Comparing apples to Apples
SAN FRANCISCO—IO Informatics, a leader in semantic data integration and knowledge management for life sciences and healthcare, will partner with Sage-N Research Inc., a company that specializes in computational proteomics, in an agreement announced last month.
The combination of the two companies' technologies creates a semantic application framework that is being used to quickly develop a highly specialized, large-scale application that leverages mass-spectrometry based proteomics with “unmatched content enrichment, interoperability and flexibility only possible with semantic data integration,” the release announcing the partnership states.
“Semantic data integration means putting data in context,” explains Dr. Erich Gombocz, IO’s chief scientific officer. “I use the example of an apple. ‘How much does an apple cost?’ is totally dependent on if you mean the fruit or the computer; without that context, you really cannot answer this question. The same holds true in a much more stringent way for biological data; data out of context is isolated and of no actionable use, but data in context of other data provides the meaningful underlying framework to understand complex interactive and interrelated intricate biological processes on a systems level. Because our technology is based on the Resource Description Framework, its data structure does not require predefined schemas, but is based in its entirety on triples—sets of resources commonly described in form of ‘A is related to B’ (or, more formally, as subject, predicate, object). Data becomes aware of their surroundings—they are ‘sentient’ of how to connect and what they mean in their context, thus the name of IO’s tools, ‘Sentient Suite.’ Because of this dynamic extensible and data-container agnostic framework, data can be mapped to ontological concepts and are easily reconfigured to changing scientific needs.”
Most importantly, Gombocz believes, since a semantic knowledge base is a network graph of data in their relationships with each other, it enables discovery of pattern-based relationship clusters and interactions that were not previously apparent. Graphic icons represent proteins, diseases and organisms, for example, with the colors and thicknesses of connecting lines indicating relative strength of the relationships.
The technology also allows users to infer and reason across the graph, and to create pattern-based queries containing, for instance, signatures for a specific biological function (such as biomarkers used as disease profile for a certain stage of a disease or a certain demographic patient group with a specific genetic profile).
“With the ever-growing Linked Open Data (LOD) in semantic format, IO’s technology provides tools to build and enrich knowledge bases for specific user needs—such as liver toxicity categorization, comparative effectiveness of cancer treatments, risk assessment of organ transplant failures or differentiation of stable versus ruptured plaques in cardiac diseases, which are all cases where IO has applied its technologies in the past. This way, knowledge is never stale; it can keep pace with scientific advances, and is actually actionable—you can use it as decision support in screening and diagnostic or therapeutic applications,” Gombocz says.
Currently, there are about 45 public databases in use by IO that contain information on organisms, pathogens, genes and proteins.
“One application of this novel approach is to identify peptides from different microorganisms with a common mechanism of actions, and to categorize them as potential biomarkers, and it also has the capability to detect microbial threats prior to onset of disease symptoms,” says Ali Pervez, vice president of marketing at Sage-N Research.
“Future applications of this technology will enable automated screening for biological threats, to characterize origin and type of disease and to develop preventive measures (drugs or vaccines) effective for several classes of microorganism,” adds Robert Stanley, president of IO.
“Together with IO’s semantic knowledge base concept, Sage-N’s Sorcerer and IO’s Sentient Knowledge Explorer and Sentient WebQuery allow us to pre-package entire knowledge bases of biological systems through meaningful interconnection of experimental and public data resources under a common architectural framework,” Gombocz notes. “The partnership has been a logical synergistic extension of capabilities through combination of innovation from both sides. IO Informatics, together with its collaborators and customers, has been instrumental in the arena of biomarker discovery and qualification, and Sage-N has been leading in spectra-based ID research for microbial pathogens. The partnership extends the efforts towards a deeper understanding of peptide- and protein-related mechanistic impact on disease-related pathways based on systems biological network views—all areas which require expertise in high-throughput workflows, scalability and dynamic knowledge building towards real-time actionable applications which account for alerting and decision support via web and mobile platforms.”
Sage-N teams with Pressure BioSciences on analysis of cell membrane proteins
SOUTH EASTON, Mass.—Sage-N Research Inc. also announced March 19 that it will collaborate with Pressure BioSciences Inc. (PBI) to develop software applications on Sage-N’s SORCERER Integrated Data Appliance platform. The new software will be designed to work with PBI’s patented and enabling pressure cycling technology (PCT) system, a technology platform that is used to extract, among other biomolecules, integral cell membrane and other proteins for subsequent mass spectrometry analysis.
According to the companies, these proteins are of significant clinical importance due to their roles in cell signal transduction in cancer, membrane transport disorders like Crohn’s disease, pathogen invasion such as HIV and their roles in other diseases and disorders. Unfortunately, integral cell membrane proteins are traditionally very difficult to extract. In some cases, harsh chemicals are used in the extraction process, causing such severe protein degradation that subsequent proteomic analysis is compromised.
PBI’s PCT platform uses rapid cycles of low and ultra-high pressure to safely and effectively extract proteins from samples (including cell membranes) that are suitable for analysis by analytical methods such as mass spectrometry. The PCT platform also provides a high level of automation, speed and reproducibility in the enzymatic breakdown of proteins. This allows the PCT-enhanced digestion to be completed in under an hour, compared to the standard four to 12 hours, according to PBI.
Sage-N’s SORCERER Integrated Data Appliance platform provides complementary software applications that are customized for each particular sample preparation chemistry. This results in a semi-automated system for membrane and other protein analysis that can use any modern tandem mass spectrometer and liquid chromatography system, says Sage-N.
“We plan to seamlessly integrate PBI’s front-end PCT Sample Preparation System—instruments and consumables—with Sage-N’s SORCERER back-end data reduction software,” explains Richard T. Schumacher, president and CEO of PBI. “We expect to offer this bundled platform as an option to stand-alone sample preparation and data reduction methods used currently by the mass spectrometry laboratory. We believe that by bundling these enabling platforms, we will be offering a higher quality, more efficient and less costly solution than they currently have for sample preparation and data reduction. Since the companies now target an identical market—the mass spectrometry laboratory—we expect to share a number of marketing and selling programs directed at this market going forward. Overall, we believe our new co-marketing program will reduce costs and increase sales for both PBI and Sage-N before the end of 2012.”