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For years, health trends encouraged us to eliminate fats from our diet yet as a whole, our (Western) society wasn’t necessarily getting healthier. Fats and oils are types of a larger group of compounds called lipids, which also include steroids such as hormones and cholesterol, and lipids are abundantly present in all parts of our body. They’re involved in many biological functions including energy storage, insulation, cell membrane formation, cellular communication and in conditions such as inflammation and immunity. Dysregulation of lipids can lead to various disorders such as obesity, diabetes, cancer, neurodegenerative conditions, metabolism disorders and heart disease. But not all fat is bad. It’s become clear that certain lipids can actually benefit human health, for example omega-3 fatty acids in fish and mono-unsaturated ones like those in olive oil.

Lipidomics: the new frontier in the –omics sciences

The development of -omics sciences (genomics, proteomics, metabolomics) and more importantly, advances in technologies and computational capacity, have paved the path for the growing field of lipidomics and the immense amount of data being generated. In the last decade, the sheer diversity of subtypes discovered among lipids easily outshines that of proteins and nucleic acids.

This high degree of molecular heterogeneity, combined with the fact that lipids are not catalytically active (they don’t produce a chemical reaction that enables their detection) and that they often exist in large complex mixtures, makes it challenging to conduct lipidomic analysis. In Utrecht, we’ve established a Lipidomics Facility to address the fundamental questions about lipids and their roles in health and disease.

Utrecht Lipidomics Facility

Lipidomics is big data science, and this is exactly what attracted me to it. I started out studying the lipid metabolism of a parasite in humans that we cultured in hamsters. Our approach wasn’t sensitive enough, so I looked around for an alternative way of conducting experiments and found high performance liquid chromatography (HPLC). HPLC increased sensitivity and separated out different lipids, but I was still left with what do those peaks represent, and the inability of this technique to identify unknown lipids. I joined forces with a group at the pharmacy department that was using mass spectrometry (MS) and from there, built the Lipidomics Facility. MS is a technique that identifies molecules based on their mass to charge ratio, and that of their fragments, and we have three of such machines, all customized for lipid analysis.

Our first instrument is specialized in targeted analysis, meaning that measurements are taken against a specific list of compounds, for example, in the case of athletes taking performance enhancers (doping). Because of the high sensitivity, it’s ideal for the detection of minor compounds such as lipid oxidation products, biosynthetic intermediates or compounds at trace levels.

Lipidomics is big data science, and this is exactly what attracted me to it.

Our second instrument is simple and robust. This is where explorative research starts. It produces clean, rough composition data and is nearly impossible to break. Our technician trains researchers how to use the instrument; however, it’s not as accurate as the MS instrument mentioned below.

The third MS instrument has high resolution, is fast and can carry out different MS experiments in parallel. This instrument can assign masses with the accuracy of a single grain in a kilogram of sugar, and can decipher the elemental composition of an unknown substance. While measuring the masses within a sample, it can also fragment the individual compounds in a different section of the instrument and measure those masses. This can tell us more about the building blocks of the lipid molecule.

Optimizing our facility

We’re currently optimizing and standardizing our workflow, and most recently, we’ve engineered high-throughput capabilities for lipid isolation. Compared with classic protocols that limited our throughput to 40 samples a day, we can now fully process a 384-well plate in a day, and for each sample, we can easily find 3000 to 4000 lipid signals. We’re also working with bioinformatics collaborators to improve our ability to provide data in an understandable format for researchers through a secure web portal.

The Lipidomics Facility is open to all researchers and we accept any type of sample. Some examples of projects we’re working on include lipid metabolism in the brain of postmortem biopsies of Parkinson’s Disease patients; we discovered a new lipid class in a common wide-spread parasite of humans and animals and are developing a vaccination against it; we’re knocking out all enzymes associated with lipid metabolism in E. coli to look at the role of each enzyme in lipid homeostasis; and we’re studying blood profiles of cows with negative energy balance, when they secrete much more energy via milk than they can take in, resulting in significant weight loss and impaired fertility.

We encourage you to come by for a consultation, and navigating the halls of Nieuw Gildestein to our work space is step one. We know it’s tricky to find, but once you’ve found us, you’ll wonder why you didn’t visit earlier.

Jos Brouwers, PhD
Department of Biochemistry and Cell Biology