13C mass isotopomer analysis (LCMS flux studies) MLL-AF9 (part III)
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus Musculus
TISSUE(S): Cells
PROVIDER: ST000170 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
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Project description:To better understand proteostasis in health and disease, determination of protein half-lives is essential. We improved the precision and accuracy of peptide-ion intensity based quantification in order to enable accurate determination of protein turnover in non-dividing cells using dynamic-SILAC. This enabled precise and accurate protein half-life determination ranging from 10 to more than 1000 hours. We achieve good proteomic coverage ranging from four to six thousand proteins in several types of non-dividing cells, corresponding to a total of 9699 unique proteins over the entire dataset. Good agreement was observed in half-lives between B-cells, natural killer cells and monocytes, while hepatocytes and mouse embryonic neurons showed substantial differences. Our comprehensive dataset enabled extension and statistical validation of the previous observation that subunits of protein complexes tend to have coherent turnover. Furthermore, we observed complex architecture dependent turnover within complexes of the proteasome and the nuclear pore complex. Our method is broadly applicable and might be used to investigate protein turnover in various cell types.
2018-06-08 | PXD008513 | Pride
Project description:The magnitude of contaminant mass-flux reduction associated with a specific amount of contaminant mass removed is a key consideration for evaluating the effectiveness of a source-zone remediation effort. Thus, there is great interest in characterizing, estimating, and predicting relationships between mass-flux reduction and mass removal. Published data collected for several field studies were examined to evaluate relationships between mass-flux reduction and source-zone mass removal. The studies analyzed herein represent a variety of source-zone architectures, immiscible-liquid compositions, and implemented remediation technologies. There are two general approaches to characterizing the mass-flux-reduction/mass-removal relationship, end-point analysis and time-continuous analysis. End-point analysis, based on comparing masses and mass fluxes measured before and after a source-zone remediation effort, was conducted for 21 remediation projects. Mass removals were greater than 60% for all but three of the studies. Mass-flux reductions ranging from slightly less than to slightly greater than one-to-one were observed for the majority of the sites. However, these single-snapshot characterizations are limited in that the antecedent behavior is indeterminate. Time-continuous analysis, based on continuous monitoring of mass removal and mass flux, was performed for two sites, both for which data were obtained under water-flushing conditions. The reductions in mass flux were significantly different for the two sites (90% vs. approximately 8%) for similar mass removals ( approximately 40%). These results illustrate the dependence of the mass-flux-reduction/mass-removal relationship on source-zone architecture and associated mass-transfer processes. Minimal mass-flux reduction was observed for a system wherein mass removal was relatively efficient (ideal mass-transfer and displacement). Conversely, a significant degree of mass-flux reduction was observed for a site wherein mass removal was inefficient (non-ideal mass-transfer and displacement). The mass-flux-reduction/mass-removal relationship for the latter site exhibited a multi-step behavior, which cannot be predicted using some of the available simple estimation functions.
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Project description:Mass isotopomer multi-ordinate spectral analysis (MIMOSA) is a step-wise flux analysis platform to measure discrete glycolytic and mitochondrial metabolic rates. Importantly, direct citrate synthesis rates were obtained by deconvolving the mass spectra generated from [U-(13)C6]-D-glucose labeling for position-specific enrichments of mitochondrial acetyl-CoA, oxaloacetate, and citrate. Comprehensive steady-state and dynamic analyses of key metabolic rates (pyruvate dehydrogenase, β-oxidation, pyruvate carboxylase, isocitrate dehydrogenase, and PEP/pyruvate cycling) were calculated from the position-specific transfer of (13)C from sequential precursors to their products. Important limitations of previous techniques were identified. In INS-1 cells, citrate synthase rates correlated with both insulin secretion and oxygen consumption. Pyruvate carboxylase rates were substantially lower than previously reported but showed the highest fold change in response to glucose stimulation. In conclusion, MIMOSA measures key metabolic rates from the precursor/product position-specific transfer of (13)C-label between metabolites and has broad applicability to any glucose-oxidizing cell.
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Project description:(13)C-Metabolic flux analysis ((13)C-MFA) is a powerful model-based analysis technique for determining intracellular metabolic fluxes in living cells. It has become a standard tool in many labs for quantifying cell physiology, e.g., in metabolic engineering, systems biology, biotechnology, and biomedical research. With the increasing number of (13)C-MFA studies published each year, it is now ever more important to provide practical guidelines for performing and publishing (13)C-MFA studies so that quality is not sacrificed as the number of publications increases. The main purpose of this paper is to provide an overview of good practices in (13)C-MFA, which can eventually be used as minimum data standards for publishing (13)C-MFA studies. The motivation for this work is two-fold: (1) currently, there is no general consensus among researchers and journal editors as to what minimum data standards should be required for publishing (13)C-MFA studies; as a result, there are great discrepancies in terms of quality and consistency; and (2) there is a growing number of studies that cannot be reproduced or verified independently due to incomplete information provided in these publications. This creates confusion, e.g. when trying to reconcile conflicting results, and hinders progress in the field. Here, we review current status in the (13)C-MFA field and highlight some of the shortcomings with regards to (13)C-MFA publications. We then propose a checklist that encompasses good practices in (13)C-MFA. We hope that these guidelines will be a valuable resource for the community and allow (13)C-flux studies to be more easily reproduced and accessed by others in the future.
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Project description:Metabolic flux analysis (MFA) is highly relevant to understanding metabolic mechanisms of various biological processes. While the pace of methodology development in MFA has been rapid, a major challenge the field continues to witness is limited metabolite coverage, often restricted to a small to moderate number of well-known compounds. In addition, isotopic peaks from an enriched metabolite tend to have low abundances, which makes liquid chromatography tandem mass spectrometry (LC-MS/MS) highly useful in MFA due to its high sensitivity and specificity. Previously we have built large-scale LC-MS/MS approaches that can be routinely used for measurement of up to ∼1,900 metabolite/feature levels [Gu et al. Anal. Chem. 2015, 87, 12355-12362. Shi et al. Anal. Chem. 2019, 91, 13737-13745.]. In this study, we aim to expand our previous studies focused on metabolite level measurements to flux analysis and establish a novel comprehensive isotopic targeted mass spectrometry (CIT-MS) method for reliable MFA analysis with broad coverage. As a proof-of-principle, we have applied CIT-MS to compare the steady-state enrichment of metabolites between Myc(oncogene)-On and Myc-Off Tet21N human neuroblastoma cells cultured with U-13C6-glucose medium. CIT-MS is operationalized using multiple reaction monitoring (MRM) mode and is able to perform MFA of 310 identified metabolites (142 reliably detected, 46 kinetically profiled) selected from >35 metabolic pathways of strong biological significance. Further, we developed a novel concept of relative flux, which eliminates the requirement of absolute quantitation in traditional MFA and thus enables comparative MFA under the pseudosteady state. As a result, CIT-MS was shown to possess the advantages of broad coverage, easy implementation, fast throughput, and more importantly, high fidelity and accuracy in MFA. In principle, CIT-MS can be easily adapted to track the flux of other labeled tracers (such as 15N-tracers) in any metabolite detectable by LC-MS/MS and in various biological models (such as mice). Therefore, CIT-MS has great potential to bring new insights to both basic and clinical metabolism research.
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