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Fields & Applications Metabolomics & Lipidomics

Popular Reflections: The Rise and Rise of Metabolomics

Have there been any major developments in the field of metabolomics – especially related to systems biology and metabolite activity screening (systems-MAS) – since you wrote the article in 2018?

Absolutely. Firstly, we refined the topic quite nicely in our 2019 Nature Reviews in Molecular Cell Biology paper (1), now calling it “Activity Metabolomics” (more catchy!). Secondly, it is apparent in my daily work that there is increasing appreciation – and demand from both academic and industrial partners – for deciphering phenotypic observations and linking them to potentially bioactive metabolites. For example, my group is focusing on desmosterol – an endogenously formed precursor of cholesterol. Just recently we showed that its controlled accumulation by inhibiting its metabolism into cholesterol caused selective liver X receptor activation and thereby triggered an anti-inflammatory/pro-resolving phenotype (2). Importantly, others confirmed the anti-inflammatory/pro-resolving properties of desmosterol also in neurological disease settings (3,4). It seems that boosting the accumulation of bioactive endogenous metabolites is becoming a cutting-edge therapeutic avenue. Recent examples from Gary’s lab include the identification of microbiome derived bioactive metabolites influencing T cell–induced colitis as well as metabolites that modulate thermal regulation during calorie restriction (5,6).

Is systems-MAS any closer to overcoming the challenges you posed, such as the need to develop effective approaches to identify active metabolites and generate libraries cataloging their bioactivity?

We feel a lot has happened. However, identifying bioactive metabolites remains a major challenge and tedious job. I believe one way forward might lie in starting out with identifying key pathways using CRISPR and iPSC technologies. For example, Martin’s group is involved in two exciting projects in this framework: one investigating the lipidomic disturbances in a library of CRISPR modified lipid transport proteins, and another (The Neurolipid Atlas, CZI funded) building a quantitative lipidomics atlas of hiPSC derived neural cells, including neurodegenerative disease-specific gene modifications. Both projects have the potential to identify novel disease-relevant lipid pathways, thereby leading to potential new targets and metabolic intermediates for bioactivity screening.

Consistent with Martin’s group, the Siuzdak lab is finding that metabolomics is the first step in identifying bioactive metabolites. And subsequent orthogonal technologies are required to complete these stories. For example, we (Siuzdak lab and collaborators) have been investigating two separate immunomodulators for years now, since their original discovery and identification.

Do you have any recent research highlights you'd like to share?

On the technical side I think that our recent work on employing enhanced in source fragmentation as a quantitative bioanalysis tool on simple single quadrupole mass spectrometers has great potential enabling QqQ like quantitative analysis on a broad range of machines – and at a much lower cost, essentially democratizing MS (7). And the ever-growing METLIN database (now at 860K molecular standards with MS/MS and neutral loss data) is certainly helping on the identification side (8).

Overall, are we any closer to being able to "fix biology with biology" using metabolites?

Yes, we are. In general terms, it is extremely important that the perception of metabolites is changing. For years, metabolites have been considered as inactive biological bystanders. But this is starting to change and metabolites are becoming increasingly recognized as master controllers of biological phenotypes. If you think about it, whole scientific fields, such as immune-metabolism, are built on this fact. Moreover, from several projects Martin is involved in, we are beginning to understand how the molecular composition of a cell determines its basic functions – consider immune cells and, in particular, immune cell subtypes, for example, M1, M2 macrophages or immunological phenomena such as trained immunity. Nevertheless, the translation of this knowledge into exploitable biological tools will be even more important – and that’s when we can talk about fixing biology with biology. Frankly, we expect novel therapies targeting the molecular composition of immune cells (in particular) to arise during the next decade. A recent example is the inhibition of 15-PGDH a prostaglandin E2 degrading enzyme (9). Moreover, neurological disorders, such as multiple sclerosis or even Alzheimer’s disease, might finally become treatable, if we understand how to molecularly control the function of specific neurological cells, a recent example is the involvement of post-squalene sterol biosynthesis in microglia facilitated repair of demyelinated lesions (3).

Thinking more broadly, what has been the most exciting advance in analytical science since you wrote the article in 2018?

There are a couple actually. The shotgun lipidomics assistant (SLA), recently published by Kevin Williams and colleagues (10), is a really cool platform allowing the quantitative-flow-injection-based analysis of up to 1400 individual lipid species (10). Martin is really happy that his group could partake in this development – it is one of the most frequently applied assays in my lab. Joshua Rabinowitz’s group published some remarkable papers on metabolic flux analysis (11) – a topic that will become increasingly important particularly when trying to fully understand metabolic homeostasis. The development of METLIN and more recently enhanced in-source fragmentation by Gary’s group has also been a great contribution, particularly considering its potential impact. The quantitative application of this development, termed Q-MRM, could enable students and less fortunate colleagues around the globe to carry out triple-quad-like quantitative analysis on affordable single quadrupole machines with similar sensitivities.

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  1. MM Rinschen et al., Nat Rev Mol Cell Biol, 20, 6, 353-367 (2019)
  2. A Körner et al., Proc Natl Acad Sci USA, 116, 41, 20623-20634 (2019)
  3. SA Berghoff et al., Nat Neurosci, 24, 1, 47-60 (2021)
  4. RG Snodgrass et al., Cell Death Differ, 28, 4, 1301-1316 (2021)
  5. JR Montenergo-Burke et al. Sci Signal. 14, 702, eabf6584 (2021)
  6. C Guijas et al. Sci Signal. 13, 648, eabb2490 (648)
  7. J Xue et al., Anal Chem, 93, 31, 10879-10889 (2021)
  8. J Xue et al., Nat Methods, 17, 952-954 (2020)
  9. AR Palla et al. Science, 371, 6528, eabc8059 (2021)
  10. B Su et al., J Am Soc Mass Spectrom, in press (2021)
  11. S Hui et al., Cell Metab, 32, 4, 575-688 (2020)
About the Author
James Strachan

Over the course of my Biomedical Sciences degree it dawned on me that my goal of becoming a scientist didn’t quite mesh with my lack of affinity for lab work. Thinking on my decision to pursue biology rather than English at age 15 – despite an aptitude for the latter – I realized that science writing was a way to combine what I loved with what I was good at.

From there I set out to gather as much freelancing experience as I could, spending 2 years developing scientific content for International Innovation, before completing an MSc in Science Communication. After gaining invaluable experience in supporting the communications efforts of CERN and IN-PART, I joined Texere – where I am focused on producing consistently engaging, cutting-edge and innovative content for our specialist audiences around the world.


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