of Alexa 647 CT-‐B recombinant was added per 1mL of cell
media and left for 10 minutes.
2.1.2.5 C-‐laurdan: C-‐laurdan was a gift from the Chang-‐Chun Ling lab at the University of Calgary.
The C-‐laurdan was diluted to a 2.5mg/mL concentration in DMSO. DC 2.4 cells were
dyed with 1ul/mL of media of C-‐laurdan 30 mins prior to GPMV collection.
2.1.2.6 Rhodamine B PE: Rhodamine B PE is a fluorescently labeled head group of the POPE lipid (an
unsaturated fatty acid tail lipid which occupies the Ld phase). Egg Liss Rhod PE (L-‐
α-‐phosphatidylethanolamine-‐N-‐[lissamine rhodamine B sulfonly]) diluted in
chloroform (1mg/mL) was purchased from Avanti polar lipids. Rhodamine B PE was
added to cell culture at 1uL/mL of cell media and left on for 10 minutes.
2.1.3 Collection of GPMVs: GPMV buffer was prepared using 10mM 4-‐(2-‐hydroxyethyl)-‐1-‐
piperazineethanesulfonic acid (HEPES), 150mM NaCl, and 2mM CaCl. A solution of
19
25mM Paraformaldehyde (PFA)/ 2mM Dithiotheritol (DTT) was prepared in 1mL of
GPMV buffer. GPMVs were first washed in GPMV buffer, and then collected using
the DTT/PFA in GPMV buffer was then added to plated cells and collected after 1
hour (Sezgin, Hermann-‐Josef, Baumgrat, Schwille, Simons, & Levental, 2012).
2.1.4 Imaging
2.1.5 Light Microscopes Over the course of the experiments, a variety of microscopes were used. The
three microscopes that aided in our experimentation were the Olympus confocal
FV1000, Zeiss Elyra, and the Quorum Diskovery flex in spinning disk mode.
The FV1000 LSM (light scanning microscope) Confocal was useful in
establishing parameters and doing preliminary experimentation. A confocal light
microscope is a basic fluorescence light microscope with a pinhole, allowing the
system to extricate the excess light and produce a crisper image in comparison to
wide field light microscopy. The drawback in confocal light microscopes is that
scanning the entirety of the image is timely and requires a fairly static specimen.
The FV1000 was the initial go to microscope in establishing fluorophore
concentrations, GPMV collection parameters and fine tuning microscopy set up.
The Zeiss Elyra was used for its ability to perform super resolution
microscopy. Super resolution is a method, which uses a confocal light microscope in
an advanced way in order to resolve structures at higher resolution. The
disadvantage of this is that this requires slower movement of the particle in
question. Initially we planned to do single particle tracking using the total internal
reflection fluoroscopy (TIRF) mode on the Elyra, and did several pilot experiments
20
in an effort to do so. The movement of the lipid domains that we intended to track
ended up being too fast for use to accurately track. This was due to our inability to
resolve between the lipid domains. In TIRF, fluorescence is excited only in close
proximity of the coverslip (approximately 200 nm). It is therefore distinct by an
absence of out of focus light and shows high signal-‐to-‐noise ratio. The disadvantage
of this was that we were only able to observe a small portion of membrane that was
in direct contact with the glass, and the highly motile domains easily moved past the
plane of focus and become invisible.
Finally, the spinning disk was also used, as it is a best for highly dynamic
imaging. The system is able to scan the entirety of the specimen at once, rather than
slowly scanning overtime like the LSM confocal. Because of the excellent temporal
resolution, it proved our best choice for the very fast movement of the lipid raft
domains.
GPMVs were imaged using glass bottom dishes purchased from World Precision
Instruments. Poly-‐L-‐lysine, purchased from Sigma-‐Aldrich, was used to aid in the
attachment of the GPMVs to the glass bottom dish while imaging. Poly-‐L-‐Lysine was
used to coat the cover glass prior to imaging for several minutes before being
pipetted off and the GPMV sample was added.
In all cases the sample was illuminated with the required laser wavelength (405-‐
C-‐laurdan, 495-‐ Bodipy Cholesterol, and, 647-‐ Alexa 647 CTB and Rhodamine B).
Images and Videos of GPMVs were saved. The images were then later used in the
creation of the Chart of Observations were the type of preparation, fluorophore,
number of GPMVs and phenomena was recorded.
21
2.1.6 Spectrofluorometer In addition to the microscopy, we also used spectrofluorometry. This
method allowed measuring changes in the C-‐laurdan fluorescence emission
spectrum as a function of temperature, though not spatially resolved. C-‐laurdan is a
lipid dye that emits at different wavelengths of light depending on the polarity of the
surrounding lipids. In our case, C-‐laurdan inserts itself into both the Lo and the Ld
domains and the overall emission spectrum shows two peaks. The relative heights
of these peaks indicate the relative amount of Lo and Ld phase, respectively. This
relationship may change as a function of temperature. We speculated that the
introduction of a signaling trigger, such as the MSU crystals would lead to such
change too.
GPMVs were dyed with C-‐laurdan and collected in the same manner as the
preparation for imaging. GPMVs in buffer were then transferred into a cuvette
from stramacells. The cuvette was then placed in a Cary Eclipse
spectrofluorometer. The spectrofluorometer was first calibrated, and then the
sample was excited with a 405nm wavelength. Two control samples were also
used, C-‐laurdan in GPMV buffer as a positive control, and GPMV buffer on its own
as a negative control. The emission spectrums was collected and graphed by the
Cary Eclipse system. The emission spectrum was first measured at 25°C, then at
55°C, two temperatures that were believed to be well below and well above the
transition temperatures of the GPMVs. The GPMV samples were cycled between
25°C and 55°C 3-‐4 times in an effort to ensure the data were reproducible within
the same sample as well as between samples. The graphed data was then
22
normalized and line smoothed using a 7-‐point triangular smooth method. The
wavelength at the maximum point for each curve was determined and recorded.
The average wavelength for the C-‐laurdan in buffer at 25°C and 55°C, and GPMVs
at 25°C and 55°C was calculated and graphed.
3 Results
3.1 GPMV Production After extensive observation and experimentation, it became clear that the
domain formation as described by Veatch was not occurring in the GPMVs the
majority of the time. Instead, a heterogeneous population of GPMVs was obtained.
We began to question if the type of vesicles shown by Veatch and Keller in their
publications were representative to the plasma membrane (Veatch, Cicuta,
Sengupta, Honerkamp-‐Smith, Holowka, & Baird, 2008). After our observations, we
could not conclude with certainty that critical behavior is indeed playing the
significant functional role; however we cannot exclude a crucial role for critical
behavior either. Our observations gave us insight into many different phenomena
occurring on the plasma membrane.
As it become obvious that the critical GPMVs published by Veatch and Keller
were not the norm, we began collecting observations on what we did observe in
GPMVs. Observations were amassed and divided them into sections of phenomena
viewed. Due to a lack of description in the literature, we named these categories of
23
phenomena. These phenomena were; phase separation, dynamic phase separation,
critical phase separation, blebbing, and vibrations.
The data was collected and organized into sections from our initial
standardization experiments to create a body of observations that could be
analyzed. As the data was from our initial standardizations, it stands to reason that
the data is not completely random in its collection however; the majority of the data
would have been collected from the center of the glass bottom dish where it was
easiest to image and the sample of GPMVs in each dish would be in solution and
settle randomly on the bottom of the glass bottom dish over time.
3.2 Phase Separation Domain formation due to phase separation was the primary focus of our
experiment. Phase Separation was by far the largest consortium of observations
made of the GPMVs (See Graph 2.1.) It is a conserved occurrence in
multicomponent lipid/protein systems and present in all cells (Sackmann, 1994).
We found that there was a great amount of variability in the vesicles that we viewed.
For example, the domains varied greatly in size, from sub micrometer domains that
were barley resolvable, to very large domains that were very obvious. We
observed three different categories of lipid phase domain separation, firstly where
the first domains were static in shape and not moving, secondly where the domains
where static in shape but otherwise moving on the GPMV, and thirdly where the
domains were both motile on the GPMV, and constantly evolving their shape. Only
this latter incidence is consistent with critical behavior. We therefore termed it
critical phase separation. However, we did not calculate the line tension for this
24
data, as it was unclear whether the domains were fusing into domains, or if they
were small highly motile domains of static shape that collided with each other.
Domains were still much smaller than published and the overall domain pattern
evolved much faster.
3.2.1 Static Phase Separation
3.2.1.1 Static Phase Separation – Results The observations from this section show a range in the domain separation
visible on the GPMV membrane, from the small patchy appearance of the phases, to
the large and extremely obvious phases that take up almost half the GPMV
membrane surface.
The vast majority of GPMVs that were observed over the course of the project
displayed the phase separation phenomena. Figure 2.1 shows a variety of GPMVs
that we observed in a single preparation, all displaying phase separation. However,
the vesicles are all at different levels with respect to the microscopes plane of focus,
and therefore show the phase separation phenomena under various different views.
The hallmark of this section of observations was that domains do not move
or change shape overtime (see Figure 2.2, 2.3, supplementary Video’s 1/2). In this
section we aimed to collect visuals from both the equatorial and top membrane
view. In Figure 2.2, we see the phase separation displayed in an equatorial view,
and in Figure 2.3, we see a top membrane view. When collating data for this section,
it was noted that phase separation may not be entirely obvious in the equatorial
view unless the phase separation was around the mid-‐section of the GPMV-‐ See
Figure 2.4 for further explanation.
25
3.2.1.2 Static Phase Separation -‐ Discussion The fact that the domains do not move or change shape could be explained by a
constant and high line tension and no intermixing between phases, indicating that
these vesicles are not a critical system.
3.2.2 Dynamic Phase Separation
3.2.2.1 Dynamic Phase Separation -‐ Results Dynamic phase separation was viewed in the Elyra in the TIRF mode and
spinning disk microscopes. Regular confocal FV1000 did not resolve these fast-‐
evolving structures. The dynamic phase separation phenomenon was observed
with a range of lipid dyes. The very fast dynamics of the moving domains also
showed the limitations of our microscopy systems.
We have categorized the dynamic phase separation as any incidence where
we observed a highly dynamic movement of the lipid rafts on the membrane surface
(see Figure 2.5, supplementary Video 3). The lipid domains are static in size and
shape, but are highly mobile. This movement is very fast, and hard to pick up on the
microscope camera.
3.2.2.2 Dynamic Phase Separation -‐ Discussion Simons’ have described small and highly mobile Lo domains as being highly
dynamic lipid assemblies that are floating freely on the Ld phase (Rajendran &
Simons, 2005). The highly dynamic nature of the lipid domains in this subset of
observations is particularly interesting in a cell singling sense. As mentioned, certain
proteins preferentially are sorted into the Lo domains (Rajendran & Simons, 2005).
It is attractive to imagine signaling as a clustering of these domains and their rapid
movement indicates a highly dynamic system (Rajendran & Simons, 2005). The
26
question of energetics for this process however remains unanswered. The Veatch
theory suggests that lipid dynamic fluctuations are due to the result of critical
fluctuations near the Tc (Honerkamp-‐Smith, et al., 2008), meaning that the highly
dynamic Lo domains that were observed in our results could be due to lipid
fluctuations where the GPMV is near the Tc. Although the GPMVs display highly
dynamic movement of the Lo domains, we have not proven that this is the definitive
behavior of the critical system. The Lo domains are still fairly static in size and
shape, which is not emblematic of would be critical behavior.
3.2.3 Critical Phase Separation
3.2.3.1 Critical Phase Separation -‐ Results Dynamic critical behavior represented a small subset of GPMV observations
(See Graph 2.1). This phenomenon was only observable under specific condition.
For this phenomenon to take place, the D.C. 2.4 cells where the GPMVs to be
collected from had to be plated at a low density. The only fluorophore that was
successful was Fast Dio (which dyed the Ld domain rather than the Lo domain). As
with the previous section, these phenomena could only be viewed on a microscope
that has both high resolving power and is fast enough to pick up the dynamic
movement, meaning that the spinning disk was the only microscope in which we
viewed this phenomenon.
3.2.3.2 Critical Phase Separation – Discussion In this section, we will describe what our best guess at critical behavior. It is
hard to distinguish between the critical behavior versus dynamic behavior without
doing an in-‐depth analysis on line tension and the critical exponent as originally
27
suggested in the Veatch paper on critical behavior (Honerkamp-‐Smith, et al., 2008).
However, such analysis was not attempted, as domains were too small, much
smaller than published by Veatch and Keller, to allow for use of their algorithms
(Veatch, Cicuta, Sengupta, Honerkamp-‐Smith, Holowka, & Baird, 2008).
These GPMVs therefore represent our best estimation of critical behavior,
where the lipid rafts not only change position on the membrane, but also are also
rapidly changing and fusing shapes over time. This behavior was best captured with
videos (See supplementary Video 4, 5, Figure 2.6). We found that to observe the
Dynamic critical phase separation in the GPMVs, the GPMVs must be harvested from
a lower density plate of cells, and that only one fluorophore could be used (See
supplementary chart of observations). After extensive trials to obtain critical
behavior, a communication with Sara Veatch revealed that this was how her team
had visualized critical behavior from GPMVs in their paper (Veatch, Cicuta,
Sengupta, Honerkamp-‐Smith, Holowka, & Baird, 2008).
The hallmarks of critical behavior are the ability of lipid domains to change
size and shape and lateral position on the membrane where the composition of
lipids and cholesterol are of a critical composition. As the Tc is approached, there is a
decrease in interfacial energy between phases (due to decreasing line tension), the
size and lifetime of the Lo and Ld decreases (Veatch, Cicuta, Sengupta, Honerkamp-‐
Smith, Holowka, & Baird, 2008) (Honerkamp-‐Smith, et al., 2008). Critical
fluctuations of GPMV membranes according to Veatch follows 2D Ising (Ising, 1925)
model scaling laws meaning that critical behavior is universal for all critical
28
compositions (Veatch, Cicuta, Sengupta, Honerkamp-‐Smith, Holowka, & Baird,
2008).
The GPMVs displaying critical behavior shall have dynamic phases where the
lipid domains have an ever-‐changing morphology, shape and size, and whereby the
lipid raft domains have extremely fast dynamic movement on the GPMV membrane.
The GPMVs in observed displaying this behavior must be at the Tc due to the fluidity
of the domains, and the low energy cost of lipid movement between the domains.
3.3 Observations of Blebbing
3.3.1 Observations of Blebbing – Results The blebbing off plasma membrane from a vesicle would give rise to a
smaller vesicle (< 5 μm) from larger (10 μm) parent vesicle. The blebbing begins as
an extrusion of plasma membrane off of the GPMV, and as the extrusion grows, there
is a neck formation and the bleb is pinched off. We viewed both blebs forming on
the plasma membrane, the products of blebbing, as well as the full process itself.
In our results, we observed blebs that were either in the process of detaching
from the GPMV membrane, or had already detached and were in close proximity to
the parent vesicle. Blebbling was observed with all dyes and in all microscopes.
Blebbing appeared to be a universal phenomenon and occurred randomly within
our samples(See Graph 2.1). The blebbing phenomenon was present throughout out
experiments and was present in both phase separated and phase mixing samples,
meaning that the blebbing phenomenon was not restricted to one specific phase.
The blebbing phenomenon was not observed to occur with all types of
fluorophores or microscope setups (see supplementary Chart of Observations). We
29
originally observed blebbing present in only the Lo phases (See Figure 2.7, 2.8) of
the GPMV however, after further experimentation we also observed blebbing in the
Rhodamine-‐PE dyed Ld phases as well (Figure 2.9). Interestingly, we observed the
blebbing to not only occur outwards from the GPMV, but also inwards in the inner
GPMV space (Figure 2.9). It was observed that blebbing of the membrane was not
restricted to a certain phase. Indeed, the blebbing was observed in both the Lo and
the Ld phases, as well as in GPMVs, which displayed even mixing of both domains.
It was also observed that bleb formation could be in the form of small
extrusions beginning to come off of the vesicle, or after completely blebbing of in the
form of smaller vesicles within the surrounding area, occasionally within the GPMV
itself.
3.3.2 Observations of Blebbing – Discussion There are many factors that account for this phenomenon including
membrane tension, lipid composition, and membrane curvature (Mellander, Kurczy,
Najafinobar, Dunevall, Ewing, & Cans, 2013). Domain formation within GPMVs is a
result of stabilization of heterogeneously organized membranes, and each lipid
domain has its own local curvature (Sackmann, 1994). Bleb formation can be boiled
down to two main factors: phase separation and membrane curvature (Sackmann,
1994). Phase separation depends on the decrease of entropy for lipid mixing, and
membrane curvature depends on the bending stiffness of the vesicle shell
(Sackmann, 1994). A vesicle of a given size has a given curvature, a curvature that is
a fixed parameter. Membrane that is under increased tension becomes bent out of
its natural state – the variable would be the stiffness of the lipid composition of the
30
entire vesicle. We will further investigate all the factors that would influence the
presence of this phenomenon.
Membrane tension as defined by (Diz-‐Muñoz, Fletcher, & Weiner, 2013)
plays a vital role in the formation of membrane blebs (Mellander, Kurczy,
Najafinobar, Dunevall, Ewing, & Cans, 2013). The surface area of a GPMV is finite,
and any small changes in the environment can lead to changes in the surface
tension. Mellander and colleagues proposed in their research on the release of
daughter vesicles (blebs) from giant unilamellar vesicles, that membrane tension
played a role in regulating the release of the blebs (Mellander, Kurczy, Najafinobar,
Dunevall, Ewing, & Cans, 2013). The size of the bleb created can affect the
membrane tension and it has been suggested that the GPMV has a limited amount of
excess membrane available to provide for formation of a bleb. Bleb formation and
the growth of a bleb thereby increase the GPMV membrane tension (Mellander,
Kurczy, Najafinobar, Dunevall, Ewing, & Cans, 2013).
The overall stiffness of the vesicle is highly variable, and assuming that the
blebbing of the vesicle from the original cell is random and contains a random
composition of membrane, it is highly likely that the GPMVs are highly variable and
possess variable membrane tension which, in turn can allow for certain GPMVs to
have conditions ripe for bleb formation while others do not.
Lipid shape and composition in the membrane plays an intimate role in
ability of a lipid membrane to attain a degree of curvature (Veatch, Cicuta, Sengupta,
Honerkamp-‐Smith, Holowka, & Baird, 2008). The volume occupied by the tails
region and the ability to pack the lipids gives the characteristics of membrane shape
31
(Frolov, Shynyrova, & Zimmerberg, 2011). Specific packing parameter [P]=V/al,
where V is the specific volume of lipid tails, l is the length of the lipid tail, and a, is
the area/lipid molecule (Israelachvili, 2011). A P of approximately 1 describes the
shape of a cylindrical lipid for example, dioleoylphosphocholine/DOPC, a P>1
describes a cone shaped lipid, for example,
dioleoylphosphotidylethanolamine/DOPE and a P<1 describes the shape of an
inverse cone lipid, for example lysophosphocholine (LPC) (Frolov, Shynyrova, &
Zimmerberg, 2011). The curvature of a membrane system where the curvature is
based wholly on the intrinsic nature of the lipids is known as the spontaneous
curvature (Mellander, Kurczy, Najafinobar, Dunevall, Ewing, & Cans, 2013). For
example, monolayers that are composed of cylindrical lipids will have a
spontaneous curvature of 0 (Frolov, Shynyrova, & Zimmerberg, 2011).
Lipids are able to generate cylindrical shape without energy input, meaning
that GPMVs in a spherical shape requires no energy input and the generation of
membrane blebs by GPMVs is a passive process, which requires no energy input
(Veatch, Cicuta, Sengupta, Honerkamp-‐Smith, Holowka, & Baird, 2008).
Membrane curvature is achieved by a force imbalance between the two
monolayers of lipids due to spatial requirements of the lipids (Frolov, Shynyrova, &
Zimmerberg, 2011). Membrane asymmetry where more cone shaped lipids occupy
the outer monolayer and more reverse cone lipids occupy the inner monolayer
resulting in a difference in pressure. This leads to monolayer torque, and the
monolayer with the biggest torque wins, bending to balance the force (Frolov,
Shynyrova, & Zimmerberg, 2011).
32
A change away from the spontaneous curvature is caused by forces applied
to the membrane by factors in the environment leading to domain driven budding,
where the domain boundary provides the driving force for membrane blebbing
(Frolov, Shynyrova, & Zimmerberg, 2011). Lipid polymorphism and the
spontaneous curvature of the membrane play a role in the regulation of domain
driven blebbing (Frolov, Shynyrova, & Zimmerberg, 2011).
It has been suggested the domain driven blebbing is due to membrane height
mismatch between the Lo and Ld phases, due to Lo having increased thickness due to
the presence of cholesterol (Frolov, Shynyrova, & Zimmerberg, 2011) and thus leads
to an increase in line tension. In an effort to lower the mismatch energy, non-‐bilayer
lipids accumulate and bleb off (Frolov, Shynyrova, & Zimmerberg, 2011). The
presence of line tension due to phase separation in heterogeneous GPMVs gives rise
to blebbing of the GPMV membrane. It is clear that in our data, all of the vesicles
displaying the blebbing phenomenon were also displaying phase separation. As a
result, the increasing phase separation resulted in blebbing of the membrane from
the GPMV and occasionally resulted in smaller daughter vesicles. As this
phenomenon is associated with phase separation, it is possible that blebbing could
occur with decreased temperatures where phase separation has increased and
creates conditions that are favorable for blebbing. As the GPMVs themselves are
formed from random blebbing from cellular membranes, the lipid composition can
vary greatly, and thus blebbing may be an occurrence based on a random lipid
composition of the GPMVs, which possess a potential to increase membrane tension
and lead to blebbing.
33
It can be concluded that a buildup of lipids creating excessive curvature in
the membrane would thus lead to conditions that would favor membrane blebbing
formation. Membrane bleb formation would also affect the composition of lipids
within the GPMVs, and thus render the GPMVs as non-‐critical systems. It is possible
that the blebbing we observed in our systems was detrimental in our attempt to
observe critical behavior due to the disruption of the critical composition of lipids in
the original GPMVs.
3.4 Vibrations
3.4.1 Vibrations -‐ Results Vesicle vibration, wherein the membrane of the vesicle vibrates such that
there are nodes created on the vesicle. This was akin to the vibration of a taught
string where there are nodes present where the wavelength of the string vibrates
about the nodes. Vibration category was a surprising observation for us. The
membrane of the GPMVs had to be under low tension and pliable to be able to
display such a phenomenon.
We observed GPMVs to be fairly stationary within the sample, yet the
membrane of the GPMV would display vibrational behavior, with clear nodes (areas
without vibration) visible on the GPMV membrane. Even more remarkably, not all
of the GPMVs in the sample would display this behavior, suggesting that only a
subset of GPMVs possessed a combination of lipids that would allow for this
phenomenon. It is clear that this phenomenon is rooted in the composition of the
membrane. We aimed to find the biological explanation for such a phenomenon and
describe it in the context of our findings.
34
Vibrations in GPMVs were observed in our later preparations of GPMVs
where we began to see the Dynamic critical behavior. In these preparations, we
were viewing the GPMVs exclusively on the spinning disk microscope, and therefore
this was the only method we used to view the vibrations. The only fluorophore that
we viewed this phenomenon was the Fast Dio fluorophore.
While imaging GPMV vesicles, we observed vibrations of the membrane and
distinct nodes present. Within the same field of view, we observed vesicles that
vibrated and others that did not. Hence, we could exclude that this observation was
based on a shaking microscope. The GPMVs vibrating also had visible nodes that the
membrane would vibrate about. This observation was curious; as only a small
proportion of the GPMVs displayed this behavior while the other GPMVs within the
same sample did not. We will attempt to provide a theory for this phenomena based
on current research.
Vibrations were observed in a fairly low percentage of GPMVs (See Graph
2.1). The plasma membrane of the GPMVs was vibrating while there were nodes
present where the rest of the membrane vibrated about. It was observed that the
GPMVs contained two nodes at the equatorial view (See Supplementary Video 6,
Figure 2.10). The membrane was viewed to be highly mobile and vibrating with a
frequency. Not all GPMVs observed in the same sample vibrated, within the same
video frame it was possible to view both vibrational and non-‐vibrational GPMVs
(See Supplementary Video 7).
35
3.4.2 Vibrations – Discussion Fluctuations of vesicles are possible due to the excess surface area available
to the GPMVs as well as the stiffness of the membrane (Milner & Safran, 1987). Any
deviation from the sphere shape is the characterization of the
fluctuations/vibrations that were observed. If the GPMV membranes were stiff,
there would be little to no fluctuations present (Milner & Safran, 1987). For GPMV
vibrations, not only must the GPMVs have sufficient membrane bending elasticity
and spontaneous membrane curvature to vibrate, but also posses a sufficient
amount of excess membrane available (Milner & Safran, 1987). According to Milner
and Safran, calculations of fluctuations of the vesicle systems can predict for
fluctuations that are consistent with the excess area of the vesicle (In this case
excess area is surface area beyond the needed volume for the sphere) (1987).
The elastic properties of the plasma membrane are well known, it has been
shown that biological plasma membranes are very soft in regards to membrane
bending and shearing yet the membrane is relatively incompressible (Sackmann,
1994). This means that GPMVs will have excess membrane available to be
deformed, yet will maintain a rather constant shape, which is what we observed.
The lateral packing density determines the bilayer elasticity of the plasma
membrane and the condensing effect of cholesterol present in the membrane leads
to an increase in the bending and compression of the membrane shape (Sackmann,
1994).
The energy requirement for bending or displacement of the membrane is the
bending energy (Mellander, Kurczy, Najafinobar, Dunevall, Ewing, & Cans, 2013)
(Milner & Safran, 1987) (Sackmann, 1994). Shape changes in the GPMVs can be
36
thought to be due to the membrane bending energy hypothesis, where the minimum
bending energy determines the global shape of the membrane but can also be
subjected to external forces affecting the shape (Sackmann, 1994). It is known that
the membrane softness plays a role in the membranes ability to be manipulated
(Mellander, Kurczy, Najafinobar, Dunevall, Ewing, & Cans, 2013) (Milner & Safran,
1987; Sackmann, 1994) and thus allows for easier undulations and a low membrane
bending energy. The vibrational phenomena that we observed is a result of
pronounced bending undulations (flickering) of the membrane and are similar to
Brownian motion (Sackmann, 1994).
The question of biological significance of the vibrational phenomena is
interesting. So far we have established that to vibrate, the membrane must possess
spontaneous membrane curvature, membrane softness, a capacity for excess
membrane, and membrane elasticity. Interestingly, it has been suggested that the
plasma membrane vibrations is a pacemaker of sorts, and is important biologically
for cell synchronization (Ehsani, 2012).
Ehsani suggested that the vibrational properties of the plasma membrane
play a vital role for the convergence and synchronization of cell-‐wide systems
(2012). Cell vibrations are like the circadian rhythm of cell, allowing the cell to
complete important biological functions with accuracy, allowing for synchronization
between cells (Ehsani, 2012).
In an effort to quantify our vibrational data, we attempted to obtain the
frequency of vibration of the plasma membrane from the captured videos. There
are well-‐established protocols for frequency measurement for small-‐amplitude
37
vibration movements (Ferrer, Espinosa, Roig, Perez, & Mas, 2013). However, we
found that the frame rate of our data was not sufficient enough for the rate of
vibration of the plasma membrane. Without a sufficient enough frame rate, it is
possible to get an accurate idea of where the nodes and the antinodes of the
vibration of the membrane occur, but we are unable to obtain the frequency or
oscillation as there is not enough distinction between the areas of the membrane in
order to accurately analyze the frequency (Figure 2.11). We also concluded that, as
our data is only 2D, where 3D data would be best for an accurate method of analysis.
This is because it may be important to ascertain if there are more than 2 nodes
present on the membrane. For example, there could be two more nodes at both the
apex and the bottom of the GPMV of which we are not aware.
3.5 Spectrofluorometer Spectrofluorometry was done to see, whether a global change in the
proportional amount of Lo vs Ld domains in lipids could be observed. We used the
spectrofluorometer and a lipid sensor dye (C-‐laurdan), which acts as a sensor for the
polarity of its environment by changing its emission spectra. The
spectrofluorometer was used to take advantage of the C-‐laurdan fluorophore, which
changes its emission based on the polarity of the solvent in which it is dissolved
(Kim, et al., 2007). This aspect of C-‐laurdan in addition to the spectrofluorometer,
allowed use to track changes in the phase distribution of the GPMVs due to changing
temperature. C-‐laurdan is unique in that it has the ability to change its emission
wavelength in response to changes in the polarity of the solvent (Kim, et al., 2007).
38
Our aim in this experiment was to show a shift in the fluorescence emission from the
GPMVs in buffer due to changing temperature.
The spectrofluorometer takes a spectral reading of the emission of a sample
after being excited with 405nm wavelength. We aimed to quantitatively show a
change in wavelength of the C-‐laurdan fluorophore dying the GPMV samples. A
change of temperature of the sample well below and well above the critical point,
should affect the emission of the C-‐laurdan based on the increase of Lo phase and
decrease of Lo phase respectively. It was found that our data did show a change
emission based on temperature however, this was negated by the fact that our
control (C-‐laurdan alone in buffer) also showed the same changes in emission,
meaning that the C-‐laurdan itself was sensitive to temperature.
After viewing the great variety of GPMVs and their phenomenon, we
endeavored to create an experiment where we could track the behavior of the
GPMVs over a large population, and determine if we could determine an overall
pattern of behavior for the GPMVs.
We supposed that if the GPMVs are behaving as critical systems, there should
be an increase in phase separation well below the Tc , where two separate phases
exist and the C-‐laurdan should display show a blue shift with decreasing polarity of
the phases. After exciting the samples at 405nm, we found that at lower
temperatures (25°C) that there was an overall blue shift in the samples, and a lower
wavelength was observed (~482nm). When the temperature was increased (55°C)
to the same samples, there was an overall red shift (~492nm) indicating a more
polar GPMV (See Graph 2.2).
39
It was interesting to see such a different between the two different
temperatures. It should be noted that all samples were cycled several times
between 25 and 55°C and the results were recorded for all cycles (See Graph 2.3, 2.4
for examples).
It is clear from our control results that temperature plays some role in the
emission spectra of C-‐laurdan (See Graph 2.2), we suspected that the change in
emission in the GPMVs is due to temperature as the change in wavelength emission
remains constant between both the control and the experimental. Because both the
control and the experimental results are fairly similar, we wanted to attempt to
better understand this phenomenon.
While it was not possible to find further information on C-‐laurdan, we were
able to find temperature data on laurdan, and very similar fluorophore with the
same emission properties. Early research states that emission spectra of laurdan in
dipalmitoylphosphatidylcholine (DPPC) shifted towards longer wavelength as the
temperature increased (Parasassi, Conti, & Gratton, 1986), which was consistent
with our data.
4 Discussion
Our original aim of this project was to provide a framework for a robust and
elegant mechanism of cell signaling. We attempted to build on the work of Veatch
(Veatch, Cucuta, Honerkamp-‐Smith, D., & Baird, 2008) in an effort to connect the
critical behavior theory to cell signaling theory as a method for understanding lipid
domain evolution in regards to cell signaling. As this project advanced, it became
40
clear that the cell systems did not behave as expected. GPMVs displayed all different
sorts of phenomenon and critical behavior was not readily observable and we were
unable to determine if the plasma membrane was behaving critically.
The result obtained presented us with multiple different phenomenon’s’
present on the GPMVs. Although critical behavior presented an elegant framework
for a signaling mechanism, the real life data showed that critical behavior was not
present in a reliable fashion within the GPMV samples. This proved to be
problematic as to present this as a mechanism, there would have to be some
regularity to critical behavior present in GPMVs. In an effort to quantify the critical
movement of the lipid raft domains, we attempted to do a single particle tracking
analysis of our data. We hoped that this would prove that the movement of the lipid
rafts is highly dynamic and can be influenced by certain environmental factors. The
limiting factor in this analysis however, is the resolution. Without sufficient
resolution of the lipid raft domains, it is impossible to do any accurate analysis on
domain movement due to the lack of clear distinction between domains. As there is
much evolution and movement of the domains, it is crucial to have ample resolution
in order to be able to make distinctions between domains. The limits on our ability
to quantify our data lies in the technology that we have available to us today. As
these lipid domains are very small, it is very hard for us to do any real analysis with
our current limits in resolution.
We were not successful in showing critical behavior as a general theme
however; we were able to collect an impressive array of phenomenon present in the
GPMVs. We believe that we were able to present a realistic overview of the behavior
41
of the plasma membrane within GPMVs, as well as a broad understanding for the
overall occurrence of these phenomena.
We hope that this data can illustrate the vast complexity of the lipid
membrane, and light the way for further research into the complex and dynamic
working of the membrane system.
42
Bibliography
Ahmed, S., Wenyu, B., Tze Cheun Less, R., Maurer-‐Stroh, S., & Goh, W. (2010). F-‐BAR domain
proteins. Commun Integr Biol. , 3 (2), 116-‐121.
Albon, N., & Srurtevent, J. (1978). Nature of the gel to liquid crystal transition of synthetic
phosphatidylcholines. Proc. Natl. Acad. Sci , 75, 2258-‐2260.
Brown, D., & London, E. (1997). Structure of Detergent-‐Resistant membrane domains: does
phase separation occur in biological membranes? J. Biochem Bioph Meth , 240, 1-‐7.
Brown, D., & Rose, J. (1992). Sorting of GPI-‐anchored proteins to glycolipid enriched
membrane subdomains during transport to the apical cell surface. Cell , 7 (68), 533-‐
44.
Brockman, H. (1994). Dipole potential of lipid membranes. Chem Phys Lipids , 73, 57-‐79.
Cooper, G. (2000). The Cell: A Molecular Approach (2nd Edition ed.). Boston: Sinauer
Associates.
Danielli, J., & Davson, H. (1935). A contribution to the theory of permability of thin films. J.
Cell Phys , 5, 495-‐508.
Diz-‐Muñoz, A., Fletcher, D., & Weiner, O. (2013). Use the force: Membrane tension as an
organizer of cell shape and motility. Trends Cell Biol , 23 (2), 47-‐53.
Dietrich, C., Yang, B., Fujuwara, T., Kusumi, A., & Jacobson, K. (2002). Relationship of lipid
rafts to transiet confienment zones detected by single particle tracking. Bio Phys J. ,
82, 274-‐284.
43
Dolmetsch, R., Pajvani, U., Fife, K., Spotts, J., & Greenberg, M. (2001). Signaling to the
nucleaus by an L-‐type calcium channel-‐calmodium complex through the MAP kinase
pathway. Science , 294, 333-‐339.
Ehsani, S. (2012). Time in the cell: a plausible role for the plasma membrane . arXiv ,
arXiv:1210.0168.
Ferrer, B., Espinosa, J., Roig, A. B., Perez, J., & Mas, D. (2013). Vibration frequency
measurement using a local multithreshold technique. Opt Express , 21 (22), 26198-‐
208.
Frolov, V., Shynyrova, A., & Zimmerberg, J. (2011). Lipid Polymorphisms and Membrane
Shape. Cold Spring Harb Prespect Biol. , 3 (11), a004747.
Gupta, N., & DeFranco, A. (2007). Lipid rafts and B cell signaling . J Semcdb , 18, 616-‐626.
Gorter, E., & Grendal, F. (1925). On biomolecular layers of lipids on the chromocytes of the
blood. J Exp Med , 41, 439-‐443.
Ising, E. (1925). Beitrag zur Theorie des Ferromagnetismus. Zeitschrift für Physik , 31 (1),
253-‐285.
Israelachvili, J. (2011). Intermolecular and Surface Forces (3rd Edition ed.). Santa Barbara:
Academic Press.
Israelachvili, J., Marčelja, S., & Horn, R. (1980). Physical rincipals of membrane organizaion.
Cambridge University Press , 13 (2), 121-‐200.
Harder, T., & Kuhn, M. (2000). Selective accumulation of raft-‐associated membrane protein
LAT in T cell receptor signaling assemblies. J Cell BIol , 151, 199-‐207.
Heberle, F., & Feigenson, G. (2011). Phase Separationg in Lipid Membranes. Cold Spring
Harb Prespect Biol , 3 (4), 1-‐13.
44
Honerkamp-‐Smith, A., Cicuta, P., Collins, M., Veatch, S., den Niks, M., Schick, M., et al. (2008).
Line Tensions, Correlation Lengths, and Critical Exponents in Lipid Membranes Near
Critical Points. Biophysical Journal , 1, 236-‐246.
Kim, H., Choo, H., Jung, S., Ko, Y., Park, W., Jeon, S., et al. (2007). A two-‐photon fluorescent
probs for lipid raft imaging; C-‐laurden . Chembiochem , 8 (5), 553-‐9.
Kornberg, L., Earp, H., Turner, C. ,., & Juliano, R. (1991). Siganl transduction by intergrins:
increased protein tyrosine phosphorylation caused by clutering of Beta 1 intergrins.
Proc. Natl. Acad. Sci. , 88, 8329-‐8396.
Lodish, H., Berk, A., & Zipurksky, S. (2000). Molecular Cell Biology (4th Edition ed.). New
York City: W. H. Freeman.
Munro, S. (2003). Lipid rafts: elusive or illusive? Cell , 115, 337-‐338.
Mellander, L., Kurczy, M., Najafinobar, N., Dunevall, J., Ewing, A., & Cans, A. (2013). Two
modes of exocytosis in an artifical cell. Scientific reports , 4, 3847.
Milner, S., & Safran, S. (1987). Dynamical fluctuations of droplet microemulsions and
vesicles. Phys. Rev A , 36, 4371.
Ng, G., Sharma, K., S., W., Desrosiers, M., Stephens, L., Schoel, W., et al. (2008). Receptor-‐
independant direct membrane binding leads to cell-‐surface lipid sorting and SYK
kinase activation in dendritic cells. J Immunol , 29, 807-‐818.
Ohtani, Y., Irie, T., Uekama, K., Fukunaga, K., & Pitha, J. (1989). Differential effects of Alpha-‐,
Beta, and Gamma-‐cyclodextrins on Human Erythrocytes. Eur J Biochem , 186, 17-‐22.
Onsager, L. (1994). Crystal statistics. I. A two-‐dimensional model with an order-‐disorder
transition. Phys Rev , 65, 117-‐149.
45
Parasassi, T., Conti, F., & Gratton, E. (1986). Time-‐Resolved fluorescence emission spectra
of laurden in phospholipi vesicles by multifrequence phase and mkodulation
fluorometry. Cellular and Molecular Biology , 32 (1), 103-‐108.
Pike, L. (2003). Lipid rafts: bringing order to chaos. J. Lipid Res , 44, 655-‐667.
Pralle, A., Keller, P., Simons, K., & Horber, J. (2000). Sphingolipid-‐cholesterol rafts diffuse as
samll entities in the plasma membrane of mammalian cells. J. Cell Biol , 148 (997-‐
1007).
Rajendran, L., & Simons, K. (2005). Lipid rafts and membrane dynamics. J Cell Sci , 118,
1099-‐1102.
Robertson, J. (1960). The molecular structure and contact relationships of cell membranes.
Prog Biophys Mol Biol , 10, 343-‐418.
Sackmann, E. (1994). Membrane bending energy concept of vesicle and cell shapes and
shape transitions . 346, 3-‐16.
Sezgin, E., Hermann-‐Josef, K., Baumgrat, T., Schwille, P., Simons, K., & Levental, I. (2012).
Elucidating membrane structure and protein behaviour using giant plasma
membrane vesicles. Natura Protocols , 7, 1042-‐1051.
Shets, E., Holowka, D., & Baird, B. (1999). Critical role for cholesterol in Lyn-‐mediated
tyrosine phosphorlyation of FcεRI and their assocation with detergent-‐resistant
membranes. J Cell Biol , 145, 877-‐887.
Simons, K., & Sampaio, J. (2000). Membrane organization and lipid rafts. Cold Spring Harb
prespec biol , 3, 1-‐27.
Simons, K., & Toomre, D. (2000). Lipid rafts and signal transduction. Nat Rev Mol Cell Biol ,
1, 31-‐39.
46
Springett, G., Kawasaki, H., & Springgs, D. (2004). Non-‐kinase second-‐messenger signaling:
new pathways with new promise. Bio Essays , 26, 730-‐738.
Stier, A., & Sackmann, E. (1973). Spin labels as enzyme substrates heterogenous lipid
distribution in liver microsomal membranes. Biochem Biophys Acta. , 311, 400-‐408.
Veatch, S., & Keller, S. (2005). Seeing spots: complex phase behaviour in simple membranes.
Biochem Biophys Acta , 1746, 172-‐185.
Veatch, S., Cucuta, P., Honerkamp-‐Smith, A., D., H., & Baird, B. (2008). Critical fluctuations in
plasma membrane vesicles. ACD Chem Biol , 3, 287-‐293.
Yu, J., Fischman, D., & Steck, T. (1973). Slective solubilization of proteins and phospholipids
from red blood cell membranes by nonionic detergents. J. Supramol Str Cell , 1, 233-‐
248.
47
Appendices
Tables Table 1.1: Select signaling events requiring recruitment of proteins
Signaling event
Lipid raft
mediated
Proteins involved Reference
T Cell Signaling
Yes TCR, ITAMs, Src Kinases Lck, Fyn and linker protein LAT, TCR/CD3, CD4/CD8
Harder and Kuhn, 2000
MSU signaling
Yes no known proteins Ng et al, 2008
Tyrosine Kinase signaling
Yes EGF receptor, PDGF receptor, insulin receptor, MAPK
Pike, 2003
G Protein-‐coupled Receptors
Yes β1 and β2 -‐adrenergic receptors, adenosine A1 receptors, m2 muscrainic cholinergic receptors, rhodopsin and bradykinin
B1 and B2 receptors, G proteins Gi and Gs
Pike, 2003
IgE siganling
Yes FceR, ITAMs, Syk family tyrosine kinsases, LAT Sheets, Holowka and Baird,
1999 BCR
signaling Yes BCR, CD40 Gupta and
DeFranco, 2007
Calcium Chanel Signaling
No L Type voltage activated channels (LTC) , MAPK Dolmetsch et. al., 2001
48
Graph 2.1: Depicting the frequency of each phenomenon viewed on GPMVs. Data
was pooled from 528 GPMVs. Taken with 63X spinning disk with Fast Dio fluorophore.
Graph 2.2: Comparison of wavelength emission of C-‐laurdan in buffer or with
GPMVs at 25°C and 55°C.
Vibrations Blebbing
Static Phase Separation Dynamic Phase Separation
Phase Separation Critical
0
1
2
3
4
5
6
7
8
Average number of vesicles displaying phenomena for each observation
460
470
480
490
500
510
520
530
Control C-‐Laurdan in Buffer GPMV samples
Wavelength
Wavelength at Maximum Emission
25C
55C
49
Graph 2.3: Graph depicting emission values of C-‐laurdan with GPMVs or in buffer as control at 25°C when excited at 405nm. The GPMV samples were cycled 2-‐3 times
between 25°C and 55°C.
Graph 2.4: Graph depicting emission values of C-‐laurdan with GPMVs or in buffer as control at 55°C when excited at 405nm. The GPMV samples were cycled 2-‐3 times
between 25°C and 55°C.
0
0.2
0.4
0.6
0.8
1
1.2
Normalized Fluorescence
Wavelength
GPMVs at 25C with C-‐laurdan C-‐Laurdan 25T
GPMV CL 25T
GPMV CL 25T1
GPMV CL 25T2
Sample 2 GPMV CL 25T Sample 2 GPMV CL 25T1
0
0.2
0.4
0.6
0.8
1
1.2
Normalized Fluorescence
Wavelength
GPMVs at 55C with C-‐laurdan C-‐Laurdan 55T
GPMV CL 55T
GPMV CL 55T1
GPMV CL 55T2
Sample 2 GPMV CL 55T
Sample 2 GPMV CL 55T1
50
Figures
Figure 2.1: Cropped image displaying the diversity of the GPMVs observed
displaying phase separation. GPMVs are dyed with Fast Dio, taken on a 63X Spinning disk.
51
Figure 2.2: Image of equatorial view of GPMV from video taken from 63X spinning disk. The GPMV displays static phase separation where the phases do not move or
change shape. GPMV is dyed with Fast Dio fluorophore.
52
Figure 2.3: Image taken from a video top view of GPMV on 63X spinning disk. The video shows a top view of GPMV displaying static phase separation where the phases do not move or change shape over time. The GPMV is dyed with Fast Dio
fluorophore.
53
Figure 2.4: Explanation on making observations on data collected for the phase
separation section.
Viewing the GPMV’s
Plane of focus
GPMV
The plane of focus is approximately 750nm in height. A lipid is Approximately 5Å, meaning that there are around 1500 lipids in the optical axis within the focal depth at any one time for the equatorial view. In contrast, there is only one lipid in the focal depth for the apical view. This explains the typically better contrast in the equatorial view.
Apical View
Equatorial View
54
Figure 2.5: Image from video of top view of GPMV displaying dynamic phase
separation. Phases display high motility. Video was taken from 63X Elyra and GPMV was dyed with Alexa 647 conjugate to Cholera toxin β subunit.
55
Figure 2.6: Image from videos of changing lipid dynamics. The lipid rafts display-‐evolving shapes, which are motile on the plasma membrane. Video was taken on 63X spinning disk with the Fast Dio fluorophore (See supplementary Video 5).
56
Figure 2.7: 63X Elyra montage image of Z stack of GPMV. GPMV is dyed with both
Rhodamine-‐PE (red) and Bodipy cholesterol (green) flurophores.
57
Figure 2.8: 63X Elyra image of a GPMV displaying blebbing phenomena. The fluorophore used is an Alexa 647 conjugate to Cholera toxin β subunit.
Figure 2.9: GPMV displaying the blebbing phenomena from a 63X Elyra image. The red is the rhodamine POPC and the green is the bodipy cholesterol fluorophores.
58
Figure 2.10: Image from Video of GPMV displaying vibration phenomenon. Video
taken with 63X spinning disk with Fast Dio fluorophore.
59
Figure 2.11: Zoomed image of Figure 2.10. The smaller red circles depicts the nodes of vibration while the larger red ovals displays the antinodes.
2 μm
Node
Antinode
