Holistic Lipidomics of the Human Gut Phenotype Using Validated Ultra-High-Performance Liquid Chromatography Coupled to Hybrid Orbitrap Mass Spectrometry.

As lipids are assigned a plethora of biological functions, it is evident that dysregulated lipid metabolism signifies a key element in many pathological conditions. With this rationale, this study presents a validated lipidomics platform to map the fecal lipidome, which integrates unique information about host-gut microbiome interactions, gastrointestinal functionality, and dietary patterns. This particular method accomplished coverage across all eight lipid categories: fatty acyls, glycerolipids, phosphoglycerolipids, polyketides, prenols, saccharolipids, sphingolipids, and sterols. Generic extraction of freeze-dried feces was achieved by solid-liquid extraction using methanol and methyl tert-butyl ether. Extracted components were separated by liquid chromatography, whereby the selected ethylene-bridged hybrid phenyl ultra-high-performance liquid chromatography stationary phase allowed fast separation of both individual lipid species and categories. Detection was achieved by high-resolution full-scan Q-Exactive Orbitrap mass spectrometry and covered a broad m/z scan range (67-2300 Da). Method validation was performed in a targeted fashion to evaluate the analytical performance across all lipid categories, revealing excellent linearity (R2 ≥ 0.9921), acceptable repeatability (coefficients of variance ≤15.6%), and stable recovery (coefficients of variance ≤11.9%). Method suitability for untargeted fingerprinting was verified, demonstrating adequate linearity (R2 ≥ 0.90) for 75.3% and acceptable repeatability (coefficients of variance ≤30%) for 84.5% of about 9000 endogenous fecal compounds. Eventually, the potential of fecal lipidomics was exemplified within a clinical context of type 2 diabetes, thereby revealing significant perturbations [orthogonal partial least-squares discriminant analysis Q2(Y) of 0.728] in the fecal lipidome between participants with normal blood glucose levels (n = 26) and those with type 2 diabetes (n = 17).

[1]  Qiang Feng,et al.  A metagenome-wide association study of gut microbiota in type 2 diabetes , 2012, Nature.

[2]  Hugues Henry,et al.  Comparison between a high-resolution single-stage Orbitrap and a triple quadrupole mass spectrometer for quantitative analyses of drugs. , 2012, Rapid communications in mass spectrometry : RCM.

[3]  B. Cummings,et al.  Extraction, chromatographic and mass spectrometric methods for lipid analysis. , 2016, Biomedical chromatography : BMC.

[4]  Vasant R. Marur,et al.  Method development for fecal lipidomics profiling. , 2013, Analytical chemistry.

[5]  Min-Hsiung Lee,et al.  Ethyl acetate/ethyl alcohol mixtures as an alternative to folch reagent for extracting animal lipids. , 2004, Journal of agricultural and food chemistry.

[6]  Masoumeh Sikaroodi,et al.  Fecal microbiome and volatile organic compound metabolome in obese humans with nonalcoholic fatty liver disease. , 2013, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.

[7]  B. Herslöf,et al.  A single step reversed-phase high performance liquid chromatography separation of polar and non-polar lipids. , 2014, Journal of chromatography. A.

[8]  P. Pozzilli,et al.  Effect of diet on type 2 diabetes mellitus: a review , 2014, Diabetes/metabolism research and reviews.

[9]  R. Cox,et al.  A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and human. , 2007, Physiological genomics.

[10]  Lynn Vanhaecke,et al.  Validated High Resolution Mass Spectrometry-Based Approach for Metabolomic Fingerprinting of the Human Gut Phenotype. , 2015, Analytical chemistry.

[11]  Ronald J. Moore,et al.  A reversed-phase capillary ultra-performance liquid chromatography–mass spectrometry (UPLC-MS) method for comprehensive top-down/bottom-up lipid profiling , 2012, Analytical and Bioanalytical Chemistry.

[12]  O. Fiehn Metabolomics – the link between genotypes and phenotypes , 2004, Plant Molecular Biology.

[13]  Li Yang,et al.  Analytical methods in lipidomics and their applications. , 2014, Analytical chemistry.

[14]  S. Kohlwein,et al.  A versatile ultra-high performance LC-MS method for lipid profiling , 2014, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[15]  G. Halliday,et al.  An Improved High-Throughput Lipid Extraction Method for the Analysis of Human Brain Lipids , 2013, Lipids.

[16]  Ying Swan Ho,et al.  Advances in sample preparation and analytical techniques for lipidomics study of clinical samples , 2015 .

[17]  J B L Hoekstra,et al.  The therapeutic potential of manipulating gut microbiota in obesity and type 2 diabetes mellitus , 2012, Diabetes, obesity & metabolism.

[18]  J. van der Greef,et al.  Urine metabolomics combined with the personalized diagnosis guided by Chinese medicine reveals subtypes of pre-diabetes. , 2012, Molecular bioSystems.

[19]  Marco Gobbetti,et al.  Fecal Microbiota and Metabolome of Children with Autism and Pervasive Developmental Disorder Not Otherwise Specified , 2013, PloS one.

[20]  M. Orešič,et al.  Metabolomics, a novel tool for studies of nutrition, metabolism and lipid dysfunction. , 2009, Nutrition, metabolism, and cardiovascular diseases : NMCD.

[21]  G. Musso,et al.  Interactions between gut microbiota and host metabolism predisposing to obesity and diabetes. , 2011, Annual review of medicine.

[22]  T Koal,et al.  Challenges in mass spectrometry based targeted metabolomics. , 2010, Current molecular medicine.

[23]  Thomas Hankemeier,et al.  Analytical strategies in lipidomics and applications in disease biomarker discovery. , 2009, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[24]  T. Ebbels,et al.  Optimizing the use of quality control samples for signal drift correction in large-scale urine metabolic profiling studies. , 2012, Analytical chemistry.

[25]  Wei Jia,et al.  Metabolomics in human type 2 diabetes research , 2013, Frontiers of Medicine.

[26]  Coral Barbas,et al.  Method validation strategies involved in non-targeted metabolomics. , 2014, Journal of chromatography. A.

[27]  A. Peters,et al.  Identification of Serum Metabolites Associated With Risk of Type 2 Diabetes Using a Targeted Metabolomic Approach , 2013, Diabetes.

[28]  Frank David,et al.  Comprehensive blood plasma lipidomics by liquid chromatography/quadrupole time-of-flight mass spectrometry. , 2010, Journal of chromatography. A.

[29]  Hugo A. Katus,et al.  A New Metabolomic Signature in Type-2 Diabetes Mellitus and Its Pathophysiology , 2014, PloS one.

[30]  J. Antignac,et al.  Mass spectrometry-based metabolomics applied to the chemical safety of food , 2011 .

[31]  Hydrophilic interaction (HILIC) and reverse phase liquid chromatography (RPLC)–high resolution MS for characterizing lipids profile disruption in serum of anabolic implanted bovines , 2015, Metabolomics.

[32]  S. Bickston,et al.  Future therapies for inflammatory bowel disease , 2003, Current gastroenterology reports.

[33]  R. Krauss Lipids and lipoproteins in patients with type 2 diabetes. , 2004, Diabetes care.

[34]  L. Herrero,et al.  Feasibility of ultra-high performance liquid and gas chromatography coupled to mass spectrometry for accurate determination of primary and secondary phthalate metabolites in urine samples. , 2015, Analytica chimica acta.

[35]  F. Vaz,et al.  Principles and practice of lipidomics , 2015, Journal of Inherited Metabolic Disease.