Comprehensive isotopomer analysis of glutamate and aspartate in small tissue samples

SUMMARY Stable isotopes are powerful tools to assess metabolism. 13C labeling is detected using nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry (MS). MS has excellent sensitivity but generally cannot discriminate among different 13C positions (isotopomers), whereas NMR is less sensitive but reports some isotopomers. Here, we develop an MS method that reports all 16 aspartate and 32 glutamate isotopomers while requiring less than 1% of the sample used for NMR. This method discriminates between pathways that result in the same number of 13C labels in aspartate and glutamate, providing enhanced specificity over conventional MS. We demonstrate regional metabolic heterogeneity within human tumors, document the impact of fumarate hydratase deficiency in human renal cancers, and investigate the contributions of TCA cycle turnover and CO2 recycling to isotope labeling in vivo. This method can accompany NMR or standard MS to provide outstanding sensitivity in isotope labeling experiments, particularly in vivo.

the optical CE is also provided for reference.

Normalized ion pair fractions
For any ion pair whose signal is not detected, a pseudo value of 100 is assigned to eliminate zero values for normalization.The raw data are ion abundance (integration of the area under the curve) of each ion pair, and they are normalized to the total ion abundance.

Raw data and correction
The chromatogram peaks of 147/75 or 147/41 sometimes have interfering peaks from other metabolites and need to be corrected.The correction is based on the principle that the isotopologue fractions among different set of fragments are identical.For example, the M+1 fraction of glutamate in a sample could be equal to either: (

Nonnegative least square regression
Nonnegative least square regression was implemented using the glmnet R package 1 , with the following parameters: lambda = lower.limits= 0, intercept = FALSE and thresh = 1e-30, such that the regression is not regularized, the coefficients are bounded between 0 and 1, and the convergence threshold is small but can generally be reached within the default number of iterations.We compared this method to other R packages with Lawson-Hanson's algorithm 2 implementation such as in the NNLS 3 or pracma 4 R packages and found the glmnet-based method to provide the lowest error from our simulation error estimation below.The total fraction of all calculation results should sum to 1.However, regression will produce a value very close to, but not equal to, 1.As a result, normalization is not necessary.

Error estimation
To determine errors in isotopomer distribution estimation due to the use of rank deficient mass isotopomer distribution matrix, we estimated error from the following simulation.We used 5,000 random beta distributions of length 32 for glutamate or 16 for aspartate (eq 1,  set to 2,  set to 5) normalized to the sum of 1 to represent positional isotopomer distribution of glutamate or aspartate.For each simulated isotopomer distribution  !, we inferred the MS/MS measurement  !through the metabolite-specific linear mapping Supplemental Data 1 -5 matrix  (eq 2), and then we implemented nonnegative least square to estimate the isotopomer distribution  & (eq 3).The difference between the simulated isotopomer distribution  ! and the calculated distribution  & in 5,000 simulations was used to generate the median error and 95% confidence interval (eq 4).

FC3 Calculation using isotopomer distribution
The FC3 calculation is described in the manuscript.
() = 11011 11000 + 11011 One example can be found in Supplementary Data III, sheet S14, in which the FC3 calculated from the isotopomer distribution and the FC3 calculated from conventional 1) the total ion abundance of 147/74 and 147/75 (negative mode) over the total ion The corrected fraction of 147/75 is obtained by subtracting the other M+1 fraction (147/74) from the average measured M+1 fractions of other fragmentation associated ion pairs (either the average of bullets 2 and 3, or the average of bullets 2, 3, and 4).