Registered report: Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of α-ketoglutarate-dependent dioxygenases

The Reproducibility Project: Cancer Biology seeks to address growing concerns about reproducibility in scientific research by conducting replications of selected experiments from a number of high-profile papers in the field of cancer biology. The papers, which were published between 2010 and 2012, were selected on the basis of citations and Altmetric scores (Errington et al., 2014). This Registered report describes the proposed replication plan of key experiments from ‘Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of α-ketoglutarate-dependent dioxygenases’ by Xu and colleagues, published in Cancer Cell in 2011 (Xu et al., 2011). The key experiments being replicated include Supplemental Figure 3I, which demonstrates that transfection with mutant forms of IDH1 increases levels of 2-hydroxyglutarate (2-HG), Figures 3A and 8A, which demonstrate changes in histone methylation after treatment with 2-HG, and Figures 3D and 7B, which show that mutant IDH1 can effect the same changes as treatment with excess 2-HG. The Reproducibility Project: Cancer Biology is a collaboration between the Center for Open Science and Science Exchange, and the results of the replications will be published by eLife. DOI: http://dx.doi.org/10.7554/eLife.07420.001


Introduction
Mutations in IDH1 and IDH2 are found in gliomas and in acute myeloid leukemia. All mutations are heterozygous and result in changes to one of two amino acids: arginine 132 in IDH1, or either arginine 172 or arginine 140 in IHD2. Wild-type IDH1 catalyzes the conversion of isocitrate to α-ketoglutarate (α-KG). The arginine mutations abolish its normal activity and instead mutant IDH1 and IDH2 reduce α-KG to generate the oncometabolite 2-hydroxyglutarate (2-HG) , which in turn affects the function of multiple α-KG dependent dioxygenases, including the TET family of 5-methylcytosine (5 mC) hydroxylases (Kinney and Pradhan, 2012;McKenney and Levine, 2013). In their Cancer Cell 2011 paper, Xu and colleagues examined the effects of excess production of 2-HG on downstream processes that could affect cancer progression. They showed that 2-HG could act as a competitive inhibitor for α-KG-dependent DNA demethylases, specifically Tet2. Ectopic expression of the mutant forms of IDH1 and IDH2 inhibited histone demethylation and 5mC hydroxylation. Examination of glioma samples from patients also showed that mutations in IDH1 were associated with increased histone methylation and decreased 5-hydroxymethylcytosine (5hmC) levels (Xu et al., 2011).
In Supplemental Figure 3I, Xu and colleagues demonstrated that transfection of U-87 MG cells with the mutant IDH1 R132H increased the amount of 2-HG in the cells, as compared to transfection with wild-type IDH1 (Xu et al., 2011). This is evidence that mutant IDH1 changes the physiological levels of 2-HG, and is replicated in Protocol 1.
Xu and colleagues first showed that 2-HG can occupy the same binding pocket as α-KG in Caenorhabditis elegans KDM7A, indicating it acts as a competitive inhibitor of α-KG. Importantly, they also presented evidence that 2-HG may outcompete α-KG, since 2-HG levels affected many enzymatic functions normally dependent on α-KG. In Figure 3A, they treated U-87 MG cells with cell permeable versions of α-KG and 2-HG, and examined levels of histone methylation by Western Blot. Treatment with increasing amounts of 2-HG led to increases in H3K9me2 and H3K79me2, consistent with the idea that 2-HG inhibited histone demethylases. This effect was abolished by co-treatment with α-KG, confirming a competitive relationship between the two metabolites (Xu et al., 2011). This experiment is replicated in Protocol 2. Xu and colleagues also examined the effect of 2-HG on the TET family of 5 mC hydroxylases using an in vitro system of purified TET2 and double-stranded oligos containing a 5mC restriction digestion site in Figure 8A. Adding increasing concentrations of 2-HG abolished the ability of TET2 to convert 5 mC to 5hmC (Xu et al., 2011). This experiment will be replicated in Protocol 5.
In addition to demonstrating that the metabolite 2-HG can affect the activity of α-KG-dependent enzymes, Xu and colleagues showed that treatment with mutant forms of IDH1 and IDH2 resulted in similar outcomes. In Figure 3D, they transfected U-87 MG cells with IDH1 R132H and assessed levels of histone methylation by Western blot. Transfection with IDH1 R132H increased histone methylation, and treatment with α-KG abolished this increase in histone methylation, consistent with the idea that α-KG and 2-HG are competitive metabolites (Xu et al., 2011). This experiment will be replicated in Protocol 3. In Figure 7B, they also examined TET activity in the presence of mutant IDH1. While 5hmC levels are normally undetectable in HEK293 cells, transfection with TET catalytic domain (CD)-expressing plasmids increased 5hmC levels to detectable amounts. Co-transfection of TET-CD and wild-type IDH1 or IDH2 increased levels of 5hmC, as expected, while co-transfection of TET-CD with mutant forms of IDH1 and IDH2 decreased 5hmC levels (Xu et al., 2011). This experiment is replicated in Protocol 4.
The work of Xu and colleagues (Xu et al., 2011), along with work from Figueroa and colleagues (Figueroa et al., 2010) and Lu and colleagues , has generated much interest in the role of altered metabolites in the changing methylation patterns seen in various types of cancer. Using a different cell line than Xu and colleagues, Lu and colleagues demonstrated that mutations in IDH2, similar to mutations in IDH1, also generated abnormal levels of 2-HG which correlated with increased global methylation levels . Kernystsky and colleagues, Duncan and colleagues and Turcan and colleague have also shown that expression of exogenous mutated IDH genes in immortalized human cancer cell lines or in erythroid progenitor cells caused increased production of 2HG and increased levels of methylation (Duncan et al., 2012;Turcan et al., 2012;Kernytsky et al., 2015). Sasaki and colleagues extended these inquiries by generating conditional knock-in IDH1 mutant mice. These mice displayed elevated serum levels of 2HG and similar patterns of hypermethylation as observed in AML patients (Sasaki et al., 2012). Akbay and colleagues generated IDH2 mutant mice and also observed an increase in global methylation in heart tissue. They also demonstrated that mice carrying IDH mutant xenograft tumors displayed higher serum levels of 2HG (Akbay et al., 2014). Recently, 2-HG production has also been associated with MYC activation in some breast cancers, which also displayed increased levels of methylation as compared to tumors with lower levels of 2-HG (Terunuma et al., 2013).

Materials and methods
Unless otherwise noted, all protocol information was derived from the original paper, references from the original paper, or information obtained directly from the authors. An asterisk (*) indicates data or information provided by the Reproducibility Project: Cancer Biology core team. A hashtag (#) indicates information provided by the replicating lab.
Protocol 1: Gas chromatography-mass spectrometry measurement of cellular α-KG and 2-HG concentrations in U87MG cells ectopically expressing mutant IDH1 This protocol describes how to transfect cells with exogenous wild-type IDH1 or mutant IDH1 R132H and assess levels of α-KH and 2-HG by gas chromatography-mass spectrometry (GC-MS), as seen in Supplemental Figure 3I.

Confirmatory analysis plan
c Statistical analysis of the replication data: ○ Note: At the time of analysis we will perform the Shapiro-Wilk test and generate a quantile-quantile plot to assess the normality of the data. We will also perform Levene's test to assess homoscedasticity. If the data appears skewed we will perform the appropriate transformation in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test. ○ One-way MANOVA of α-KG and 2-HG levels in vector-transfected, IDH1-wildtype transfected, and IDH1 R132H -transfected cells with the following Bonferroni corrected comparisons: ■ α-KG levels planned comparisons: c vector vs IDH1 WT . c vector vs IDH R132H . c IDH1 WT vs IDH R132H . ■ 2-HG levels planned comparisons: c vector vs IDH1 WT . c vector vs IDH R132H . c IDH1 WT vs IDH R132H . c Meta-analysis of original and replication attempt effect sizes: ○ Compute the effect sizes of each comparison, compare them against the reported effect size in the original paper and use a meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot.
Known differences from the original study c Aspects of the Western blot protocol are provided by the replicating lab; complete details of the original protocol were unavailable. c Since the cell density during transfection is unknown in the original paper, the replicating lab will optimize growth conditions and cell density for transfection.

Provisions for quality control
All data obtained from the experiment-raw data, data analysis, control data and quality control data-will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/kvshc/). c Sequence data confirming plasmid identity. c Western blots confirming exogenous protein expression. c STR profiling confirming cell line authenticity. c Mycoplasma testing confirming lack of contamination. c Growth characteristics of the cells will be optimized.
Protocol 2: Western blot to assess histone methylation in U-87 MG cells following treatment with oct-2-HG and/or oct-α-KG This protocol describes how to treat U-87 MG cells with cell permeable versions of 2-HG and α-KG and assess histone methylation via Western blot, as seen in Figure 3A and Supplemental Figure 3F. c All cells will be sent for mycoplasma testing and STR profiling.

Sampling
1. Plate U-87 MG cells in 60 mm dishes. 2. 24 hr after plating, treat cells with 10 or 20 mM racemic Oct-2-HG or 5 mM Oct-α-KG or vehicle (DMSO) for 4-6 hr. a. To form racemic mixtures of Oct-2-HG, mix equal amounts of the L and R enantiomers. 3. Wash cells once with cold PBS, then lyse cells in 0.5 mL of SDS loading buffer.
a. 4× SDS-PAGE loading buffer: 50 mM Tris pH 6.8, 2% SDS, 10% glycerol, 1% B-ME, 12.5 mM EDTA, 0.02% bromophenol blue. b. # Measure protein concentration using a CBX assay. 4. Heat lysates at 99˚C for 10 min. 5. Run equal amounts of protein per well on a 4-20% SDS-PAGE gel at 220V until ladder marker reaches the bottom of the gel. 6. # Equilibrate gel in transfer buffer for 15 min. 7. # Meanwhile, cut membrane and 4 pieces 3 MM filter paper to size of gel. a. red pole (+) < clear plate < pad < 2 × 3 MM filter paper < membrane < gel < 2 × 3 MM filter paper < pad < black pole (−). 9. # Add stirring bar and ice box to transfer box and fill box with transfer buffer until cassette is submerged. a. Run at 100 V for 1 hr. 10. # Wash membrane in wash buffer for 2 × 5 min.
a. Blocking buffer: 3% non-fat milk in PBS. 12. # Incubate membrane with one of the following primary antibody in blocking buffer for 2 hr at RT or O/N at 4˚C (use manufacturer's suggested dilution in blocking buffer). a. H3K9me2. b. H3K79me2. c. H3. i. See Step 17 to strip and re-probe the blot with subsequent antibodies. 13. # Wash 5 min 2× with wash buffer. 14. # Incubate membrane with secondary antibody for 90 min at RT (use manufacturer's suggested dilution in blocking buffer). a. HRP-conjugated Goat Anti-Mouse IgG H&L: 1: 2000. 15. # Wash 3 × 5 min in wash buffer. 16. # Detect HRP-conjugated secondary antibodies with chemiluminescent detection according to the manufacturer's protocol and image on the Typhoon scanner. 17. Strip the blot in between probes: a. Wash the membrane with 100 ml stripping buffer (100 mM beta-mercaptoethanol, 1% SDS 25 mM glycine pH 2.0) for 30 min with agitation. b. Wash the stripped membrane twice with Western blotting wash buffer, 600 ml each wash, for 10 min with agitation. c. Go to the blocking step of the western blot protocol. d. Check that stripping was successful by repeating the detection step (without re-probing).
Record image of the stripped gel. This will confirm the first antibody-HRP conjugate is removed and/or inactivated. If the stripping procedure is successful, wash the membrane with washing buffer and repeat the blocking-probing and detection steps for the second antibody. i. Note: if stripping is unsuccessful, individual blots will be performed. 18. Quantify intensity of bands on western blots using ImageQuant 5. for each condition. Fold change in intensity relative to vehicle treated cells is plotted on the y axis (as seen in Supp. Figure 3F).

Confirmatory analysis plan
c Statistical analysis of the replication data: ○ Note: At the time of analysis we will perform the Shapiro-Wilk test and generate a quantilequantile plot to assess the normality of the data. We will also perform Levene's test to assess homoscedasticity. If the data appears skewed we will perform the appropriate transformation in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test. ○ Compute the effect sizes of each comparison, compare them against the reported effect size in the original paper and use a meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot.
Known differences from the original study c The original racemic mixture of Oct-2-HG was synthesized in house by the original lab. The replicating lab is purchasing both L and R enantiomers and mixing them in equal amounts to form a racemic mixture. c Aspects of the Western blot protocol are provided by the replicating lab; complete details of the original protocol were unavailable.

Provisions for quality control
All data obtained from the experiment-raw data, data analysis, control data and quality control data-will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/kvshc/). c STR profiling confirming cell line authenticity. c Mycoplasma testing confirming lack of contamination. c Images of stripped gel membranes confirming stripping was successful.

Protocol 3: Transfection of U-87 MG cells and determination of histone methylation by western blot
This protocol describes the transfection of U-87 MG cells with the mutant form of IDH1 and assessing methylation by Western blot, as seen in Figure 3D and Supplemental Figure 3J. a. red pole (+) < clear plate < pad < 2 × 3 MM filter paper < membrane < gel < 2 × 3 MM filter paper < pad < black pole (−). 10. # Add stirring bar and ice box to transfer box and fill box with transfer buffer until cassette is submerged. a. Run at 100 V for 1 hr. 11. # Wash membrane in wash buffer for 2 × 5 min.
a. Blocking buffer: 3% non-fat milk in PBS. 13. # Incubate membrane with primary antibody in blocking buffer for 2 hr at room temperature (RT) or overnight at 4˚C (use manufacturer's suggested dilution in blocking buffer a. Wash the membrane with 100 ml stripping buffer (100 mM betamercaptoethanol, 1% SDS 25 mM glycine pH 2.0) for 30 min with agitation. b. Wash the stripped membrane twice with Western blotting wash buffer, 600 ml each wash, for 10 min with agitation. c. Go to the blocking step of the western blot protocol. d. Check that stripping was successful by repeating the detection step (without re-probing).
Record image of the stripped gel. This will confirm the first antibody-HRP conjugate is removed and/or inactivated. If the stripping procedure is successful, wash the membrane with washing buffer and repeat the blocking-probing and detection steps for the second antibody. i. Note: if stripping is unsuccessful, individual blots will be performed. 19. Quantify intensity of bands on western blots using ImageQuant 5.2. Normalize levels of methylated histones to total H3 protein level. Normalize IDH1 R132H + vehicle and IDH1 R132H + octα-KG treated samples to vector + vehicle samples for each normalized methylated histone. 20. Repeat independently 5 additional times.
Deliverables c Data to be collected: ○ Full scans of western blots for H3, IDH1, H3K4me1, H3K4me3, H3K9me2, H3K27me2, and H3K79me2 (as seen in Figure 3D) including ladder. ○ Raw values of intensity of western blot bands as measured by ImageQuant 5.2 software. ○ Quantification of methylated histone values normalized to total protein level. ○ Quantification of average values and standard deviations for each condition. Levels of methylated histone in vector control cells are set to 100% and levels of methylated histone for other conditions are relative to vector control. ○ Table of average ± standard deviation of methylated histone levels normalized to H3 for each condition and relative to vector control cells (as seen in Supplemental Figure 3J).

Confirmatory analysis plan
c Statistical analysis of the replication data: ○ Note: At the time of analysis we will perform the Shapiro-Wilk test and generate a quantile-quantile plot to assess the normality of the data. We will also perform Levene's test to assess homoscedasticity. If the data appears skewed we will perform the appropriate transformation in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test. ○ One-way MANOVA of normalized H3K4me1, H3K4me3, H3K9me2, H3K27me2, and H3K79me2 levels from IDH1 R132H + vehicle and IDH1 R132H + oct-α-KG cells with the following Bonferroni corrected comparisons: ■ H3K4me1 levels of IDH1 R132H vs IDH1 R132H + oct-α-KG. ■ H3K4me3 levels of IDH1 R132H vs IDH1 R132H + oct-α-KG. ■ H3K9me2 levels of IDH1 R132H vs IDH1 R132H + oct-α-KG. ■ H3K27me2 levels of IDH1 R132H vs IDH1 R132H + oct-α-KG. ■ H3K79me2 levels of IDH1 R132H vs IDH1 R132H + oct-α-KG. ○ Bonferroni corrected one-sample t-tests (outside the MANOVA framework) of normalized levels from IDH1 R132H + vehicle of the following conditions compared to constant (vector + vehicle set to 100): ○ H3K4me1. ○ H3K4me3. ○ H3K9me2. ○ H3K27me2. ○ H3K79me2. c Meta-analysis of original and replication attempt effect sizes: ○ Compute the effect sizes of each comparison, compare them against the reported effect size in the original paper and use a meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot.
Known differences from the original study c While the manufacturer was specified for antibodies used, the exact catalog number was not. The RP:CB core team chose the most appropriate antibody from the manufacturer based on manufacturer's recommended applications and user reviews of the antibody. c Aspects of the Western blot protocol are provided by the replicating lab; complete details of the original protocol were unavailable.

Provisions for quality control
All data obtained from the experiment-raw data, data analysis, control data and quality control data-will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/kvshc/). c STR profiling confirming cell line authenticity. c Mycoplasma testing confirming lack of contamination. c Images of stripped gel membranes confirming stripping was successful.

Protocol 4: Dot blot to measure of levels of 5hmC in genomic DNA
This protocol describes how to transfect HEK293 cells with vectors expressing the catalytic domain of TET2 (TET2-CD) and wild-type or mutant forms of IHD1 and IDH2 and then assess genomic DNA hydroxymethylation by dot blot, as seen in Figure 7B and Supplemental Figure 7C.  ix. Cohort 9: FLAG-TET2-CD + FLAG-IDH2 R172K . 4. *For each cohort, transfect two parallel plates; harvest genomic DNA from one plate (proceed to

Materials and reagents
Step 5) and protein from the second plate (proceed to Step 7). 5. 36-40 hr after transfection, isolate genomic DNA from cells on the first plate using the QIAamp kit according to the manufacturer's instructions. a. Determine DNA concentration and purity. 6. Dot blot to assess levels of 5hmC: a. Quantify gDNA concentration using a NanoDrop. # Spot genomic DNA onto nitrocellulose membrane using a pipet, then crosslink the DNA to the membrane by UV irradiation for 2 min. i. The following amounts of genomic DNA should be spotted: 250 ng, 100 ng, 50 ng, 25 ng, 10 ng, and 5 ng. b. Bake nitrocellulose membrane at 80˚C for # 1 hr. c. Block membrane with 5% skim milk in TBS with 0.1% Tween 20 (TBST) for 1 hr. d. Perform western blot on spotted nitrocellulose with the following antibody: anti-5hmC. Incubate membrane with primary antibody diluted 1:10,000 overnight at 4˚C. e. Wash membrane three times with TBST. f. Incubate membrane with secondary antibody (HRP-conjugated anti-rabbit IgG) diluted 1:2000 for 1 hr at room temperature. g. Wash membrane three times with TBST, then treat with ECL and scan with a Typhoon scanner. h. Quantify dot-blot using Image-Quanta software. 7. Check expression of exogenous proteins by Western blot using the second plate.
a. Wash cells once with cold PBS, then lyse cells in 0.5 ml of SDS loading buffer. i. # 4× SDS-PAGE loading buffer: 50 mM Tris pH 6.8, 2% SDS, 10% glycerol, 1% B-ME, 12.5 mM EDTA, 0.02% bromophenol blue. b. Heat lysates at 99˚C for 10 min. c. Run SDS-PAGE gel until ladder marker reaches the bottom of the gel. d. # Equilibrate gel in transfer buffer for 15 min. e. # Meanwhile, cut membrane and 4 pieces 3 MM filter paper to size of gel.
i. Soak membrane in MeOH for a few seconds, then wash with H 2 O.
ii. Soak membrane, 3 mM filter paper and pads in transfer buffer.
i. Run at 100 V for 1 hr. h. # Wash membrane in wash buffer for 2 × 5 min.
i. Blocking buffer: 3% non-fat milk in PBS. j. # Incubate membrane with primary antibody in blocking buffer for 2 hr at RT or O/N at 4˚C (use manufacturer's suggested dilution in blocking buffer). i. α FLAG. k. # Wash 5 min 2× with wash buffer. l. # Incubate membrane with secondary antibody for 90 min at RT (use manufacturer's suggested dilution in blocking buffer). i. HRP-conjugated Goat Anti-Mouse IgG H&L: 1:2000. m. # Wash 3 × 5 min in wash buffer. n. # Detect HRP-conjugated secondary antibodies with chemiluminescent detection according to the manufacturer's protocol and image on the Typhoon scanner. o. Quantify intensity of dots on western blots using ImageQuant 5.2.
i. Normalize values to FLAG-TET2-CD transfected cells. 8. Repeat independently three additional times.
Deliverables c Data to be collected: ○ Chromatograms and sequence files confirming plasmid identity. ○ DNA concentration and purity data. ○ Full scans of dot blots for anti-5hmC and western blots for anti-FLAG (as seen in Figure 7B). ○ Raw values of intensity of dot blot as measured by Image-Quanta software. ○ Quantification of 5hmc values relative to TET2-CD. ○ Quantification of average values and standard deviations for each condition for all experiments. ○ Bar graph and table of average values and standard deviations relative to TET2-CD samples (as seen in Figure 7B and Supplemental Figure 7C).

Confirmatory analysis plan
c Statistical analysis of the replication data: ○ Note: At the time of analysis we will perform the Shapiro-Wilk test and generate a quantilequantile plot to assess the normality of the data. We will also perform Levene's test to assess homoscedasticity. If the data appears skewed we will perform the appropriate transformation in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test. ○ Comparison of the various genotypes for each of the DNA concentrations.
■ Bonferonni corrected one-sample t-test of normalized 5hmC levels of the following cohorts compared to constant (TET2-CD set to 1): . c Meta-analysis of original and replication attempt effect sizes: ○ Compute the effect sizes of each comparison, compare them against the reported effect size in the original paper and use a meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot.
Known differences from the original study c Aspects of the Western blot protocol are provided by the replicating lab; complete details of the original protocol were unavailable.

Provisions for quality control
All data obtained from the experiment-raw data, data analysis, control data and quality control data-will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/kvshc/).
c Sequence data confirming plasmid identity. c Western blots confirming exogenous protein expression. c STR profiling confirming cell line authenticity. c Mycoplasma testing confirming lack of contamination.
Protocol 5: Radiolabeled 5mC-5hmC conversion assay This protocol describes how to run the in vitro assay to examine the effect of 2-HG on the TET family of methyl hydroxylases, as seen in Figure 8A.
Sampling c This experiment will be performed independently a total of 6 times for a final power of ≥80%. ○ The original data is qualitative, thus to determine an appropriate number of replicates to initially perform, sample sizes based on a range of potential variance was determined. ○ See Power calculations for details. c Each experiment consists of 8 cohorts: ○ No recombinant protein. ○ Each cohort will detect: ■ 5m-dCMP. ■ 5hm-dCMP.
Note: This protocol contains information from Ito and colleagues (2010). c 10 mM D-2-HG vs 50 mM D-2-HG. ○ Bonferroni corrected one-sample t-tests (outside the ANOVA framework) of normalized 5hmC levels of TET2-CD protein treated with the following concentrations of D-2-HG compared to constant (TET2-CD + vehicle set to 1): c 10 mM D-2-HG. c 50 mM D-2-HG. c Meta-analysis of original and replication attempt effect sizes: ○ The replication data (mean and 95% confidence interval) will be plotted with the original reported data value plotted as a single point on the same plot for comparison.
Known differences from the original study c The lab provided the protocol for expansion of the viral aliquot shared by the original authors for generation of the recombinant FLAG-TET2 protein.

Provisions for quality control
All data obtained from the experiment-raw data, data analysis, control data and quality control data-will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/kvshc/).
c Sequence data confirming viral insert identity. c Data about viral titer and amount of and quality of protein generated.

Power calculations
Power calculations are performed to calculate the number of samples required to achieve at least 80% power and the indicated alpha error. For a detailed breakdown of all power calculations, please see spreadsheet at https://osf.io/gnsti/wiki/home/.

Protocol 1
Summary of original data c Note: Data estimated from published figures.

Test family
c Due to a lack of raw original data, we are unable to perform power calculations using a MANOVA. We are determining sample size calculations using a two-way ANOVA. c Two-way ANOVA followed by Bonferroni corrected comparisons.
Supp. Figure 3I *Because the original data reported null variances, the calculations below used the average of the non-null variances, 11.9, in place of a SD of 0.

Power calculations
c Calculations were performed with R software, version 3.1.2 (R Core Team, 2014) and G*Power software, version 3.1.7 (Faul et al., 2007).

Sensitivity calculations
c Comparing 2-HG levels from Vector to IDH1 WT: ○ Based on a sample size of 4 per group, we will be able to see an effect size of 3.3710662 with α = 0.01 and a power of 80%.  Power calculations c Power calculations were performed using G*Power software, version 3.1.7 (Faul et al., 2007).

Protocol 5
Summary of original data c Note: Data estimated from published figures. Figure 7B: Relative 5hmC intensity Mean SD N 50 ng Genomic DNA  TET2 + 50 mM L-2-HG 0.03 c One way ANOVA followed by Bonferroni corrected comparisons. c Outside the ANOVA framework ○ Bonferroni corrected one-sample t-tests compared to 1 (TET2 + vehicle).

Power calculations
c Because the original data presented does not have variance (s.e.m. or s.d.), we have performed power calculations using several different levels of calculated variance and an assumed number of replicates to determine a suitable number of replications to perform. c Calculations were performed with R software, version 3.1.2 (R Core Team, 2014) and G*Power software, version 3.1.7 (Faul et al., 2007).

2% variance
Calculated variances and assumed N