Nanopore analysis of salvianolic acids in herbal medicines.

Natural herbs, which contain pharmacologically active compounds, have been used historically as medicines. Conventionally, the analysis of chemical components in herbal medicines requires time-consuming sample separation and state-of-the-art analytical instruments. Nanopore, a versatile single molecule sensor, might be suitable to identify bioactive compounds in natural herbs. Here, a phenylboronic acid appended Mycobacterium smegmatis porin A (MspA) nanopore is used as a sensor for herbal medicines. A variety of bioactive compounds based on salvianolic acids, including caffeic acid, protocatechuic acid, protocatechualdehyde, salvianic acid A, rosmarinic acid, lithospermic acid, salvianolic acid A and salvianolic acid B are identified. Using a custom machine learning algorithm, analyte identification is performed with an accuracy of 99.0%. This sensing principle is further used with natural herbs such as Salvia miltiorrhiza, Rosemary and Prunella vulgaris. No complex sample separation or purification is required and the sensing device is highly portable.

Unambiguous discrimination of all 20 proteinogenic amino acids and their modifications by nanopore.

Natural proteins are composed of 20 proteinogenic amino acids and their post-translational modifications (PTMs). However, due to the lack of a suitable nanopore sensor that can simultaneously discriminate between all 20 amino acids and their PTMs, direct sequencing of protein with nanopores has not yet been realized. Here, we present an engineered hetero-octameric Mycobacterium smegmatis porin A (MspA) nanopore containing a sole Ni2+ modification. It enables full discrimination of all 20 proteinogenic amino acids and 4 representative modified amino acids, Nω,N'ω-dimethyl-arginine (Me-R), O-acetyl-threonine (Ac-T), N4-(ß-N-acetyl-D-glucosaminyl)-asparagine (GlcNAc-N) and O-phosphoserine (P-S). Assisted by machine learning, an accuracy of 98.6% was achieved. Amino acid supplement tablets and peptidase-digested amino acids from peptides were also analyzed using this strategy. This capacity for simultaneous discrimination of all 20 proteinogenic amino acids and their PTMs suggests the potential to achieve protein sequencing using this nanopore-based strategy.