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Nestlé Builds Automated Mass Spec Workflow for High-Throughput Discovery Proteomics

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NEW YORK (GenomeWeb) – Researchers at the Nestlé Institute of Health Sciences in Lausanne, Switzerland have put together a high-throughput platform for mass spec-based discovery proteomics.

The platform, which consists of an almost fully automated sample preparation system linked to nano-LC and a Thermo Fisher Orbitrap Elite instrument can run on the order of 1,000 isobarically labeled samples in 15 weeks, Loïc Dayon, a proteomics and metabolomics researcher at NIHS and one of the developers of the platform, told GenomeWeb.

The effort, which Dayon and his colleagues detailed in a paper published this month in the Journal of Proteome Research, is an example of the ongoing move within mass spec-based proteomics toward automation with the aim of upping throughput and improving reproducibility.

More specifically, the platform is an example of the automatizing of discovery proteomics workflows, which have typically been run at lower throughput than validation and clinical workflows.

Indeed, much of the proteomics community's concerns around mass spec assay throughput has revolved around targeted validation work and actual clinical assays. For instance, in a presentation at the 2011 Mass Spectrometry: Applications to the Clinical Lab annual meeting, SISCAPA Assay Technologies CEO Leigh Anderson called out the field's then inability to run the number of samples needed to sufficiently validate clinical biomarker assays.

"I'm a little bit embarrassed to say that in the 5,000 or 10,000 papers on biomarker proteomics, I don't know of a single one in which anybody has actually run 1,000 samples," he said. "And it's well known in the diagnostics community that if you can't run a few thousand samples, you can't know if a biomarker is clinically relevant. So this is a huge limitation that we need to overcome. Robustness and automation are becoming major barriers to applying this kind of [proteomic] methodology to solving our problems."

Since then, the throughput of targeted proteomic assays has significantly improved as researchers and vendors have managed to automate large portions of these workflows. Today, numerous academic and industry parties have run validation trials consisting of several thousand samples and at least two firms, Integrated Diagnostics and Sera Prognostics, have launched clinical MRM-MS proteomic assays.

Discovery proteomics experiments, however, often still consist of relatively few samples, which, the JPR authors noted, can lead to "compromised study designs and insufficient statistical power." These initial small sample sizes, they added, often lead to findings that then cannot be replicated in larger validation trials.

In their facility, Dayon and his colleagues have sought to improve this situation by employing the sort of automation that has in recent years become a more common part of targeted workflows.

The NIHS platform consists of a manual depletion step followed by automated sample reduction, alkylation, overnight digestion, and isobaric labeling with six-plex Tandem Mass Tags. This is followed by a three-hour LC gradient and then mass spec analysis.

According to Dayon, the system as currently configured can process 200 samples every three weeks: one week for the manual depletion, a second week for the sample prep (consisting of two 96-well plates processed sequentially), and then a third week for the LC-MS/MS analysis.

He noted, as well, that there remain several points in the assay where throughput might be further improved. The most significant improvement, he said, would come from adapting the depletion step so that it could be done in a 96-well plate format, allowing many samples to be depleted in parallel and enabling use of a robotics system for the work.

In addition, Dayon said, the system has the capacity to do the automated sample prep steps on two 96-well plates at once, as opposed to sequential as was done in the JPR study.

In that study the researchers used the platform to look at 1,000 samples from the Diet, Obesity, and Genes Dietary Study (Diogenes), a dietary intervention study looking at factors including weight gain and cardiovascular risk in obese families across eight European centers, tracking body mass index-associated proteins and gender-specific proteins at two time points.

Their results, they said, demonstrated that "analyzing a large number of human plasma samples for biomarker discovery with [mass spec] using isobaric tagging is feasible, providing robust and consistent biological results."

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