Literature DB >> 24529441

Methods for performing lipidomics in white adipose tissue.

Lee D Roberts1, James A West1, Antonio Vidal-Puig2, Julian L Griffin3.   

Abstract

Lipid metabolism is central to the function of white adipose tissue, with the tissue having a central role in storing triacylglycerides following feeding and releasing free fatty acids and monoacylglycerides during periods of fasting. In addition, lipid species have been suggested to play a role in lipotoxicity and as signaling molecules during adipose tissue inflammation. This chapter details how mass spectrometry (MS) can be used to profile a range of lipid species found in adipose tissue. The initial step required in any MS-based approach is to extract the lipid fraction from the tissue. We detail one commonly used method based on the Folch extraction procedure. The total fatty acid composition of the lipid fraction can readily be defined using gas chromatography-MS, and we provide a method routinely used for rodent and human adipose tissue samples. However, such approaches do not provide insight into what lipid classes the various fatty acids are associated with. To better understand the global lipid profile of the tissue, we provide a general-purpose liquid chromatography-MS-based approach useful for processing phospholipids, free fatty acids, and triacylglycerides. In addition, we provide a method for profiling eicosanoids, a class of important lipid-signaling molecules, which have been implicated in white adipose tissue inflammation in rodent models of obesity, insulin resistance, and type 2 diabetes.
© 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Eicosanoids; Fatty acids; Mass spectrometry; Phospholipids; Triacylglycerides

Mesh:

Substances:

Year:  2014        PMID: 24529441     DOI: 10.1016/B978-0-12-800280-3.00012-8

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  8 in total

Review 1.  Form(ul)ation of adipocytes by lipids.

Authors:  Kfir Lapid; Jonathan M Graff
Journal:  Adipocyte       Date:  2017-03-01       Impact factor: 4.534

2.  Integration of metabolomics, lipidomics and clinical data using a machine learning method.

Authors:  Animesh Acharjee; Zsuzsanna Ament; James A West; Elizabeth Stanley; Julian L Griffin
Journal:  BMC Bioinformatics       Date:  2016-11-22       Impact factor: 3.169

3.  Comparison of hepatic and serum lipid signatures in hepatocellular carcinoma patients leads to the discovery of diagnostic and prognostic biomarkers.

Authors:  Yonghai Lu; Juanjuan Chen; Chong Huang; Ning Li; Li Zou; Sin Eng Chia; Shengsen Chen; Kangkang Yu; Qingxia Ling; Qi Cheng; Mengqi Zhu; Weidong Zhang; Mingquan Chen; Choon Nam Ong
Journal:  Oncotarget       Date:  2017-12-13

4.  Using lipidomics to reveal details of lipid accumulation in developing seeds from oilseed rape (Brassica napus L.).

Authors:  Helen K Woodfield; Amaury Cazenave-Gassiot; Richard P Haslam; Irina A Guschina; Markus R Wenk; John L Harwood
Journal:  Biochim Biophys Acta Mol Cell Biol Lipids       Date:  2017-12-22       Impact factor: 4.698

5.  Metabolomics dataset of PPAR-pan treated rat liver.

Authors:  Zsuzsanna Ament; James A West; Elizabeth Stanley; Xuefei Li; Tom Ashmore; Lee D Roberts; Jayne Wright; Andrew W Nicholls; Julian L Griffin
Journal:  Data Brief       Date:  2016-05-10

6.  PPAR-pan activation induces hepatic oxidative stress and lipidomic remodelling.

Authors:  Zsuzsanna Ament; James A West; Elizabeth Stanley; Tom Ashmore; Lee D Roberts; Jayne Wright; Andrew W Nicholls; Julian L Griffin
Journal:  Free Radic Biol Med       Date:  2015-11-30       Impact factor: 7.376

7.  Lipidomics of human adipose tissue reveals diversity between body areas.

Authors:  Naba Al-Sari; Tommi Suvitaival; Ismo Mattila; Ashfaq Ali; Linda Ahonen; Kajetan Trost; Trine Foged Henriksen; Flemming Pociot; Lars Ove Dragsted; Cristina Legido-Quigley
Journal:  PLoS One       Date:  2020-06-16       Impact factor: 3.240

Review 8.  Sample Preparation Methods for Lipidomics Approaches Used in Studies of Obesity.

Authors:  Ivan Liakh; Tomasz Sledzinski; Lukasz Kaska; Paulina Mozolewska; Adriana Mika
Journal:  Molecules       Date:  2020-11-13       Impact factor: 4.411

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.