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Thermo Fisher, Sciex Unveil Additions to Cloud Computing Platforms at ASMS 2015


NEW YORK (GenomeWeb News) – With an eye toward improved pathway and multi-omic analyses, Sciex and Thermo Fisher Scientific presented additions to their cloud computing offerings at the American Society for Mass Spectrometry annual meeting this week in St. Louis.

Sciex officially launched the commercial version of its OneOmics collaboration with Illumina, a project that aims to combine mass spec-based proteomics data with next-generation sequencing.

Thermo Fisher, meanwhile, added a proteomics data module to its Thermo Fisher Cloud platform, a move that was "a downpayment" on its ultimate goal of more fully integrating its mass spec-based proteomics and next-generation sequencing assets, Ken Miller, the company's vice president of marketing for life science mass spectrometry, told GenomeWeb.

The Thermo Fisher Cloud currently includes data modules for Sanger sequencing and quantitative PCR — along with the proteomics module announced this week — but does not yet contain a module for NGS data.

Having acquired the Ion Torrent NGS technology through its 2013 purchase of Life Technologies, Thermo Fisher appeared the best positioned among mass spec vendors to develop and commercialize workflows for the growing proteogenomics field, which aims to combine genomic and proteomic analyses.

Sciex, however, beat Thermo Fisher to the punch with its OneOmics collaboration with Illumina, which the company announced last year. Under that collaboration, Sciex placed its Swath Proteomics Cloud Tool Kit, a suite of informatics tools for use with the company's Swath mass spec technology, in Illumina's BaseSpace cloud computing environment, allowing researchers to integrate proteomic and NGS analyses.

Proteogenomics has in recent years become a fast growing research area, with projects like the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium combining protein biomarker discovery with genomic characterization, and a number of high-profile studies using proteogenomic analyses to search deeper into the proteome and contribute to genome annotations.

The rise of such approaches is based significantly on the ability of researchers to use NGS sequencing, and RNA-seq in particular, to generate sample-specific search databases for their proteomic analyses. This allows researchers to identify protein forms not present in conventional generic search databases, such as alternative splice forms, which they can then annotate on the genomic level. It also has the potential to improve the depth of coverage and peptide matching by restricting the search space to protein forms actually present in the particular sample being investigated.

This week, Sciex announced that it has expanded the OneOmics program beyond an initial group of roughly 50 beta users to the larger research community.

In addition to the Swath Proteomics Cloud Tool Kit, the OneOmics platform hosts apps developed by outside researchers. A key goal for the effort moving forward will be to foster development of such apps, noted Aaron Hudson, senior director of academic and clinical research business at Sciex.

"We really are pushing to get the omics community to develop apps on top of this [platform] to start to integrate these omics data together," he said.

Currently, Hudson added, the OneOmics system hosts around half a dozen apps, including one developed by Yale University researcher Christopher Colangelo for integrating RNA-seq and Swath data, which enables generation of sample-specific proteomic search databases from RNA-seq data; and the Institute for Systems Biology's SwathAtlas, a tool for planning Swath experiments and depositing and searching Swath datasets. It also includes Advaita Bioinformatics' iPathwayGuide App, which enables pathway analysis and drug and disease analysis of mass spec-based proteomic and NGS data.

The current version of the OneOmics platform supports only Swath mass spec data. In an interview with GenomeWeb following the initial launch of the platform, Hudson said that Sciex had led with this form of mass spec due to its high reproducibility, which made it well suited to integration with NGS data.

"You can run 100 samples and quantify and identify a few thousand proteins reproducibly, so that starts to bring [proteomics] into the kind of capabilities Illumina has had for a while with RNA-seq and the next-gen sequencing," he said.

Hudson said this week that Sciex is now working to add modules supporting other forms of mass spec proteomics data.

Thermo Fisher's addition of proteomics to its cloud computing platform allows researchers to integrate protein data with the Sanger sequencing and qPCR analysis tools already supported by the platform.

It also facilitates pathway analysis based on proteomic data, "translating mass spectrometry into the language of biology, which is pathways," Miller said. Using the new proteomics module, researchers can identify differentially represented proteins and pathways from their experiments for follow up via other omics analyses or additional proteomics work.

The platform runs on the Amazon Web Services Cloud. Researchers can obtain free 10GB cloud accounts.

The Sciex and Thermo Fisher cloud efforts are part of a larger trend within proteomics toward cloud computing. Proteomics has traditionally lagged behind genomics in its use of cloud computing, but as datasets grow larger due to improved instrumentation and higher-throughput workflows, and researchers continue to explore proteogenomics and other multiomic analyses, the approach has become a more attractive option.

Most notably, last year, ISB researchers developed cloud functionality for the Trans-Proteomic Pipeline mass spec informatics suite, one of the most widely used proteomics informatics tools.

The TPP suite, which runs on Amazon Web Services, includes applications for mass spec data representation and visualization as well as peptide identification and validation, protein inference, quantification, spectral library building and searching, and biological inference. In a demonstration of the cloud-based TPP system, the ISB researchers processed 1,100 mass spec runs through four different search engines in 9.5 hours and at a total cost of less than $100.

In an interview with GenomeWeb upon launch of the TPP cloud suite, ISB researcher Eric Deutsch said he expected cloud computing for proteomics would continue to grow in popularity as prices declined and dataset sizes increased. He also cited the increased interest in proteogenomics and the significant computing resources required for such work as driving adoption of cloud computing by the field.

In addition to the TPP development, a team led by University of Washington researcher Michael MacCoss has developed the Chorus cloud application which allows researchers to store, analyze, and share mass spec data of any file type.

Scientists including MacCoss, the University of Pittsburgh's Nathan Yates, and InfoClinika President and CEO Andrey Bondarenko founded the non-profit Stratus Biosciences to manage the Chorus project, which also uses Amazon Web Services.

Launched at the 2013 ASMS meeting, the platform now supports 1,086 user accounts and holds more than 20 terabytes of mass spec proteomics data.