HHS Public Access

Author manuscript
Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
Author Manuscript

Published in final edited form as:

Annu Rev Phys Chem. 2021 April 20; 72: 51–72. doi:10.1146/annurev-physchem-090419-115951.

Critical Phenomena in Plasma Membrane Organization and

Function
Thomas R. Shaw1, Subhadip Ghosh2, Sarah L. Veatch1,2,3
1Program in Applied Physics, University of Michigan, Ann Arbor, Michigan, USA;
2Program in Biophysics, University of Michigan, Ann Arbor, Michigan, USA;
Author Manuscript

3Department of Physics, University of Michigan, Ann Arbor, Michigan, USA

Abstract
Lateral organization in the plane of the plasma membrane is an important driver of biological
processes. The past dozen years have seen increasing experimental support for the notion that lipid
organization plays an important role in modulating this heterogeneity. Various biophysical
mechanisms rooted in the concept of liquid–liquid phase separation have been proposed to explain
diverse experimental observations of heterogeneity in model and cell membranes with distinct but
overlapping applicability. In this review, we focus on the evidence for and the consequences of the
hypothesis that the plasma membrane is poised near an equilibrium miscibility critical point.
Critical phenomena explain certain features of the heterogeneity observed in cells and model
systems but also go beyond heterogeneity to predict other interesting phenomena, including
Author Manuscript

responses to perturbations in membrane composition.

Keywords
critical composition fluctuations; thermodynamics; cell membrane; membrane microdomains;
lipid rafts

1. OVERVIEW
The spatial organization of the plasma membrane on 10–100-nm length scales has been a
topic of interest in biology for decades. Heterogeneity has been hypothesized to play
important roles in many membrane-associated biological processes, from the coordination of
Author Manuscript

signal transduction machinery, to endo- and exocytosis, to polarization, as iconically

described in the lipid raft hypothesis (1). Various biophysical notions have been marshaled
to provide explanations of membrane heterogeneity, especially from equilibrium
thermodynamics and phase transitions, as coexisting liquid phases are readily observed in
both purified membranes and membranes isolated from plasma membranes (2, 3). One
important thread of this ongoing conversation explains nanoscale membrane structure in
terms of critical phenomena. In contrast to a classical phase separation picture of plasma

DISCLOSURE STATEMENT
The authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the
objectivity of this review.
 Shaw et al. Page 2

membrane domains, which implies stable, discrete regions of defined composition, critical
Author Manuscript

phenomena are subtle, dynamic, and malleable and inhabit the relevant nanoscopic length
scales.

In this review, we conduct a brief historical survey of membrane domains in both model and
biological membranes and describe the consensus that has been reached regarding the
macroscopic miscibility phase behavior of model membranes as well as the remaining
controversies regarding the microscopic heterogeneity reported in other regions of phase
space. We introduce membrane criticality and the accumulated evidence that eukaryotic
plasma membranes are near-critical. We discuss how the concept of criticality fits into
conventional descriptions of raft phenomenology and describe some unique areas in which
criticality could play roles in biological function that go beyond the simple organization of
components.
Author Manuscript

2. AN EARLY HISTORY OF DOMAINS IN MODEL AND CELL MEMBRANES

There is a long history of detecting heterogeneity in bilayer membranes containing
cholesterol. Some of the earliest studies that interrogated purified membranes in the late
1960s and early 1970s found evidence that liquid membranes containing a single
phospholipid species and cholesterol contained structure on the 1–100-nm length scales
accessible to the spectroscopic methods available at the time (4–9). Over the decades,
evidence for these microscopic domains in binary mixtures of phospholipids and cholesterol
continued to accumulate through additional spectroscopic studies; calorimetry; the
application of fluorescence techniques such as fluorescence quenching, anisotropy, and
Förster resonance energy transfer (FRET); and imaging methodologies such as freeze-
fracture electron microscopy (10–21).
Author Manuscript

Largely in parallel with this physical chemistry characterization of membranes, cell

biologists also postulated that membranes within cells might contain lipid-mediated
substructures that could be important for cell functions. Early evidence of this came from the
observation that cells could polarize their membrane lipid composition via the differential
trafficking of lipid species (22). In addition, cholesterol or similar sterols have long been
known to be vital to the proper functioning of most eukaryotic plasma membranes, as
manipulation of membrane cholesterol content has been shown to interfere with functions
including endocytosis, several receptor-mediated signaling cascades, and cell cycle control
(23–26). In the early 1990s it was discovered that some detergents only partially solubilize
cellular membranes, especially the plasma membrane (27, 28), and it was postulated that the
insoluble fractions represented distinct membrane domains (1, 20). Researchers found that
artificially clustering some membrane components individually could drive macroscopic
Author Manuscript

colocalization, a process termed copatching, which was detectable by conventional

fluorescence microscopy (29). Subsequent spectroscopic and fluorescence measurements
supported the hypothesis that cell membranes were heterogeneous in their lipid and protein
content (30–32), and many studies correlated biological function with presumed membrane
heterogeneity that had been probed and perturbed via these and related assays (33–36). Each
of these methods had well-documented flaws (37), but the remarkable consistency of the

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 3

conclusions drawn from different methodologies provided convincing evidence that lipid-
Author Manuscript

driven heterogeneity is relevant to the plasma membrane.

3. LIQUID–LIQUID PHASE SEPARATION IN MODEL MEMBRANES

3.1. Purified Membranes
In 2001, the first observations of macroscopically phase-separated fluid domains were
reported in bilayer membranes reconstituted from cellular extracts (38, 39). These initial
observations emphasized similarities between the composition of the coexisting phases in
model membranes and the heterogeneity measured in cells by detergent solubilization
methods. Soon after, minimal systems of at least three lipid components were shown to form
macroscopically phase-separated domains in bilayers: a high melting temperature (Tm) lipid,
a low Tm lipid, and a sterol such as cholesterol (40). Phase diagrams describing this
macroscopic phase transition have now been mapped by numerous groups using a range of
Author Manuscript

methods and are in good qualitative agreement (41–49). An introduction to reading and
interpreting three component phase diagrams is given in Figure 1, and several experimental
phase diagrams are presented in Figure 2.

A range of experimental (50–56) and simulation (57, 58) approaches using different lipid
combinations have produced results consistent with phase diagrams topologically similar to
those shown in Figure 1b, and their detailed characteristics have been described in several
comprehensive review articles (3, 59, 60). Liquid immiscibility is most often observed at
temperatures below the Tm of the high Tm lipid (42, 44–46), although there are exceptions
(41). In the typical case, reported phase diagrams have a region of liquid–liquid coexistence,
a region of three-phase coexistence (two liquids and a solid), and two regions of liquid–solid
coexistence. One of the liquid phases is called the liquid-disordered (Ld) phase, and it
Author Manuscript

resembles the liquid crystalline phase (Lα) of pure phospholipids (61). The second liquid
phase, which is called the liquid-ordered (Lo) phase (15), was first characterized in mixtures
of saturated phospholipids and cholesterol (8, 16, 18). Most authors refer to both Lo and Ld
as Lα phases. The solid phase (So) is often called gel and there are several distinct gel phases
observed in purified membranes, including the solid lamellar phases designated Lβ and Lβ′
(62).

The high cholesterol edge of the three-phase triangle is sloped such that the Lo phase
contains a higher cholesterol mole fraction than does the Ld phase. This edge of this triangle
is also the first tie-line in the liquid–liquid coexistence region. As cholesterol is increased
further, the tie-lines run roughly parallel to one another, meaning that the cholesterol
concentration increases roughly linearly in both phases. The Lo–Ld coexistence region
Author Manuscript

terminates in a miscibility critical point at which in principle the tie-lines merge to a single
point. In practice, this region of the phase diagram is surprisingly flat, meaning that the tie-
lines remain long and shorten over a very small range of compositions. As the temperature is
lowered, the Lo–Ld immiscibility gap extends to higher concentrations of cholesterol and
low Tm lipid, as does the concentration of components at the critical point (41, 45, 48). At a
constant temperature, the miscibility gap expands when the Tm of the high Tm component is
increased or when the Tm of the low Tm lipid is decreased (41, 42, 44). No macroscopic
miscibility gap is observed for some combinations of low and high Tm lipids (42, 44, 63). A

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 4

closed loop miscibility gap is found when the extremely low Tm lipid diphytanoyl
Author Manuscript

phosphatidylcholine (DPhPC) is used (41), meaning that Lo–Ld coexistence occurs at

temperatures above the Tm of the saturated component and that there are two critical points.
The phase behavior of the mixed system can depend on more than just the Tm of its
components. For example, sphingomyelin (SM) lipids are more effective at establishing
coexisting phases than are glycerol-phospholipids with phosphatidylcholine (PC)
headgroups (44, 58) even when the main chain transition occurs at similar temperatures for
the SM and PC lipids used.

Although the equilibrium thermodynamics description of the macroscopic miscibility

transition is now largely accepted, questions remain regarding the thermodynamic basis of
the microscopic heterogeneity also routinely observed in membranes containing cholesterol.
These structures are frequently reported at temperatures and compositions at which
membranes remain uniform on a macroscopic scale using methods that are sensitive to
Author Manuscript

molecular-scale organization such as FRET, fluorescence quenching, or electron spin

resonance (ESR) spectroscopy. Membranes can be tuned from a state with macroscopic
phase separation to one with microscopic heterogeneity by raising the temperature (64, 65),
by titrating in an additional component that disrupts the macroscopic phase transition (see,
e.g., References 50, 52, and 66), or by probing different ratios of the same lipid species at a
fixed temperature (65). Submicrometer structure is also reported in binary mixtures of
saturated lipids and cholesterol (7, 67) and in some ternary membranes that do not exhibit
macroscopic Lo–Ld immiscibility at any temperature or lipid ratio (21, 47, 63, 68). Recent
experimental developments in purified membranes have begun to probe how leaflet
asymmetry impacts phase separation and the presence of submicrometer structure in purified
membranes (69, 70).
Author Manuscript

Experimental observations have motivated numerous theories to explain the presence of

microstructure at thermodynamic equilibrium. Critical phenomena provide a possible
mechanism to bridge between the macro- and microscales in the form of dynamic
fluctuations (45, 71). Other theories enable static, finite-sized domains by including some
repulsive mechanism to oppose the formation of macroscopic domains (72–74). These
theories too predict domains that span macro- to microscales. Recent experimental work
(75) has begun to directly test some of these theories.

3.2. Isolated Membranes

The first observations of macroscopic liquid immiscibility in vesicles blebbed directly from
living cells came in 2007 (2), and these vesicles were named giant plasma membrane
vesicles (GPMVs) due to their close resemblance to the giant unilamellar vesicles (GUVs)
Author Manuscript

used widely in fluorescence microscopy investigations of purified lipid mixtures. Earlier

work using a similar vesicle preparation had characterized their lipid and protein content by
mass spectrometry (76) and had observed heterogeneity using ESR (30), a spectroscopic
method that can detect heterogeneity on the molecular scale. Baumgart et al. (2) detected the
sorting of fluorescent lipid analogs and fluorescently tagged proteins with respect to phases
in GPMVs at temperatures well below those at which cells were grown, leading the

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 5

researchers to conclude that this phase transition was not relevant for cells under normal
Author Manuscript

growth conditions.

Soon after, other methods emerged to isolate plasma membranes from cells, all of which
could yield coexisting liquid phases (77, 78), although the conditions needed to achieve
phase separation differed depending on the method used. A subsequent study found
correlations between biochemically defined detergent-resistant membranes and the Lo phase
detected in GPMVs (79) and that the surface fraction of Lo phase at low temperature was
altered by acute treatments to manipulate cholesterol levels in vesicles (79, 80). In all cases,
miscibility transition temperatures (Tmix) remained well below growth temperatures in
isolated cells, emphasizing that such macroscopic domains were not likely to form under
physiological conditions. A possible explanation came in 2008 when it was shown that
freshly isolated GPMVs exhibited hallmarks of criticality, placing them close to a room
temperature miscibility critical point (81). Over time, additional studies have documented
Author Manuscript

how GPMV phase behavior is impacted by growth conditions in cells (82–84) and
differentiation into other cell types (85, 86), and lipidomics analysis has begun to
characterize the vast compositional complexity of these membranes (82, 84, 87).

While there are many similarities between the phase behavior observed in GPMVs and
purified model membranes, there are also key differences (88). The coexisting phases
detected in GPMVs differ in their physical properties from their purified membrane
counterparts. The viscosity and hydration of phases is more similar in GPMVs compared to
that in GUVs, as measured through the diffusion of membrane components or using order-
sensing fluorophores that report on local hydration within the hydrophobic region of the
membrane (89). These different physical properties can be sensed by incorporated proteins.
Some transmembrane proteins, particularly those with palmitoylated cysteines, are observed
Author Manuscript

to partition into the Lo phase in GPMVs, whereas few are reported to partition into the Lo
phase in purified membranes (90).

GPMVs are model membranes that differ from intact plasma membranes in important ways.
Plasma membranes exist in close association to the actin cytoskeletal cortex, while GPMVs
are missing polymerized cytoskeletal components and tend to be depleted in proteins that
associate with actin (91). Notably, the cell plasma membrane does not macroscopically
phase separate even under conditions that cause GPMVs to phase separate, or in fact under
any known conditions, even when phase-separated GPMVs remain attached to an intact cell
membrane (92). GPMVs are depleted of phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2]
(93), which typically makes up several mole percent of the inner plasma membrane leaflet in
intact cells (94). A recent report demonstrates that isolated GPMVs are frequently permeable
Author Manuscript

to large hydrophilic markers (95), indicating that their membranes contain long-lived
defects. While cell membranes are asymmetric in their lipid and protein composition, at least
some of this asymmetry is lost in the GPMV generation and isolation process (2, 93). The
interpretation of GPMV experiments is also complicated by their sensitivity to
methodological choices. For example, the most common method used to prepare GPMVs
involves incubating cells with a low concentration of formaldehyde and a reducing agent,
and the choice of the reducing agent can greatly impact the Tmix and physical properties of

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 6

phases of the resulting GPMVs (78, 96). This is due, at least in part, to the ability of some
Author Manuscript

reducing agents to modify membrane proteins and lipids.

4. PHASE-SEPARATED DOMAINS ARE RELATED TO BUT DIFFERENT

FROM RAFT HETEROGENEITY IN INTACT CELLS
Phases are robust macroscopic entities with well-defined compositions and, with the
exception of in the yeast vacuole (97, 98), structures resembling liquid–liquid phase
separation are not observed in intact cells. Instead, the vast majority of membrane domains
in cells are microscopic and require significant perturbations to be visualized or isolated. In
line with this, several recent studies have directly concluded that there is no evidence of a
miscibility phase transition in intact cells when cells are examined through the lens of
several different experimental observables (99, 100). Nonetheless, a large number of
Author Manuscript

experimental studies provide strong evidence that the heterogeneity reported in intact cells is
closely related to the macroscopic phase separation observed in GPMVs. Two excellent
recent reviews (101, 102) discuss many of these findings, as well as some exceptions. We
highlight several lines of evidence below.

1. In many cases, proteins that are associated with live-cell heterogeneity or with
detergent-resistant membranes are also found to partition into the Lo -like phase
of GPMVs. In particular, single-pass transmembrane and peripheral proteins
containing palmitoylations are more likely to be found in detergent-resistant
membranes and to partition into the Lo phase in GPMVs, while proteins
containing branched and unsaturated geranylgeranyl or prenyl groups tend to be
solubilized by detergents and to partition into the Ld phase in GPMVs. Recent
work has begun to extend this to multipass proteins that can accommodate more
Author Manuscript

complex protein–lipid interactions (103–105). Protein partitioning is likely

dictated by the identity of lipids that solvate transmembrane proteins in complex
membranes (106, 107)

2. Cells actively tune their plasma membrane Tmix in response to changes in growth
conditions, and conditions that change Tmix lead to different phenotypes. For
example, experiments indicate that cells in culture actively tune the Tmix of their
membrane to be a fixed temperature below their growth temperature (82) and
that the Tmix decreases in cells under conditions that inhibit cell growth (83).
Other studies have documented that acute treatments with lipophilic small
molecules or dietary lipids that alter Tmix correlate with changes in signaling
outcomes, cellular differentiation, and even the general anesthetic response (85,
108, 109). While these correlations with Tmix may be a result of a mutual
Author Manuscript

correlation with an unrelated quantity, the accumulated evidence suggests that

maintaining Tmix plays important roles in cellular processes.

3. In model membranes, Tmix predicts structure observed in single-phase

membranes. While model membranes appear homogeneous at the macroscopic
scale above Tmix, the value of Tmix can predict the presence of structure at
smaller scales or under conditions in which membranes are perturbed by
clustering one component. A recent report (96) documents the temperature

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 7

dependence of both macroscopic phase behavior and microscopic heterogeneity

Author Manuscript

in GPMVs under a range of perturbation conditions. This work found that the
microscopic heterogeneity in GPMVs at elevated temperature was highly
correlated with their macroscopic transition temperature Tmix, suggesting that the
same could be true in intact cells. An older study found that macroscopic
membrane domains enriched in phase-marking probes could be stabilized even
well above Tmix (80). These and other studies have led to the idea that the value
of Tmix is a measure of the stability of raft-like domains under physiological
conditions, even though cells do not appear to experience phase separation
directly.

4. Theoretical arguments support that coupling to an intact cytoskeletal network

disrupts the macroscopic phase transition. It is well established that quenched
disorder abolishes first-order phase transitions in two-dimensional (2D) systems
Author Manuscript

such as membranes (110). The cortical actin cytoskeleton, which is linked to the
plasma membrane through a system of adapter proteins, is likely to play the role
of quenched disorder in the intact plasma membrane (92, 111). Experimental
studies in model membranes support the main conclusion of this theory, which is
that a broadly distributed cytoskeletal network disrupts macroscopic domains
while stabilizing small-scale structure (112). Direct tests in intact cells have yet
to be reported, but broad evidence exists for important connections between
cortical actin and raft heterogeneity (113–117).

5. The evidence for phase-driven partitioning within intact cells is increasing.

Recent work using single-molecule fluorescence methods is beginning to draw
more direct connections between phases in vesicles and domains in cells (118,
119). These studies monitor the recruitment and exclusion of probes with respect
Author Manuscript

to clustered proteins in intact cells and have found that probe concentration in
clusters mirrors partitioning with respect to phase-separated domains in model
membranes, although typically with a smaller magnitude.

To explain these experimental developments, several theoretical avenues have been explored,
with a goal of explaining the lack of a macroscopic phase separation in intact cells. Any
complete biophysical model of membrane heterogeneity must first account for this fact, and
therefore must be more complex than the simple phase-separation picture. These
explanations include coupling to quenched disorder in the form of the cytoskeleton (92,
111); coupling to curvature in a way that produces a microemulsion (72, 74, 120); and
nonequilibrium suppression of domain growth, for example, by active lipid transport or the
remodeling of membrane-coupled actin structures (121, 122). Many of these models,
Author Manuscript

including the critical phenomena that are discussed in the next section, are closely related to
the canonical phase-separation picture (123).

5. CRITICALITY AND ITS CONNECTION TO THE PLASMA MEMBRANE

Equilibrium critical phenomena are special relationships between the thermodynamic
properties of a system that emerge due to a diverging correlation length of the system in the
vicinity of a critical point. Key physical quantities such as the heat capacity, susceptibility,

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 8

and interfacial energy between domains also exhibit specific behaviors as the critical point is
Author Manuscript

approached. These properties of critical systems are universal, meaning that the dominant
behavior is governed by a small number of effective parameters regardless of the
complicated details of microscopic interactions (Figure 3). The physics of criticality has
been covered in detail in many textbooks (124–127). A useful introduction for biophysicists
is given in Reference 128.

5.1. Historical Foundations of Critical Phenomena

The physics of criticality has developed over the last 200 years, beginning with the
observation of a critical temperature for several liquids above which there is no liquid–gas
transition (129). The van der Waals equation of state first published in 1873 was the first
model that featured a critical point with this property (130). In 1918, Ornstein & Zernicke
(131) formalized the study of spatial fluctuations in liquid–gas systems, a key development.
Author Manuscript

In the first half of the twentieth century, precise measurements of near-critical liquid–gas
systems (132) as well as magnetic systems (133) indicated that classical equations of state
were inadequate to explain the near-critical region of phase space, for example, that the
shape of the liquid–gas coexistence curve is qualitatively different than that predicted by the
van der Waals equation. In 1944, Lars Onsager (134) exactly solved the 2D Ising model,
which allowed for the study of critical exponents in that system. In 1952, Lee & Yang (135)
observed that phase transitions correspond to nonanalyticities of the partition function in the
thermodynamic limit. Soon after, Widom (136) and others proposed power-law scaling for
various quantities at critical points and derived relationships between different critical
exponents from that hypothesis. Real-space [Kadanoff (137)] and momentum-space [Wilson
(138)] renormalization group methods explained the emergence of these power laws and
provided avenues for computing approximate values for the critical exponents in general
Author Manuscript

systems,. They also set a uniform framework for other conceptual advances. A broader class
of nonequilibrium critical points can also be defined, generalizing this equilibrium concept.
Biological nonequilibrium critical points have received considerable attention in recent
years; for a review see, e.g., Mora & Bialek (139).

5.2. Unique Properties of Critical Systems

Coexistence regions generically terminate in a critical point except in special circumstances,
and the Lo–Ld miscibility of purified and isolated membranes is no exception. On the phase
triangle shown in Figure 1b, the critical point occurs on the high cholesterol edge of the Lo–
Ld miscibility gap. Initial evidence of critical behavior in membranes came from nuclear
magnetic resonance (NMR) studies of multilamellar vesicles, which detected enhanced line
broadening in the vicinity of known critical points (45). This was attributed to the diffusion-
Author Manuscript

mediated exchange of lipids between fluctuations with submicrometer dimensions. Later

work directly visualized micron-sized critical fluctuations (above the critical temperature Tc)
and fluctuating phases (below Tc) in GUVs of purified lipids, providing evidence that
membranes belong to the 2D Ising model universality class, meaning that fluctuations
exhibited a temperature dependence that is universal to 2D systems with a 1D order
parameter (71). Subsequent measurements confirmed this observation in supported
membranes by atomic force microscopy (48) and probed the dynamics of critical
membranes (140). At the same time, isolated GPMVs were also discovered to exhibit critical

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 9

behaviors in the vicinity of a room temperature critical point (81). Again, fluctuations were
Author Manuscript

consistent with the 2D Ising model universality class. These observations and their
implications have been previously reviewed in greater detail (128).

One of the key features of a critical point is that its fingerprints extend well beyond the
phase transition itself (Figure 3). An important parameter is t, the difference between the
temperature of the system and the Tc, normalized by Tc in units of Kelvin. The correlation
length ξ, or characteristic size of critical composition fluctuations, is predicted to vary as
ξ(t) = ξ0/t, where ξ0 is a parameter with dimensions close to the size of molecules in the
system and in membranes was measured to be roughly 1 nm. Note that as T → Tc, t → 0, so
that the correlation length becomes infinite. If extrapolating this relationship using a room
temperature critical point (Tc = 22°C = 295 K), then 20-nm-sized fluctuations are expected
at 37°C, which corresponds to t = 0.05. This prediction is in good agreement with recent
experimental work probing heterogeneity in GPMVs by FRET, which detects evidence for
Author Manuscript

larger than 10-nm structures in GPMVs over this same temperature range (96). Similar
observations have also been made in purified model membranes (141). Note that t need not
be a physical temperature. Instead, it is any trajectory in the phase diagram that runs
perpendicular to tie-lines close to the critical point. Thus, while some Ising model images of
Figure 3a are obtained by varying temperature in the model, the corresponding three-
component lattice model images are obtained by varying composition at fixed temperature,
as indicated in the phase diagram.

Another physical property that can extend well beyond the phase transition itself is the
susceptibility (χ). The susceptibility measures how large a local composition difference
arises from a local force applied to components of one of the phases, e.g., by clustering
components that prefer Lo lipids. In other words, in a highly susceptible membrane, a
Author Manuscript

domain of distinct local composition can be stabilized by clustering only a small subset of
components or by weakly biasing the concentration of many components that have the same
order preference. In the Ising universality class, χ varies with t as χ ∝ t−7/4. This too has
experimental support in vesicles, where robust domains are stabilized well above Tmix by
organizing a small subset of components via an actin network or a streptavidin crystal that
partially decorates a vesicle surface (114, 142) or by adhesion to a supported membrane
(80).

Direct theoretical predictions of critical phenomena such as the scaling of the correlation
length and the magnitude of the susceptibility are quite useful for predicting the
consequences of perturbations to membrane heterogeneity, but the theory quickly becomes
intractable when coupled to more complex biological phenomena. Statistical mechanical
Author Manuscript

lattice models based on the Ising model can be useful in this situation. These models
typically contain only two components (often called up and down spins because of the Ising
model’s origin as a model of magnetic systems) positioned on a lattice, where the
components at the lattice sites are either allowed to change identity (such that the
composition or magnetization can vary) or are allowed to exchange with other sites on the
lattice (such that the composition remains fixed). Universality guarantees that, as long as the
system is close to the critical point, the Ising model captures the relevant mesoscopic
heterogeneity of the membrane for appropriate choices of the Ising reduced temperature t

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 10

and magnetization m (Figure 3). That is, the Ising model accurately recapitulates the
Author Manuscript

thermodynamics of the effective Lo order parameter at length scales beyond a few lipid
diameters, despite the extreme simplicity of the microscopic interaction in the model, which
is a simple nearest-neighbor interaction potential. As a result, when a biological system is
coupled to the Lo order parameter, an Ising model modified to include this coupling is
expected to reflect the relevant biophysical phenomena. Past work has used this approach to
model the coupling of fluctuations to cortical actin (92), to explain changes in
phosphorylation steady states upon clustering of a component for various values of t and m
(118, 143), and to predict how proximity to the critical point affects conformational state
equilibria of proteins whose boundaries are sensitive to lipid order (144).

5.3. Evidence for Criticality Playing a Role in Cells

If intact plasma membranes exhibit heterogeneity similar to that observed in GPMVs, this
Author Manuscript

could easily be relevant to the biological function of membrane proteins. An important line
of evidence that criticality plays a role in biological function has come from the tuning of the
GPMV critical point. For a system to be near a critical point, two parameters must be tuned,
those corresponding to t (temperature) and m (composition) of the (fixed-composition) Ising
model. In the extremely large space of lipid mixtures of varying composition, there are many
critical points—an n − 2-dimensional manifold in the n-dimensional space. However, there
is no generic reason that tuning the concentration of any given lipid corresponds to tuning
just t, or just m, or neither; general perturbations affect both t and m. Thus, it is somewhat
surprising that the cell arrives near a critical point if it constructs its membranes without
explicitly or implicitly tuning to the critical point, given that lipid composition is modulated
by a wide variety of perturbations. In other words, the fact that plasma membrane
composition is near-critical is unlikely to simply be a coincidence. Furthermore, at least in
Author Manuscript

certain cases, eukaryotic cells adapt to perturbations in ways that preserve the distance to the
critical point and corresponding physical properties. Zebrafish cells cultured at a range of
temperatures from 20°C to 32°C produce GPMVs with correspondingly altered Tc values
(82).

The concept of high susceptibility near a critical point is useful in interpreting recent single-
molecule and super-resolution studies documenting the partitioning of phase-marking probes
to protein clusters in intact cells (118, 119, 143). In these studies, antibodies are used to
cross-link a membrane component that prefers either the Lo or Ld phase, then the differential
partitioning of probes is monitored with respect to these domains. When proteins that prefer
the Lo phase are clustered, probes that also prefer Lo tend to be recruited, and those that
prefer Ld tend to be excluded. In contrast, when proteins that prefer the Ld phase are
clustered, probes that prefer Lo are excluded, and probes that prefer Ld are recruited. Similar
Author Manuscript

to experiments with vesicles adhered to supported membranes (80), the act of clustering a
protein or peptide biases the concentration of many components in ways that can be detected
when membranes have high susceptibility. In some cases, the extent of probe partitioning
approaches that observed in phase-separated vesicles (143), while in others the sorting of
components is much weaker (118). These differences could arise from differences in either
the coupling of protein clusters to membranes or the susceptibility of the membrane in
different experimental systems.

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 11

6. CRITICALITY AS IT RELATES TO BIOLOGICAL FUNCTION

Author Manuscript

Since the inception of the raft hypothesis, the study of the functional relevance of membrane
domains has focused on their ability to compartmentalize protein and lipid components so
that they can optimally function within biochemical networks (1). Critical phenomena are in
many ways consistent with this framework. A supercritical membrane contains domains
resembling ordered and disordered phases, and components that partition with the same
phase colocalize within these domains. The fluctuations are small and dynamic, consistent
with evolving descriptions of rafts over the decades (145–148), but fluctuations alone are not
an effective means to strongly colocalize or confine membrane components. This new reality
requires us to move beyond the simple mechanisms proposed in the early raft literature to
propose and test mechanisms that exploit the unique material properties of critical systems.
Several proposals are highlighted in Figure 4 and described in this section.
Author Manuscript

6.1. Interactions Between Proteins

Composition fluctuations can mediate forces between membrane proteins via a process
termed critical Casimir forces that was first described between conducting plates in vacuum
(149). In essence, proteins sense an effective attractive potential if they partition into the
same phase because coming into close proximity allows them to share the same local lipids,
as shown in Figure 4a (150, 151). In contrast, proteins that prefer different environments
sense an effective repulsion, because there is an energetic cost to mixing their local
environments. These potentials are weak (on the order of the thermal energy kBT) but have a
range given by the correlation length and the size of the protein or protein cluster. This range
is long compared to other interaction modes experienced by membrane proteins such as
curvature, electrostatics, and van der Waals potentials. Note that repulsion of components
that prefer different phases has a larger magnitude than does attraction between components
Author Manuscript

that prefer the same phase. Casimir forces may contribute to the stability of protein
assemblies, including phase-separated polymer droplets that assemble on membranes.
Casimir forces are also expected to alter biochemistry occurring at the membrane by
increasing or decreasing the rates at which the proteins encounter one another. It is tempting
to speculate that one functional role of palmitoylation, the posttranslational modification that
places a saturated acyl chain on proteins, is to tune the magnitude of these Casimir forces for
specific protein species.

6.2. Susceptibility to Receptor Clustering

The high susceptibility of a critical membrane provides a means for the cell to sense the
redistribution of a subset of membrane constituents by an external force (Figure 4b).
Clustering a membrane protein that prefers one phase biases the local lipid composition in
Author Manuscript

proportion to the heightened susceptibility of the system. This effect can impact biochemical
reactions that take place within these clusters, drastically altering the chemical steady state
of the system. We have studied this effect in the context of B cell–receptor (BCR) signaling
(118, 143). Here, the act of clustering the BCR or another ordered membrane component by
an extracellular ligand stabilizes an ordered domain that contains a higher local
concentration of kinase and a lower concentration of phosphatase than the membrane as a
whole. This establishes a local environment that favors receptor phosphorylation and

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 12

activation. In principle, this class of activation mechanism could contribute to a wide range
Author Manuscript

of signaling pathways that are initiated by receptor clustering at the cell surface. This type of
mechanism could also play a role in establishing biochemical environments in membrane
regions where components are organized by processes occurring at the inner plasma
membrane leaflet, such as at junctions between the endoplasmic reticulum and plasma
membrane (152), or at sites where scaffolding adaptor proteins are anchored to membranes,
such as in neuronal synapses (153).

6.3. Allosteric Regulation of Single Proteins

Beyond contributing to the organization of proteins, the size and stability of fluctuations in
the membrane can also impact the functioning of single proteins. One mechanism that has
been proposed requires that two conformational states of the protein in question have
different boundary lipid preferences for Lo or Ld lipids (144). If that is the case, then a
Author Manuscript

change in Tc differentially affects the free energies of the two conformational states.
Roughly, a spatially extended lipid preference carries a free energy cost that decreases near
Tc, so that a conformational state with a strong order preference becomes more probable
when fluctuations are large compared to the protein diameter. This model was proposed to
explain the striking correlations between Tc-altering effects and the anesthetic or anesthetic-
reversing potencies of a wide range of treatments, including short- and long-chain n-alcohols
and hydrostatic pressure (108, 109).

6.4. Tuning Binding of Allosteric Regulators

The chemical potential μ of a component is the thermodynamic parameter that controls the
proclivity of that component to enter or exit a system, for example, its availability to bind in
a binding pocket. Formally, the chemical potential is the increment of free energy to move
Author Manuscript

one particle into the system from a particle bath. Equivalently, the chemical activity α ∝
eμ/kT can be used. In an ideal gas or ideal dilute solution, the chemical potential has a simple
logarithmic relationship to concentration and is linear in temperature (so that activity is
proportional to concentration) and insensitive to the concentrations of other components
(154). However, a near-critical mixture is far from ideal: The critical point is precisely where
weak cooperative interactions between the many components lead to strong effects (124).
Therefore, we expect strong relationships between the chemical potentials of different
components, especially when those components modulate Tc.

Many transmembrane proteins have been shown to be modulated by binding to membrane

components, prominently including cholesterol (154, 155) and phosphatidylinositol lipids
(156) as well as many other signaling lipids (157). If the chemical potential of some of these
components is strongly modulated by the concentration changes of other components,
Author Manuscript

binding-site occupancy also varies, and we expect to see changes in protein functions that
depend on the binding of those components. Recent work by Ayuyan & Cohen (154) has
resulted in the development of sensitive methods for measuring and controlling the chemical
potential of cholesterol in the plasma membrane and found that cholesterol chemical
potential varies by ~2 kBT in different physiologically relevant cellular conditions. That
amount is certainly adequate to induce substantial changes in binding-site occupancy. Work
remains to be done to explore if these differences can be attributed in any way to the critical

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 13

phase transition, but we can speculate that perturbations that change membrane criticality
Author Manuscript

may act indirectly by impacting the activity of membrane components.

6.5. Criticality Coupled to Other Processes Describes a Broad Array of Raft Phenomena
The Ising universal critical phenomena are a good start for understanding membrane
heterogeneity, but they are also clearly insufficient to explain all phenomena. As stated in
Section 5, critical phenomena alone are not expected to give rise to regions of tight
clustering or confinement of proteins and lipids, as is sometimes attributed to membrane
domains. This said, the local membrane environment could impact the conformational states
sampled by membrane proteins in ways that facilitate binding through stronger protein-
binding sites. This type of synergistic effect could underlie a range of cholesterol-dependent
processes observed at the plasma membrane, including, for example, the transient pinning
observed in studies of membrane protein and lipid dynamics (158).
Author Manuscript

Another example in which there is potential for synergy between criticality and other
organizing principles relates to the active composite model proposed by Rao & Mayor (159).
This model posits that the plasma membrane interacts with a heterogeneous cortical actin
network composed of both active and passive components. The passive components largely
resemble quenched disorder, as described in Section 3. The active component is composed
of motor-driven short actin filaments that can actively drive certain membrane proteins and
lipids into close proximity, coupling across membrane leaflets. Considering this model in a
critical membrane provides a simple means to correlate domain structure across leaflets
without requiring strong interactions such as interdigitation, because the cooperativity
inherent in a phase transition can amplify weak couplings that may be present. Moreover,
the high susceptibility of a critical membrane allows it to robustly remodel when external
forces are applied, including those originating from the actin cortex.
Author Manuscript

More broadly, we envision that plasma membrane criticality is only one of several
organizing principles that contribute to plasma membrane functions. Interactions mediated
by curvature and electrostatics may be superimposed over those mediated via criticality to
define the plasma membrane interactome. There also may be interesting cross talk between
these various interaction modes. For example, studies have shown that the sorting of lipids
into curved membranes can be mediated by the binding of curvature-sensing proteins that
have preferences for one membrane phase (160). Proteins and peptides can also organize
lipids through electrostatics, which in turn can stabilize domains impacted by the
fluctuations of Lo and Ld lipids. The broader implications of this potential cross talk are
largely unexplored and could give rise to qualitatively new phenomena accessible to cell
membranes (161).
Author Manuscript

7. CONCLUDING REMARKS
While it has long been appreciated that plasma membrane lipids are capable of intriguing,
nonideal behaviors, much of the past literature is clouded by imperfect methods and an
incomplete conceptual framework with which to conceptualize experimental observations.
This backdrop led to controversial and often unphysical descriptions of lipid rafts. The past
decade or so has brought key advances, including membrane isolations that largely preserve

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 14

plasma membrane protein and lipid content and super-resolution imaging methods that do
Author Manuscript

not suffer from the same pitfalls that plagued early raft research. Alongside these advances,
the membrane community has begun to appreciate the rich phenomena that naturally occur
near miscibility critical points, many of which exhibit strong parallels with long-standing
observations in both the membrane biophysics and membrane biology literatures. Moving
forward, the challenges will be to isolate these effects to enable a definitive measurement of
the role of criticality in cell membranes and to explore how these immiscibility-mediated
interactions work alongside other physical and biochemical organizing principles to
contribute to the rich array of biological functions at the cell surface.

ACKNOWLEDGEMENTS:
We thank Sarah Shelby and Ben Machta for helpful discussions, and Aurelia Honerkamp-Smith for supplying the
raw data used to generate parts of Figure 3. The authors’ work is funded by grants from the National Science
Author Manuscript

Foundation (MCB1552439 and DMR1905600) and the National Institutes of Health (R01GM129347 and
R01GM110052).

LITERATURE CITED
1. Simons K, Ikonen E. 1997. Functional rafts in cell membranes. Nature 387(6633):569–72 [PubMed:
9177342]
2. Baumgart T, Hammond AT, Sengupta P, Hess ST, Holowka DA, et al. 2007. Large-scale fluid/fluid
phase separation of proteins and lipids in giant plasma membrane vesicles. PNAS 104(9):3165–70
[PubMed: 17360623]
3. Veatch SL, Keller SL. 2005. Seeing spots: complex phase behavior in simple membranes. Biochim.
Biophys. Acta Mol. Cell Res 1746(3):172–85
4. Oldfield E, Chapman D. 1971. Effects of cholesterol and cholesterol derivatives on hydrocarbon
chain mobility in lipids. Biochem. Biophys. Res. Commun 43(3):610–16 [PubMed: 4327446]
5. Oldfield E, Chapman D. 1972. Dynamics of lipids in membranes: heterogeneity and the role of
Author Manuscript

cholesterol. FEBS Lett 23(3):285–97 [PubMed: 11946637]

6. Engelman DM, Rothman JE. 1972. The planar organization of lecithin-cholesterol bilayers. J. Biol.
Chem 247(11):3694–97 [PubMed: 5030638]
7. Shimshick EJ, McConnell HM. 1973. Lateral phase separations in binary mixtures of cholesterol
and phospholipids. Biochem. Biophys. Res. Commun 53(2):446–51 [PubMed: 4352068]
8. Chapman D, Penkett SA. 1966. Nuclear magnetic resonance spectroscopic studies of the interaction
of phospholipids with cholesterol. Nature 211(5055):1304–5 [PubMed: 6008053]
9. Ladbrooke BD, Williams RM, Chapman D. 1968. Studies on lecithin-cholesterol-water interactions
by differential scanning calorimetry and X-ray diffraction. Biochim. Biophys. Acta Biomembr
150(3):333–40
10. Opella SJ, Yesinowski JP, Waugh JS. 1976. Nuclear magnetic resonance description of molecular
motion and phase separations of cholesterol in lecithin dispersions. PNAS 73(11):3812–15
[PubMed: 1069266]
11. Lentz BR, Barrow DA, Hoechli M. 1980. Cholesterol-phosphatidylcholine interactions in
Author Manuscript

multilamellar vesicles. Biochemistry 19(9):1943–54 [PubMed: 6892884]

12. Rubenstein JLR, Owicki JC, McConnell HM. 1980. Dynamic properties of binary mixtures of
phosphatidylcholines and cholesterol. Biochemistry 19(3):569–73 [PubMed: 6243951]
13. Recktenwald DJ, McConnell HM. 1981. Phase equilibriums in binary mixtures of
phosphatidylcholine and cholesterol. Biochemistry 20(15):4505–10 [PubMed: 6269591]
14. Alecio MR, Golan DE, Veatch WR, Rando RR. 1982. Use of a fluorescent cholesterol derivative to
measure lateral mobility of cholesterol in membranes. PNAS 79(17):5171–74. Corrigendum. 1982.
PNAS 79(24):7949 [PubMed: 6957857]

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 15

15. Hjort Ipsen J, Karlström G, Mourtisen OG, Wennerström H, Zuckermann MJ. 1987. Phase
equilibria in the phosphatidylcholine-cholesterol system. Biochim. Biophys. Acta Biomembr
Author Manuscript

905(1):162–72
16. Vist MR, Davis JH. 1990. Phase equilibria of cholesterol/dipalmitoylphosphatidylcholine mixtures:
deuterium nuclear magnetic resonance and differential scanning calorimetry. Biochemistry
29(2):451–64 [PubMed: 2302384]
17. Almeida PF, Vaz WL, Thompson TE. 1992. Lateral diffusion in the liquid phases of
dimyristoylphosphatidylcholine/cholesterol lipid bilayers: a free volume analysis. Biochemistry
31(29):6739–47 [PubMed: 1637810]
18. Huang TH, Lee CW, Das Gupta SK, Blume A, Griffin RG. 1993. A 13C and 2H nuclear magnetic
resonance study of phosphatidylcholine/cholesterol interactions: characterization of liquid–gel
phases. Biochemistry 32(48):13277–87 [PubMed: 8241184]
19. McMullen TPW, McElhaney RN. 1995. New aspects of the interaction of cholesterol with
dipalmitoylphosphatidylcholine bilayers as revealed by high-sensitivity differential scanning
calorimetry. Biochim. Biophys. Acta Biomembr 1234(1):90–98
20. Ahmed SN, Brown DA, London E. 1997. On the origin of sphingolipid/cholesterol-rich detergent-
Author Manuscript

insoluble cell membranes: physiological concentrations of cholesterol and sphingolipid induce

formation of a detergent-insoluble, liquid-ordered lipid phase in model membranes. Biochemistry
36(36):10944–53 [PubMed: 9283086]
21. Feigenson GW, Buboltz JT. 2001. Ternary phase diagram of dipalmitoyl-PC/dilauroyl-PC/
cholesterol: nanoscopic domain formation driven by cholesterol. Biophys. J 80(6):2775–88
[PubMed: 11371452]
22. van Meer G, Simons K. 1982. Viruses budding from either the apical or the basolateral plasma
membrane domain of MDCK cells have unique phospholipid compositions. EMBO J 1(7):847–52
[PubMed: 6329709]
23. Heiniger H-J, Kandutsch AA, Chen HW. 1976. Depletion of L-cell sterol depresses endocytosis.
Nature 263(5577):515–17 [PubMed: 972701]
24. Alderson JCE, Green C. 1975. Enrichment of lymphocytes with cholesterol and its effect on
lymphocyte activation. FEBS Lett 52(2):208–11 [PubMed: 1132474]
25. Lohr KM, Snyderman R. 1982. Amphotericin B alters the affinity and functional activity of the
oligopeptide chemotactic factor receptor on human polymorphonuclear leukocytes. J. Immunol
Author Manuscript

129(4):1594–99 [PubMed: 6286769]

26. Dahl C, Biemann HP, Dahl J. 1987. A protein kinase antigenically related to pp60v-src possibly
involved in yeast cell cycle control: positive in vivo regulation by sterol. PNAS 84(12):4012–16
[PubMed: 2438691]
27. Brown DA, Rose JK. 1992. Sorting of GPI-anchored proteins to glycolipid-enriched membrane
subdomains during transport to the apical cell surface. Cell 68(3):533–44 [PubMed: 1531449]
28. Fiedler K, Kobayashi T, Kurzchalia TV, Simons K. 1993. Glycosphingolipid-enriched, detergent-
insoluble complexes in protein sorting in epithelial cells. Biochemistry 32(25):6365–73 [PubMed:
8518282]
29. Harder T, Scheiffele P, Verkade P, Simons K. 1998. Lipid domain structure of the plasma
membrane revealed by patching of membrane components. J. Cell Biol 141(4):929–42 [PubMed:
9585412]
30. Ge M, Gidwani A, Brown HA, Holowka D, Baird B, Freed JH. 2003. Ordered and disordered
phases coexist in plasma membrane vesicles of RBL-2H3 mast cells. An ESR study. Biophys. J
Author Manuscript

85(2):1278–88 [PubMed: 12885671]

31. Gidwani A, Holowka D, Baird B. 2001. Fluorescence anisotropy measurements of lipid order in
plasma membranes and lipid rafts from RBL-2H3 mast cells. Biochemistry 40(41):12422–29
[PubMed: 11591163]
32. Kenworthy AK, Edidin M. 1998. Distribution of a glycosylphosphatidylinositol-anchored protein
at the apical surface of MDCK cells examined at a resolution of <100 Å using imaging
fluorescence resonance energy transfer. J. Cell Biol 142(1):69–84 [PubMed: 9660864]

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 16

33. Sheets ED, Holowka D, Baird B. 1999. Critical role for cholesterol in Lyn-mediated tyrosine
phosphorylation of FcεRI and their association with detergent-resistant membranes. J. Cell Biol
Author Manuscript

145(4):877–87 [PubMed: 10330413]

34. Pierce SK. 2002. Lipid rafts and B-cell activation. Nat. Rev. Immunol 2(2):nri726
35. Plowman SJ, Muncke C, Parton RG, Hancock JF. 2005. H-ras, K-ras, and inner plasma membrane
raft proteins operate in nanoclusters with differential dependence on the actin cytoskeleton. PNAS
102(43):15500–5 [PubMed: 16223883]
36. Brown DA, London E. 1998. Functions of lipid rafts in biological membranes. Annu. Rev. Cell
Dev. Biol 14:111–36 [PubMed: 9891780]
37. Munro S 2003. Lipid rafts: elusive or illusive? Cell 115(4):377–88 [PubMed: 14622593]
38. Dietrich C, Bagatolli LA, Volovyk ZN, Thompson NL, Levi M, et al. 2001. Lipid rafts
reconstituted in model membranes. Biophys. J 80(3):1417–28 [PubMed: 11222302]
39. Samsonov AV, Mihalyov I, Cohen FS. 2001. Characterization of cholesterol-sphingomyelin
domains and their dynamics in bilayer membranes. Biophys. J 81(3):1486–500 [PubMed:
11509362]
40. Veatch SL, Keller SL. 2002. Organization in lipid membranes containing cholesterol. Phys. Rev.
Author Manuscript

Lett 89(26):268101 [PubMed: 12484857]

41. Veatch SL, Gawrisch K, Keller SL. 2006. Closed-loop miscibility gap and quantitative tie-lines in
ternary membranes containing diphytanoyl PC. Biophys. J 90(12):4428–36 [PubMed: 16565062]
42. Veatch SL, Keller SL. 2003. Separation of liquid phases in giant vesicles of ternary mixtures of
phospholipids and cholesterol. Biophys. J 85(5):3074–83 [PubMed: 14581208]
43. Ionova IV, Livshits VA, Marsh D. 2012. Phase diagram of ternary cholesterol/
palmitoylsphingomyelin/palmitoyloleoyl-phosphatidylcholine mixtures: spin-label EPR study of
lipid-raft formation. Biophys. J 102(8):1856–65 [PubMed: 22768941]
44. Veatch SL, Keller SL. 2005. Miscibility phase diagrams of giant vesicles containing
sphingomyelin. Phys. Rev. Lett 94(14):148101 [PubMed: 15904115]
45. Veatch SL, Soubias O, Keller SL, Gawrisch K. 2007. Critical fluctuations in domain-forming lipid
mixtures. PNAS 104(45):17650–55 [PubMed: 17962417]
46. Zhao J, Wu J, Heberle FA, Mills TT, Klawitter P, et al. 2007. Phase studies of model
biomembranes: complex behavior of DSPC/DOPC/cholesterol. Biochim. Biophys. Acta
Author Manuscript

Biomembr 1768(11):2764–76
47. Petruzielo RS, Heberle FA, Drazba P, Katsaras J, Feigenson GW. 2013. Phase behavior and domain
size in sphingomyelin-containing lipid bilayers. Biochim. Biophys. Acta Biomembr
1828(4):1302–13
48. Connell SD, Heath G, Olmsted PD, Kisil A. 2013. Critical point fluctuations in supported lipid
membranes. Faraday Discuss 161:91–111 [PubMed: 23805740]
49. Khadka NK, Ho CS, Pan J. 2015. Macroscopic and nanoscopic heterogeneous structures in a three-
component lipid bilayer mixtures determined by atomic force microscopy. Langmuir
31(45):12417–25 [PubMed: 26506226]
50. Konyakhina TM, Wu J, Mastroianni JD, Heberle FA, Feigenson GW. 2013. Phase diagram of a 4-
component lipid mixture: DSPC/DOPC/POPC/chol. Biochim. Biophys. Acta Biomembr
1828(9):2204–14
51. Mills TT, Tristram-Nagle S, Heberle FA, Morales NF, Zhao J, et al. 2008. Liquid-liquid domains in
bilayers detected by wide angle X-ray scattering. Biophys. J 95(2):682–90 [PubMed: 18390623]
Author Manuscript

52. Konyakhina TM, Feigenson GW. 2016. Phase diagram of a polyunsaturated lipid mixture: brain
sphingomyelin/1-stearoyl-2-docosahexaenoyl-sn-glycero-3-phosphocholine/ cholesterol. Biochim.
Biophys. Acta Biomembr 1858(1):153–61
53. de Almeida RFM, Borst J, Fedorov A, Prieto M, Visser AJWG. 2007. Complexity of lipid domains
and rafts in giant unilamellar vesicles revealed by combining imaging and microscopic and
macroscopic time-resolved fluorescence. Biophys. J 93(2):539–53 [PubMed: 17449668]
54. Sibold J, Tewaag VE, Vagedes T, Mey I, Steinem C. 2020. Phase separation in pore-spanning
membranes induced by differences in surface adhesion. Phys. Chem. Chem. Phys 22(17):9308–15
[PubMed: 32309836]

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 17

55. Kahya N, Scherfeld D, Bacia K, Poolman B, Schwille P. 2003. Probing lipid mobility of raft-
exhibiting model membranes by fluorescence correlation spectroscopy. J. Biol. Chem
Author Manuscript

278(30):28109–15 [PubMed: 12736276]

56. Aufderhorst-Roberts A, Chandra U, Connell SD. 2017. Three-phase coexistence in lipid
membranes. Biophys. J 112(2):313–24 [PubMed: 28122217]
57. Sodt AJ, Sandar ML, Gawrisch K, Pastor RW, Lyman E. 2014. The molecular structure of the
liquid-ordered phase of lipid bilayers. J. Am. Chem. Soc 136(2):725–32 [PubMed: 24345334]
58. Sodt AJ, Pastor RW, Lyman E. 2015. Hexagonal substructure and hydrogen bonding in liquid-
ordered phases containing palmitoyl sphingomyelin. Biophys. J 109(5):948–55 [PubMed:
26331252]
59. Goñi FM, Alonso A, Bagatolli LA, Brown RE, Marsh D, et al. 2008. Phase diagrams of lipid
mixtures relevant to the study of membrane rafts. Biochim. Biophys. Acta Mol. Cell Biol. Lipids
1781(11):665–84
60. Heberle FA, Feigenson GW. 2011. Phase separation in lipid membranes. Cold Spring Harb.
Perspect. Biol 3(4):a004630 [PubMed: 21441593]
61. Ladbrooke BD, Chapman D. 1969. Thermal analysis of lipids, proteins and biological membranes
Author Manuscript

a review and summary of some recent studies. Chem. Phys. Lipids 3(4):304–56 [PubMed:
4905514]
62. Janiak MJ, Small DM, Shipley GG. 1979. Temperature and compositional dependence of the
structure of hydrated dimyristoyl lecithin. J. Biol. Chem 254(13):6068–78 [PubMed: 447695]
63. Heberle FA, Wu J, Goh SL, Petruzielo RS, Feigenson GW. 2010. Comparison of three ternary lipid
bilayer mixtures: FRET and ESR reveal nanodomains. Biophys. J 99(10):3309–18 [PubMed:
21081079]
64. Pathak P, London E. 2011. Measurement of lipid nanodomain (raft) formation and size in
sphingomyelin/POPC/cholesterol vesicles shows TX-100 and transmembrane helices increase
domain size by coalescing preexisting nanodomains but do not induce domain formation. Biophys.
J 101(10):2417–25 [PubMed: 22098740]
65. Pathak P, London E. 2015. The effect of membrane lipid composition on the formation of lipid
ultrananodomains. Biophys. J 109(8):1630–38 [PubMed: 26488654]
66. Konyakhina TM, Goh SL, Amazon J, Heberle FA, Wu J, Feigenson GW. 2011. Control of a
Author Manuscript

nanoscopic-to-macroscopic transition: modulated phases in four-component DSPC/DOPC/POPC/

chol giant unilamellar vesicles. Biophys. J 101(2):L8–10 [PubMed: 21767476]
67. Collado MI, Goñi FM, Alonso A, Marsh D. 2005. Domain formation in sphingomyelin/cholesterol
mixed membranes studied by spin-label electron spin resonance spectroscopy. Biochemistry
44(12):4911–18 [PubMed: 15779918]
68. de Almeida RFM, Fedorov A, Prieto M. 2003. Sphingomyelin/phosphatidylcholine/cholesterol
phase diagram: boundaries and composition of lipid rafts. Biophys. J 85(4):2406–16 [PubMed:
14507704]
69. Doktorova M, Heberle FA, Eicher B, Standaert RF, Katsaras J, et al. 2018. Preparation of
asymmetric phospholipid vesicles for use as cell membrane models. Nat. Protoc 13(9):2086–101
[PubMed: 30190552]
70. Lin Q, London E. 2015. Ordered raft domains induced by outer leaflet sphingomyelin in
cholesterol-rich asymmetric vesicles. Biophys. J 108(9):2212–22 [PubMed: 25954879]
71. Honerkamp-Smith AR, Cicuta P, Collins MD, Veatch SL, den Nijs M, et al. 2008. Line tensions,
correlation lengths, and critical exponents in lipid membranes near critical points. Biophys. J
Author Manuscript

95(1):236–46 [PubMed: 18424504]

72. Leibler S, Andelman D. 1987. Ordered and curved meso-structures in membranes and amphiphilic
films. J. Phys 48(11):2013–18
73. Palmieri B, Yamamoto T, Brewster RC, Safran SA. 2014. Line active molecules promote
inhomogeneous structures in membranes: theory, simulations and experiments. Adv. Colloid
Interface Sci 208:58–65 [PubMed: 24630340]
74. Brodbek L, Schmid F. 2016. Interplay of curvature-induced micro- and nanodomain structures in
multicomponent lipid bilayers. Int. J. Adv. Eng. Sci. Appl. Math 8(2):111–20

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 18

75. Cornell CE, Skinkle AD, He S, Levental I, Levental KR, Keller SL. 2018. Tuning length scales of
small domains in cell-derived membranes and synthetic model membranes. Biophys. J
Author Manuscript

115(4):690–701 [PubMed: 30049406]

76. Fridriksson EK, Shipkova PA, Sheets ED, Holowka D, Baird B, McLafferty FW. 1999.
Quantitative analysis of phospholipids in functionally important membrane domains from
RBL-2H3 mast cells using tandem high-resolution mass spectrometry. Biochemistry 38(25):8056–
63 [PubMed: 10387050]
77. Lingwood D, Ries J, Schwille P, Simons K. 2008. Plasma membranes are poised for activation of
raft phase coalescence at physiological temperature. PNAS 105(29):10005–10 [PubMed:
18621689]
78. Levental I, Grzybek M, Simons K. 2011. Raft domains of variable properties and compositions in
plasma membrane vesicles. PNAS 108(28):11411–16 [PubMed: 21709267]
79. Levental I, Byfield FJ, Chowdhury P, Gai F, Baumgart T, Janmey PA. 2009. Cholesterol-dependent
phase separation in cell-derived giant plasma-membrane vesicles. Biochem. J 424(2):163–67
[PubMed: 19811449]
80. Zhao J, Wu J, Veatch SL. 2013. Adhesion stabilizes robust lipid heterogeneity in supercritical
Author Manuscript

membranes at physiological temperature. Biophys. J 104(4):825–34 [PubMed: 23442961]

81. Veatch SL, Cicuta P, Sengupta P, Honerkamp-Smith A, Holowka D, Baird B. 2008. Critical
fluctuations in plasma membrane vesicles. ACS Chem. Biol 3(5):287–93 [PubMed: 18484709]
82. Burns M, Wisser K, Wu J, Levental I, Veatch SL. 2017. Miscibility transition temperature scales
with growth temperature in a zebrafish cell line. Biophys. J 113(6):1212–22 [PubMed: 28552311]
83. Gray EM, Díaz-Vázquez G, Veatch SL. 2015. Growth conditions and cell cycle phase modulate
phase transition temperatures in RBL-2H3 derived plasma membrane vesicles. PLOS ONE
10(9):e0137741 [PubMed: 26368288]
84. Levental KR, Lorent JH, Lin X, Skinkle AD, Surma MA, et al. 2016. Polyunsaturated lipids
regulate membrane domain stability by tuning membrane order. Biophys. J 110(8):1800–10
[PubMed: 27119640]
85. Levental KR, Surma MA, Skinkle AD, Lorent JH, Zhou Y, et al. 2017. ω−3 polyunsaturated fatty
acids direct differentiation of the membrane phenotype in mesenchymal stem cells to potentiate
osteogenesis. Sci. Adv 3(11):eaao1193 [PubMed: 29134198]
Author Manuscript

86. Cammarota E, Soriani C, Taub R, Morgan F, Sakai J, et al. 2020. Criticality of plasma membrane
lipids reflects activation state of macrophage cells. J. R. Soc. Interface 17(163):20190803
[PubMed: 32019470]
87. Symons JL, Cho K-J, Chang JT, Du G, Waxham MN, et al. 2020. Lipidomic atlas of mammalian
cell membranes reveals hierarchical variation induced by culture conditions, subcellular
membranes, and cell lineages. Soft Matter In press. 10.1039/D0SM00404A
88. Sezgin E, Levental I, Grzybek M, Schwarzmann G, Mueller V, et al. 2012. Partitioning, diffusion,
and ligand binding of raft lipid analogs in model and cellular plasma membranes. Biochim.
Biophys. Acta Biomembr 1818(7):1777–84
89. Kaiser H-J, Lingwood D, Levental I, Sampaio JL, Kalvodova L, et al. 2009. Order of lipid phases
in model and plasma membranes. PNAS 106(39):16645–50 [PubMed: 19805351]
90. Lorent JH, Diaz-Rohrer B, Lin X, Spring K, Gorfe AA, et al. 2017. Structural determinants and
functional consequences of protein affinity for membrane rafts. Nat. Commun 8:1219 [PubMed:
29089556]
91. Menon AK, Holowka D, Webb WW, Baird B. 1986. Cross-linking of receptor-bound IgE to
Author Manuscript

aggregates larger than dimers leads to rapid immobilization. J. Cell Biol 102(2):541–50 [PubMed:
2935543]
92. Machta BB, Papanikolaou S, Sethna JP, Veatch SL. 2011. Minimal model of plasma membrane
heterogeneity requires coupling cortical actin to criticality. Biophys. J 100(7):1668–77 [PubMed:
21463580]
93. Keller H, Lorizate M, Schwille P. 2009. PI(4,5)P2 degradation promotes the formation of
cytoskeleton-free model membrane systems. ChemPhysChem 10(16):2805–12 [PubMed:
19784973]

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 19

94. McLaughlin S, Wang J, Gambhir A, Murray D. 2002. PIP2 and proteins: interactions, organization,
and information flow. Annu. Rev. Biophys. Biomol. Struct 31:151–75 [PubMed: 11988466]
Author Manuscript

95. Skinkle AD, Levental KR, Levental I. 2020. Cell-derived plasma membrane vesicles are permeable
to hydrophilic macromolecules. Biophys. J 118(6):1292–300 [PubMed: 32053777]
96. Li G, Wang Q, Kakuda S, London E. 2020. Nanodomains can persist at physiologic temperature in
plasma membrane vesicles and be modulated by altering cell lipids. J. Lipid Res 61:758–66
[PubMed: 31964764]
97. Toulmay A, Prinz WA. 2013. Direct imaging reveals stable, micrometer-scale lipid domains that
segregate proteins in live cells. J. Cell Biol 202(1):35–44 [PubMed: 23836928]
98. Rayermann SP, Rayermann GE, Cornell CE, Merz AJ, Keller SL. 2017. Hallmarks of reversible
separation of living, unperturbed cell membranes into two liquid phases. Biophys. J 113(11):2425–
32 [PubMed: 29211996]
99. Lee I-H, Saha S, Polley A, Huang H, Mayor S, et al. 2015. Live cell plasma membranes do not
exhibit a miscibility phase transition over a wide range of temperatures. J. Phys. Chem. B
119(12):4450–59 [PubMed: 25747462]
100. Sevcsik E, Brameshuber M, Fölser M, Weghuber J, Honigmann A, Schütz GJ. 2015. GPI-
Author Manuscript

anchored proteins do not reside in ordered domains in the live cell plasma membrane. Nat.
Commun 6:6969 [PubMed: 25897971]
101. Levental I, Levental KR, Heberle FA. 2020. Lipid rafts: controversies resolved, mysteries remain.
Trends Cell Biol 30(5):341–53 [PubMed: 32302547]
102. Kusumi A, Fujiwara TK, Tsunoyama TA, Kasai RS, Liu A-A, et al. 2020. Defining raft domains
in the plasma membrane. Traffic 21(1):106–37 [PubMed: 31760668]
103. Castello-Serrano I, Lorent JH, Ippolito R, Levental KR, Levental I. 2020. Myelin-associated
MAL and PLP are unusual among multipass transmembrane proteins in preferring ordered
membrane domains. J. Phys. Chem. B 124(28):5930–39 [PubMed: 32436385]
104. Marinko JT, Kenworthy AK, Sanders CR. 2020. Peripheral myelin protein 22 preferentially
partitions into ordered phase membrane domains. PNAS 117(25):14168–77 [PubMed: 32513719]
105. Yang S-T, Kreutzberger AJB, Kiessling V, Ganser-Pornillos BK, White JM, Tamm LK. 2017.
HIV virions sense plasma membrane heterogeneity for cell entry. Sci. Adv 3(6):e1700338
[PubMed: 28782011]
Author Manuscript

106. Anderson RGW, Jacobson K. 2002. A role for lipid shells in targeting proteins to caveolae, rafts,
and other lipid domains. Science 296(5574):1821–25 [PubMed: 12052946]
107. Corradi V, Mendez-Villuendas E, Ingólfsson HI, Gu R-X, Siuda I, et al. 2018. Lipid–protein
interactions are unique fingerprints for membrane proteins. ACS Cent. Sci 4(6):709–17
[PubMed: 29974066]
108. Gray E, Karslake J, Machta BB, Veatch SL. 2013. Liquid general anesthetics lower critical
temperatures in plasma membrane vesicles. Biophys. J 105(12):2751–59 [PubMed: 24359747]
109. Machta BB, Gray E, Nouri M, McCarthy NLC, Gray EM, et al. 2016. Conditions that stabilize
membrane domains also antagonize n-alcohol anesthesia. Biophys. J 111(3):537–45 [PubMed:
27508437]
110. Grinstein G, Ma S. 1982. Roughening and lower critical dimension in the random-field Ising
model. Phys. Rev. Lett 49(9):685–88
111. Yethiraj A, Weisshaar JC. 2007. Why are lipid rafts not observed in vivo? Biophys. J 93(9):3113–
19 [PubMed: 17660324]
112. Honigmann A, Sadeghi S, Keller J, Hell SW, Eggeling C, Vink R. 2014. A lipid bound actin
Author Manuscript

meshwork organizes liquid phase separation in model membranes. eLife 3:e01671 [PubMed:
24642407]
113. Kwik J, Boyle S, Fooksman D, Margolis L, Sheetz MP, Edidin M. 2003. Membrane cholesterol,
lateral mobility, and the phosphatidylinositol 4,5-bisphosphate-dependent organization of cell
actin. PNAS 100(24):13964–69 [PubMed: 14612561]
114. Liu AP, Fletcher DA. 2006. Actin polymerization serves as a membrane domain switch in model
lipid bilayers. Biophys. J 91(11):4064–70 [PubMed: 16963509]

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 20

115. Shelby SA, Veatch SL, Holowka DA, Baird BA. 2016. Functional nanoscale coupling of Lyn
kinase with IgE-FcεRI is restricted by the actin cytoskeleton in early antigen-stimulated
Author Manuscript

signaling. Mol. Biol. Cell 27(22):3645–58 [PubMed: 27682583]

116. Gudheti MV, Curthoys NM, Gould TJ, Kim D, Gunewardene MS, et al. 2013. Actin mediates the
nanoscale membrane organization of the clustered membrane protein influenza hemagglutinin.
Biophys. J 104(10):2182–92 [PubMed: 23708358]
117. Chichili GR, Rodgers W. 2009. Cytoskeleton-membrane interactions in membrane raft structure.
Cell. Mol. Life Sci 66(14):2319–28 [PubMed: 19370312]
118. Stone MB, Shelby SA, Núñez MF, Wisser K, Veatch SL. 2017. Protein sorting by lipid phase-like
domains supports emergent signaling function in B lymphocyte plasma membranes. eLife
6:e19891 [PubMed: 28145867]
119. Kinoshita M, Suzuki KGN, Matsumori N, Takada M, Ano H, et al. 2017. Raft-based
sphingomyelin interactions revealed by new fluorescent sphingomyelin analogs. J. Cell Biol
216(4):1183–204 [PubMed: 28330937]
120. Allender DW, Giang H, Schick M. 2020. Model plasma membrane exhibits a microemulsion in
both leaves providing a foundation for “rafts.” Biophys. J 118(5):1019–31 [PubMed: 32023433]
Author Manuscript

121. Foret L 2005. A simple mechanism of raft formation in two-component fluid membranes.
Europhys. Lett 71(3):508–14
122. Gowrishankar K, Ghosh S, Saha S, Rumamol C, Mayor S, Rao M. 2012. Active remodeling of
cortical actin regulates spatiotemporal organization of cell surface molecules. Cell 149(6):1353–
67 [PubMed: 22682254]
123. Schmid F 2017. Physical mechanisms of micro- and nanodomain formation in multicomponent
lipid membranes. Biochim. Biophys. Acta Biomembr 1859(4):509–28 [PubMed: 27823927]
124. Goldenfeld N 2018. Lectures on Phase Transitions and the Renormalization Group Boca Raton,
FL:CRC Press
125. Cardy J 1996. Scaling and Renormalization in Statistical Physics Cambridge, UK: Cambridge
Univ. Press
126. Kardar M 2007. Statistical Physics of Fields Cambridge, UK: Cambridge Univ. Press
127. Chaikin PM, Lubensky TC. 2010. Principles of Condensed Matter Physics Cambridge, UK:
Cambridge Univ. Press
Author Manuscript

128. Honerkamp-Smith AR, Veatch SL, Keller SL. 2009. An introduction to critical points for
biophysicists; observations of compositional heterogeneity in lipid membranes. Biochim.
Biophys. Acta Biomembr 1788(1):53–63
129. Cagniard de la Tour C. 1822. Exposé de quelques résultats obtenu par l’action combinée de la
chaleur et de la compression sur certains liquides, tels que l’eau, l’alcool, l’éther sulfurique et
l’essence de pétrole rectifiée. Ann. Chim. Phys 21:127–32
130. van der Waals JD, Rowlinson JS. 2004. On the Continuity of the Gaseous and Liquid States
Mineola, NY: Dover
131. Ornstein L, Zernike F. 1918. Die linearen Dimensionen der Dichteschwankungen. Phys. Zeit
19:134–37
132. Guggenheim EA. 1945. The principle of corresponding states. J. Chem. Phys 13(7):253–61
133. Fisher ME. 1967. The theory of equilibrium critical phenomena. Rep. Prog. Phys 30(2):615–730.
Corrigendum. 1968. Rep. Prog. Phys. 31:418–20
134. Onsager L 1944. Crystal statistics. I. A two-dimensional model with an order-disorder transition.
Author Manuscript

Phys. Rev 65(3–4):117–49

135. Lee TD, Yang CN. 1952. Statistical theory of equations of state and phase transitions. II. Lattice
gas and Ising model. Phys. Rev 87(3):410–19
136. Widom B 1965. Equation of state in the neighborhood of the critical point. J. Chem. Phys
43(11):3898–905
137. Kadanoff LP. 1966. Scaling laws for Ising models near Tc. Phys. Phys. Fiz 2(6):263–72
138. Wilson KG. 1971. Renormalization group and critical phenomena. I. Renormalization group and
the Kadanoff scaling picture. Phys. Rev. B 4(9):3174–83

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 21

139. Mora T, Bialek W. 2011. Are biological systems poised at criticality? J. Stat. Phys 144(2):268–
302
Author Manuscript

140. Honerkamp-Smith AR, Machta BB, Keller SL. 2012. Experimental observations of dynamic
critical phenomena in a lipid membrane. Phys. Rev. Lett 108(26):265702 [PubMed: 23004996]
141. Frazier ML, Wright JR, Pokorny A, Almeida PFF. 2007. Investigation of domain formation in
sphingomyelin/cholesterol/POPC mixtures by fluorescence resonance energy transfer and Monte
Carlo simulations. Biophys. J 92(7):2422–33 [PubMed: 17218467]
142. Manley S, Horton MR, Lecszynski S, Gast AP. 2008. Sorting of streptavidin protein coats on
phase-separating model membranes. Biophys. J 95(5):2301–7 [PubMed: 18502811]
143. Núñez MF, Wisser K, Veatch SL. 2019. Synergistic factors control kinase-phosphatase
organization in B-cells engaged with supported bilayers. Mol. Biol. Cell 31(7):667–82 [PubMed:
31877064]
144. Kimchi O, Veatch SL, Machta BB. 2018. Ion channels can be allosterically regulated by
membrane domains near a de-mixing critical point. J. Gen. Physiol 150(12):1769–77 [PubMed:
30455180]
145. Lingwood D, Simons K. 2010. Lipid rafts as a membrane-organizing principle. Science 327:46–
Author Manuscript

50 [PubMed: 20044567]
146. Pike LJ. 2006. Rafts defined: a report on the Keystone symposium on lipid rafts and cell function.
J. Lipid Res 47:1597–98 [PubMed: 16645198]
147. Levental I, Veatch SL. 2016. The continuing mystery of lipid rafts. J. Mol. Biol 428(24, Part
A):4749–64 [PubMed: 27575334]
148. Sezgin E, Levental I, Mayor S, Eggeling C. 2017. The mystery of membrane organization:
composition, regulation and roles of lipid rafts. Nat. Rev. Mol. Cell Biol 18(6):361–74 [PubMed:
28356571]
149. Casimir HBG. 1948. On the attraction between two perfectly conducting plates. Indag. Math
10:261–63
150. Machta BB, Veatch SL, Sethna JP. 2012. Critical Casimir forces in cellular membranes. Phys.
Rev. Lett 109(13):138101 [PubMed: 23030121]
151. Reynwar BJ, Deserno M. 2008. Membrane composition-mediated protein-protein interactions.
Biointerphases 3(2):FA117–24 [PubMed: 20408660]
Author Manuscript

152. Saheki Y, De Camilli P. 2017. Endoplasmic reticulum-plasma membrane contact sites. Annu. Rev.
Biochem 86:659–84 [PubMed: 28301744]
153. Zeng M, Chen X, Guan D, Xu J, Wu H, et al. 2018. Reconstituted postsynaptic density as a
molecular platform for understanding synapse formation and plasticity. Cell 174(5):1172–87.e16
[PubMed: 30078712]
154. Ayuyan AG, Cohen FS. 2018. The chemical potential of plasma membrane cholesterol:
implications for cell biology. Biophys. J 114(4):904–18 [PubMed: 29490250]
155. Fantini J, Epand RM, Barrantes FJ. 2019. Cholesterol-recognition motifs in membrane proteins.
Adv. Exp. Med. Biol 1135:3–25 [PubMed: 31098808]
156. De Craene J-O, Bertazzi DL, Bär S, Friant S. 2017. Phosphoinositides, major actors in membrane
trafficking and lipid signaling pathways. Int. J. Mol. Sci 18(3):634
157. Shimizu T 2009. Lipid mediators in health and disease: enzymes and receptors as therapeutic
targets for the regulation of immunity and inflammation. Annu. Rev. Pharmacol. Toxicol 49:123–
50 [PubMed: 18834304]
Author Manuscript

158. Eggeling C, Ringemann C, Medda R, Schwarzmann G, Sandhoff K, et al. 2009. Direct

observation of the nanoscale dynamics of membrane lipids in a living cell. Nature
457(7233):1159–62 [PubMed: 19098897]
159. Rao M, Mayor S. 2014. Active organization of membrane constituents in living cells. Curr. Opin.
Cell Biol 29:126–32 [PubMed: 24975942]
160. Sorre B, Callan-Jones A, Manneville J-B, Nassoy P, Joanny J-F, et al. 2009. Curvature-driven
lipid sorting needs proximity to a demixing point and is aided by proteins. PNAS 106(14):5622–
26 [PubMed: 19304798]

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 22

161. Mitra ED, Whitehead SC, Holowka D, Baird B, Sethna JP. 2018. Computation of a theoretical
membrane phase diagram and the role of phase in lipid-raft-mediated protein organization. J.
Author Manuscript

Phys. Chem. B 122(13):3500–13 [PubMed: 29432021]

Author Manuscript
Author Manuscript
Author Manuscript

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 23
Author Manuscript
Author Manuscript

Figure 1.
Phase diagram of lipid mixtures. (a) Phase diagrams of three component mixtures (C1, C2,
and C3) are conventionally drawn on an equilateral triangle. The three vertices are pure
mixtures of each lipid component, points along the edges are binary mixtures, and points
within the triangle contain all three components. Compositions can be read by measuring the
perpendicular distance to each edge and adding the resulting percentages, which always sum
to 100%. Two examples are shown. (b) A qualitative phase diagram for ternary lipid
mixtures of high melting temperature (Tm) lipids, low Tm lipids, and cholesterol. Thick red
lines indicate the boundaries of liquid–solid (So) coexistence, and the thick blue line
Author Manuscript

represents the boundary of liquid-liquid coexistence of the liquid-disordered (Ld) and liquid-
ordered (Lo) phases. Points along this boundary also indicate the composition of coexisting
phases, and the specific compositions in coexistence are indicated by blue and red shaded
areas within binary coexistence regions. The purple triangle represents compositions that
exhibit all three phases in coexistence. The compositions of the three phases are indicated by
the three vertices of the triangle. The Ld–Lo coexistence region terminates at a miscibility
critical point along the high cholesterol edge that is indicated by an orange star.
Author Manuscript

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 24
Author Manuscript
Author Manuscript

Figure 2.
Phase diagrams of ternary lipid mixtures exhibit the same overall topology. Curves on the
Author Manuscript

phase diagrams indicate phase boundaries. In particular, the high cholesterol phase boundary
defines the boundary of the liquid-liquid miscibility gap in each case. Sample points and/or
deduced tie-line endpoints are indicated in some cases, and some diagrams label single
phases as Lα or Ld, Lo, and Lβ or So with abbreviations given below. (a) DPhPC/ DPPC/
Chol by fluorescence microscopy at 16°C. Panel a adapted from Reference 41 with
permission. (b) DOPC/DPPC/Chol by deuterium NMR spectroscopy. Panel b adapted from
Reference 45 with permission. (c) DOPC/DSPC/Chol by fluorescence microscopy and
FRET. Panel c adapted from Reference 46 with permission. (d) DPC/PSM/Chol by FRET,
neutron scattering, and DSC. Panel d adapted from Reference 47 with permission. (e)
POPC/PSM/Chol by EPR spectroscopy. Panel e adapted from Reference 43 with permission.
(f) DOPC/eggSM/Chol by atomic force microscopy at 28°C. Panel f adapted from Reference
48 with permission. Abbreviations: BSM, brain sphingomyelin; Chol, cholesterol; DOPC,
Author Manuscript

1,2-dioleoyl-sn-glycero-3-phosphocholine; DPC, dodecylphosphocholine; DPhPC,

diphytanoyl phosphatidylcholine; DPPC, dipalmitoylphosphatidylcholine; DSC, differential
scanning calorimetry; DSPC, 1,2-distearoyl-sn-glycero-3-phosphocholine; eggSM, egg
sphingomyelin; EPR, electron paramagnetic resonance; FRET, Förster resonance energy
transfer; Lα, lamellar liquid crystalline phase; Lβ, a lamellar gen phase; Ld, liquid-
disordered phase; Lo, liquid-ordered phase; NMR, nuclear magnetic resonance; POPC,1-

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 25

palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine; PSM, palmitoylsphingomyelin; So, solid

Author Manuscript

or gel phase.
Author Manuscript
Author Manuscript
Author Manuscript

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 26
Author Manuscript
Author Manuscript

Figure 3.
Critical systems exhibit universal features that extend beyond the two-phase region. (a)
Simulation snapshots of two lattice models. (Top) An Ising model at various reduced
temperatures t and compositions m, and (middle) a three-component model with interactions
designed to reproduce typical phase diagrams of ternary mixtures of Cholesterol (dark blue),
a low melting temperature (Tm) lipid (yellow) and a high Tm lipid (cyan) at fixed
temperature and various compositions. (Bottom) Model parameters used for (i)-(vi) in each
Author Manuscript

model are indicated on the respective phase diagram. Compositions of the three-component
model are chosen so that the effective reduced temperature t and effective magnetization m
of the model match the t and m of the corresponding Ising model. Miscibility gaps, tie-lines,
and the directions of t and m are shown on each schematic phase diagram. The regions that
correspond to liquid-ordered (Lo) and liquid-disordered (Ld) mixtures in ternary lipid
mixtures are also indicated. (b) Measurements of the divergence of correlation length ξ
versus t as the critical point is approached from the one-phase region. (Top) In the two
models from panel a. For the three-component model, t is the cholesterol (Chol) content
normalized by the Chol content at the critical point. (Middle) In GUVs and giant plasma
membrane vesicles (GPMVs) with varying temperature. Data from Reference 128. In each
case, the expected 2D Ising power law ξ ∝ t−1 is observed although the proportionality
constant differs, resulting in each data set being plotted with a different y-axis scale.
(Bottom) Representative GUV and GPMV images near the critical point.
Author Manuscript

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 27
Author Manuscript
Author Manuscript
Author Manuscript

Figure 4.
Four functional mechanisms primarily driven by liquid-ordered (Lo)–liquid-disordered (Ld)
phase partitioning in a near-critical membrane. Membrane proteins and other components
are characterized by how they partition into Lo–Ld domains, as shown here schematically.
The combination of the partitioning of various components confers to the systems particular
properties that can be used to drive biological function. a) Critical Casimir forces yield an
effective attraction between components with like order preference (blue-blue circles), and
an effective repulsion between components that prefer opposite lipid order (blue-magenta
circles). The strength of these interactions increases rapidly when t is reduced andξ becomes
large. (b) Clustering a protein that prefers Lo lipids (green circle) induces a distinct Lo
Author Manuscript

domain due to the high susceptibility of the membrane near the critical point. As a result,
other Lo-preferring proteins (blue circles) are recruited to the cluster, and Ld -preferring
proteins (magenta circles) are excluded. Similarly, an Ld domain can be stabilized by
clustering an Ld-preferring component. (c) The white shape is a large protein with two
conformations, pentagon or star. One conformation (pentagon) has no order preference, and
the other (star) prefers an Lo environment. The star conformation becomes more likely as t is
decreased, because there are large patches of Lo membrane that satisfy its preferred

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.
 Shaw et al. Page 28

boundary condition. (d) Changes in t also result in changes in the chemical potentials of
Author Manuscript

some membrane components, including components (red ovals) that can bind to a membrane
protein (orange squares) as an allosteric modulator. Therefore, a change in t can induce
differences in binding-site occupancy and the resulting distribution of protein states.
Author Manuscript
Author Manuscript
Author Manuscript

Annu Rev Phys Chem. Author manuscript; available in PMC 2022 April 20.