Unknown

Dataset Information

0

The SensorOverlord predicts the accuracy of measurements with ratiometric biosensors.


ABSTRACT: Two-state ratiometric biosensors change conformation and spectral properties in response to specific biochemical inputs. Much effort over the past two decades has been devoted to engineering biosensors specific for ions, nucleotides, amino acids, and biochemical potentials. The utility of these biosensors is diminished by empirical errors in fluorescence-ratio signal measurement, which reduce the range of input values biosensors can measure accurately. Here, we present a formal framework and a web-based tool, the SensorOverlord, that predicts the input range of two-state ratiometric biosensors given the experimental error in measuring their signal. We demonstrate the utility of this tool by predicting the range of values that can be measured accurately by biosensors that detect pH, NAD+, NADH, NADPH, histidine, and glutathione redox potential. The SensorOverlord enables users to compare the predicted accuracy of biochemical measurements made with different biosensors, and subsequently select biosensors that are best suited for their experimental needs.

SUBMITTER: Stanley JA 

PROVIDER: S-EPMC7544824 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

altmetric image

Publications

The SensorOverlord predicts the accuracy of measurements with ratiometric biosensors.

Stanley Julian A JA   Johnsen Sean B SB   Apfeld Javier J  

Scientific reports 20201008 1


Two-state ratiometric biosensors change conformation and spectral properties in response to specific biochemical inputs. Much effort over the past two decades has been devoted to engineering biosensors specific for ions, nucleotides, amino acids, and biochemical potentials. The utility of these biosensors is diminished by empirical errors in fluorescence-ratio signal measurement, which reduce the range of input values biosensors can measure accurately. Here, we present a formal framework and a w  ...[more]

Similar Datasets

| S-EPMC5603529 | biostudies-literature
| S-EPMC4344385 | biostudies-literature
| S-EPMC6037473 | biostudies-literature
| S-EPMC3166341 | biostudies-literature
| S-EPMC7486618 | biostudies-literature
| S-EPMC5585204 | biostudies-literature
| S-EPMC5517509 | biostudies-literature
| S-EPMC9763403 | biostudies-literature
| S-EPMC6721044 | biostudies-literature
| S-EPMC6792296 | biostudies-literature