bioRxiv preprint doi: https://doi.org/10.1101/2020.10.31.361725; this version posted November 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Natural isotope correction improves analysis of modification dynamics

Jörn Dietze,† Alienke van Pijkeren,‡,¶ Mathias Ziegler,§ Marcel Kwiatkowski,∗,k and Ines Heiland∗,†,⊥

†Department of Arctic and Marine Biology, UiT The Arctic University of Norway ‡Lab for Metabolic Signaling, Department of Biochemistry, University of Innsbruck, Austria ¶Department of Analytical Biochemistry, Groningen Research Institute of Pharmacy, The Netherlands §Department of Biomedicine, University of Bergen, Norway kFunctional Proteo-Metabolomics, Department of Biochemistry, University of Innsbruck, Austria ⊥Department of Clinical Medicine, University of Bergen, Norway

E-mail: [email protected]; [email protected]

Abstract Introduction

Stable isotope labelling in combination with Protein modifications such as phosphorylation, high resolution approaches methylation or acetylation have an important are increasingly used to analyse both metabolite regulatory function in biology and are the basis and protein modification dynamics. To enable of environmental adaptation and phenotypic correct estimation of the resulting dynamics it variations. While it is well known that pro- is critical to correct the measured values for nat- tein phosphorylations are highly dynamic and urally occurring stable isotopes, a process com- result from a complex interplay between protein monly called isotopologue correction or decon- kinases and phosphatases, the dynamics of other volution. While the importance of isotopologue protein modifications such as methylation and correction is well recognized in metabolomics, acetylation has been less well investigated. The it has received far less attention in availability of stable isotope labelled compounds approaches. Although several tools exist that and high resolution mass spectrometry has, how- enable isotopologue correction of mass spectro- ever, more recently paved the way to analyse metry data, none of them is universally applic- the dynamics of protein methylation, acetyla- able for all potential experimental approaches. tion, phosphorylation and glycosylation1,2. We here present PICor which has been stream- As basically all protein modifications are effec- lined for multiple isotope labelling isotopologue tuated by small metabolic compounds, one can correction in proteomics or metabolomics ap- use partially or fully labelled metabolic precurs- proaches. We demonstrate the importance for ors to monitor changes in concentrations of both accurate measurement of the dynamics of pro- metabolic intermediates and protein modifica- tein modifications, such as histone acetylation. tions over time. Figure 1 depicts a typical ex- perimental workflow for stable isotope labelling experiments. Following incubation of cells with labelled precursors, metabolites and are extracted at various time points, separated by

1 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.31.361725; this version posted November 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. gas chromatography (GC) or liquid chromato- fication turnover. The theoretical basis and ap- graphy (LC) and analyzed by mass spectrometry plication of available tools for metabolites varies. (MS). Correction can for example be done based on spectra from naturally occurring compounds. This approach is, however, not feasible for pro- teomics applications, as it would require to have 13C-Glucose all peptides of interest available as standards, m/z Medium 664 665 666 667 668 669 Cell Culture GC/LC-MS Measured Mass Spectrum let alone inclusion of protein modifications. Sim- ilarly unfeasible for proteomics related measure- ments is the application of tools that require the reporting of all expected isotopologues as is the case for example for IsoCor5. The ap- M0 M1 M2 M3 M4 M5 Downstream Corrected Isotope Analysis Mass Spectrum Correction proach we choose here, corrects measured values based on the calculated theoretical isotope dis- Figure 1: Typical workflow of 13C labelling ex- tribution. The latter can be described using periment. Adapted from Midani et al.3 probability matrices. Commonly, two general approaches exist (3,6,7): In the so-called classical Molecules with the same composition of iso- approach, the same spectrum or distribution is topes, so-called isotopomers, are chemically used to correct all isotopologues. This is also the identical. Their intact precusor ions are isobaric basis for correction methods based on measured and therefore indistinguishable by MS analysis. spectra from naturally occurring substances. In An additional fragmentation by tandem mass molecules, however, that have all light isotopes spectrometry (MS/MS or MS2) using e.g. colli- replaced by their heavy counterparts, no heavier sion induced dissociation (CID), allows to loc- isotopologues can exist. These methods there- alize the isotopes based on their presence in fore lead to an estimation bias towards heavy the individual fragments. The obtained data isotopologues especially for large molecules with need to be appropriately processed, in order to high label incorporation. We therefore used a correctly calculate metabolite or protein modific- so-called skewed matrix approach, that corrects ation dynamics. A further complication in this each isotoplogue with its own set of theoret- analysis is the necessity to correct the obtained ical calculated correction factors (schematic rep- values for natural isotope abundance, called iso- resentation see figure 2a). This method is for top(ologu)e correction or deconvolution. This is example implemented in the R-based toolbox critical, because naturally occurring compounds IsoCorrectoR8 and in AccuCor4. already contain 1.1% of the stable heavy isotope For the identification and quantification of 13C. Thus, integration of 13C-labeled precursors isobaric modified histone species, Yuan et al.9 requires the correction for this naturally occur- developed an alternative method for isotope cor- ing isotope and potentially also for other stable rection using a deconvolution approach based natural isotopes such as deuterium, 18O, or 15N, on MS/MS measurements. The corresponding depending on whether or not these isotopes can toolbox EpiProfile has been primarily developed be resolved by the detection method used4. Es- to analyse isobaric modified histone peptides pecially the labeling of large metabolites as well irrespective of whether they arise from label as peptides and proteins could otherwise lead integration or are caused by similar chemical to large errors in the estimation of the label composition. As this method allows to identify integration dynamics. which part of the molecule is labelled with heavy In recent years, a number of tools have been isotopes it does enable some correction for nat- made available that enable isotopologue correc- ural isotope abundance. But, beside the disad- tion for metabolites. But very little attention vantage of requiring MS/MS measurements, it has been paid to natural isotope correction in does not provide a full isotopologue correction as proteomics or for the analyses of protein modi- visualized in figure 2b. The resulting estimation

2 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.31.361725; this version posted November 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. error is increasing with the number of possible isotopologues and the number of atoms labelled. We have developed PICor (https://github. com/MolecularBioinformatics/PICor), a py- thon based isotopologue correction tool that is applicable for the analysis of both labelled meta- 133 bolites as well as peptides and protein modific- 100 ations. It enables the correction for incorpora- 60 Correction 34 of M=0 tion of multiple different isotopes for example 15 3 0.5 8 2 0.4 m/z m/z both 13C and 15N and uses the skewed matrix 664 665 666 667 668 669 664 665 666 667 668 669 approach. Importantly, our approach is based 133 133 on the theoretical distribution of isotopologues.

Therefore, only the most abundant or import- 44 34 Correction of M=1 ant isotopologues need to be measured and thus 8 2 0.4 0 0 0 m/z m/z incomplete datasets can be used. Using time 664 665 666 667 668 669 664 665 666 667 668 669 course measurements of acetylated histone pep- (a) 69.2% tides we demonstrate that appropriate correc- 100 Unlabelled NAD tion for natural isotope distribution considerably 30.8% 44 improves the accuracy of the analyses. 56.2% 100 13C-labelled NAD MS2 33.6% NAD 60 Correction 0 1 2 3

75.0% 8.2%1.7% 0.3% Isotope 133 Results 153 0.5 Correction m/z 664 665 666 667 668 669 To highlight the importance of isotope correc- 25.0% 44 tion and to compare different tools available we

used the large metabolite NAD (figure 3a) as NAD 0 1 2 3 example. Using an imaginary NAD labelling (b) spectrum makes visualization more comprehens- ible as the number of potential isotopologues Figure 2: Schematic representation of isotopo- is much lower as for any peptide and it allows logue correction methods using an artificial spec- the comparison with other tools, as some of trum of 13C-labelled NAD containing 75% unla- them cannot be used for the analysis of pep- belled NAD and 25% single 13C-labelled NAD. tides. Still NAD is sufficiently large to visual- Red depicts the contributions of unlabelled NAD ize effects occurring in larger compounds. As and blue the ones of the single labelled NAD. shown in figure 3a the corrected spectra derived (a) Visualisation of the skewed matrix approach. with PICor match those of other tools, that use M+0 correction requires the addition of all nat- the same correction approach, like IsoCorrectoR urally labelled heavier isotopologues. The lower and AccuCor. The results do, however, clearly panel demonstrate the sequential process for differ from those correction methods using the M+1 correction. This correction process needs classical matrix correction, such as IsoCor. It to be done for each isotopologue. The lower should be noted that AccuCor cannot be used right panel shows the fully corrected spectrum. to do isotopologue correction in experiments us- (b) Comparison between the isotope deconvolu- ing label combinations such as for example 13C tion done by EpiProfile and the full isotopologue and 15N, even though correction for all natur- correction done by our approach. ally occurring isotopes present in the molecule is done. Analyses of labelled compounds with more than one incorporated isotope can to our knowledge only be done with IsoCorrectoR and IsoCor, with the latter having the disadvantage

3 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.31.361725; this version posted November 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. of using the classical correction. modificationa M+4 isotopologue of the peptide When correcting for natural isotopes it is im- was observed. Figure 3b shows the dynamics of portant to consider the mass resolution of the the different labels over a 24 hour time course, experiments4. Nowadays, it is common to use both for the corrected and the uncorrected meas- a measurement resolution that can separate urements. The slope of the time courses for the 13C and 15N. But, resolving the mass difference corrected and the uncorrected data are consid- between 13C and deuterium would require a res- erably different due to the overrepresentation olution that is unfeasible in practice, due to of labelled compounds at time point zero that required measurement time. PICor, therefore, stems from naturally occuring 13C. enables isotopologue correction for all label com- binations according to the mass resolution used SILAC – Quantitive proteomics in the experiments, making it especially relevant for labelling experiments using combinations of Besides metabolic labelling of proteins and pro- 13C and deuterium. To make PICor applicable tein modifications, stable isotopes are routinely for proteomics approaches one only needs to applied in to investigate provide a table with measurements for the iso- differentially expressed proteins. For example topologues of interest and not a full list for all in SILAC (Stable Isotope Labeling with Amino possible isotopologues as for example required acids in Cell culture) experiments, cells are cul- for the analysis with IsoCor. Table 1 summar- tured in media containing either unlabelled lys- 13 13 15 izes the potential application areas as well as the ine or arginine, or C or C and N labelled correction method used by the aforementioned amino acids. SILAC is not only used for a quant- isotope correction tools. itative comparison of protein abundance under different experimental conditions, but has also been used to investigate protein turnover. After Histone Acetylation cell lysis and protein extraction, differentially To demonstrate the effect of natural isotope cor- labelled samples are mixed and subjected to rection on labelling experiments in proteomics quantitative LC-MS based proteome analysis. we analysed experimental time course data from The sample origin is determined based on the 13C-labelled glucose supplementation on histone mass shift. To date it is not common to correct acetlylations. Histone acetylations are import- for natural isotopes in SILAC based quantitat- ant for transcriptional regulation. The acetyla- ive proteomics. This might be due to the fact tion of lysine residues in histones neutralizes the that usually only fold changes above 2 were con- charge of the side chain and thus changes the sidered. However, with increasing accuracy and ability of histones to bind DNA: this in turn requests for higher precision and the goal to leads to changes in the 3 dimensional structure identify more fine grain changes between differ- and accessibility of the DNA. ent experimental conditions, isotope correction Figure 3b shows an experimental time course will also become more relevant in these exper- for 13C-glucose labelling. In such a metabolic iments. Figure 4 shows the potential effect of labelling experiment, the naturally occuring 12C- isotope correction in triple SILAC experiments. glucose is replaced with 13C-glucose during cell PICor has been used to calculate the theoretical culture. Labelled glucose is consequently conver- difference between corrected and uncorrected ted into 13C-acetyl-Co-enzyme A. This is, among values for the sample peptide SLDIFTVGGSG- others, the substrate for histone acetyl trans- DGVVTNSAWETFQR. Even though the errors ferases that catalyze the transfer of the acetyl are much smaller than for metabolic labelling, group onto a nitrogen in the lysine side chain it would be expected to contribute a systemat- of a protein, resulting in a M+2 isotopologue. ical error if SILAC is for example used in time As an example we here measured the histone course experiments to estimate synthesis and 3 peptide H3(18-26) that can be modified at degradation rates. two lysine residues (K18, K23). Upon complete

4 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.31.361725; this version posted November 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. (a) Metabolite: NAD (b) Peptide: KQLATKAAR

140 Uncorrected M0 uncorrected Our Approach Accucor 120 IsoCorrectoR 80% uncorrected IsoCor 100 60% 80

60 40% Abundance 40 20% M2 uncorrected 20 Isotopologue Abundance M4 corrected 0% 0 M0 M1 M2 M3 M10 M11 M12 M13 0 5 10 15 20 25 Time in h

Figure 3: (a) Comparison of different isotope correction tools using an artificial spectrum of 13C labelled NAD as example. (b) MS time course of histone 3 peptide H3(18-26) acetylated at none (M0), one (M2) or two (M4) lysine residues (K18, K23) solid line – isotope corrected data; dashed line – uncorrected data

Table 1: Advantages and application area of different tools for isotopologue correction. (Adj.: high resolution mode with resolution dependent correction)

PICor IsoCorrectoR AccuCoR IsoCor Programming language Python R R Python Multiple isotope labels Yes Yes No No Resolution Adj. Low & High Adj. Low & Adj. Correction matrix Skewed Skewed Skewed Classic

Outline 105 Uncorrected Corrected New high-resolution mass spectrometry ap-

100 proaches now enable the analysis of metabolite and protein modification dynamics using meta- 95 bolic stable isotope labelling techniques. Due to the high number of atoms in a peptide the Abundance 90 amount of naturally labelled peptides is relat- ively large compared to small metabolic com- 85 pound. Therefore, correct and complete isotopo- logue correction is essential to correctly estimate No Label 15N 13C 13C 15N 4 6 6 4 protein modification dynamics. PICor is a tool Figure 4: Comparison between corrected and developed to enable isotopologue correction for uncorrected values in a triple SILAC ap- both metabolites and proteins applicable to com- proach. Value are given relative to the un- plex labelling experiments. labelled sample. The artificial dataset ana- Acknowledgement JD, MZ and IH have lysed had equal amounts of uncorrected values been supported by the Norwegian Research and the following peptide sequence was used: Foundation. MK has received funding from SLDIFTVGGSGDGVVTNSAWETFQR the Promotion program for Young Scientists at

5 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.31.361725; this version posted November 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. University of Innsbruck (project no: 316826). Dettmer, K. Correcting for natural iso- tope abundance and tracer impurity in MS-, MS/MS- and high-resolution-multiple- References tracer-data from stable isotope labeling ex- periments with IsoCorrectoR. Scientific Re- (1) Zheng, Y.; Sweet, S. M. M.; Pop- ports 2018, 8, 1–10. ovic, R.; Martinez-Garcia, E.; Tipton, J. D.; Thomas, P. M.; Licht, J. D.; Kelleher, N. L. (9) Yuan, Z. F.; Sidoli, S.; Marchione, D. M.; Total kinetic analysis reveals how combin- Simithy, J.; Janssen, K. A.; Szurgot, M. R.; atorial methylation patterns are established Garcia, B. A. EpiProfile 2.0: A Com- on lysines 27 and 36 of histone H3. Proceed- putational Platform for Processing Epi- ings of the National Academy of Sciences Proteomics Mass Spectrometry Data. J Pro- 2012, 109, 13549–13554. teome Res 2018, 17, 2533–2541. (2) van Pijkeren, A.; Bischoff, R.; Kwi- atkowski, M. Mass spectrometric analysis of PTM dynamics using stable isotope labeled Experimental metabolic precursors in cell culture. Analyst 2019, 144, 6812–6833. Chemicals

(3) Midani, F. S.; Wynn, M. L.; Schnell, S. The Water, acetonitrile (ACN), formic acid (FA, importance of accurately correcting for the all HPLC-grade) were obtained from Thermo natural abundance of stable isotopes. Ana- Fisher Scientific (Dreieich, Germany). All other lytical Biochemistry 2017, 520, 27–43. chemicals were purchased from Sigma-Aldrich (Munich, Germany) unless otherwise noted. (4) Su, X.; Lu, W.; Rabinowitz, J. D. Metabol- ite Spectral Accuracy on Orbitraps. Analyt- Metabolic labeling with uni- ical Chemistry 2017, 89, 5940–5948. formely labeled 13C-glucose and (5) Millard, P.; Delépine, B.; Guionnet, M.; histone extraction Heuillet, M.; Bellvert, F.; Létisse, F. IsoCor: isotope correction for high-resolution MS The murine macrophage-like cell line RAW264.7 labeling experiments. Bioinformatics 2019, (American Type Culture Collection, Wesel, Ger- 1–4. many) was cultured in 6-well plates at 37◦C and 5% CO2 atmosphere in DMEM with 4.5 (6) Rosenblatt, J.; Chinkes, D.; Wolfe, M.; g/L glucose. Media was supplemented with 2 Wolfe, R. R. Stable isotope tracer ana- mM extra L-Glutamine and 10% (v/v) heat- lysis by GC-MS, including quantification inactivated FBS. For the labeling experiment, of isotopomer effects. American Journal of RAW264.7 cells were first cultured in media Physiology-Endocrinology and Metabolism containing uniformly 12C-glucose ([U–12C]-Glc) 1992, 263, E584–E596. for 38 hours. Subsequently, the culture media was replaced by [U–13C]-Glc (Euroisotope, Saar- (7) Fernandez, C. A.; Rosiers, C. D.; Pre- brücken, Germany) containing media and the vis, S. F.; David, F.; Brunengraber, H. Cor- cells were cultured for 24 hours. The cells were rection of13C Mass Isotopomer Distribu- harvested by scraping before the exchange of tions for Natural Stable Isotope Abundance. culture medium (t= 0h) or after 24 hours in- Journal of Mass Spectrometry 1996, 31, 255– cubation in [U–13C]-Glc containing media (t= 262. 24h). (8) Heinrich, P.; Kohler, C.; Ellmann, L.; For histone extraction, the cells were washed ◦ Kuerner, P.; Spang, R.; Oefner, P. J.; twice with a PBS solution (T= 37 C) and lysed by adding 1mL of ice-cold lysis buffer (PBS,

6 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.31.361725; this version posted November 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 0.5% Triton X-100 (v/v), 1 mM phenylmethyl- (FA) to final concentration of 0.1% FA. sulfonyl fluoride (PMSF), 1 mM sodium butyr- ate, 10 µM suberanilohydroxamic acid (SAHA), LC-MS/MS analysis and prepro- 10 mM nicotinamide). The cells were sub- sequently sonificated on ice (3 tunes, 10 sec. cessing 50%) and centrifuged for 10 min at 10,000 rcf For LC-MS/MS analysis, 100 ng of the tryptic at 4◦C. After aspirating the supernatant, the peptide digests were injected on a nano-ultra pellets were resuspended in 0.5 mL ice-cold re- pressure liquid chromatography system (Dionex suspension buffer (13 mM EDTA, 10 mM 2- UltiMate 3000 RSLCnano pro flow, Thermo Amino-2-(hydroxymethyl)-1,3-propanediol (Tris Scientific, Bremen, Germany) coupled via base), pH 7.4). After centrifugation (10 min electrospray-ionization (ESI) source to a tribrid at 10,000 rcf, 4◦C) and aspiration of the su- orbitrap mass spectrometer (Orbitrap Fusion pernatant, pellets were resuspended in 200 µL Lumos, Thermo Scientific, San Jose, CA, USA). ice-cold HPLC-H2O. Sulfuric acid (H2SO4) was The samples were loaded (15 µL/min) on a added to the samples to a final concentration trapping column (nanoE MZ Sym C18, 5µm, of 0.4M. Samples were incubated on ice for 1 180umx20mm, Waters, Germany, buffer A: 0.1% hour on a shaker using 400 rpm. After cent- FA in HPLC-H2O; buffer B: 80% ACN, 0.1% FA ◦ rifugation (10 min at 10,000 rcf, 4 C), the su- in HPLC-H22O) with 5% buffer B. After sample pernatant containing the histone proteins, was loading, the trapping column was washed for added to 1.5 mL acetone and left at -20◦C 2 min with 5% buffer B (15 µL/min) and the overnight to precipitate the proteins. After peptides were eluted (250 nL/min) onto the sep- centrifugation, acetone was removed and the aration column (nanoE MZ PST CSH, 130 A, pellet was dried at room temperature. The C18 1.7µ, 75µ mx250mm, Waters, Germany) pellet was subsequently redissolved in 50 µL and separated with a gradient of 5–30% B in 25 HPLC-H2O. Protein concentration was determ- min, followed by 30-50% in 5 min. The spray was ined using the microplate BCA protein assay kit generated from a steel emitter (Fisher Scientific, (Thermo Fisher Scientific, Dreieich, Germany) Dreiech, Germany) at a capillary voltage of 1900 following the manufacturer’s instructions. V. For MS/MS measurements, an inclusion list was used for the two times acetylated isotopo- Tryptic in-solution digestion logue species of the H3 peptide KQLATKAAR. The fragment spectra were acquired in the orbit- For tryptic digestion, 6 µg of the histone extract rap mass analyzer using a resolution of 15,000 were diluted in HPLC-H2O to a final volume of (at m/z 200), a normalized HCD collision energy 50 µL. For reduction, the samples were incub- of 30, an AGC target of 5e4 and a maximum ated with 10 mM dithiothreitol (DTT, dissolved injection time of 120 ms. The full MS spectra in 100 mM ammonium bicarbonate (ABC), pH were acquired in the orbitrap mass analyzer with ◦ 8.3) for 10 min at 57 C on a shaker (600 rpm). a resolution of 60,000 (at m/z 200), an AGC Afterwards, the samples were alkylated with 20 target of 4e5, a maximum injection time of 50 mM iodacetamide (IAA, dissolved in 100 mM ms and over a m/z-range of 350-1650 using the ABC, pH 8.3) and incubated for 30 min at room ETD source for internal mass calibration. temperature in the dark. Subsequently, free Data analysis was performed in FreeStyle IAA was quenched by adding 10 mM of DTT 1.6 (Version 1.6.75.20, Thermo Scientific, (dissolved in 100 mM ABC, pH 8.3). For tryptic Bremen, Germany). For the three two- digestion, the samples were incubated with 1 times acetylated KQLATKAAR isotopologues µL of a trypsin solution (c = 0.2 µg/µL sequen- (K(ac12C)QLATK(ac12C)AAR, m/z: 535,8195; cing grade modified trypsin, dissolved in trypsin K(ac12C)QLATK(ac13C)AAR, m/z: 536,8228; resuspension buffer, Promega, Walldorf, Ger- K(ac13C)QLATK(ac13C)AAR, m/z: 537,8262), ◦ many) for 16 hours at 37 C. Afterwards, the extracted ion chromatograms (EIC) of all iso- samples were acidified by adding formic acid topes of the isotopic distributions of the different

7 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.31.361725; this version posted November 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. isotopologues were generated with a mass tol- erance of +/- 3 ppm. For peak detection, the Genesis algorithm was used with the follow- ing parameters: percent of highest peak: 10, minimum peak height (signal/noise): 5, signal- to-noise threshold: 3, tailing factor: 3. The peak area and the peak height was exported for each isotope of the isotopic distributions of the three different isotopologues to a tab-delimited text file.

Natural isotope correction We used the skewed matrix approach for correc- tion of high resolution natural isotope abund- ance as described Heinrich et al. 20188. PI- Cor is a Python based implementation of the isotopologue correction tool and is freely available on GitHub https://github.com/ MolecularBioinformatics/PICor and can be used for any organic compound. The user needs to specify the chemical composition and the type of labeling experiment and supply a data file with the peak integration values from MS measurements for the isotopologues of interest. It is not required to provide measurements for all possible isotopologues, which makes it applic- able for proteomics data. Full documentation can be found in the GitHub repository.

Software for isotopologue correc- tion The following software versions were used for the comparison of isotopologue corrections:

• AccuCor: v0.2.3.9000

• IsoCor: v2.2.0

• IsoCorrectoR: v1.6.2

• PICor (our tool): v1.0.0

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