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Fields & Applications Metabolomics & Lipidomics, Translational Science

Right on Target

sponsored by Agilent Technologies

What are the main advantages of targeted metabolomics?

Metabolomics seeks to understand all the metabolites in a cell, biofluid, or organism. This creates a catch-all approach in which you make a lot of compromises in sample preparation and untargeted data acquisition – leading to not only unintended bias, but also complicated datasets requiring expert analysis.

In targeted metabolomics, you are often conducting hypothesis-driven research – really drilling down to the biological pathways most likely impacted by the disease of interest. The value of a targeted approach is that it’s much easier for a researcher to implement and makes the data much clearer. This reduces not only sample costs, but also labor costs by allowing a more standardized data analysis pipeline that requires fewer hours to review and makes results easier to interpret.

This ultimately allows targeted metabolomics methods to be adopted for small-scale experiments and then easily scaled up to large cohort studies for biomarker research. Thus, the targeted approach is a good first step for any investigator bringing this new metabolomics technology into their lab.

What challenges affect the separation of targeted metabolites?

The real challenge in analyzing the metabolome is the diversity of chemistry and the wide concentration range of metabolites in any given cell or biofluid. Molecules have a highly diverse set of properties – from highly polar saccharides and amino acids to very nonpolar lipid species. Some molecules, such as organic acids, are even sensitive to metal content in standard LCs, which is one of the reasons we created the Agilent Infinity II BioLC – to reduce chromatographic peak tailing and improve resolution for those metal-sensitive compounds. This can reduce false peak assignment, giving greater confidence that the marker you’re assessing is genuine.

It’s clear that you need a range of methods to accurately separate, identify, and quantify all these different metabolites – and that’s one of the reasons we set out to develop a collection of highly curated targeted omics methods to help people spend less time building methods and more time generating data they can count on.

Are there problems with “one-size-fits-all” approaches?

The challenge of “one-size-fits-all” approaches to metabolomics is that they often require serious compromises in the range of molecules they can detect accurately and confidently. This leads to ambiguity in compound identification and quantitation. By taking a more deliberate, targeted approach, you can home in on the metabolite data you’re most interested in and be confident in it. This not only allows you to select the approach that best fits your research needs, but also provides tremendous value for the investment.

“One-size-fits-all” approaches also raise the bar on the skill level of the instrument technicians and investigators – skills a lab might have difficulty finding in today’s labor market. Even a skilled operator could easily take six months of valuable research time to develop a satisfactory method.

Talk me through some of Agilent’s work in this area…

At Agilent, we have built a portfolio of products that can be used for any part of the omics journey. Whether it’s our Captiva Lipid-EMR Plates for sample prep, superior separations on our Infinity II BioLC and Poroshell 120 HILIC-Z columns, or highly sensitive 6495C Triple Quadrupole Mass Spectrometers, we’re positioned to help researchers through their entire metabolomics journey.

With this portfolio of products, we have some talented researchers working on method development. For example, our team has meticulously put together our HILIC-Z targeted metabolomics method – including over 500 metabolites with retention times and multiple transitions – so you don’t have to. For our targeted lipidomics method, we collaborated with leading researcher Peter Meikle, a professor at the Baker Heart and Diabetes Institute in Australia. Peter and Agilent wanted a robust lipidomics method with 763 lipids commonly found in plasma that could easily scale up for large cohort research studies. Peter’s team really went the extra mile – they even developed a website to aid researchers in reviewing their data! (To find out more about Peter Meikle’s work, we have a presentation on plasma lipidome profiling, which you can view here.)

I’d also like to highlight our Automated Dual Metabolite + Lipid Cell sample prep workflow, which enables high metabolite and lipid recovery from the same sample. The power of these protocols is that they can readily be used in front of our targeted metabolomics and lipidomics methods for even greater accuracy by reducing sample prep variability caused by manual processing and freeing up skilled researchers to work on other tasks.

Overall, why should metabolomics researchers consider Agilent?

With these targeted omics methods, we’ve created a single platform where researchers can easily switch between highly curated methods for multiple omics. This makes it much easier to bring omics technology into the lab and focus on what matters – generating high-quality biological data.

So, I’d encourage readers to click here to find out more about how we collaborate with our partners and to check out our selection of targeted omics app notes and webinars.

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