1

Cancer Cell, Volume 23 Supplemental Information

PGC1 Expression Defines a Subset of Human

Melanoma Tumors with Increased Mitochondrial

Capacity and Resistance to Oxidative Stress

Francisca Vazquez, Ji-Hong Lim, Helen Chim, Kavita Bhalla, Geoff Girnun, Kerry Pierce, Clary B. Clish, Scott R. Granter, Hans R. Widlund, Bruce M. Spiegelman, and Pere Puigserver Inventory of Supplemental Information Supplemental Data Figure S1, related to Figure 1 Supplemental table 1, related to Figure 1 Supplemental table 2, related to Figure 1 Supplemental table 3, related to Figure 1 Figure S2, related to Figure 2 Figure S3, related to Figure 3 Figure S4, related to Figure 4 Figure S5, related to Figure 5 Figure S6, related to Figure 7

Supplemental Experimental Procedures Supplemental References

2

Stage Gender

Chi-square 1.17 p-value 0.76

B

Age

1 1

5 3

2 4

1 1

Low-PGC1 High-PGC1

2

8

6

2

IIIa

IIIb

IIIc

IV

6 6

3 3

Low-PGC1 High-PGC1

12

6

Male

Female

Age

Low-Pgc1a High-Pgc1a

0

20

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A Lin data set

Short-term melanoma cultures

800

600

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900

1200

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IDH3A ATP5g1 CytC COX5A ERRNdufs3 0

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pBabe-HA pBabe-HA-PGC1 A375 pBabe: pur

o

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A375

PGC1

Tubulin

Complex V (VF1a)

Complex I (Nduf9) Complex III (Core2)

Complex IV (Cox IV)

Complex I (Nduf9) Complex III (Core2)

Complex IV (Cox IV)

* * * * * *

E

PG

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ativ

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sion

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pmel A375 A375P

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52

0

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1000

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2000

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1A (

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Lung adenocarcinoma cell lines

4

Figure S1, related to Figure 1 (A) Relative expression of PPARGC1A mRNA expression in 82 short-term

melanoma cultures from the Lin et al. (Lin et al., 2008) data set.

(B) Analysis of significant association with a (a) stage, (b) gender or (c) age in

high and low PGC1 expressing melanoma tumors. Correlation between high or

low PGC1 expression from the GSE19234 data set (Bogunovic et al., 2009) and

clinico-pathologic parameters was determined using χ-square analysis for

nominal variables and t-test for age.

(C) qRT-PCR analysis of mitochondrial genes in stable PGC1 in A375

(PGC1negative) melanoma cells. Values represent mean±SD of two

independent experiments performed in triplicate. *p < 0.05.

(D) Western blot analysis of mitochondrial respiration-associated proteins after

overexpression of PGC1 in A375 cells.

(E) qRT-PCR analysis of PGC1 expression levels in immortalized primary

melanocytes, A375 and A375P cells.

(F) Gene expression levels of PPARGC1A (219195_at probe) across 52 lung

adenocarcinoma cell lines. Data is from the RMA normalized CCLE expression

data set (www.broadinstitute.org/ccle).

(G) A representative enrichment plot from the GSEA analysis.

5

Supplemental Table 1. GSEA analysis of genes ranked by positive correlation with PGC1 expression in short-term melanoma cultures

NAME NES FDR q-val

REACTOME_ELECTRON_TRANSPORT_CHAIN 2.51 0

REACTOME_GLUCOSE_REGULATION_OF_INSULIN_SECRETION 2.2 0

REACTOME_CITRIC_ACID_CYCLE 2.12 0

REACTOME_REGULATION_OF_INSULIN_SECRETION

2.01 0

REACTOME_INTEGRATION_OF_ENERGY_METABOLISM

1.91 0.01

REACTOME_METABOLISM_OF_AMINO_ACIDS

1.83 0.03

REACTOME_BRANCHED_CHAIN_AMINO_ACID_CATABOLISM

1.79 0.04

REACTOME_PYRUVATE_METABOLISM_AND_TCA_CYCLE

1.77 0.04

REACTOME_AMINO_ACID_TRANSPORT_ACROSS_THE_PLASMA_MEMBRANE 1.77 0.05

REACTOME_TRANSPORT_OF_MATURE_MRNA_DERIVED_FROM_AN_INTRON_ CONTAINING_TRANSCRIPT

1.66 0.11

REACTOME_METABOLISM_OF_CARBOHYDRATES

1.61 0.14

REACTOME_TRANSPORT_OF_RIBONUCLEOPROTEINS_INTO_THE_HOST_NUCLEUS

1.6 0.14

REACTOME_AMINO_ACID_AND_OLIGOPEPTIDE_SLC_TRANSPORTERS

1.63 0.14

REACTOME_E2F_TRANSCRIPTIONAL_TARGETS_AT_G1_S

1.62 0.14

REACTOME_PHASE_II_CONJUGATION

1.57 0.16

REACTOME_TRANSPORT_OF_THE_SLBP_INDEPENDENT_MATURE_MRNA

1.58 0.16

REACTOME_NUCLEAR_IMPORT_OF_REV_PROTEIN

1.56 0.17

REACTOME_REGULATION_OF_GLUCOKINASE_BY_GLUCOKINASE_REGULATORY_ PROTEIN

1.55 0.17

REACTOME_NEP_NS2_INTERACTS_WITH_THE_CELLULAR_EXPORT_MACHINERY

1.54 0.17

REACTOME_REV_MEDIATED_NUCLEAR_EXPORT_OF_HIV1_RNA

1.51 0.2

Gene expression of 82 melanoma short-term cultures extracted from the data set

of Lin et al. (Lin et al., 2008) and ranked for positive correlation with PPARGC1A

expression (219195_at probe) was analyzed with the GSEA. The significantly

enriched (q <0.25) gene sets ranked by normalized enrichment score are shown.

6

Supplemental Table 2. Gene sets enriched in control compared to PGC1 depleted A375 cells

NAME NES FDR q-val

 REACTOME_INTEGRATION_OF_ENERGY_METABOLISM 2.1 0.01

REACTOME_REGULATION_OF_INSULIN_SECRETION 2.09 0.01

REACTOME_GLUCOSE_REGULATION_OF_INSULIN_SECRETION 2.07 0.01

REACTOME_PYRUVATE_METABOLISM_AND_TCA_CYCLE 1.92 0.07

REACTOME_CITRIC_ACID_CYCLE 1.84 0.15

REACTOME_BRANCHED_CHAIN_AMINO_ACID_CATABOLISM 1.83 0.15

REACTOME_PYRUVATE_METABOLISM 1.81 0.14

REACTOME_ELECTRON_TRANSPORT_CHAIN 1.8 0.14

REACTOME_GLUCONEOGENESIS 1.79 0.14

REACTOME_GLUCOSE_METABOLISM 1.77 0.16

REACTOME_METABOLISM_OF_CARBOHYDRATES 1.72 0.23

Gene expression profile of A375P cells stably expressing control shRNAs or two

different shRNAs against PGC1 was analyzed with the GSEA algorithm. The

significantly enriched (q<0.25) gene sets ranked by normalized enrichment score

are shown.

7

Supplemental Table 3. Gene sets correlated with PPARGC1A expression in

lung adenocarcinoma cell lines.

NAME NES FDR q-val

REACTOME_REGULATION_OF_INSULIN_SECRETION 2.27 0.00

REACTOME_INTEGRATION_OF_ENERGY_ METABOLISM

2.25 0.00

REACTOME_GLUCOSE_REGULATION_OF_INSULIN_ SECRETION

2.24 0.00

REACTOME_ELECTRON_TRANSPORT_CHAIN 2.02 0.01

REACTOME_PYRUVATE_METABOLISM_AND_TCA_CYCLE 1.97 0.02

REACTOME_DIABETES_PATHWAYS 1.91 0.03

REACTOME_CITRIC_ACID_CYCLE 1.92 0.03

REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS 1.86 0.05

REACTOME_GLUCONEOGENESIS 1.73 0.13

REACTOME_GLUCOSE_METABOLISM 1.74 0.14

REACTOME_REGULATION_OF_LIPID_METABOLISM_BY_PEROXISOME_PROLIFERATOR_ACTIVATED_RECEPTOR_ALPHA

1.66 0.23

Gene Expression data from 52 lung adenocarcinoma cell lines from CCLE was

used to perform GSEA analysis. The table is showing the gene sets that are

significantly enriched (q<0.25).

8

A

B

C

mRNA expression (10081_at, RMA, log2) Copy number (log 2 ratio)

TP53 mutations BRAF mutations (V600D; V600E)

mRNA expression (10081_a, RMA, log2)

gege

9

E‐Box1  E‐box2 

Fold enrichment 13.26 FDR 0.02 

Fold enrichment 20.28 FDR 0.03 

E

D

-0.2 0.0 0.2 0.4 0.6 0.8 1.0-0.2

0.0

0.2

0.4

0.6

0.8

Proliferative (r)

Inva

sive

(r)

F

10

Figure S2, related to Figure 2

(A) Heat-maps of PGC1 expression (10891_at, RMA, log2) and copy number

levels (log2 ratio) in 60 melanoma cell lines (data from

www.broadinstitute.org/ccle), (Barretina et al., 2012).

(B) Heat-maps of PGC1 expression and p53 and BRAF mutations (V600E and

V600D) in 60 melanoma cell lines (data from www.broadinstitute.org/ccle),

(Barretina et al., 2012).

(C) qRT-PCR analysis of PGC1 target gene expression levels after knock-

down of MITF in A375P cells. Values represent means ± SD of three

independent experiments performed in triplicate. *p < 0.05 and **p < 0.01.

(D) Schematic representation of the PGC1 promoter construct.

(E) Genome view of PPARGC1A promoter showing the fold enrichment of MITF

occupancy. Data is from the annotated MACS output file from Strub et al. (Strub

et al., 2011) (Boxes indicate the regions of enrichment). The arrows indicate

the position of the oligonucleotides used in the CHIP experiment. The position of

the two E-Boxes is labeled.

(F) “Proliferative phenotype” signature of PGC1 positive melanoma tumors.

HOPP (Heuristic online phenotype prediction)

(http://jurmo.ch/hopp/hopp_about_hopp.php) was used to calculate the

correlation of the high (red) and low (black) PGC1 expressing melanoma

samples from the Riker data set with the proliferative or invasive phenotype

signatures as defined in Widmer at al, 2012. A Widmer plot of the values is

shown.

11

Re

lativ

e m

eta

bol

ite le

vels

F1P/F6P/G

1P/G6P

F16DP/F26DP/G16DP

DHAP

3-phosp

hoglycera

te PEP

Lactate

glycolytic intermediates

Re

lativ

e m

eta

bo

lite

leve

ls

citra

te

aconita

te

isocit

rate

-ketoglutara

te

succ

inate

fumarate/m

aleate

malate

TCA cycle intermediates

* * * * *

**

* * *

shScr shPGC1 shScr shPGC1

0

0.5

1

1.5

2

0

0.2

0.4

0.6

0.8

1.0

1.2

A B

Figure S3, related to Figure 3

Metabolomic analysis of (A) glycolytic and (B) TCA cycle intermediates. Data

was acquired using liquid chromatography and mass spectrometry. Values

represent mean ± SD of three independent experiments performed in duplicate.

*p < 0.05 and **p < 0.01.

12

1 2 3 4 1 2 3 4 1 2 3 4

0

5

10 15

20 25

30

35 C

ell N

um

be

rs (

x 1

000

)

0

10

20

30

40

50

Ce

ll N

um

be

rs (

x 10

00)

1 2 3 4 1 2 3 4

pBabe-HA-PGC1pBabe-puro

0

10

20

30

40

50

Cel

l Nu

mb

ers

(x

100

0)

0 2 4 6 8

10 12 14 16 18

Ce

ll N

um

bers

(x

10

00)

0

10

20

30

40

50

Ce

ll N

um

bers

(x

10

00

)

pWZL-blast pWZL-HA-MITF

pBabe-puro pBabe-HA-PGC1

pWZL-blast pWZL-HA-MITF

PG

C1

mR

NA

leve

ls

A375 SK-MEL-2

MIT

F m

RN

A le

vels

A375

5

100

150

200

250

300

0

5

100

150

200

250

300

0

A375

*

A375 SK-MEL-2

** **

A375

shRPS6 shScr

A375P

shRPS6 shScr

shRPS6 - + - +

A375 A375P

RPS6 (Long)

RPS6 (Short)

Tubulin

Days Days

Days Days Days

A

B C

D

a b

a b

13

Figure S4, related to Figure 4

(A) (a) Cell number analysis of A375P and A375 cell lines after RPS6 knock-

down. (b) Western blot analysis for the levels of RPS6 protein. Data represent

means ± SD of three independent experiments performed in triplicate. **p < 0.01.

(B) Cell number analysis of two PGC1 negative cell lines, A375 and SK-MEL-2,

ectopically expressing PGC1. Cells were infected with empty vector or PGC1

retroviruses and selected with puromycin (5 g/ml) for 6 days. Cell numbers were

measured for 4 days after puromycin. Data represent mean ± SD of three

independent experiments performed in quadruplicate.

(C) Cell number analysis in A375 ectopically expressing MITF. A375 cells were

infected with empty vector or MITF retroviruses and selected by blasticidin (5

g/ml) for 6 days. Cell numbers were measured for 4 days after blasticidin

selection. Data represent mean ± SD of three independent experiments

performed in quadruplicate. *p < 0.05.

(D) (a) PGC1 and (b) MITF mRNA expression levels in the cell lines described

in A and B were measured by qRT-PCR. Values represent mean ± SD of three

independent experiments performed in triplicate.

14

shMITF - - #1 #4 #1 #4

Ad-GFP Ad-PGC1

PGC1

Cleaved-PARP

Tubulin

p27

H2AX

Rel

ativ

e in

ten

sitie

s

0

5

10

15

20

shMITF - #1 #4 - #1 #4

Cleaved-PARP H2AX p27

- #1 #4 - #1 #4 - #1 #4 - #1 #4

Ad-GFP Ad-PGC1

shM

ITF

#1

shS

cr

shP

GC

1

shM

ITF

#1

shS

cr

shP

GC

1

Vehicle NAC

PGC1

MITF

Cleaved-PARP

H2AX

p27

Tubulin

A

B

a b

Figure S5, related to Figure 5

(A) (a) Western blot analysis of protein markers for apoptosis, DNA damage and

cell cycle arrest in A375P cells infected with lentivirus encoding MITF or control

shRNAs. 3 days after selection, cells were infected with adenoviruses encoding

GFP or Flag-HA-PGC1for 48 hours. (b) Quantitation of the signal intensity of

the western blots. Values represent mean ± SD of three independent

experiments.

(B) Western blot analysis of protein markers for apoptosis, DNA damage and cell

cycle arrest in A375P cells infected with lentiviruses expressing MITF or PGC1

shRNAs. 4 days after puromycin selection, infected cells were treated with 2mM

of NAC (N-Acetyl-L-Cystein) for 48 hours prior to harvesting.

15

Ce

ll V

iab

ility

(%

)

0

20

40

60

80

100

120

Piperlongumine (5M) - - + + - - + + PLX4032 (5M) - + - + - + - +

shScr shPGC1

0

1

2

3

4

5

A37

5P

Me

Wo

SK

-ME

L-5

G36

1

KO

29A

A3

75

SK

-ME

L-28

SK

-ME

L-2

RP

MI7

951

WM

115

PGC1positive PGC1negative

Ind

uctio

n f

old

of D

CF

-DA

(P

iper

long

um

ine/

Co

ntro

l)

A B

Figure S6, related to Figure 7

(A) Viability of A375P control and PGC1 depleted cells treated with PLX4032

and/or piperlongumine. Values represent mean ± SD of two independent

experiments performed in triplicate.

(B) ROS levels after piperlongumine treatment in PGC1 positive (red) and

negative (black) cell lines. ROS levels were measured using the DCF-DA dye

and FACS analysis. Values represent mean ± SD of two independent

experiments performed in triplicate.

Supplemental Experimental Procedures

GSEA analysis

For the GSEA analysis of the short-term melanoma cultures, the CEL files from

the 82 short-term melanoma in the Lin et al. (Lin et al., 2008) data set were used

to create an expression file using GenePattern and the default parameters. This

file was then used as input for the GSEA analysis.

For the lung cancer cell lines, the RMA normalized probe level mRNA expression

data was extracted from the CCLE data set and used as input for the GSEA

analysis. GSEA analysis were performed as described in the main experimental

procedures. The genes were ranked by correlation with the expression values of

the 219195_at probe for the Lin et al. and lund adenocarcinoma data sets. For

16

the analysis of the A375P data set, the default parameters were used but the

permutation type was changed to gene set.

Proliferative and invasive phenotype signatures enrichment

We classified the melanoma tumors from the Riker dataset into PGC1 high

(15th highest expressing) or PGC1 low (15th lowest expressing) using the

values for the 219195_at probe. We then used HOPP (Heuristic online

phenotype prediction) to compute the enrichment of these samples with the

“invasive” and “proliferative” melanoma signatures, as defined by Widmer et al.

(http://www.jurmo.ch/hopp/hopp_default_geo.php). We plotted the correlation

values in a Widmer plot (Widmer et al., 2012).

Correlation with clinical parameters

GSE1923 gene expression data set and clinical parameters were downloaded

from GEO. Samples were classified to high or low PGC1 levels by selecting the

25% top and bottom expressing tumors, respectively. The expression levels were

averaged for samples from the same patient. Survival curves were calculated

from these samples using Kaplan-Meier analysis and log rank test using survival

days since initial diagnosis. Correlation between PGC1 expression and stage or

gender was calculated using chi-square analysis. Correlation between PGC1

expression and age was calculated using t-test. Analysis was performed using

PRISM.

Western Blot

Cells were lysed in a buffer contained 1% IGEPAL, 150 mM NaCl, 20 mM

HEPES (pH7.9), 10 mM NaF, 0.1 mM EDTA, 1 mM Sodium orthovanadate and

1X protease inhibitor cocktail. Protein concentration was quantified using BCA

protein concentration assay kit (Error! Hyperlink reference not valid.). Equal

amounts of protein were electrophoresed on SDS-polyacrylamide gels and

transferred to Immobilon-P membrane (Millipore). Membranes were incubated

with primary antibodies in 5% bovine serum albumin containing 0.05% Tween-20

17

overnight at 4oC. The membrane was then incubated with HRP-conjugated

secondary antibody for 1 h at room temperature, and visualized using a Super

Signal West Dura Substrate (Error! Hyperlink reference not valid.) or ECL Plus

(GE healthcare).

Glucose Consumption, Lactate Production and ATP Levels

The lactate and glucose assay kit (BioVision Research Products) were used to

measure extracellular lactate and glucose, following manufacturer’s instructions.

Briefly, equal number of cells were seeded in 6-well plates and cultured in

phenol-red free DMEM for 24 h. Cultured medium was then mixed with the

reaction solution. Lactate levels were measured at 450 nm and glucose levels

were measured at 570 nm using a FLUO star Omega plate reader. Cells were

lysed and protein concentration was measured using BCA protein assay kit and

values were normalized to cellular protein concentration.

Intracellular ATP levels were determined in cell lysates using a luciferin-

luciferase based ATP determination kit (Invitrogen), according to the

manufacturer’s instructions. Briefly, equal number of cells were seeded in 6-well

plates and cell lysates were diluted appropriately in reaction buffer. The

luminescent readings were acquired using a FLUO star Omega micro plate

reader. Sample concentrations were calculated based on a standard curve of

known ATP concentrations. Protein concentration was measured using BCA

protein assay kit (Error! Hyperlink reference not valid.) and all values were

normalized to cellular protein concentration.

Apoptosis and Mitochondrial Membrane Potential Assays

Apoptotic cells were measured using Annexin-V-FITC and propidium iodide (BD

Pharmigen). Briefly, equal number of cells were seeded in 6-well plates. 72h

after seeding, cells were trypsinized, washed once with PBS and stained with

FITC-labelled anti-Annexin-V antibody and propidium iodide. Fluorescence was

acquired using BD FACS Canto II with FACS DIVA software.

18

Mitochondrial membrane potential was measured using the JC-1 dye (Invitrogen)

according to manufacturer’s instructions. Briefly, equal number of cells were

seeded in 6 well plates and 72 h later were incubated with 2 µM JC-1 for 15 min

in the same growth medium. Cells were then trypsinized, washed with PBS and

fluorescence was analyzed using a BD FACS Canto II with FACS DIVA software.

Metabolite Analysis

Scrambled or PGC1 shRNA stably expressing A375P cells were cultured for 48

h. At this time, medium was changed and cells were further cultured for 30

minutes. Monolayers were then washed with ice-cold PBS and metabolites were

extracted using ice-cold 80% methanol, three times. Each extraction was pooled.

Hydrophilic interaction liquid chromatography (HILIC)- negative ion mode mass

spectrometry (MS) data were acquired using an LC-MS system comprised of an

AQUITY UPLC system (Waters; Milford, MA) and a 5500 QTRAP mass

spectrometer (AB SCIEX; Foster City, CA). The extracts were injected directly

onto a 150 x 2.0 mm Luna NH2 column (Phenomenex; Torrance, CA) that was

eluted at a flow rate of 400μL/min with initial conditions of 10% mobile phase A

(20 mM ammonium acetate and 20 mM ammonium hydroxide in water) and 90%

mobile phase B (10 mM ammonium hydroxide in 75:25 v/v acetonitrile/methanol)

followed by a 10 min linear gradient to 100% mobile phase A. Multiple reaction

monitoring (MRM) was used to acquire targeted MS data for specific metabolites

in the negative ion mode. The ion spray voltage was -4.5 kV and the source

temperature was 500°C. Declustering potentials and collision energies were

optimized for each metabolite by infusion of reference standards prior to sample

analyses. The scheduled MRM algorithm in the Analyst 1.5 software program

(AB SCIEX; Foster City, CA) was used to automatically set dwell times for each

transition. MultiQuant software (version 1.1; AB SCIEX; Foster City, CA) was

used for automated peak integration, and metabolite peaks were manually

reviewed for quality of integration and compared against a known standard to

confirm identity.

19

Quantitative Real-Time PCR

Total RNA was isolated with Trizol (Invitrogen), and 2 µg of total RNA was used

for cDNA synthesis using high capacity cDNA reverse transcription kit (Applied

Biosystems). Quantitative real-time PCRs were carried out using SYBR Green

PCR Master Mix (Applied Biosystems). Experimental Ct values were normalized

to 36B4, and relative mRNA expression was calculated versus 36B4 expression.

Chromatin Immunoprecipitation Assays

ChIP assays were performed using ChIP Assay Kit (Upstate) according to

manufacture’s instructions. A375P cells were crosslinked with 1% formaldehyde

for 10 min at 37ºC and quenched with 0.125 M glycine. MITF and DNA

complexes were immunoprecipitated using anti-MITF mouse monoclonal

(Labvision/Thermo-Fisher) from the sonicated cell lysates, and the

immunoprecipitated DNA was quantified using Real-time PCR analysis, as

described above. Primers used for PCR correspond to the putative E-box within

the PGC1 promoter (region -586 to -467): 5’-ACA TAC AGG CTA TTT TGT

TGA TTA AAC-3’ and 5’-GCA AGA GCT TAT CAC ATG ATG CA-3’.

 

Reagents and Antibodies

N-acetyl-L-cysteine, Trolox, PEITC, H2O2, Q-VD-OPH, anti-SOD2 and anti-Flag

M2 antibodies were purchased from Sigma-Aldrich. Piperlongumine was

purchased from BioVision Research Products. Antibodies against cleaved-

caspase-3, 8, 9, PARP and RPS6 were purchased from Cell Signaling

Technology. Anti-PGC1 was purchased from Santa Cruz Biotechnology. Anti-

tubulin was purchased from Millipore. Anti-M-MITF has been previously

described (Huber et al., 2003). Anti-Ndufs3, ATP5b, Cox5a and MitoProfile total

OXPHOS antibody cocktail to detected mitochondria respiration proteins were

purchased from Mitosciences.

20

Plasmids

To construct pBabe-puro-HA-PGC1, a mouse cDNA from was PCR amplified

with KOD polymerase using the primers

F:CAGGATCCAATGGCTTGGGACATGTGCAGC and R:

GACTCGAGTTACCTGCGCAAGCTTCTCTG, digested with BamH1/XhoI, and

subsequently ligated into pcDNA3.1-HA to generate N-terminally HA-tagged

PGC1. The HA-PGC1 cassette was then excised by PmeI digest and blunt-

end cloned into the SnaBI site of pBABE.puro. pWZL-HA-MITF has been

previously described (Garraway et al., 2005).

The pLKO vectors used for the experiments were obtained from the TRC

consortium. PGC1 shRNA #1 (TRCN0000001165 (used only for gene-

expression arrays) PGC1 shRNA#2 (TRCN0000001166). Ndufs3

(TRCN0000036617), ATP5b (TRCN0000043437), Cox5a (TRCN0000045961),

GFP (TRCN0000072181), RPS6 (TRC0000040081), MITF shRNA # 1

(TRC0000019122), MITF shRNA #4 (TRC0000019119). Control shRNAs were

cloned into the pLKO vector using the following oligos. Control shRNA #1 is

forward: 5’-

CCGGCCTCGATTCCCTCAATGATCTCGAGATCATTGAGGGAATCGAGGTTTT

TG-3’ and reverse:

AATTCAAAAACCTCGATTCCCTCAATGATCTCGAGATCATTGAGGGAATCGA

GG. Control shRNA #2 is forward: 5’-

CCGGCAACAAGATGAAGAGCACCAACTCGAGTTGGTGCTCTTCATCTTGTT

GTTTTG-3’ and reverse: 5’-

AATTCAAAAACAACAAGATGAAGAGCACCAACTCGAGTTGGTGCTCTTCATC

TTGTTG-3’.

21

Primers used for quantitative real time PCR (qRT-PCR)

Gene Forward Primer Reverse Primer

PGC1 GTAAATCTGCGGGATGATGG AATTGCTTGCGTCCACAAA

ERR TGAGAAGCTCTATGCCATGCCTGAC CCAGCACCAGCACCTCCATCC

SOD2 TTGGCCAAGGGAGATGTTAC AGTCACGTTTGATGGCTTCC

GpX1 CCCTCTGAGGCACCACGGT TAAGCGCGGTGGCGTCGT

IDH3 CTGCTCAGTGCCGTGATG TCCTCTGTGAAGTCTGAGCATTT

Ndufs3 GCTGACGCCCATTGAGTCTG GGAACTCTTGGGCCAACTCC

Cyt C GGAGGCAAGCATAAGACTGG TCCATCAGGGTATCCTCTCC

Cox5a GGGAATTGCGTAAAGGGATAA TCCTGCTTTGTCCTTAACAACC

ATP5g1 ATCATTGGCTATGCCAGGAA ATGGCGAAGAGGATGAGGA

M-MITF CATTGTTATGCTGGAAATGCTAGA GGCTTGGTGTATGTGGTACTTGG

TYR TTGGCAGATTGTCTGTAGCC AGGCATTGTGCATGCTGCTT

36b4 CATGTTGCTGGCCAATAAGG TGGTGATACCTAAAGCCTGGAA

GLRX5 AGCTCCGACAAGGCATTAAA AGTGGATCCCCAGCTTTTTC

TXN2 TCAAGACCGAGTGGTCAACA AATATCCACCTTGGCCATCA

MGST2 CTGCTGGCTGCTGTCTCTATTC TTGTTGTGCCCGAAATACTCTC

GSTM4 TTGGAGAACCAGGCTATGGAC TTCCCCAGGAACTGTGAGAAGT

TXNDC14 GGACAAGAGGGTCACTTGGA AGGGTAGGGAGTTGCTTGGT

PRDX2 TGACACGATTAAGCCCAACGT GCACAAGCTCACTATCCGTTAGC

22

GSTK1 TCCAGATTCCCATCCACTTC GACGCTTTCTCCAGCATCTC

GSTM1 CTATGATGTCCTTGACCTCCACCGTATA ATGTTCACGAAGGATAGTGGGTAGCTGA

Supplemental References Huber, W. E., Price, E. R., Widlund, H. R., Du, J., Davis, I. J., Wegner, M., and Fisher, D. E. (2003). A tissue-restricted cAMP transcriptional response: SOX10 modulates alpha-melanocyte-stimulating hormone-triggered expression of microphthalmia-associated transcription factor in melanocytes. The Journal of biological chemistry 278, 45224-45230. Widmer, D. S., Cheng, P. F., Eichhoff, O. M., Belloni, B. C., Zipser, M. C., Schlegel, N. C., Javelaud, D., Mauviel, A., Dummer, R., and Hoek, K. S. (2012). Systematic classification of melanoma cells by phenotype-specific gene expression mapping. Pigment cell & melanoma research 25, 343-353.