A Conversation on the "Latest and Greatest" in Metabolomics
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Aided by advances in high-throughput technologies, the metabolomics research field has gained significant traction in recent years. A plethora of literature is published each day exploring the impact of metabolite research on human health and disease, and it can be hard to keep up with the latest advances that are shaping the field.
Technology Networks recently spoke with Baljit Ubhi, Ph.D., Global Business Lead, Metabolomics and Lipidomics Markets at SCIEX. In this interview, Ubhi provides her insight on the recent developments in metabolomics, addressing the increasing focus on the microbiome and how it impacts metabolic disease, and explores the future directions of research, such as "precision nutrition".
Molly Campbell (MC) What have been some of the most exciting developments in the metabolomics research field thus far in 2019?
Baljit Ubhi (BU): As you are no doubt aware, we are made up of a vast army of microbes. The microbiome (a collection of those microbes) protects us against germs, breaks down food to release energy, and produces vitamins. I think the increased understanding of how the microbiome impacts metabolic disease, and even gut-derived metabolites and their responsibility in many of these biological processes, has meant the interrogation at the functional level has really put a lens and importance on metabolomics-based approaches.
Furthermore, the microbiome has a significant impact on the diagnosis and treatment of human diseases. Specifically, the microbiome has been linked to obesity, diabetes and certain cancers and more recently autoimmune disorders. Metabolomics is therefore a powerful research tool for the systemic analysis of all the external factors that can have an effect on the phenotype and metabolic phenotyping provides a systemic read-out of an individual or a group of individuals by which you can assess not only the current physiological status, but also evaluate the risk to develop a certain disease or the response to a particular therapy. This information can then be applied to precision medicine and public healthcare initiatives
MC: What insight can metabolic flux analysis offer over conventional metabolomics analysis?
BU: Metabolomics provides an instant snapshot of biology at a fixed-time; however, metabolism is a dynamic process. Metabolic flux describes the rate of metabolite conversion through a pathway and allows empirical estimation rates through stable isotope labelling experiments e.g. 6C13-glucose. Traditional metabolomics analyses only capture one snapshot in time, when the sample was collected. However, using a metabolic flux study, where a tracer is introduced over a series of timepoints, allows for the capture of a deeper level of information.
The simplest way to understand this is to think of yourself as lost on the way home while driving. There are three routes. They can all get you home. That is what an “unlabelled” or traditional metabolomics experiment has the ability to tell you. What it cannot tell you is if there is a traffic jam/block on one of the possible routes. This is the information you can gain from a “labelled” experiment (flux). Moreover, you can determine the rate of how fast traffic is moving for you to choose which route to select.
Knowledge of metabolic fluxes (and kinetics) is essential to unravel sites and mechanisms of metabolic regulation and thus augment the understanding of how metabolism is embedded in cellular decisions. Metabolic flux, describing the rate of metabolite conversion through a pathway, paves the way for identification of selective and novel therapeutic targets.
MC: What are some of the cutting-edge metabolomics and lipidomics applications in life sciences and clinical research?
BU: Right now, there is a need is to analyze large number of samples and obtain the most information in the shortest timeframe with limited sample preparation. This has been termed high-throughput (HT-) metabolomics.
However, few labs do this and instead typically run a very fast method (90-seconds or less). On a recent lab visit, the lab was running a 60-second method where they screened samples to get a full metabolic profile and then used that data to infer their multiple reaction monitoring (MRMs) for a targeted assay with highest sensitivity and obtain quantitative data on a handful of selected targets. This is “leap-frogging” the traditional, untargeted metabolomics workflow where labs would acquire 10-15-minute methods and then spend weeks, if not months, bogged down in peak identification.
MC: How is metabolite profiling by MS-based metabolomics aiding the drug development process?
BU: I mentioned above how metabolomics and specially labelled “flux” analyses can aid in the identification of selective and novel therapeutic targets. But metabolomics is being used even before this phase during the “discovery” phase where basic biological research is being conducted to identify novel biomarkers, and to understand the mechanism of action. Combined with target identification, metabolomics is used to infer the lead identification to lead optimization process in early drug discovery.
Once there is a lead candidate, the biology teams move into the “preclinical” phase. Here, metabolomics is used for preclinical based studies, so animal studies are conducted and dosed with the lead compound. Safety studies are undertaken, and metabolomics has been used to understand and explore unwanted toxic side effects of the lead compound. All this data is used to file the IND (investigational new drug application).
Moving into the “development” phase, clinical trials begin and the project team responsible for delivering the large amount of data for filing the new drug application (NDA) gets underway. Here, metabolomics can be used for patient stratification and to identify which patients would/should respond to the therapy in question. Most recently, metabolomics is being used in the “manufacturing” stages for process development (and scaling up process) as well as quality testing including QA/QC and lot-to-lot evaluation of the finished product.
In biopharmaceutical companies, cell culture media optimization is a critical step during the development and scale up of biotherapeutic production. Monitoring the critical quality attributes during process development is achieved through monitoring the small molecules (metabolomics). Making sure the cell culture media has the right balance of nutrients needed for cell growth during production of therapeutic proteins is essential for the yield and quality of the final product.
MC: What technological challenges do researchers still face in the metabolomics research space? How is SCIEX looking to overcome these challenges?
BU: Challenges with respect to metabolite identification and the lack of liquid chromatography-mass spectrometry (LC-MS/MS) databases for metabolite confirmation remains a huge bottleneck in the field. Researchers cannot advance their workflows to actionable results from which they can make biological decisions. To improve metabolite identification and quantitation in complex samples for untargeted metabolomics, SCIEX partnered with IROA Technologies.
Secondly, these researchers struggle to efficiently process all of their metabolomics data from a diverse range of workflows. Our co-marketing relationship with EluciData, will allow scientists to interpret these results in a biological context to further advance the fields of target identification and validation, as well as deeply characterize the underlying biology.
MC: What do you envision will be the next breakthrough in the metabolomics research field?
BU: “Precision nutrition” is a term floating around the community right now. The precision medicine objective is how to get the right treatment to the right patient. However, precision nutrition’s goal is to manipulate diets without the need for any medical intervention. Again, the microbiome and its impact on digestion and gut-derived metabolites is extremely important here.
Baljit Ubhi, Global Business Lead, Metabolomics and Lipidomics Markets at SCIEX, was speaking with Molly Campbell, Science Writer, Technology Networks.