Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations

Stephanie A Nummer; Alexandra J Weeden; Chloe Shaw; Brenda K Snyder; Thomas B Bridgeman; Song S Qian

doi:10.1016/j.mex.2018.03.011

Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations

MethodsX. 2018 Apr 12:5:304-311. doi: 10.1016/j.mex.2018.03.011. eCollection 2018.

Authors

Stephanie A Nummer¹, Alexandra J Weeden², Chloe Shaw³, Brenda K Snyder⁴, Thomas B Bridgeman^{1

4}, Song S Qian¹

Affiliations

¹ Department of Environmental Sciences, University of Toledo, 2801 W. Bancroft Street, MS# 604, Toledo, OH 43606-3390, USA.
² Environmental Science Major, Hanover College, Hanover, IN 47243, USA.
³ Environmental Studies Major, Gustavus Adolphus College, Sait Peter, MN 56082, USA.
⁴ The Lake Erie Center, The University of Toledo, Oregon, Toledo, OH 43616, USA.

Abstract

This study is aimed at exploring the optimal ELISA standard curve fitting process for reducing measurement uncertainty. Using an ELISA kit for measuring cyanobacterial toxin (microcystin), we show that uncertainty associated with the estimated microcystin concentrations can be reduced by defining the standard curve as a four-parameter logistic function on the natural log concentration scale, instead of the current approach of defining the curve on the concentration scale. The model comparison method is outlined in this paper, allowing it to be transferable to test different statistical models for other ELISA test kits.

Keywords: Cyanobacteria; Drinking water; Harmful algal bloom; Nonlinear regression.