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Use of Fibonacci numbers in lipidomics - Enumerating various classes of fatty acids.

ABSTRACT: In lipid biochemistry, a fundamental question is how the potential number of fatty acids increases with their chain length. Here, we show that it grows according to the famous Fibonacci numbers when cis/trans isomerism is neglected. Since the ratio of two consecutive Fibonacci numbers tends to the Golden section, 1.618, organisms can increase fatty acid variability approximately by that factor per carbon atom invested. Moreover, we show that, under consideration of cis/trans isomerism and/or of modification by hydroxy and/or oxo groups, diversity can be described by generalized Fibonacci numbers (e.g. Pell numbers). For the sake of easy comprehension, we deliberately build the proof on the recursive definitions of these number series. Our results should be of interest for mass spectrometry, combinatorial chemistry, synthetic biology, patent applications, use of fatty acids as biomarkers and the theory of evolution. The recursive definition of Fibonacci numbers paves the way to construct all structural formulas of fatty acids in an automated way.

SUBMITTER: Schuster S

PROVIDER: S-EPMC5223158 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Use of Fibonacci numbers in lipidomics - Enumerating various classes of fatty acids.

Schuster Stefan S Fichtner Maximilian M Sasso Severin S

Scientific reports 20170110

In lipid biochemistry, a fundamental question is how the potential number of fatty acids increases with their chain length. Here, we show that it grows according to the famous Fibonacci numbers when cis/trans isomerism is neglected. Since the ratio of two consecutive Fibonacci numbers tends to the Golden section, 1.618, organisms can increase fatty acid variability approximately by that factor per carbon atom invested. Moreover, we show that, under consideration of cis/trans isomerism and/or of ...[more]

PMID: 28071669

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Project description:Branched fatty acid esters of hydroxy fatty acids (FAHFAs) are an important family of endogenous lipids, possessing antidiabetic and anti-inflammatory functions. Therefore, analysis of FAHFAs in biological samples obtained under healthy and disease states can uncover underlying mechanisms of various relevant disorders (e.g., diabetes and autoimmune diseases). Up to now, due to their extremely low abundance, the determination of the changed levels of these species is still a huge challenge, even though great efforts have been made by utilizing liquid chromatography-tandem mass spectrometry with or without derivatization. Herein, we described a novel method for analysis of FAHFAs present in lipid extracts of biological examples after solid-phase extraction and chemical derivatization with one authentic FAHFA specie as an internal standard based on the principles of multi-dimensional mass spectrometry-based shotgun lipidomics. The approach possessed marked sensitivity, high specificity, and broad linear dynamic range of over 3 orders without obvious matrix effects. Moreover, after chemical derivatization, the molecular masses of FAHFAs shift from an overlapped region with ceramide species to a new region without overlaps, removing these contaminating signals from ceramides, and thereby reducing the false results of FAHFAs. Finally, this novel method was successfully applied for determining FAHFAs levels in varieties of representative biological samples, including plasma from lean and overweight/obese individuals of normoglycemia, and tissue samples (such as liver and white adipose tissue from diabetic (db/db) mice). We revealed significant alterations of FAHFAs in samples under patho(physio)logical conditions compared to their respective controls. Taken together, the developed method could greatly contribute to studying altered FAHFA levels under a variety of biological/biomedical conditions, and facilitate the understanding of these lipid species in the patho(physio)logical process.

Dataset Information

Use of Fibonacci numbers in lipidomics - Enumerating various classes of fatty acids.

Publications

Use of Fibonacci numbers in lipidomics - Enumerating various classes of fatty acids.

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