Binary code, a flexible tool for diagnostic metabolite sequencing of medicinal plants.

The principle of chromatographic fingerprint is that certain diagnostic metabolites should be always distributed in a given plant and currently, it has been widely accepted as a promising means for medicinal plant authentication. Moreover, the chemical profile is the only evidence to clarify the ingredients of those consumable plant products, e.g. traditional Chinese medicine (TCM) prescriptions. Herein, efforts were made to describe the diagnostic metabolome of medicinal plant or TCM prescription using a binary code sequence. Forty-five well-known medicinal plants along with six relevant prescriptions were employed for concept illustration and proof. Each plant was subjected to chemical characterization, and diagnostic metabolites of all plants were gathered into a chemical pool containing 595 compounds. A robust method enabling the detection of all 595 constituents was then developed using LC coupled to scheduled multiple reaction monitoring. Analyst™ software was responsible for automatically judging the presence (defined as "1") or absence (defined as "0") of each analyte with a defined signal-to-noise threshold (S/N > 100). After converting each medicinal plant to a binary sequence consisting of 595 codes, an in-house database was built by involving all sequences. The potentials of sequence library retrieval towards plant authentication, preliminary chemical characterization, and deformulation of TCM prescriptions were demonstrated after that the diagnostic metabolome of each test sample was translated to a binary code sequence. Above all, binary code is a flexible tool for diagnostic metabolite sequencing of medicinal plants, and it should be an alternative tool of DNA barcoding towards plant authentication.

A full solution for multi-component quantification-oriented quality assessment of herbal medicines, Chinese agarwood as a case.

The quality of herbal medicines (HMs) is the prerequisite for their pronounced therapeutic outcomes in clinic, and multi-component (also known as quality markers, Q-markers) quantification has been widely emphasized as a viable means for quality evaluation. Because of the chemical diversity, the quality control practices are extensively dampened by four principal technical bottlenecks, including the lack of authentic compounds, large polarity span, extensive concentration range, and signal misrecognition for those potential Q-markers. An attempt to promote the potential of LC-MS/MS is made herein to cope with those obstacles and Chinese agarwood was employed as a case study. Firstly, a home-made fraction collector was introduced to automatically fragment the entire extract into a panel of fractions-of-interest. Secondly, quantitative 1H-NMR was deployed to offset the LC-MS/MS potential towards in-depth chemical profiling each fraction, and those well-defined fractions were then pooled and combined with some accessible authentic compounds to generate the pseudo-mixed standard solution. Thirdly, serial improvements were conducted for LC-MS/MS measurements. Reversed phase LC and hydrophilic interaction LC were serially coupled in respond to the large polarity window, and online parameter optimization, response tailoring, as well as RRCEC (relative response vs. collision energy curve) matching were integrated in MS/MS domain to advance the quantitative confidences. Simultaneous determination was conducted for 26 components, in total, in Chinese agarwood after method validation. In particular, authentic compound-free quantification was achieved for eight 2-(2-phenylethyl)chromone derivatives. Above all, the strategy is a promising solution to completely tackle with the technical barriers toward Q-marker quantification-oriented quality control of Chinese agarwood, as well as other HMs.