Analytical chemistry has always been the key to advances in scientific knowledge. It bridges the gap between a hypothesis and a theory by providing tools to test and validate our ideas. Nowadays, its power is greater than ever. Breathtaking advances in instrumental analysis and computational capabilities make it possible to separate and measure myriad compounds in very complex samples. In turn, these advances have opened the door to –omics technologies – including metabolomics. Metabolomics is a powerful approach because metabolite concentrations, unlike genes or proteins, directly reflect the biochemical activity of a biological system. Metabolomics represents the phenotype, and gives real-time data on the end points that matter (for example, illness or response to a drug).
Classical research is based on generating a hypothesis and developing the necessary assays to prove or disregard the hypothesis, which is time consuming and limited. New technologies have given us the opportunity to carry out a different type of research, looking at all the changes that occur in a system. I often compare it with fishing. Traditional research is like fishing for salmon – you select the best place, time, rod and bait for the job, and you come home either with a salmon, or with nothing. Metabolomics is like fishing from a boat with a huge fishing net. You catch everything that is there, and while some of your haul will be plastic bags and seaweed, you are likely to find a variety of interesting fish. Every so often, you might even get lucky and catch a mermaid! Detecting changes to the concentrations of metabolites in a perturbed system by differential analysis opens up an unlimited number of applications. We can identify biomarkers with potential as diagnostic markers, gather data to stratify patients or predict the trajectory of a disease over time. We can interpret metabolic changes to understand the mechanism of a disease, identify a target, and design new therapies. In cellular assays, metabolomics can give a broad picture of all the changes produced in response to a treatment. In summary, metabolomics can provide answers in basic research, personalized medicine, drug design, biotechnology and many other fields. Luckily for analytical chemistry researchers, there is a lot of space for improvement in metabolomics workflow. To name just a few:
- The whole process should be validated to ensure reproducibility in results.
- Validation parameters and quality control procedures need to be established, with a joint effort of societies, journals and research groups to come to consensus.
- Metabolite identification is still one of the bottlenecks, together with data interpretation; in that regard, different groups and companies are working on cured databases and intelligent software systems.
- Reproducible ionization sources in LC are still a challenge for companies devoted to technical development.
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