The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Mass isotopomer distribution analysis: a technique for measuring biosynthesis and turnover of polymers
Abstract
Mass isotopomer distribution analysis (MIDA) is a technique for measuring biosynthesis and turnover of polymers in vivo. A stable isotopically enriched precursor is administered, and the relative abundances of different mass isotopomers in the polymer of interest are measured by mass spectrometry (MS). By comparison of statistical distributions predicted from the binomial or multinomial expansion to the pattern of excess isotopomer frequencies observed in the polymer, the enrichment of the biosynthetic precursor subunits (p) for newly synthesized polymers is calculated. MIDA thereby provides a solution to the problem of determining the isotope content in the actual precursor molecules that entered a particular polymeric product (the “true” precursor). The fraction of polymer molecules in a mixture that were newly synthesized during an isotopic experiment (fractional synthesis) can then be calculated. We describe some mathematical characteristics of MIDA and point out certain advantageous features. For example, mathematical estimates of p remain valid even if there does not exist a single anatomic or functional precursor pool. The interpretation of decay curves of endogenously labeled polymers may be improved by the use of higher mass isotopomers, which better fulfill the assumption of flash labeling. By combining fractional synthesis values with rate constants of decay, absolute endogenous synthesis rates can be calculated. Thus, by using probability logic combined with MS analysis, MIDA allows dynamic measurements to be made through analyses on a polymer alone during both isotopic incorporation and decay phases. The method has been applied to fatty acids, cholesterol, and glucose and is potentially applicable to nucleic acids, porphyrins, perhaps proteins, and many other classes of polymers.
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Metadata
- Authors
- Hellerstein, M. K., & Neese, R. A.
- Venue
- American Journal of Physiology-Endocrinology and Metabolism
- Publisher
- American Physiological Society
- Published
- 1992-11-01
- Volume
- 263
- Issue
- 5
- Pages
- E988-1001
- ISSN
- 0193-1849 (ISSN-L)
- 1522-1555
- OpenAlex
- W1862881433
- Cited by
- 283
- References
- 16
- FWCI
- 0.76
- Type
- journal article
- Language
- en
- Open access
- closed
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