Fundamental trade-offs between information flow in single cells and cellular populations

Abstract

Signal transduction networks allow eukaryotic cells to make decisions based on information about intracellular state and the environment. Biochemical noise significantly diminishes the fidelity of signaling: networks examined to date seem to transmit less than 1 bit of information. It is unclear how networks that control critical cell-fate decisions (e.g., cell division and apoptosis) can function with such low levels of information transfer. Here, we use theory, experiments, and numerical analysis to demonstrate an inherent trade-off between the information transferred in individual cells and the information available to control population-level responses. Noise in receptor-mediated apoptosis reduces information transfer to approximately 1 bit at the single-cell level but allows 3-4 bits of information to be transmitted at the population level. For processes such as eukaryotic chemotaxis, in which single cells are the functional unit, we find high levels of information transmission at a single-cell level. Thus, low levels of information transfer are unlikely to represent a physical limit. Instead, we propose that signaling networks exploit noise at the single-cell level to increase population-level information transfer, allowing extracellular ligands, whose levels are also subject to noise, to incrementally regulate phenotypic changes. This is particularly critical for discrete changes in fate (e.g., life vs. death) for which the key variable is the fraction of cells engaged. Our findings provide a framework for rationalizing the high levels of noise in metazoan signaling networks and have implications for the development of drugs that target these networks in the treatment of cancer and other diseases.

Single-cell information analysis reveals small intra- and large intercellular variations increase cellular information capacity

“…Analysis of 45 a single-cell channel from the Ca 2+ response in HEK293 cells stimulated with acetylcholine repetitively at various concentrations enabled the calculation of the channel capacity, which is the maximal amount of information that the channel can transfer, at 2 bits (21). This 2-bit channel capacity is higher than the 1-bit capacity calculated for cell-population channels in other studies (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20). With organs, such as skeletal muscle, functioning not as a single cell, but as the sum of single cells, a multiple-cell channel should correspond to the physiological 5 communication channel.…”

“…For a cell-population channel, the mutual information relating stimulation intensity and cellular response contains only 1 bit information (Fig. 1C, left, table S1) (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20), indicating that the cellular response can distinguish only the two conditions of 20 stimulation: the presence or absence of stimulation. Physiologically, cellular responses are often gradually controlled by the intensity of stimulation, meaning that a cellular response can encode more than 1 bit information.…”

Entangled signal pathways can both control expression stability and induce stochastic focusing

“…We point out that the EM essentially belongs to the frequency modulation (FM) strategy since it regulates the gene expression (refer to (Eqn 1)) by modulating the off-state dwell time, whereas the IM to the amplitude modulation (AM) strategy since it regulates the gene expression by changing the on-state dwell time [44][45][46][47][48]. The combination of the results in Fig.…”

The impact of non-genetic heterogeneity on cancer cell death

“…For example, analysis of the signalling pathway activated by TRAIL suggests that limits on the fidelity of information transmission through the pathway are not imposed by biological or physical limitations, but rather may be necessary to allow graded cell death responses in a population (Suderman et al 2017). …”