Using plasma membrane nanoclusters to build better signaling circuits

Abstract

Cellular signaling pathways do not simply transmit data; they integrate and process signals to operate as switches, oscillators, logic gates, memory modules and many other types of control system. These complex processing capabilities enable cells to respond appropriately to the myriad of external cues that direct growth and development. The idea that crosstalk and feedback loops are used as control systems in biological signaling networks is well established. Signaling networks are also subject to exquisite spatial regulation, yet how spatial control modulates signal outputs is less well understood. Here, we explore the spatial organization of two different signal transduction circuits: receptor tyrosine kinase activation of the mitogen-activated protein kinase module; and glycosylphosphatidylinositol-anchored receptor activation of phospholipase C. With regards to these pathways, recent results have refocused attention on the crucial role of lipid rafts and plasma membrane nanodomains in signal transmission. We identify common design principals that highlight how the spatial organization of signal transduction circuits can be used as a fundamental control mechanism to modulate system outputs in vivo.

Figure 1

Ras and GPI-AR nanoclusters share many key biophysical properties. (a) K-Ras nanoclusters. Binding of EGF to the EGF receptor activates K-Ras, triggering the formation of Ras nanoclusters on the inner leaflet of the plasma membrane. These nanoclusters consist of active Ras (Ras*), the MAPK module (Raf, MEK and ERK), and scaffold proteins (galectin and KSR1). Ras nanoclusters have approximately seven Ras proteins, an average radius of 6–12 nm and short life-times (~0.4 s). SFVT and EM studies show that Raf is recruited to immobile Ras nanoclusters for activation. Formation of K-Ras nanoclusters requires an intact actin cytoskeleton but is lipid-raft-independent. During their brief life-times, each nanocluster generates a digital burst of active ERK (ERKpp). (b) GPI-AR nanoclusters. Cross-linking of GPI-ARs by ligands (e.g. the cross-linking of GPI-AR CD59 by C8) generates GPI-AR nanoclusters of approximately six GPI-AR molecules on the outer leaflet of the plasma membrane. CD59 GPI-AR nanoclusters recruit single molecules of Gαi2 and Lyn to the inner leaflet of the plasma membrane underneath the CD59 nanocluster. This is achieved through both protein–protein and lipid-raft interaction, as shown by the fact that GPI-AR clustering is cholesterol-dependent. Gαi2 activates Lyn, thereby inducing the binding of CD59 nanocluster to F-actin, and promoting brief (~0.6 s) immobilization of the GPI-AR nanocluster. PLCγ2 molecules are transiently recruited to immobilized CD59 clusters to generate a digital burst of inositol-(1,4,5) triphosphate (IP3). The similarity between the Ras and GPI-AR nanocluster systems is striking. Both Ras and GPI-AR systems contain few molecules (approximately seven molecules of Ras, and approximately six molecules of CD59), both systems have short lifespans (Ras nanoclusters ~0.4s, immobilized GPI-AR nanocluster ~0.6s) and both systems are active only when immobilized on the membrane. Most importantly, both systems generate digital bursts of output.

Figure 2

EGF signal transduction is digitized across the plasma membrane. (a) Ras nanoclusters operate as high-gain amplifiers generating high or maximal levels of ERKpp output over a wide range of Raf kinase inputs. The figure shows how signal output varies against input as amplifier gain is increased. At the highest level of gain –the level at which Ras nanoclusters operate – nanocluster output closely approximates a switch with a very low activation threshold. (b) Because Ras nanoclusters function as high-gain amplifiers, during their brief existence they generate maximal ERKpp output to generate a digital burst of ERKpp that is released into the cytosol. In this way, the plasma membrane functions as an analog-to-digital converter (ADC), with the digital bursts from nanoclusters operating as the discrete quantal units. (c) The analog EGF input present in the extracellular matrix (ECM) activates the EGF receptor, which triggers the formation of several Ras nanoclusters. This formation, which occurs through an unknown mechanism, is directly proportional to the external EGF concentration. (d) As the output of each nanocluster is dumped into the cytoplasm, the digital pulses from each nanocluster are summed to give a final cellular analog ERKpp output. In this way, the cytoplasm reverses the digital conversion that occurred at the plasma membrane, and thus it functions as a digital-to-analog converter (DAC). This linear, analog–digital–analog circuit relay generates the robust, high-fidelity signal transmission that occurs across the plasma membrane in vivo.

Figure 3

Nanoclusters make ideal components to build high-fidelity biological circuits. The fidelity of signal transfer in a linear ADC is a function of two variables: the sampling precision (i.e. the number of increments between zero and maxim) and the sampling rate (i.e. how many samples are taken over time). Panels (a) compare the fidelity of low versus high sampling-precision. With low sampling-precision [upper panel (a)] (sampling precision is represented by dotted lines), the output curve (blue) is a poor representation of the input signal (red curve). With higher sampling-precision, the output curve closely matches the input signal [lower panel (a)]. Some mammalian cells have up to 40 000 Ras nanoclusters on the inner leaflet of the plasma membrane, and thus the resolution between zero and maximal input for these systems is incredibly high in vivo. (b) The ability to accurately convey a continuous input over time is a function of sampling rate. The fidelity of signal output (blue curve) from a continuous input (red curve) for 1 min using a low sampling rate (4 times/min) is poor [upper panel (b)]. By increasing the sampling rate to 20 times/min [lower panel (b)], the fidelity of the output is significantly increased. Both Ras and GPI-AR nanoclusters sample their respective input signals >100 times/minute. Thus, it is the combination of high sampling-precision and high sampling-rates that enables biological circuits incorporating nanocluster components to generate high-fidelity signal transmission in vivo.

Figure 4

Nanoclusters simplify signal transduction circuits. Many biological events take place very rapidly; for example, high-frequency oscillations (a). If the life-times of the individual signaling components are longer than the oscillatory frequency, then oscillations, or any other rapid change, are impossible to generate (b). The speed of the output change is therefore limited by the life-times of the individual signaling components. By contrast, if the signaling components are relatively short-lived, then their individual quantal pulses can be simply added up to generate the bulk, system output (c). The advantage of this system is that it eliminates the need for complex integration while allowing for the rapid changes of output. It is the elimination of complex integration from transduction circuits, the ability to transmit rapid change, the facility for high-fidelity signal transmission and the inherent robustness of nanoswitches that makes them ideal components for biological circuits.