Open AccessN-Terminal Derivatization-Assisted Identification of Individual Amino Acids Using a Biological Nanopore Sensor
Author(s) -
Xiaojun Wei,
Dumei Ma,
Zehui Zhang,
Leon Y Wang,
Jonathan L. Gray,
Libo Zhang,
Tianyu Zhu,
Xiaoqin Wang,
Brian Lenhart,
Yingwu Yin,
Qian Wang,
Chang Liu
Publication year - 2020
Publication title -
acs sensors
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.055
H-Index - 57
ISSN - 2379-3694
DOI - 10.1021/acssensors.0c00345
Subject(s) - nanopore , derivatization , nanopore sequencing , amino acid , chemistry , peptide , combinatorial chemistry , nanotechnology , chromatography , computational biology , dna sequencing , materials science , biochemistry , dna , biology , high performance liquid chromatography
Nanopore technology has been employed as a powerful tool for DNA sequencing and analysis. To extend this method to peptide sequencing, a necessary step is to profile individual amino acids (AAs) through their nanopore stochastic signals, which remains a great challenge because of the low signal-to-noise ratio and unpredictable conformational changes of AAs during their translocation through nanopores. We showed that the combination of an N-terminal derivatization strategy of AAs with nanopore technology could lead to effective in situ differentiation of AAs. Four different derivatization reactions have been tested with five selected AAs: Ala, Phe, Tyr, His, and Asp. Using an α-hemolysin nanopore, we demonstrated the feasibility of derivatization-assisted identification of AAs regardless of their charge composition and polarity. The method was further applied to discriminate each individual AA in testing data sets using their established nanopore profiles from training data sets. We envision that this proof-of-concept study will not only pave a way for identification of individual AAs but also lead to future applications in protein/peptide sequencing using the nanopore technology.