Thyroid hormones (THs) are a variety of iodine-containing hormones that demonstrate critical physiological impacts on cellular activities. The assessment of thyroid function and the diagnosis of thyroid disorders require accurate measurement of TH levels. However, largely due to their structural similarities, the simultaneous discrimination of different THs is challenging. Nanopores, single-molecule sensors with a high resolution, are suitable for this task. In this paper, a hetero-octameric Mycobacterium smegmatis porin A (MspA) nanopore containing a single nickel ion immobilized to the pore constriction has enabled simultaneous identification of five representative THs including l-thyroxine (T4), 3,3',5-triiodo-l-thyronine (T3), 3,3',5'-triiodo-l-thyronine (rT3), 3,5-diiodo-l-thyronine (3,5-T2) and 3,3'-diiodo-l-thyronine (3,3'-T2). To automate event classification and avoid human bias, a machine learning algorithm was also developed, reporting an accuracy of 99.0%. This sensing strategy is also applied in the analysis of TH in a real human serum environment, suggesting its potential use in a clinical diagnosis.
Keywords: Mycobacterium smegmatis porin A; biological nanopore; nickel-nitrilotriacetic acid; single-molecule detection; thyroid hormone.