This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Isotope variability due to natural processes provides important information for studying a variety of complex phenomenon like determining the genesis of a given sample, dietary studies of species, nitrification rates in trees etc. These measurements require very high-precision determination of isotope ratios of a particular element involved. Isotope Ratio Mass Spectrometers (IRMS) are widely employed tools for such a high-precision analysis. IRMS instruments accept the sample analyte in the form of only a limited number of gases which must represent the isotopic characteristics of the original sample, which causes lack of flexibility. This work aims at overcoming the limitations inherent to IRMS by estimating the elemental isotopic abundance from the experimental isotopic distribution.Experimental isotopic distribution is an indirect measure of the isotopic abundances of various elements present in the molecule. It can be represented by the joint convolution of the isotopic abundances of each of the individual atoms. Mathematical techniques have been developed in order to factor out the known isotopic abundance contributions from various elements followed by calculation of the corresponding unknown values for the element of interest. An estimate for the required isotopic abundance is generated from each of the observed isotopic peaks by solving the convolution equations, and the final result is reported to be the mean of each of the individual values obtained.Computer generated simulations were carried out in order to generate the experimental isotopic distributions for a given molecule with known elemental composition and isotopic abundances. The results thus obtained were subjected to the developed theoretical framework in order to estimate the isotopic abundance for Carbon from each isotopic peak, with the abundance values for the other elements being taken into consideration in the calculation. These estimated results are shown to be in good agreement with their true values. Increasing the number of ions for generating the experimental isotopic distribution greatly improves the estimate. This is because in the limit of infinite number of ions, experimental isotopic distribution approaches its theoretical counterpart and is a true representative of the composition of its constituents. High molecular weight molecules are shown to be particularly advantageous because of the presence of larger number of isotopic peaks in the isotopic distribution leading to a greater amount of information. Initial results reveal that with sufficiently high number of ions and multiple experiments, it is possible to distinguish between the samples varying very slightly in the Carbon isotopic abundance. For example, the estimate can distinguish whether the sample originated from marine plankton (C13 abundance = 1.09%, Delta C13=-19.5) or meat from an animal feeding on a C4 plant (C13 abundance=1.1%, Delta C13=-12.5). Results from the experimental data will be presented comparing the true abundance value with its estimated counterpart. This approach eliminates the need to convert the sample into gaseous form. The results are applicable to any type of mass spectrometer, and for any type of sample. The results can also be extended to estimate the isotopic abundance of any unknown element provided the isotopic abundance of the other elements are known a priori.A paper was published detailing the method and calculations in Analytical Chemistry.

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Lu, Yanyan; Jiang, Yan; Prokaeva, Tatiana et al. (2017) Oxidative Post-Translational Modifications of an Amyloidogenic Immunoglobulin Light Chain Protein. Int J Mass Spectrom 416:71-79
Sethi, Manveen K; Zaia, Joseph (2017) Extracellular matrix proteomics in schizophrenia and Alzheimer's disease. Anal Bioanal Chem 409:379-394
Hu, Han; Khatri, Kshitij; Zaia, Joseph (2017) Algorithms and design strategies towards automated glycoproteomics analysis. Mass Spectrom Rev 36:475-498
Ji, Yuhuan; Bachschmid, Markus M; Costello, Catherine E et al. (2016) S- to N-Palmitoyl Transfer During Proteomic Sample Preparation. J Am Soc Mass Spectrom 27:677-85
Hu, Han; Khatri, Kshitij; Klein, Joshua et al. (2016) A review of methods for interpretation of glycopeptide tandem mass spectral data. Glycoconj J 33:285-96
Pu, Yi; Ridgeway, Mark E; Glaskin, Rebecca S et al. (2016) Separation and Identification of Isomeric Glycans by Selected Accumulation-Trapped Ion Mobility Spectrometry-Electron Activated Dissociation Tandem Mass Spectrometry. Anal Chem 88:3440-3
Wang, Yun Hwa Walter; Meyer, Rosana D; Bondzie, Philip A et al. (2016) IGPR-1 Is Required for Endothelial Cell-Cell Adhesion and Barrier Function. J Mol Biol 428:5019-5033
Srinivasan, Srimathi; Chitalia, Vipul; Meyer, Rosana D et al. (2015) Hypoxia-induced expression of phosducin-like 3 regulates expression of VEGFR-2 and promotes angiogenesis. Angiogenesis 18:449-62
Yu, Xiang; Sargaeva, Nadezda P; Thompson, Christopher J et al. (2015) In-Source Decay Characterization of Isoaspartate and ?-Peptides. Int J Mass Spectrom 390:101-109
Steinhorn, Benjamin S; Loscalzo, Joseph; Michel, Thomas (2015) Nitroglycerin and Nitric Oxide--A Rondo of Themes in Cardiovascular Therapeutics. N Engl J Med 373:277-80

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