Cookie or Gelato?
How a two-dimensional liquid chromatography (2D-LC) method helps characterize – and, therefore, differentiate – industrial hemp strains
Margot Lespade | | News
Industrial hemp is hot, garnering the increased attention of several industries – from pharma to food. “There are a growing number of studies that highlight the benefits of hemp consumption in all its diverse forms – oil, inflorescence, seeds, proteins,” says Lidia Montero, first author of a new study presenting an advanced analytical method for hemp analysis (1). “Together with its increasing legalization, this means hemp has become a very hot topic in recent years.”
But not all hemp strains are alike – and the genetic diversity at play can have a significant impact on the resulting metabolite profile, which in turn may affect its application. For example, pharmaceutical, food, or cosmetic companies may want to target specific customer needs based on the properties offered by the predominant bioactive compounds. And that would demand a deeper understanding of the chemical makeup of different strains – and the ability to differentiate between them. But such detail can only be gained with a more comprehensive exploration of the metabolite profiles of different genetic varieties. And that’s why Montero and colleagues from the University of Duisberg-Essen, Germany, have developed a comprehensive two-dimensional liquid chromatography (2D-LC) method, which, when combined with a new demodulation process, is capable of identifying differences between the two varieties of industrial hemp in terms of their cannabinoid and phenolic profiles (1).
Of the two strains – dubbed “cookie” and “gelato” – the cookie strain showed higher cannabinoid content and a higher number of cannabinoid markers, while the gelato strain was richer in representative phenolic compounds.
The key benefit of 2D-LC, according to the authors, is a huge gain in separation power compared with conventional (one-dimensional) LC. When characterizing complex samples, such as hemp, a single column is unlikely to resolve all analytes, leading to incomplete characterization and a loss of potentially valuable information. “In 2D-LC, we can select and couple two independent separation mechanisms,” says Montero. “We obtain a first separation, and any analytes that coelute in this first separation can be separated in a complementary second dimension.”
Though 2D-LC has traditionally been tedious, complex, and time-consuming, modern 2D-LC systems have streamlined the approach. “2D-LC is now a very attractive analytical tool in cannabis research, providing necessary information about the chemical composition of this plant, which, in turn, will increase knowledge about its potential therapeutic properties and establish the relationship between compound and bioactivity.”
To hammer home the point, the team also discovered hundreds of compounds not previously identified in hemp. But there is still room for improvement, says Montero. “Our goal is to continue working on the analysis of industrial hemp strains by combining 2D-LC with other separation techniques like ion mobility and tandem mass spectrometry.”
- L Montero et al, Analytical and Bioanalytical Chemistry (2022). DOI: 10.1007/s00216-022-03925-8