To maximize the value of investigations and the information obtained, it is desirable for analysts in the food industry to be able to characterize as many components and aspects of a food sample as possible in a timely manner. This is where a foodomics approach comes in.
What is foodomics?
The term “Foodomics” was coined in 2009 and refers to the study of food and nutrition through the application and integration of -omics technologies, encompassing analytical chemistry, biological techniques and data analysis and interrogation. The key areas where foodomics offers the greatest insights are in food safety, traceability, quality and authenticity, and in establishing links between food and health. Foodomics studies aim to improve consumer's well-being, health, and knowledge.
But to achieve this, powerful analytical tools are needed. Key requirements are the ability to cope with a high throughput of samples, increased resolving power and the capacity to separate lots of compounds. Two-dimensional liquid chromatography (2DLC) is one such tool.
2DLC as a tool for food analysis
In recent years, the price, availability and usability of 2DLC have improved greatly. Used in partnership with mass spectrometry (MS), these advances are boosting the capabilities of two of the three primary omics disciplines, metabolomics and proteomics.
With one-dimensional liquid chromatography (1DLC), complex samples may result in un-resolvable overlapping peaks. Additionally, compounds that coelute in 1DLC cannot be differentiated, offering only limited information on affected samples.
In 2DLC, the first dimension offers conventional separation. The eluant from the first separation is then applied to a second-dimension column with separation selectivity significantly different to the first column. Consequently, 2DLC improves the ability to resolve closely related peaks greatly. Compounds that coelute in the first dimension can also be separated out in the second dimension. The peak capacity (the number of peaks that can be fitted into a chromatogram between the dead point and the “last peak”, each peak being separated from the neighboring peak by at least 4s), the most common metric of separation power, of 2DLC is therefore superior to 1DLC.
2DLC for known unknowns and unknown unknowns
The workflow for 2DLC offers a degree of flexibility. Whilst it may be desirable to retain all eluent from the first separation to apply to the second separation – useful if looking to identify unknowns, this comprehensive analysis is not always necessary. In targeted studies, a subset of fractions from the first separation only may be applied to the second separation, a technique known as “heart-cutting”. The passage of eluant from the first separation to the second separation may be varied too, either manually transferring fractions, having an automatic transition or pausing the first column while the second separation takes place (off-line, on-line and stop-flow protocols respectively).
2DLC as the future of foodomics
In the context of food analysis, where sample complexity is a common barrier, analytical techniques that are capable of overcoming this hurdle are therefore a welcome addition to the foodomics toolbox. The application of 2DLC in food metabolomic and proteomic analyses are however, far from widespread currently, in large part due to issues with established workflows and data analysis. Consequently, there is still room for improvement for 2DLC to become an established mainstay in this field.