Cluster size regulates protein sorting in the
Nin ˜a C. Hartmana, Jeffrey A. Nyeb, and Jay T. Grovesa,c,d,1
Departments ofaChemistry andbChemical Engineering,cHoward Hughes Medical Institute, anddPhysical Biosciences and Materials Sciences Divisions,
Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720
Edited by Douglas T. Fearon, University of Cambridge, Cambridge, United Kingdom, and approved June 18, 2009 (received for review March 12, 2009)
During antigen recognition by T cells, signaling molecules on the T
cell engage ligands on the antigen-presenting cell and organize
into spatially distinctive patterns. These are collectively known as
the immunological synapse (IS). Causal relationships between
large-scale spatial organization and signal transduction have pre-
viously been established. Although it is known that receptor
mechanisms by which different proteins become spatially sorted
remain unclear. These sorting processes contribute a facet of signal
regulation; thus their elucidation is important for ultimately un-
derstanding signal transduction through the T cell receptor. Here
we investigate protein cluster size as a sorting mechanism using
the hybrid live T cell?supported membrane system. The clustering
state of the co-stimulatory molecule lymphocyte function-
associated antigen-1 (LFA-1) is modulated, either by direct anti-
body crosslinking or by crosslinking its intercellular adhesion
molecule-1 ligand on the supported bilayer. In a mature IS, native
LFA-1 generally localizes into a peripheral ring surrounding a
central T cell receptor cluster. Higher degrees of LFA-1 clustering,
induced by either method, result in progressively more central
localization, with the most clustered species fully relocated to the
central zone. These results demonstrate that cluster size directly
influences protein spatial positioning in the T cell IS. We discuss a
sorting mechanism, based on frictional coupling to the actin
cytoskeleton, that is consistent with these observations and is, in
principle, extendable to all cell surface proteins in the synapse.
actin ? mechanobiology ? membrane ? transport ? receptor
from molecular dimensions to the size of the cell itself. One
particularly dramatic example is the T cell immunological syn-
and an antigen-presenting cell (APC), within which a variety of
receptor and adhesion proteins engage their cognate ligands on
the apposed cell surface (1, 2). Before contact, no large-scale
organization is present on either cell surface. However, within
minutes of the initial encounter between an APC displaying
appropriate antigen and a complementary T cell, a highly
coordinated transport process is initiated that ultimately sorts
dozens of membrane proteins on both cell surfaces into a series
of concentric rings. This spatial pattern of proteins is not unique
to T cells; similar structures have also been observed between
natural killer cells and B cells and their target cells, as well as
between certain immune cells and neurons (3, 4). Recent work
has demonstrated the importance of protein spatial distribution
to both effector functions and as a signal regulatory mechanism
(5–7). However, the mechanism of IS formation is unclear.
In the case of the T cell-B cell interaction, the rapid spatial
sorting of cell membrane proteins into multiple specific regions
within the intercellular junction is driven from within the T cell
(8). Substitution of the B cell with a synthetic supported lipid
bilayer (SLB) displaying key proteins produces minimal differ-
ences in the antigen specificity or protein spatial organization
(2). The transport mechanism is postulated to be based on actin
espite their dynamic liquid nature, cell membranes exhibit
distinctive spatial organization on length scales ranging
T cell (8–10). Disruption of this actin flow using cytoskeletal
inhibitors blocks transport (8, 10). Associations of cell-surface
proteins with actin are thought to exist via adaptor proteins, such
as talin, which is known to couple lymphocyte function-
associated antigen-1 (LFA-1) to the actin cytoskeleton (11).
Similarly, ezrin has been reported to be an adaptor protein for
the T cell receptor (TCR) (12). Although simply coupling to
actin flow may be sufficient for protein transport, additional
regulation is required to achieve differential sorting of multiple
proteins within the IS.
Differential protein sorting is markedly illustrated by com-
parison of TCR and LFA-1, which become segregated into the
central supramolecular activation cluster (cSMAC) and the
surrounding peripheral supramolecular activation cluster
motion on the cell surface reveals that these 2 proteins move in
the same direction under the influence of centripetal F-actin
flow (9, 10, 13). The mechanism directing them to different
destinations, microns apart, remains mysterious. Before trans-
port, TCR engagement of the peptide-major histocompatibility
complex (pMHC) on the apposed membrane leads to the
formation of TCR clusters that contain approximately 100 TCR
molecules, which are subsequently transported to the cSMAC (9,
14). LFA-1 does not form such large-scale clusters upon binding
its ligand, intercellular adhesion molecule-1 (ICAM-1) (11, 15).
Thus, we speculate that differences in cluster size may contribute
to protein sorting.
In the present study, we manipulate the clustered state of
LFA-1 in primary murine T cells to directly investigate the effect
of protein cluster size on spatial sorting. Cluster size is increased
by crosslinking LFA-1 with a non-blocking bivalent monoclonal
antibody (Bi-X LFA-1). Crosslinking the primary antibody with
a secondary antibody to form a tetravalent crosslinker against
LFA-1 leads to a more clustered state (Tetra-X LFA-1). Thus,
2 degrees of clustering beyond the native state, which may
already be clustered to a small degree, are accessible. Compared
with non-crosslinked LFA-1, Bi-X LFA-1 is transported further
inward toward the inner zone of the pSMAC, immediately
surrounding the cSMAC. Crosslinking with a tetravalent agent
leads to localization of LFA-1 to the cSMAC along with TCR.
Use of bivalent and tetravalent crosslinkers against ICAM-1
induces similar alterations in the spatial position of LFA-
1:ICAM-1 complexes. Thus, increasing the clustering state of
LFA-1, either directly by using anti-LFA-1 antibodies or indi-
rectly by crosslinking its ICAM-1 ligand, biases its distribution
toward the synapse center. Moreover, spatial sorting of the
Author contributions: N.C.H., J.A.N., and J.T.G. designed research; N.C.H. and J.A.N. per-
formed research; N.C.H., J.A.N., and J.T.G. analyzed data; and N.C.H., J.A.N., and J.T.G.
wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
1To whom correspondence should be addressed. E-mail: email@example.com.
This article contains supporting information online at www.pnas.org/cgi/content/full/
August 4, 2009 ?
vol. 106 ?
no. 31 ?
Observation of LFA-1:Tetra-X ICAM-1 clusters in the cSMAC
composition. Additionally, topographic imaging of this altered
cSMAC region by reflection interference contrast microscopy
(RICM) indicates that membrane topography conforms to the
interleaved protein composition (Fig. 6 D and E). Although size
exclusion may be a factor in protein segregation over shorter
length scales, it is not the primary force behind cSMAC forma-
tion. A more recently proposed hypothesis suggests that cluster
stability may contribute a differentiating characteristic that
(10). In this model, sorting occurs because LFA-1 clusters need
the actin-deficient cSMAC while LFA-1 cannot. Our observa-
tion of externally crosslinked LFA-1 entering the cSMAC is
consistent with this hypothesis. However, the additional strati-
fication and exclusion we observe of non-crosslinked, active
LFA-1 by the species coupled to a bivalent crosslinker within the
pSMAC is more difficult to account for based on cluster stability
alone (Fig. 5H). We thus conclude that, although cluster stability
will certainly contribute to spatial sorting, differential stability is
not required for sorting. The predominant discrimination mech-
anism operating over most of the synaptic junction appears to be
based on overall strength of protein coupling to actin. A com-
pelling feature of the relatively simple frictional coupling mech-
anism is the ease with which it could be used by all proteins
within the IS.
Primary T cells directly harvested from splenocytes of first-generation AND ?
B10.BR transgenic mice were expanded to T cell blasts and maintained as
described (6, 19). This protocol is approved by the Animal Welfare and
Research Committee under Protocol 17702. Coverslips patterned with metal
lines were made as before (6, 13) and used as the bottom face of a tempera-
(3:1 H2SO4:H2O2), rinsed with H2O, and dried under a stream of N2 gas.
Histidine-tagged ICAM-1, ICAM-1-YFP fusion protein, and MHC Class II I-EK
were expressed and purified as before (17). Full-length and fabfragments of
H155 anti-LFA-1 and H57 anti-TCR antibodies were prepared by standard
by overnight incubation at 100 ?M at 37 °C in pH 4.5 citrate buffer. DOPC
(1,2-dioleoyl-sn-glycero-3-phosphocholine) bilayers comprised of 2 mol%
Ni2?-NTA-DOGS were prepared by standard methods. SLBs were incubated
with ICAM-1 and MHC for 1 h in Tris buffer. The flow cell was heated to 37 °C
and rinsed with 10 mL buffer before the addition of T cells. For crosslinking
experiments, T cells or ICAM-1 on the SLB were incubated for 20 min with the
crosslinking agents before cell interaction with the bilayer, as indicated.
Tetravalent crosslinkers were formed by incubating the primary antibodies
with the secondary antibodies for 20 min before incubation with the cells or
the SLB. Total internal reflection fluorescence microscopy (TIRF) images were
acquired on a Nikon TE2000 inverted microscope with a 100 ? 1.49 NA oil
immersion TIRF objective and a Cascade 512B EMCCD camera (Roper). Epiflu-
orescence images were taken on Nikon TE300 inverted microscope with a
100 ? 1.3 NA oil immersion objective and a CoolSnapHQ Camera (Photomet-
rics). Data were acquired with the MetaMorph software package (Molecular
for ImageJ software (33). A more detailed Materials and Methods section is
part of the SI Text.
ACKNOWLEDGMENTS. This work was supported by the Chemical Sciences,
Geosciences and Biosciences Division, Office of Basic Energy Sciences, of the
U.S. Department of Energy under Contract No. DE-AC03–76SF00098. Pat-
terned substrates were made by B.L. Jackson and R. Petit in the University of
California, Berkeley, Microlab and Lawrence Berkeley National Laboratory
Molecular Foundry. The authors thank M.B. Forstner, M. Davis, B. Lillemeier,
Boryana Manz, J.P. Hickey, A. Smoligovets, E. Liu, L. Mahadevan, R. Varma, T.
Starr, and M.L. Dustin for helpful discussions, reagents, and technical help.
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