发布: 2018年09月05日第8卷第17期 DOI: 10.21769/BioProtoc.3003 浏览次数: 7302
评审: Vivien Jane Coulson-ThomasMindy CallAnonymous reviewer(s)
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Abstract
Using gas chromatography mass spectrometry (GC-MS) to analyze the citric acid cycle (CAC) and related intermediates (such as glutamate, glutamine, GABA, and aspartate) is an analytical approach to identify unexpected correlations between apparently related and unrelated pathways of energy metabolism. Intermediates can be as expressed as their absolute concentrations or relative ratios by using known amounts of added reference standards to the sample. GC-MS can also distinguish between heavy labeled molecules (2H- or 13C-labeled) and the naturally occurring most abundant molecules. Applications using tracers can also assess the turnover of specific metabolic pools under various physiological and pathological conditions as well as for pathway discovery.
The following protocol is a relatively simple method that is not only sensitive for small concentrations of metabolic intermediates but can also be used in vivo or in vitro to determine the integrity of various metabolic pathways, such as flux changes within specific metabolite pools. We used this protocol to determine the role of phosphoenolpyruvate carboxykinase 1 (Pck1) gene in mouse macrophage cells to determine the percent contribution from a precursor of 13C labeled glucose into specific CAC metabolite pools.
Background
With the development of altered gene expression in cells and mice, there is a need to understand how these deleted or over-expressed genes impact the regulation of metabolic pathways. In this protocol, we used stable isotopes to determine how the flux of glucose into the CAC altered the contribution of glucose into the pools of citrate, succinate and malate. The use of stable isotopes with targeted analysis of metabolism is just one benefit to using stable isotopes in cell culture.
The method described in this protocol for functional quantification of intracellular metabolites was done by growing bone marrow-derived macrophage cells (BMDM) in U-13C-glucose medium. The cells were extracted in organic solvent and the percent contribution of 13C glucose was calculated. The fractional amount of 13C label incorporated into each the CAC-related metabolite pools was also determined. The calculations were based on the ratio of 13C label of each intracellular metabolite versus the unlabeled metabolite; for absolute concentration analysis of cell samples, one would need to correct for reference to the intracellular volume of the extracted cells (Feldberg et al., 2009), as well as add non-interfering reference standards for quantifying of levels of CAC intermediates, as previously described (Ko et al., 2018). This protocol can also be used in isolated perfused livers or whole body metabolism studies (Yang et al., 2008a; Zhang et al., 2015).
Using a novel mouse model that had a deletion of phosphoenolpyruvate carboxykinase 1 (Pck1) in the myeloid cells (Pck1MC-KO), stable isotopes were used to determine the role of this gene in macrophages (Ko et al., 2018) with respect to glucose metabolism. The protocol explains the isolation and differentiation of BMDM. These cells were isolated, differentiated and incubated with U13C-glucose to analyze their metabolism. The BMDM cells were collected, and the fractional contribution of the precursor to the product was based on the mole percent enrichments (MPE) derived from the 13C label incorporation into the total pool of each of the metabolites (products). Mass isotopomer analysis enables the measurements of unlabeled analyte (M0) relative to the labeled analyte (M+1, 2, or 3, etc.), (Yang et al., 2008a; Kombu et al., 2011; Ko et al., 2018). The measured mass isotopomer distributions were calculated for each of the masses and expressed as mole percent enrichment (MPE) after correcting for natural isotope abundances.
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文章信息
版权信息
© 2018 The Authors; exclusive licensee Bio-protocol LLC.
如何引用
Readers should cite both the Bio-protocol article and the original research article where this protocol was used:
分类
免疫学 > 免疫细胞分离 > 巨噬细胞
细胞生物学 > 细胞新陈代谢 > 其它化合物
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