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Tracing Compartment-Specific Redox Pathways Using Stable Isotopes and Mass Spectrometry
1  University of California, San Diego, Department of Bioengineering

Abstract:

Metabolism is central to virtually all cellular functions and contributes to a range of diseases.  A quantitative understanding of how biochemical pathways are dysregulated in the context of diseases such as cancer and metabolic syndrome is necessary to identify new therapeutic targets.  To this end we apply stable isotope tracers, mass spectrometry, and metabolic flux analysis (MFA) to study metabolism in mammalian cells, animal models, and human patients.  Using these approaches we have characterized how proliferating and differentiated cells regulate flux of glucose and amino acids into mitochondria for maintaining redox homeostasis and lipid biosynthesis. Recently, we have developed novel methods for studying pyridine nucleotide metabolism, employing 2H tracers and mass spectrometry to quantify how specific metabolic pathways are used to regenerate NADH and NADPH. To better understand how redox pathways are regulated in the cytosol and mitochondrial matrix we have generated compartment-specific enzyme reporters that exploit the neomorphic activity of mutant isocitrate dehydrogenases (IDHs). Specifically, R132H IDH1 and R172K IDH2 produce (D)2-hydroxyglutarate (2HG) in the cytosol and mitochondria, respectively. Quantitation of labeling from specifically labeled 2H tracers provides critical insights into NAD(P)H-producing pathways in each compartment. We have employed this approach to identify redox pathway regulation under hypoxia, where oxidative pentose phosphate pathway flux is upregulated to fuel reductive carboxylation. The application of MFA to cell and animal models greatly improves our ability to characterize intracellular metabolic processes, providing a mechanistic understanding of cellular physiology and metabolic function.

Keywords: metabolic flux analysis, NADPH, NADH, mitochondria, cytosol, IDH1, hypoxia, serine, one carbon metabolism
Comments on this paper
Daqiang Pan
Question
Hi Christian,

Thank you for your interesting presentation and results. I have one question about 2HG. Have you identified the L and D form of 2HG in your case?

Kind regards,

Daqiang
Christian Metallo
In the context of endogenous or exogenous mutant IDH1 or IDH2 expression the predominant species produced is D-2HG. In cells expressing wild-type IDH1 and IDH2 the main species detected is L-2HG. The source of electons for production of D-2HG and L-2HG are NADPH and NADH, respectively. This difference is effectively traced using our approach.

Christian Frezza
labelling under hypoxia
Hi Christian,
excellent presentation, as always! I am intrigued by the observation that under hypoxia you see decreased % labelling from 4-H2 glucose on lactate and malate. If you normalise lactate and malate to G3P, the flux seems unchanged, though, suggesting that GAPDH activity is preserved. Is that correct? Also, have you checked the m+2 glyc3P? You expect it to be increased, correct?


Thanks for your time and see you soon

Christian
Christian Metallo
Thanks Christian,
Excellent point about normalized labeling! Since these are pseudo steady state measurements, I think this simply reflects the decreased labeling of the precursor pools (GAP and subsequently NAD). The decreased labeling of the precursor pool suggests that the TPI-aldolase exchange flux is increased.


Having said that, it is clear from literature as well as our own glucose uptake and lactate secretion measurements that there is a net increase in glycolytic flux under hypoxia. I suspect that the exchange (reverse) flux increases relative to the forward flux. GAPDH oxidation is presumably the cause of this result, but we need to always remember that glycolysis increases. This highlights how critical the wording can be (I was probably quite loose in describing flux changes).


In the end, more definitive answers to these net flux questions would ideally come from non-stationary MFA experiments, which we are considering.

I think that M+2 labeling of G3P is quite low but will check on this point in the raw data when everyone returns from Thanksgiving.
Christian Frezza
Thanks Christian, you raised good points here about the difference between the net increase in flux and exchange. As you said, very difficult to word it.
Keep on with the excellent work!
Christian Metallo
Hi Christian,
Regarding the M+2 G3P labeling, we generally see low levels (<3%) of M+2. This is a tricky measurement to interpret since the labeling is a function of 1) glycerol taken up by cells, 2) de novo G3P/lipid synthesis, 3) TPI/aldolase exchange, and 4) G3PDH shuttling.


I do think the question of which shuttles are most active under certain conditions is a great application of this tracing. We looked at one shuttle collaboratively, but kinetic approaches are probably needed to account for all variables.
Christian
Christian Frezza
Thanks Christian. I totally agree, your approach is very powerful to investigate the activity of these shuttles, including the G3P, under pathological conditions. Indeed, your talk made us thinking about it in a specific mitochondrial dysfunction we are investigating.
I hope to discuss this soon in person

Cheers

Christian

Maria Fuller
Maria Fuller
Great presentation - as always - and a fabulous approach to be able to measure flux rather than just a single snapshot in time. Have you looked at whether you can block particular pathways with inhibitors and see if other pathways are upregulated and/or can compensate. This would be particularly useful for interrogating inherited metabolic disease.
Christian Metallo
Thanks Maria.
We have tried out inhibitors. By and large, those types of experiments highlight how "dirty" these compounds can be, as the results are never as clean as you might expect. Many more enzymes than those annotated are likely inhibited. We have done targeted knockdown using shRNA and/or CRISPR/Cas9 and recapitulate expected results (e.g. G6PD knockdown). Some of this work is in revision. With shRNA off-target effects are also an important consideration, and clonal variation can complicate CRISPR-based results. We have also applied this approach to BCAA catabolic pathways (Green et al. Nat Chem Bio 2016 and more to come).


Maria Fuller
thank you
thanks christian. we have noticed off-target effects with some chemical inhibitors of enzyme activities that claim to have none, which makes the downstream consequences difficult to interpret. I'll continue to follow the progress of your work in the literature. once again, many thanks indeed for your most insightful and informative presentation.




 
 
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