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With Nonlinear Deal, Waters Seeks Improved Informatics for Data-Independent MS, 'Omics Integration


(This story originally ran on Aug. 9.)

Waters' recent software development deal with informatics firm Nonlinear Dynamics marks an effort by the firm to maximize the utility of its ion mobility mass spec technology for proteomics and metabolomics research, the company told ProteoMonitor this week.

The agreement, which the company announced last week, calls for Waters and Nonlinear to co-develop new software to analyze data from large-scale proteomics and metabolomics experiments and, especially, to develop algorithms to more fully utilize "the ion mobility information" generated by the firm's Synapt mass spec systems, said James Langridge, Waters' director of proteomics.

Langridge suggested the companies' development efforts would focus in particular on data-independent acquisition mass spec and integration of data across 'omics disciplines – both areas that are emerging as significant points of interest for mass spec vendors (PM 5/25/2012 and PM 6/8/2012).

Waters' ion mobility technology uses a neutral buffer gas to separate ions prior to mass spec analysis, offering an additional dimension of separation to conventional LC-MS. The company introduced a first-generation version of the technology in 2006 and an updated version in 2009, but, Langridge said, it has "never really been able to get to all of the information contained in [ion mobility] datasets."

"We see a lot of potential value in the [ion mobility] technology, but the reality is that you need good underlying algorithms to take advantage of it," he said, noting that that Nonlinear deal was aimed at addressing this need.

Langridge suggested that Waters' move to improve the informatics surrounding its ion mobility mass spec was driven in part by growing researcher interest in data-independent mass spec and, particularly, its use for targeted, quantitative applications.

As opposed to data-dependent mass spec, in which the mass spectrometer performs an initial scan of precursor ions entering the instrument and selects a sampling of those ions for fragmentation, data-independent mass spec selects broad m/z windows and fragments all precursors in that window, allowing researchers to collect MS/MS spectra on all ions in a sample and simultaneously obtain both qualitative and quantitative data.

Data-independent acquisition techniques have been around since 2004, with Waters among the first mass spec vendors to market a proprietary DIA method, introducing in 2006 its MSE technique, which relies on its ion mobility technology to divide samples into isolation windows for DIA analysis.

Yet, while DIA methods have existed for nearly a decade, widespread interest in extracting targeted, quantitative information from DIA data sets is a more recent phenomenon.

As University of Washington researcher Michael MacCoss told ProteoMonitor in an interview on DIA mass spec earlier this year, "The data acquisition that is occurring now is no different than what's been done since 2004. The thing that's different is that more recently the data analysis has changed to: Can we find peptide X in this data? As opposed to, let's try to find signals and [make peptide IDs.]"

MacCoss noted that AB Sciex became the first vendor to package and push a solution for these targeted workflows when it released its TripleTOF 5600+ instrument featuring its Swath data-independent acquisition technique at this year's American Society for Mass Spectrometry annual meeting. Langridge suggested that Waters' deal with Nonlinear was in part a response to such increased interest on the part of customers and competitors.

"Other companies are [now] looking to understand how they can take account of data-independent acquisition," he said. "We've had a history for quite some time with this kind of approach, and we're constantly looking to stay ahead in this area. This [deal] allows us to start to use start-of-the-art informatics tools to really dig into these [DIA] data sets."

"I think there's a lot of interest there because, while you kind of think of two workflows – the discovery aspect and the targeted aspect – some of that is going to merge in the future," he added. "People are saying, "I want to monitor certain proteins, but I also really want to know what's happening off target. I think that's why these types of strategies are going to be really powerful in the future."

In addition to the shift toward interrogating DIA data for targeted information, the Nonlinear deal is also emblematic of growing interest in integrating data from different 'omics disciplines – in this case proteomics and metabolomics.

The first product of the companies' collaboration is Waters' TransOmics software, a package intended for integration of proteomic, metabolomic, and lipidomic data that the firm introduced in May at ASMS.

"I think it's quite apparent that by looking at multiple levels – you look at the genome, you look at the proteome or metabolome – by looking at how those research domains and the data correlate, you get a better underlying picture of the biology and what's going on," Langridge said. "There might be cases where you can't differentiate disease from control using a proteomic approach, but you can at the metabolite level, or vice versa. So I think that's why you'll see increasingly that as capabilities improve, you'll see informatics platforms starting to try to integrate these types of data."

"Our goal is to develop the bedrock for quantitative proteomics and quantitative metabolomics experiments," he said. "They've been very separate disciplines … but I think what you see increasingly is that proteomics researchers in particular are interested in accessing metabolomic capabilities – being able to run those types of samples for systems biology-type experiments."

The co-development agreement, Langridge noted, has an initial three-year timeframe, but, he said, Waters expects to extend this window and hopes for a long-term collaboration.

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