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.