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Manual for using mass spectrometer data correction software
By Dr. Le You
(Compatible with MATLAB 2007b and earlier version)
This protocol shows the use of an MATLAB based toolbox [1] for the correction of raw isotopic
labeling data derived from GC-MS. Intracellular metabolites need to be derivatized to increase
volatility before GC-MS detection. Two derivatization reagents are widely used. Proteinogenic
amino acids are usually derivatized by N-tert-butyldimethylsilyl-N-methyltrifluoroacetamid
(TBDMS) while intracellular metabolites are derivatized by N-Methyl-N-(trimethylsilyl)
trifluoroacetamide (MSTFA). This step, however, introduces significant noises due to the high
natural labeling of Si, C, N, H, and O in the derivatization reagent. The toolbox introduced below
can correct such natural labeling.
1. TBDMS-derivatized metabolites.
Three characteristic fragments were mostly used for the TBDMS-derivatized proteinogenic
amino acids (Figure 1). Fragment [M-57]+ contains the entire amino acid, and fragment [M-159]+
lacks the α carboxyl group of the amino acid. For leucine and isoleucine, the [M-57]+ peak was
overlapped by other mass peaks. Therefore, [M-15]+ is used instead to analyze the entire amino
acid labeling. Also, the [f302]+ group is often detected in most amino acids. It contains only the
first (α-carboxyl group) and second carbons in an amino acid backbone. However, [f302]+ is not
recommended for quantitatively analyzing the metabolic fluxes because this MS peak often has
high noise-to-signal ratios[2].
Figure 1. TBDMS derivatized amino acids
To perform the correction with the toolbox, first run the ‘MsCorr.p’ file in the folder provided
(Figure 2), and a new window will appear immediately (Figure 3).
Figure 2. Run ‘MSCorr.p’.
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Figure 3. Open the new window
Click the load list below the left column and load the ‘TBDMS2014’ file, which is our updated
file with all the recently added metabolites. (Figure 4) The list of characteristic fragments will
appear in the second column. Subsequently, copy the raw data of the metabolite that needs to be
corrected into the file named ‘data’ and load the data file by clicking ‘load list’ below the third
column. (Figure 5)
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Figure 4. Load the list of metabolites
Figure 5. Load the raw data
Select the corresponding metabolite from the first column and the characteristic on the second
column. Then click the ‘Run Correction’ on the right. (Figure 6) The corrected results will be
shown below. In certain cases, the m/z values of characteristic fragment is not continuous. These
values have to be adjusted before the correction. For example, the [M-57]+ fragment of alanine
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(which has the m/z of 260, 261, 262, 263) may show as 260.1, 261.2, 262.0,263.1. These values
have to be adjusted to have the same decimal place value.
Figure 6. Run the correction
2. MSTFA-derivatized metabolites.
Two characteristic fragments were mostly used for the MSTFA-derivatized intracellular free
metabolites (Figure 2). Fragment [M-15]+ contains the entire molecule. Fragment [M-117]+ lacks
the α carboxyl group of the metabolites.
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Figure 7. MSTFA derivatized amino acids
To perform correction with the toolbox, first run the ‘MsCorr.p’ file in the folder provided. Click
the load list below the left column and load the ‘MSTFA2014’ file, which is our updated file
with all the recently added metabolites. The list of characteristic fragments will appear in the
second column. Subsequently, copy the raw data of the metabolite that needs to be corrected into
the file named ‘data’ and load the data file by clicking ‘load list’ below the third column. Select
the corresponding metabolite from the first column and the characteristic on the second column.
Click the ‘Run Correction’ button on the right. The corrected results will be shown below and
similar adjustments of m/z values may be needed.
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Table 1. TBDMS-derivatized metabolites
Metabolites
MW -TBDMS
[M-57]+/[M-15]+
[M-159]+/[M-85]+
f302
Alanine
317
260
158
302
Glycine
303
246
218*
302
Valine
345
288
186
302
Leucine
359
344*
200
302
[M-15]+ fragment is used
Isoleucine
359
344*
200
302
[M-15]+ fragment is used
Proline
343
286
184
302
Methionine
377
320
218
302
Serine
447
390
288
302
Threonine
461
404
376*
302
Phenylalanine
393
336
234
302
Aspartate
475
418
316
302
Glutamine
489
432
330
302
Lysine
488
431
329
302
Histidine
497
440
338
302
Tyrosine
523
466
364
302
Note
[M-85]+ fragment is used
[M-85]+ fragment is used
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Table 2. MSTFA-derivatized metabolites
Metabolites
MW-MSTFA
[M-15]+
[M-117]+
Glyoxylate
175
160
43*
Pyruvate
189
174
72*
Lactate
234
219
117*
Alanine
233
218
116
Glycine
291
276
174
Valine
261
246
144
Succinate
262
247
147
Fumarate
260
245
143
Serine
321
306
204
Threonine
263
248
146
273
258
158
319
304
302
Aspartate
349
334
232
Glutamine
363
348
246
Malate
350
335
333
Citrate
480
465
463
α-ketoglutarate
Note
[M-117]+ fragment is not
accurate.
[M-117]+ fragment is not
accurate.
[M-117]+ fragment is not
accurate.
The first and fifth carbon link to
form a cycle.
Both fragments are not
accurate.
Both fragments are not
accurate.
References
1. Wahl SA, Dauner M, Wiechert W: New tools for mass isotopomer data evaluation in 13C
flux analysis: Mass isotope correction, data consistency checking, and precursor
relationships. Biotechnol Bioeng 2004, 85(3):259-268.
2. Antoniewicz MR, Kelleher JK, Stephanopoulos G: Accurate assessment of amino acid
mass isotopomer distributions for metabolic flux analysis. Anal Chem 2007, 79(19):75547559.
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