Highly automated and accurate analysis of pesticides residuals is essential to ensure the safety of human foods and animal feeds. Recent advancement in High Resolution Mass Spectrometry (HRMS) hardware systems have made it possible to screen for hundreds of these target compounds within a single LC/MS run, without the time-consuming method development or maintenance required of the conventional LC/MS/MS analysis. To make HRMS compound screening practically useful, a highly efficient and accurate software system is urgently needed to minimize both the false positives and the false negatives and to perform accurate quantitation. Cerno Bioscience (Cerno) will meet these challenges by applying advanced multivariate computational techniques and the uniquely suitable MS peak shape calibration technology it has developed so that full MS spectral information, accurate not only in mass (m/z) but more importantly in MS spectral profiles, can be brought to bear for these complex samples. In addition to the elimination of false positives above and beyond mass accuracy, spectral accuracy can reduce or eliminate false negatives by relaxing the often aggressive requirement on mass accuracy. When multivariate computational techniques are applied to such fully calibrated MS profile data, it is feasible to detect and eliminate the far moe harmful false negatives seen in complex food samples due to the inevitable mass spectral overlaps. As an added advantage, such fully calibrated MS data will also enable mass spectral domain quantitation and avoid the error-prone process of chromatographic peak area integration. During Phase I of this project, Cerno will: 1) develop advanced multivariate computational techniques for efficient processing of calibrated mass spectral data;2) implement the computational techniques in a software prototype for highly accurate mass spectral screening of hundreds of compounds in complex food matrices;3) investigate with up to 800 standard compounds added into actual food matrices and fully establish the proof-of-principle. In Phase II, Cerno will: 1) expand to actual food safety analysis by working with its academic and industrial partners;2) expand MS data system support to include at least three major HRMS suppliers'instruments;3) build a commercial software product for HRMS screening of actual food products;4) commence alpha and beta testing and seek feedback from 3-5 pesticide residue analysis laboratories. Upon successful completion of Phase II, Cerno will work with its academic and industry partners to launch this innovative software solution and make it available to food safety scientists working in both government and industry laboratories.

Public Health Relevance

The wider availability of fast scanning HRMS systems offers an attractive solution for high throughput screening of a large number of compounds but also presents a number of technical challenges including data processing, detection and elimination of false positives and false negatives, and accurate quantitation. Cerno Bioscience will investigate the application of advanced multivariate computational techniques and the spectral accuracy concept to meet these challenges. The unique and novel approach Cerno will develop under this project will make high throughput HRMS screening practically viable and thus have a profound and immediate impact on food safety in particular and the public health in general.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
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Special Emphasis Panel (ZRG1-IMST-G (10))
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Sheeley, Douglas
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Cerno Bioscience
United States
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