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ETH Zurich Team Uses NMR for Multi-Omic Analysis of RNA Folding Network


NEW YORK – Researchers from the Swiss Federal Institute of Technology (ETH) Zurich have used what they call a "systems NMR" approach to generate multiple levels of omics data that characterize a biological network.

Described in a paper published this week in Nature Methods, the approach uses nuclear magnetic resonance (NMR) spectroscopy to dynamically quantify the components of a co-transcriptional RNA folding network, simultaneously measuring RNA, proteins, and metabolites and various of their interactions.

According to Yaroslav Nikolaev, an ETH Zurich researcher and corresponding author on the paper, the study revealed a number of previously unobserved interactions between components of the network while also demonstrating the potential utility of such NMR-based experiments.

NMR uses magnetic fields to perturb the nuclei of analytes being observed, causing them to produce a signal that can be used for identification and quantification. While NMR spectroscopy has numerous life science applications, it is more commonly used for research in areas like chemistry and physics, Nikolaev said.

However, he said, the technology has certain qualities that could make it attractive for broader applications in life sciences research.

Compared to mass spectrometry, for example, the signals recorded by NMR are more reproducible and quantitative, Nikolaev said.  "In mass spec, different molecules ionize differently, and results often depend on the instrument condition, so you need more calibrations. In NMR, the signals of different molecules can be directly and quantitatively compared with each other, and results are much more reproducible, independent of instrument type and condition."

Additionally, NMR allows for non-destructive monitoring of analytes. "So you could have a sample of live cells and look at what is going on inside of them in a time-resolved manner without destroying them," he said.

NMR is hampered by its relatively poor sensitivity, however. "With conventional NMR, you currently need around micromolar concentrations to be able to detect things," Nikolaev said. "So we can't exploit it to quantify certain molecules at exact physiological concentrations. Which is why purification and/or enrichment of target molecules is often needed for NMR."

Nonetheless, Nikolaev said he believed the systems NMR approach he and his colleagues described could help fill the gap between biochemical assays, "where you take one purified biomolecule and look at its functional mechanisms in detail," and omics-based approaches "where you try to observe everything" but without collecting in-depth mechanistic information.

"Systems NMR could give you the possibility to look at intermediate complexity networks in greater mechanistic detail than omics does," he said. "That is one of the things we've tried to do with this paper – to put that idea in peoples' minds."

In their experiment, Nikolaev and his colleagues used NMR to study co-transcriptional RNA folding, a process through which identical RNA molecules can form different folded structures depending on what effector molecules are available during transcription. As the authors noted, the main reactions in this process are "RNA synthesis from metabolites, RNA folding, and protein–RNA interactions." Using NMR, they were able to simultaneously and dynamically monitor the metabolites, RNA, and proteins involved, as well as their interactions.

Studying the system in vitro, the researchers could monitor the eight-reaction network across 35 time points, observing phenomena that included non-specific protein-RNA and nucleotide-RNA binding and the phase separation of proteins during RNA transcription.

The latter occurrence has "become a big focus in cellular biochemistry in recent years," Nikolaev said. "The ability of proteins and RNA to phase-separate into membrane-less compartments inside cells is very important for cellular organization, and we were able to observe such phase separation in the relatively small network of five proteins and one RNA. Now we have an experimental system where we can look at structural and mechanistic details of this process in vitro."

He suggested this was an example of the kind of "emergent network properties" a systems NMR approach could help study.

"Our expectation is that the more people try to look at these bigger networks, the more of these kinds of emergent properties they will see," he said. "At the moment, if you look at things biochemically, you will usually have only one or two molecules in your experiment. But if you have 10 or 15 different kinds of molecules and you quantify what is going on with them and make a mathematical model from the data, then you'll probably see things that you didn't expect."

Nikolaev said he and his colleagues have since begun looking at similar networks in cell lysate and were likewise able to observe the formation of RNA and RNA-protein interactions in that environment.

The ultimate step, he added, would be using a combination of systems NMR and in-cell NMR to quantify such processes in live cells, though he noted that for true in-cell NMR (as opposed to work in cell lysates), "the efficiency of methods for delivery of NMR-labeled molecules into living cells still needs to be improved, as labeling is required to distinguish molecules of interest from the overall cellular background."

Nikolaev said that moving forward, he sees NMR studies of crosstalk between protein signaling and metabolism as particularly exciting.

"If you have proteins and metabolites involved in a network, then by exploiting the ability to look at both at the same time with high dynamic resolution, you will probably gain a lot of insight," he said. "With signaling, the cells are sensing their environment and then often rewiring their metabolism to adapt to this environment, and I think combining quantification on signaling proteins and metabolic pathways is an area with great potential."

Firms like Nightingale Health and Numares are using NMR for clinical research and development of metabolite-based tests for conditions like cardiovascular disease and cancer, but NMR's penetration into life sciences research remains limited. Bruker, the dominant vendor in the space, has a broad life sciences portfolio, but Nikolaev said its NMR business is more focused on applications in chemistry.

"I think NMR is still underexploited in biological applications, beginning with the fact that we don't really learn much NMR during our [undergraduate and graduate] biology studies," he said. "My belief is it can be exploited much more in biochemistry and systems biochemistry applications."

He added that the journey of mass spectrometry from being largely a tool of physicists and chemists to its current role as a key life sciences technology might provide a template of sorts for NMR.

"At the end of the 1990s, few could have predicted that [mass spec] would be used for proteomics and life science so much," he said. "So perhaps we see now the potential for this sort of application in NMR."