Looking Beyond the Event Horizon:Modeling the Synapse

by Yves Konigshofer

Introduction• Cell-to-cell (e.g. T cell / APC) contact sometimes leads to

the formation of a synapse

• Over the past few years, more and more molecules have been identified that accumulate at a synapse

• TCR, MHC, LFA-1, ICAM-1, CD2, CD4, CD8, CD28, etc.

• Different patterns have resulted from the accumulation of these molecules

• Different explanations have been given for the shapes and the significances of these patterns

Why Simulate Cell-to-Cell Contact?

• To determine whether or not the observed accumulation patterns at a synapse are compatible with the explanations for their generation

• To determine what pieces of the puzzle are currently missing but are needed to properly characterize and understand the events that shape cell-to-cell contact and lead to the formation of a synapse

The Representation of Cells, Molecules, and the Synapse

• There are two cells that touch each other in a contact area (synapse)

• These cells are represented as one or more spheres• Each sphere has a representation of the contact area• There are one or more different types of molecules• Each type of molecule is found on one particular

sphere

• Definable amounts of molecules of each type are found on the surfaces of the spheres

• Only those molecules that are found inside of the contact area interact with each other

The Contact Area• There is only one contact area• This contact area is divided into

rings and sectors, which give rise to regions

• Most calculations are done on a per-region basis

• Molecules interact with other molecules that are found inside of the same region

• Bound molecules cannot leave the contact area while they are still bound

Release, Diffusion, and Binding• Release is calculated using the koff values for the

dimers

• Diffusion is calculated using the diffusion coefficient, D, for the molecule or dimer

• Binding is calculated using the 2D and 3D kon values for the molecules trying to bind inside of particular regions, their concentrations inside of these regions, and the distance between the opposing membranes

Defining the Characteristics of Different Types of Molecules

Optimal binding distances, bound and free diffusion coefficients, bound and free diffusion biases, bound and free optimal region entry heights, color, on-rates for binding, off-rates for release, confinement distances, binding times for endocytosis, transit times until exocytosis, modifiers for many of these parameters, etc.

Three Major Types of Binding

A) One molecule is always immobile B) 2x reduction in D after binding C) 200x reduction in D after binding

The Event Horizon

0123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179degrees from the middle of the contact area

rela

tive

num

ber o

f mol

ecul

es

Modeling the Effects of LFA-1 (CD11a/CD18) Activation

• LFA-1• an integrin (aLb2)• binds ICAM-1• essentially immobile when cells are resting

• D ≈ 2.3E-15 m2/s (Kucik et al.)• mobile when cells are activated

• D ≈ 2.9E-14 m2/s• its affinity for ICAM-1 changes after activation (Lollo

et al. and Tominaga et al.)• activated kon ≈ 2.0E+5 M-1s-1; koff ≈ 0.1 s-1

• resting kon ≈ 3.7E+2 M-1s-1; koff ≈ 0.033 s-1

LFA-1 Activation and ICAM-1 Binding

Resting Activated

Modeling Interactions Between Activated T cells and APCs

• Some Assumptions• The TCR moves preferentially towards the synapse• The TCR is removed after being bound for 10 seconds• The molecules have the following diffusion coefficients:

• TCR : 1.0E-14 m2/s (no reported values)• MHC : 2.0E-14 m2/s (large range of

values)• LFA-1 : 2.9E-14 m2/s (stimulated cells)• ICAM-1 : 2.0E-14 m2/s (no reported values)

• The cells membranes are between 40 and 80 nm apart• TCR / MHC interact optimally at 15 nm• LFA / ICAM-1 interact optimally at 40 nm

T cell Activation(random peptide)

Large Molecule

TCR MHC LFA-1 ICAM-1

TCR / MHC: kon = 1.0E+3 M-1s-1, koff = 2.0 s-1

T cell Activation?(random diffusion)

Large Molecule

TCR MHC LFA-1 ICAM-1

Observations and Conclusions• When molecules bind each other on opposing cells, the

standard result is the formation of a ring• koff is important, kon is not

• getting molecules not to bind is difficult• Diffusion coefficients of molecules need to be measured

for the types of cells being simulated• Directed as opposed to random diffusion is needed for

the formation of the central TCR / MHC cluster during T cell / APC interactions

• Lots of parameters still need to be measured to accurately model cell-to-cell interactions

Acknowledgements• Chien lab• Davis lab

• Cenk Sumen• Lawren Wu

• Duke University• Jun Yang

The Simulation

T cell Activation(strong agonist peptide)

Large Molecule

TCR MHC LFA-1 ICAM-1

TCR / MHC: kon = 1.57E+3 M-1s-1, koff = 0.063 s-1

(2B4 MCC/IEk)