Abstract
Carbohydrate digestion in the mammalian gastrointestinal tract is catalyzed by α-amylases and α-glucosidases to produce monosaccharides for absorption. Inhibition of these enzymes is the major activity of the drugs acarbose and miglitol, which are used to manage diabetes. Furthermore, delaying carbohydrate digestion via inhibition of α-amylases and α-glucosidases is an effective strategy to blunt blood glucose spikes, a major risk factor for developing metabolic diseases. Here, we present an in vitro protocol developed to accurately and specifically assess the activity of α-amylases and α-glucosidases, including sucrase, maltase and isomaltase. The assay is especially suitable for measuring inhibition by compounds, drugs and extracts, with minimal interference from impurities or endogenous components, because the substrates and digestive products in the enzyme activity assays are quantified directly by high-performance anion-exchange chromatography with pulsed amperometric detection (HPAE-PAD). Multiple enzyme sources can be used, but here we present the protocol using commercially available human α-amylase to assess starch hydrolysis with maltoheptaose as the substrate, and with brush border sucrase-isomaltase (with maltase, sucrase and isomaltase activities) derived from differentiated human intestinal Caco-2(/TC7) cells to assess hydrolysis of disaccharides. The wet-lab assay takes ~2–5 h depending on the number of samples, and the HPAE-PAD analysis takes 35 min per sample. A full dataset therefore takes 1–3 d and allows detection of subtle changes in enzyme activity with high sensitivity and reliability.
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Data availability
The data that support the anticipated results are available on figshare at https://figshare.com/articles/dataset/Barber_et_al_Nature_Protocols_Source_Data_-_Figure_4_xlsx/19709740, https://figshare.com/articles/dataset/Barber_et_al_Nature_Protocols_Source_Data_-_Figure_5_xlsx/19709890 and https://figshare.com/articles/dataset/Barber_et_al_Nature_Protocols_Source_Data_-_Figure_6_xlsx/19709896. Source data are provided with this paper.
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Acknowledgements
We thank A. Kerimi for setting up the preceding methods on the Integrion and help in translocating polyphenols and equipment to the laboratory, and E. Balland for help in setting up a functional laboratory at Monash University. The Caco2/TC7 cell line was a kind gift from M. Rousset, Centre de Recherche des Cordeliers, Paris, France.
Author information
Authors and Affiliations
Contributions
E.B. had the initial idea to publish the methods as a protocol. E.B., R.V. and M.J.H. established and improved the α-glucosidase and α-amylase enzyme assays, and generated data. G.W. designed and supervised the research and oversaw the development of the protocols. All authors edited the manuscript and approved the final version.
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G.W. is a scientific advisor for Nutrilite, USA, and receives research funding from Nutrilite, USA, and TPM, Australia. The other authors declare no competing interests.
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Nature Protocols thanks Kiyoshi Yasukawa and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Related links
Key references using this protocol
Barber, E. et al. Foods 10, 1939 (2021): https://doi.org/10.3390/foods10081939
Visvanathan, R. et al. Food Chem. 343, 128423 (2021): https://doi.org/10.1016/j.foodchem.2020.128423
Key data used in this protocol
Barber, E. et al. Foods 10, 1939 (2021): https://doi.org/10.3390/foods10081939
Visvanathan, R. et al. Food Chem. 343, 128423 (2021): https://doi.org/10.1016/j.foodchem.2020.128423
Supplementary information
Supplementary Table 1
Example raw data for α-glucosidase assay, quantified by HPAE-PAD in triplicate injections.
Source data
Source Data Fig. 4
Raw and processed source HPAE-PAD data.
Source Data Fig. 5
Raw and processed source HPAE-PAD data.
Source Data Fig. 6
Raw and processed source HPAE-PAD data.
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Barber, E., Houghton, M.J., Visvanathan, R. et al. Measuring key human carbohydrate digestive enzyme activities using high-performance anion-exchange chromatography with pulsed amperometric detection. Nat Protoc 17, 2882–2919 (2022). https://doi.org/10.1038/s41596-022-00736-0
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DOI: https://doi.org/10.1038/s41596-022-00736-0
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