An engineered nanopore identifies saccharides, amino acids, peptides and ribonucleotides.

Abstract

Simultaneous characterization of proteins, RNAs and glycans with a nanopore remains a substantial challenge. To advance toward this goal, we introduce a multifunctional adaptor, maleimido-C2-formylphenylboronic acid (maleimido-C2-FPBA), into the Mycobacterium smegmatis porin A (MspA) nanopore at the pore constriction site. Here we demonstrate that the engineered nanopore, MspA-FPBA, enables the simultaneous identification of a diverse set of analytes, including 21 proteinogenic amino acids, three post-translationally modified (PTM) amino acids, four canonical nucleoside monophosphates (NMPs), three epigenetically modified NMPs, four monosaccharides and five peptides. Combined with machine learning, this sensor achieves an overall accuracy of 98.7%. Furthermore, it generates predictable event signatures for specific analyte types, enabling the machine learning model to identify analytes without strictly relying on prearchived event features, as demonstrated by the nanopore analysis of yeast cell extract. Lastly, we apply MspA-FPBA for compositional analysis of G2 glycopeptides. Future integration of hydrolase with MspA-FPBA may further improve MspA-FPBA utility as a single system to identify diverse biomolecules.