Reliability factor for identification of amylolytic enzyme activity in the optimized starch-iodine assay

Aline L.O Gaenssle,Marc J.E.C Van Der Maarel,Edita Jurak

doi:10.1016/j.ab.2020.113696

Aline L.O Gaenssle, Marc J.E.C Van Der Maarel + Show 1 more

Open Access

https://doi.org/10.1016/j.ab.2020.113696

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Journal: Analytical biochemistry	Publication Date: Mar 19, 2020
Citations: 6	License type: cc-by

Affiliation: University of Groningen

Abstract

Amylolytic enzymes are a group of proteins degrading starch to its constitutional units. For high-throughput screening, simple yet accurate methods in addition to the reducing ends assays are required. In this article, the iodine assay, a photometric assay based on the intensely colored starch-iodine complex, was adapted to enable accurate and objective differentiation between enzyme and background activity using a newly introduced mathematical factor. The method was further improved by designing a simple setup for multiple time point detection and discussing the applicability of single wavelength measurements.

Highlights

One of the most important sources of carbohydrates for human diet is starch [1], a structure entirely built up of glucose units interlinked via α-1,4- and α-1,6-glucosidic bonds, forming linear chains and branch points, respectively
Quantitative determination of catalytic activity of amylolytic enzymes is conducted via estimation of the amount of formed reducing sugars by using methods such as the Nelson-Somogyi [4] and dinitrosalicylic acid (DNS) assay [5]
Challenges for the interpretation of the data regarding the shift in λmax caused by some amylolytic enzymes and the differentiation between background and enzyme activity were both addressed by proposing a procedure and mathematical formula, respectively

Summary

Introduction

One of the most important sources of carbohydrates for human diet is starch [1], a structure entirely built up of glucose units interlinked via α-1,4- and α-1,6-glucosidic bonds, forming linear chains and branch points, respectively. In this case it was recommended to estimate the enzyme activity based on the absorbance values at the λmax of each time point. For all experiments in which all data points exhibited a λmax within the given range, the overestimation was below 10%, providing a sufficiently narrow window for accurate detection of enzyme activity at a single wavelength.

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Conclusion