Limits of Detection Based on the Four-Parameter Logistic Model for E. coli Determined using a Fluorescent-based Sensor

  • Siti Nadzirah Padrilah Biotechnology and Nanotechnology Research Centre, Malaysian Agricultural Research and Development Institute (MARDI), Persiaran MARDI-UPM, 43400 Serdang, Selangor, Malaysia.
  • Noor Azlina Masdor Biotechnology Research Centre, Malaysian Agricultural Research and Developmental Institute (MARDI), 43400 Serdang, Selangor, Malaysia.
Keywords: Pathogen; E. coli; fluorescence sensor; four-parameter logistic; Limits of detection

Abstract

Because of the huge number of outbreaks, bacterial infection is becoming more common, which is compounded by the rise of antibiotic resistance. These issues have warranted the development of sensitive detection and therapeutic devices. A fluorescence-based detection of the pathogen E. coli is previously developed using a mini-emulsion technique to create fluorescent/electroactive poly(3-hexylthiophene) P3HT nanoparticles (NPs) stabilized with CTAB or cetyltrimethylammonium bromide, a quaternary ammonium salt forming CTAB-P3HT NPs. Limits of detection for the bacterium based on fluorescence spectroscopy is 5 CFU/mL. The curve showed a sigmoidal calibration curve but was not modelled according to any of the sigmoidal models available. The aim of this study is to use the Four-Parameter Logistic Model to determine the LOD value more accurately. The modelling exercise gave values of the parameters a, d, Log EC50 and Hillslope representing the maximum and minimum responses, value that produces a 50% signal response, and a slope-like parameter (Hill coefficient) of -0.01427 (DF/F0), 0.6189 (DF/F0), 3.473 and 0.413, respectively. The LOD value was 30 CFU/mL with the 95% confidence interval from 13 to 64 CFU/mL. The usage of the 4Pl model in this study was successful, since it was able to represent the entire date curve. The correlation coefficient values of 0.986 indicated good fitting of the experimental data to the 4PL model. The 4PL model has been found to be a good model in fitting the calibration curve for the detection of E. coli.
Published
2021-07-31
Section
Articles