Noise filtering tradeoffs in spatial gradient sensing and cell polarization response

<p>Abstract</p> <p>Background</p> <p>Cells sense chemical spatial gradients and respond by polarizing internal components. This process can be disrupted by gradient noise caused by fluctuations in chemical concentration.</p> <p>Results</p> <p>We investigated how external gradient noise affects spatial sensing and response focusing on noise-filtering and the resultant tradeoffs. First, using a coarse-grained mathematical model of gradient-sensing and cell polarity, we characterized three negative consequences of noise: Inhibition of the extent of polarization, degradation of directional accuracy, and production of a noisy output polarization. Next, we explored filtering strategies and discovered that a combination of positive feedback, multiple signaling stages, and time-averaging produced good results. There was an important tradeoff, however, because filtering resulted in slower polarization. Simulations demonstrated that a two-stage filter-amplifier resulted in a balanced outcome. Then, we analyzed the effect of noise on a mechanistic model of yeast cell polarization in response to gradients of mating pheromone. This analysis showed that yeast cells likely also combine the above three filtering mechanisms into a filter-amplifier structure to achieve impressive spatial-noise tolerance, but with the consequence of a slow response time. Further investigation of the amplifier architecture revealed two positive feedback loops, a fast inner and a slow outer, both of which contributed to noise-tolerant polarization. This model also made specific predictions about how orientation performance depended upon the ratio between the gradient slope (signal) and the noise variance. To test these predictions, we performed microfluidics experiments measuring the ability of yeast cells to orient to shallow gradients of mating pheromone. The results of these experiments agreed well with the modeling predictions, demonstrating that yeast cells can sense gradients shallower than 0.1% μm^-1, approximately a single receptor-ligand molecule difference between front and back, on par with motile eukaryotic cells.</p> <p>Conclusions</p> <p>Spatial noise impedes the extent, accuracy, and smoothness of cell polarization. A combined filtering strategy implemented by a filter-amplifier architecture with slow dynamics was effective. Modeling and experimental data suggest that yeast cells employ these elaborate mechanisms to filter gradient noise resulting in a slow but relatively accurate polarization response.</p

Robust Spatial Sensing of Mating Pheromone Gradients by Yeast Cells

Projecting or moving up a chemical gradient is a universal behavior of living organisms. We tested the ability of S. cerevisiae a-cells to sense and respond to spatial gradients of the mating pheromone α-factor produced in a microfluidics chamber; the focus was on bar1Δ strains, which do not degrade the pheromone input. The yeast cells exhibited good accuracy with the mating projection typically pointing in the correct direction up the gradient (∼80% under certain conditions), excellent sensitivity to shallow gradients, and broad dynamic range so that gradient-sensing was relatively robust over a 1000-fold range of average α-factor concentrations. Optimal directional sensing occurred at lower concentrations (5 nM) close to the Kd of the receptor and with steeper gradient slopes. Pheromone supersensitive mutations (sst2Δ and ste2300Δ) that disrupt the down-regulation of heterotrimeric G-protein signaling caused defects in both sensing and response. Interestingly, yeast cells employed adaptive mechanisms to increase the robustness of the process including filamentous growth (i.e. directional distal budding) up the gradient at low pheromone concentrations, bending of the projection to be more aligned with the gradient, and forming a more accurate second projection when the first projection was in the wrong direction. Finally, the cells were able to amplify a shallow external gradient signal of α-factor to produce a dramatic polarization of signaling proteins at the front of the cell. Mathematical modeling revealed insights into the mechanism of this amplification and how the supersensitive mutants can disrupt accurate polarization. Together, these data help to specify and elucidate the abilities of yeast cells to sense and respond to spatial gradients of pheromone

Vernier Ring Based Pre-bond Through Silicon Vias Test in 3D ICs

Defects in TSV will lead to variations in the propagation delay of the net connected to the faulty TSV. A non-invasive Vernier Ring based method for TSV pre-bond testing is proposed to detect resistive open and leakage faults. TSVs are used as capacitive loads of their driving gates, then time interval compared with the fault-free TSVs will be detected. The time interval can be detected with picosecond level resolution, and digitized into a digital code to compare with an expected value of fault-free. Experiments on fault detection are presented through HSPICE simulations using realistic models for a 45 nm CMOS technology. The results show the effectiveness in the detection of time interval 10 ps, resistive open defects 0.2 kΩ above and equivalent leakage resistance less than 18 MΩ. Compared with existing methods, detection precision, area overhead, and test time are effectively improved, furthermore, the fault degree can be digitalized into digital code

Effect of different rice planting methods on the water, energy and carbon footprints of subsequent wheat

The rice-wheat rotation system is an important planting system in the middle and lower reaches of the Yangtze River. Studies on the effects of different rice planting methods on the water, energy, and carbon footprints of subsequent wheat have rarely been reported. In this study, the effects of different rice cultivation practices on the water, energy, and carbon footprints of subsequent wheat were investigated among different rice-wheat rotation systems including dry direct-seeded rice (DSR)-wheat rotation, wet direct-seeded rice (WSR)-wheat rotation and transplanted rice(TPR)-wheat rotation. Results showed that the yield of wheat after DSR was 8,552 kg ha−1, which was 14.61 and 4.72% higher than the yields after WSR and TPR, respectively. In addition, the water and carbon footprints of wheat after DSR were lower than those after WSR and TPR, while its energy and carbon production efficiencies and net ecosystem economic benefits were higher than those after WSR and TPR. Notably, the use of fertilizers and fuel are the two major contributors to the high energy inputs and greenhouse gas emissions in wheat production. In summary, wheat after DSR has higher ecological and economic benefits, and we recommend that it be promoted as the preferred wheat planting model in rice-wheat rotation areas

Modeling yeast cell polarization induced by pheromone gradients

Yeast cells respond to spatial gradients of mating pheromones by polarizing and projecting up the gradient toward the source. It is thought that they employ a spatial sensing mechanism in which the cell compares the concentration of pheromone at different points on the cell surface and determines the maximum point, where the projection forms. Here we constructed the first spatial mathematical model of the yeast pheromone response that describes the dynamics of the heterotrimeric and Cdc42p G-protein cycles, which are linked in a cascade. Two key performance objectives of this system are (1) amplification-converting a shallow external gradient of ligand to a steep internal gradient of protein components and (2) tracking-following changes in gradient direction. We used simulations to investigate amplification mechanisms that allow tracking. We identified specific strategies for regulating the spatial dynamics of the protein components (i.e. their changing location in the cell) that would enable the cell to achieve both objectives