Data analysis algorithm for high throughput enzymatic oxygen consumption assays based on quenched-fluorescence detection

  • Vladimir I. Ogurtsov
  • , James Hynes
  • , Yvonne Will
  • , Dmitri B. Papkovsky

Research output: Contribution to journalArticlepeer-review

Abstract

A simple and efficient data analysis algorithm for biological oxygen consumption assays based on quenched-fluorescence oxygen sensing is presented. The algorithm allows the linearization of raw fluorescence profiles in transformed co-ordinates thereby facilitating data processing and generating accurate results for multiple samples analysed in parallel on a fluorescence reader. This approach provides stability with respect to the uncertainty of the reaction start time, it allows on-the-flight determination of kinetic parameters by pairwise reading method, and additional filtration of raw data leading to improved accuracy. This methodology was validated with three independent sets of data from the analysis of activity and inhibition of isolated rat liver mitochondria representing a complex oxygen-dependent enzymatic system. It demonstrated good performance allowing accurate determination of enzymatic parameters from simple linear regression analysis (R2 as high as 0.999), good correlation with simulated data and general convenience.

Original languageEnglish
Pages (from-to)581-590
Number of pages10
JournalSensors and Actuators B: Chemical
Volume129
Issue number2
DOIs
Publication statusPublished - 22 Feb 2008

Keywords

  • Data analysis algorithms
  • Enzymatic assays
  • High throughput screening
  • Quenched-fluorescence oxygen sensing

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