Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA.
Phys Rev Lett. 2010 Jun 18;104(24):248101. doi: 10.1103/PhysRevLett.104.248101. Epub 2010 Jun 14.
Berg and Purcell [Biophys. J. 20, 193 (1977)] calculated how the accuracy of concentration sensing by single-celled organisms is limited by noise from the small number of counted molecules. Here we generalize their results to the sensing of concentration ramps, which is often the biologically relevant situation (e.g., during bacterial chemotaxis). We calculate lower bounds on the uncertainty of ramp sensing by three measurement devices: a single receptor, an absorbing sphere, and a monitoring sphere. We contrast two strategies, simple linear regression of the input signal versus maximum likelihood estimation, and show that the latter can be twice as accurate as the former. Finally, we consider biological implementations of these two strategies, and identify possible signatures that maximum likelihood estimation is implemented by real biological systems.
Berg 和 Purcell [Biophys. J. 20, 193 (1977)] 计算了单细胞生物通过少数被计数分子的噪声来限制浓度感应准确性的方式。在这里，我们将他们的结果推广到浓度斜坡的感应，这通常是生物学上相关的情况（例如，在细菌趋化性期间）。我们通过三种测量设备（单个受体、吸收球体和监测球体）计算了斜坡感应不确定性的下限。我们对比了两种策略，即输入信号与最大似然估计的简单线性回归，结果表明后者比前者准确两倍。最后，我们考虑了这两种策略的生物学实现，并确定了最大似然估计被实际生物系统实现的可能特征。
