A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells

Article

A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells Graphical Abstract

Authors Hypoxia

SLC1A5

SLC1A5 variant

HIF2α

Hee Chan Yoo, Seung Joon Park, Miso Nam, ..., Geum-Sook Hwang, Seungmin Bang, Jung Min Han

Correspondence SLC1A5 gene

Gln

[email protected] M T S

GSH Plasma membrane

Drug resistance, ROS ATP

Glu

αKG

TCA cycle

mTORC1 activity Mitochondria

Highlights d

The SLC1A5 variant is a mitochondrial glutamine transporter

d

The SLC1A5 variant has a mitochondrial targeting sequence

d

Hypoxia controls SLC1A5 variant expression through HIF-2a

d

The SLC1A5 variant mediates mitochondrial glutamine metabolism in cancer

Yoo et al., 2020, Cell Metabolism 31, 1–17 February 4, 2020 ª 2019 Elsevier Inc. https://doi.org/10.1016/j.cmet.2019.11.020

In Brief Despite the importance of glutamine in cancer metabolism, the mitochondrial glutamine transporter has long been unknown. Yoo et al. show that a variant of SLC1A5 has a mitochondrial targeting signal for mitochondrial localization and is induced by HIF-2a. SLC1A5 variant knockdown suppressed cancer cell growth, supporting an oncogenic role.

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

Cell Metabolism

Article A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells Hee Chan Yoo,1 Seung Joon Park,1,2 Miso Nam,3 Juwon Kang,1 Kibum Kim,1,2 Joo Hye Yeo,1 Joon-Ki Kim,4 Yunkyung Heo,1 Hee Seung Lee,5 Myeong Youl Lee,6 Chang Woo Lee,6 Jong Soon Kang,6 Yun-Hee Kim,4 Jinu Lee,1 Junjeong Choi,1 Geum-Sook Hwang,3 Seungmin Bang,5 and Jung Min Han1,2,7,* 1Yonsei

Institute of Pharmaceutical Sciences, College of Pharmacy, Yonsei University, Incheon 21983, South Korea of Integrated OMICS for Biomedical Science, Yonsei University, Seoul 03722, South Korea 3Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 03759, South Korea 4Research Institute of National Cancer Center, Goyang-si, Gyeonggi-do 10408, South Korea 5Division of Gastroenterology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, South Korea 6Laboratory Animal Center, Korea Research Institute of Bioscience and Biotechnology, Ochang, Chungbuk 28116, South Korea 7Lead Contact *Correspondence: [email protected] https://doi.org/10.1016/j.cmet.2019.11.020 2Department

SUMMARY

INTRODUCTION

Glutamine is an essential nutrient that regulates energy production, redox homeostasis, and signaling in cancer cells. Despite the importance of glutamine in mitochondrial metabolism, the mitochondrial glutamine transporter has long been unknown. Here, we show that the SLC1A5 variant plays a critical role in cancer metabolic reprogramming by transporting glutamine into mitochondria. The SLC1A5 variant has an N-terminal targeting signal for mitochondrial localization. Hypoxia-induced gene expression of the SLC1A5 variant is mediated by HIF-2a. Overexpression of the SLC1A5 variant mediates glutamine-induced ATP production and glutathione synthesis and confers gemcitabine resistance to pancreatic cancer cells. SLC1A5 variant knockdown and overexpression alter cancer cell and tumor growth, supporting an oncogenic role. This work demonstrates that the SLC1A5 variant is a mitochondrial glutamine transporter for cancer metabolic reprogramming.

Glutamine, the most abundant amino acid in blood, is crucial for the synthesis of TCA (tricarboxylic acid) cycle metabolites, nonessential amino acids, nucleotides, fatty acids, antioxidants, and ATP energy (Fan et al., 2013; Metallo et al., 2011; Son et al., 2013; Yang et al., 2017). Cancer cells and rapidly proliferating cells are especially dependent on glutamine (Wise and Thompson, 2010), which is converted to glutamate by the mitochondrial glutaminase (GLS) (Cassago et al., 2012). Glutamate is subsequently deaminated to a-ketoglutarate (a-KG) by glutamate dehydrogenase (GDH). Incorporation of a-KG into the TCA cycle is the major anaplerotic step in glutamine metabolism (DeBerardinis et al., 2008). As a signaling molecule, glutamine activates the mTORC1 (mechanistic target of rapamycin complex 1) pathway and promotes cell growth (Dura´n et al., 2012). Cancer cells take up glutamine through several glutamine transporter families: SLC1, 6, 7, and 38 (Pochini et al., 2014). Among these transporters, SLC1A5 (also known as ASCT2), an obligatory sodium-dependent transporter for neutral amino acids (Kekuda et al., 1996), has been deeply studied since it was shown to be involved in several cancers (Liu et al., 2018; Willems et al., 2013). Inhibition of SLC1A5 impedes glutamine uptake, leading to disturbance of mTORC1 signaling and activation of autophagy (Nicklin et al., 2009) and cancer cell growth (Hassanein et al., 2013).

Context and Significance Altered metabolism is a hallmark of cancer. Cancer cells frequently develop glutamine addiction that fuels the TCA cycle, macromolecular biosynthesis, and redox homeostasis. Despite the importance of glutamine in cancer metabolism, the identity of the mitochondrial glutamine transporter has been unknown. In this study, researchers at Yonsei University in Korea and their collaborators discover that a variant of the transporter protein SLC1A5 is a mitochondrial glutamine transporter. The identified SLC1A5 variant promotes a metabolic switch in cancer cells, by enhancing glutamine metabolism, and contributes to drug resistance. This role of the SLC1A5 variant may resolve several paradoxes in cancer metabolism and drug resistance and may serve as a basis for the development of cancer therapies that inhibit mitochondrial glutamine metabolism. Cell Metabolism 31, 1–17, February 4, 2020 ª 2019 Elsevier Inc. 1

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

A

B

PNGase F : –

Human SLC1A5 Genomic Locus

–

+

–

+

45

E8

35

1A5_var

Na,K-ATPase

Merge

DAPI

Enlarged

Merge

Enlarged

Signal intensity Signal intensity

DAPI

60

1A5

F

1A5_var Cox4

300 200 100 0

0

5

200

10 15 20 1A5 Na,K-ATPase

150 100 50 0

0

5

10

35

1A5_var

15

Index of colocalization (%)

E5 E6 E7

E

1A5

+

75

45

D

Cox4

–

+

60

25

1A5_var

–

+

75

1A5 E2 E3 E4

sisi-con si-1A5 1A5_var

PNGase F : –

+

SLC1A5 SLC1A5_var Transcription start Transcription start

E1

C

1A5 1A5_var

Con

1A5_var

***

100

***

***

1A5

80 60 40 20 0

20

Cox4

In vitro mitochondrial Gln uptake (pmole/μg)

OM

1A5_var 1A5_var

1A5

Tom20

Na,K-ATPase

Tim23

β-actin

MnSOD2

LAMP2

1A5_var 1A5_var D186A

Con 1A5

*

50

J si-con

In vitro mitochondrial Gln uptake (pmole/μg)

I Matrix

H IM

HM Cyto PM Lyso

G

Mito

Distance (μm)

*

*

40 30 20 10 0 5 15 60

5 15 60

5 15 60

* *

20

10

0

5 15 60

5 15 60

Time (min)

L 1A5

1A5_var

si-con

* *

150 100 50 0

Ala

Ser

M

In vitro mitochondrial amino acid uptake (%)

In vitro mitochondrial amino acid uptake (%)

Con 200

Gln

si-1A5

si-1A5_var

100

50

***

***

***

0

Ala

Glu

N

Ser

Gln

3 ***

2 *

*

* *

1

0

Gln :

Relative D-KG level

Relative D-KG level

2.0 ***

1A5_var

* 45 30 15

n.s

n.s

n.s

0

P

Whole cell Mitochondria

Con

60

Con HgCl2GPNA BnzSer

Glu

O 4

5 15 60

5 15 60

Time (min)

In vitro mitochondrial Gln uptake (pmole/μg)

K

si-1A5_var

si-1A5

30

1.5

Whole cell Mitochondria *

*

N-term *

*

1.0 C-term 0.5

Intermembrane space

0

– + – + – +

– + – + – +

Con 1A5 1A5 _var

Con 1A5 1A5 _var

Gln :

– + – + – +

– + – + – + Matrix

Figure 1. A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter (A) The schematic shows exons and introns within the human SLC1A5 gene locus and two transcriptional variants of the SLC1A5 gene. (B and C) MiaPaCa2 cells were transfected with control (Con), SLC1A5, or SLC1A5_var vectors (B) or with control, SLC1A5, or SLC1A5_var siRNA (C), and cell lysates were analyzed by immunobloting. (legend continued on next page)

2 Cell Metabolism 31, 1–17, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

For the mitochondrial glutaminolysis, cytosolic glutamine must diffuse across the outer mitochondrial membrane (Zalman et al., 1980) and pass through the inner mitochondrial membrane using the mitochondrial glutamine transporter (Mate´s et al., 2009). Only preliminary evidence on this transporter has been reported (Molina et al., 1995; Indiveri et al., 1998). These studies have demonstrated the presence of a specific glutamine carrier system across the inner mitochondrial membrane. However, despite its importance in cancer metabolism, the exact identity of the mitochondrial glutamine transporter is still unknown. In this study, we show that a novel variant of the SLC1A5 gene, transcribed from its alternative transcription initiation site, is localized to the inner mitochondrial membrane through its N-terminal mitochondrial targeting signal. Hypoxia-induced expression of the SLC1A5 variant is mediated by HIF-2a. Overexpression of the SLC1A5 variant induces metabolic reprogramming, ATP generation, glutathione synthesis, and gemcitabine resistance in pancreatic cancer cells. Knockdown of the SLC1A5 variant impaired mitochondrial function and decreased cancer cell growth. These results suggest that the mitochondrial glutamine transporter, SLC1A5 variant, plays critical roles in cancer metabolism and would be one of the most promising therapeutic targets. RESULTS A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter To find the mitochondrial glutamine transporter, we first predicted that the mitochondrial glutamine transporter would have structural similarity to the core domain of the existing glutamine transporters and then examined their variants. In humans, the SLC1A5 gene, which is composed of eight exons, has two transcriptional variants that differ in the transcription initiation site (NM_005628.2 and NM_001145145.1) (Figure 1A). A long transcript (SLC1A5, known as ASCT2, GenBank: NM_005628.2) lacking exon 2 encodes 541 amino acids, while a short SLC1A5 variant (SLC1A5_var, GenBank: NM_001145145.1) lacking exon 1 encodes 339 amino acids (Figures S1A and S1B). The bioinformatics analysis using human SLC1A5_var amino acid sequence showed the conservation of this variant in different species (Figures S1C and S1D). In normal mouse tissues and human tissue expression database (GTEx), SLC1A5_var showed the highest expression in prostate (Figures S1E– S1G), suggesting the functional role of SLC1A5_var in prostate physiology, although further investigation is needed.

Next, we analyzed the expression of SLC1A5_var in normal and cancer tissues using The Cancer Genome Atlas (TCGA). Higher SLC1A5_var expression was noted in adenocarcinomas of pancreas, colon, lung, ovary, breast, and liver (Figure S1H). Kaplan-Meier analysis indicated that high SLC1A5_var expression was closely correlated with poor survival outcomes in several adenocarcinomas except colon (Figure S1I). Compared to normal human pancreatic ductal epithelial (HPDE) cells, all tested pancreatic cancer cells showed higher gene expression of endogenous SLC1A5_var (Figure S1J). In colon cancer cell lines, the gene expression of endogenous SLC1A5_var was higher than that in normal human colon epithelial (FHC) cells (Figure S1K). In lung cancer cell lines, except NCI-H358, the gene expression of both endogenous SLC1A5_var and SLCA5 was higher than that in normal human fibroblast (BJ) cells or normal human bronchial epithelial (16HBE) cells (Figure S1L). Endogenous and exogenous SLC1A5_var was detected with anti-SLC1A5 antibody that can recognize the SLC1A5_var after peptide-N-glycosidase F (PNGase F) treatment. The band shifted after PNGase F treatment, implying that these two proteins are highly glycosylated (Figure 1B). Silencing of SLC1A5 or SLC1A5_var by their specific siRNAs (Figure S1A) reduced the expression of each protein (Figure 1C). Consistent with the gene expression pattern of SLC1A5_var, the protein expression of SLC1A5_var was higher in pancreatic, colon, and lung cancer cell lines (Figure S1M), supporting the elevated expression of endogenous SLC1A5_var in several types of cancer cells. Next, we determined the subcellular localization of SLC1A5_var. Immunofluorescence analysis showed that SLC1A5_var colocalized with a mitochondria Cox4 but not with plasma membrane (Na,K-ATPase), ER (ERp72), Golgi (GM130), or lysosome (LAMP2) markers, indicating the mitochondrial localization of SLC1A5_var, while SLC1A5 colocalized with Na,K-ATPase (Figures 1D–1F and S2A–S2D). We also monitored the subcellular localization of other glutamine transporters. SLC38A1, SLC38A2, and SLC7A5 colocalized with Na,K-ATPase, whereas SLC38A9 colocalized with LAMP2 (Figures S2E and S2F). We examined the expression of several plasma membrane glutamine transporters such as SLC1A5, SLC38A1, SLC38A2, SLC6A14, SLC7A6, and SLC7A5 in MiaPaCa2 and Panc1 cells. Among them, SLC38A1, SLC38A2, SLC1A5, and SLC7A5 were highly expressed, implying the functional redundancy of plasma membrane glutamine transporters (Figure S2G). By subcellular fractionation analysis, a large amount of SLC1A5_var was found in the COX4-enriched fraction while SLC1A5 was found in the Na,KATPase-enriched fraction (Figure 1G). Furthermore, SLC1A5_var

(D) Immunofluorescence of SLC1A5_var or SLC1A5. Cells were reacted with indicated antibodies. Nuclei were counterstained with DAPI. (E) The fluorescence intensity profile across the line for both green and red channels in (D). (F) Quantification of colocalization between SLC1A5_var and subcellular organelle markers. (G) Subcellular fractionation of SLC1A5_var in MiaPaCa2 cells. HM, homogenate; Cyto, cytosol; PM, plasma membrane; Lyso, lysosome; Mito, mitochondria. (H) Submitochondrial fractionation of MiaPaCa2 cells for SLC1A5_var. OM, mitochondrial outer membrane; IM, inner membrane. (I and J) [3H]glutamine uptake into mitochondria purified from MiaPaCa2 cells in overexpression (I) or knockdown (J) condition. (K and L) Radiolabeled amino acid uptake into mitochondria purified from MiaPaCa2 cells in overexpression (K) or knockdown (L) condition. Ala, alanine; Ser, serine; Gln, glutamine; Glu, glutamate. (M) [3H]glutamine uptake into mitochondria purified from MiaPaCa2 cells expressing Con or SLC1A5_var. HgCl2, 20 mM mercury chloride; GPNA, 100 mM L-g-glutamyl-p-nitroanilide; BnzSer, 100 mM benzylserine. (N and O) Intracellular and mitochondrial a-KG levels in MiaPaCa2 cells in overexpression (N) or knockdown (O) condition. (P) Visualization of SLC1A5_var topology as generated by Protter. The error bars represent mean ± SD (*p < 0.05; **p < 0.01; ***p < 0.005; n.s., not significant).

Cell Metabolism 31, 1–17, February 4, 2020 3

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

A

C

B

D

F

E

H

G

I

J

K

Figure 2. The SLC1A5 Variant Has an N-Terminal Mitochondrial Targeting Sequence (A) Schematic sequence of the N terminus (NT) and C terminus (CT) of SLC1A5_var. WT, wild type; 3A, R9A/R15A/K17A; 2A, R44A/K45A. (B) PrediSi prediction for the NT of SLC1A5_var. (legend continued on next page)

4 Cell Metabolism 31, 1–17, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

co-fractionated with Tim23, an inner mitochondrial membrane marker, but not with Tom20, an outer mitochondrial membrane marker, or MnSOD2, a mitochondrial matrix marker (Figure 1H). These data clearly show that SLC1A5_var is localized to the mitochondria while SLC1A5 is localized to the plasma membrane. Next, we examined the role of glycosylation on the localization of SLC1A5_var using tunicamycin, inhibitor of N-linked glycosylation (Tkacz and Lampen, 1975). Tunicamycin decreased the colocalization of SLC1A5_var and Cox4 (Figures S2H–S2J) and the amount of SLC1A5_var in Cox4-enriched fraction (Figure S2K). Furthermore, SLC1A5 was detected in the cytosolic fraction by tunicamycin treatment (Figure S2K). These results suggest that glycosylation is involved in proper subcellular localization of SLC1A5_var and SLC1A5. To examine the role of SLC1A5_var on mitochondrial glutamine uptake, we made an alanine mutant (D186A) within the conserved SLC1A5_var NMDG motif, a sodium ion binding site (Figure S3L). In the mitochondrial glutamine uptake assay, only the purified mitochondria from SLC1A5_var-overexpressing cells showed increased glutamine uptake compared to those from control cells (Figure 1I). Contrarily, downregulation of SLC1A5_var, but not SLC1A5, suppressed mitochondrial uptake of glutamine (Figure 1J). Additionally, SLC1A5_var, but not SLC1A5, controlled the uptake of alanine and serine, which are other SLC1A5 substrates, but not glutamate (Figures 1K and 1L). We further investigated whether SLC1A5 inhibitors such as GPNA (l-g-Glutamyl-pnitroanilide) and benzylserine could inhibit SLC1A5_var-mediated mitochondrial glutamine transport. Pretreatment with these inhibitors interrupted both basal and SLC1A5_var-mediated mitochondrial glutamine uptake (Figure 1M). In the mitochondria, glutamine is catalyzed to glutamate by GLS (Cassago et al., 2012). At least three GLSs (GLS1, GLS2, and GLS1 variant, GAC) have been identified. All these GLSs are known to be localized to the mitochondria (Lukey et al., 2019; Li et al., 2019; Velletri et al., 2013). Consistently, we observed the co-localization of GLSs and Mitotracker (Figures S2M and S2N) and the enrichment of GLSs in the Cox4-enriched fraction (Figure S2O), implying that glutamine is mainly metabolized through the mitochondrial glutaminolysis pathway. Since mitochondrial glutamine is metabolized to a-KG (DeBerardinis et al., 2008), we monitored the effect of SLC1A5_var on the a-KG level in whole cells or purified mitochondria. Overexpression of SLC1A5_var increased (Figure 1N) and knockdown of SLC1A5_var decreased (Figure 1O) glutamine-derived a-KG levels in whole cells and purified mitochondria. SLC1A5_var is predicted to have six transmembrane domains with both its N terminus and C terminus in the intermembrane space (Figure 1P). These results demonstrate that SLC1A5_var is a mitochondrial glutamine transporter.

The SLC1A5 Variant Has a Mitochondrial Targeting Sequence (MTS) Next, we examined whether SLC1A5_var has a specific MTS. For mitochondrial translocation, molecular chaperones recognize the MTS of a protein and deliver it to the mitochondrial surface where mitochondrial translocase resides (Chacinska et al., 2009). The N-terminal or C-terminal fragment of SLC1A5_var was fused to the EGFP protein to identify its MTS (Figure 2A). In addition, since the N-terminal fragment of SLC1A5_var has a predicted MTS (Figure 2B), point mutations were introduced within the N-terminal fragment of SLC1A5_var (Figure 2A). Interestingly, the wild-type N terminus (termed NT_WT) and R9A/ R15A/K17A N terminus mutant (termed NT_3A) drove mitochondrial localization of EGFP (Figures 2C and 2D), but the R44A/ K45A N terminus mutant (termed NT_2A) showed diffused cytosolic staining (Figure 2C). Using subcellular fractionation (Figure 2E), EGFP fused with NT_WT or NT_3A was detected with Cox4 in the purified mitochondrial fraction (P4), whereas control EGFP and NT_2A-fused EGFP were detected in the cytosolic and endomembrane fractions (Figure 2F). To further confirm the importance of SLC1A5_var MTS, the R44A/K45A mutation (termed SLC1A5_var_2A) was introduced into the full-length SLC1A5_var. Immunofluorescence analysis showed that this mutation disrupted the mitochondrial localization of SLC1A5_var (Figures 2G–2I). In addition, SLC1A5_var_2A was not detected with Cox4 in the mitochondrial P4 fraction (Figure 2J). The purified mitochondrial fraction from cells overexpressing SLC1A5_ var_2A could no longer take up glutamine, while that from cells overexpressing SLC1A5_var showed increased glutamine uptake (Figure 2K). These data demonstrate that SLC1A5_var has a functional MTS for mitochondrial localization. Hypoxia Induces SLC1A5 Variant Expression In hypoxia, cancer cells utilize glutamine for lipid synthesis, ATP energy, and TCA cycling (Metallo et al., 2011; Fan et al., 2013; Le et al., 2012). Hence, we investigated whether hypoxia controlled the gene expression of SLC1A5_var. In eight different pancreatic cancer cell lines, the gene expression of both SLC1A5_var and SLC1A5 increased in hypoxia compared to normoxia, and the gene expression of SLC1A5_var increased more than that of SLC1A5 (Figure S3A). Hypoxia, cobalt chloride, and deferoxamine (DFO) treatment induced the gene expression and the protein expression of SLC1A5_var and SLC1A5 in MiaPaCa2 cells (Figures S3B and S3C). To further characterize the association between hypoxia and transcriptional regulation of SLC1A5_var, we prepared two luciferase reporter constructs. One contained nucleotides
2,342 through +1 of the SLC1A5_var promoter, and the other

(C) Colocalization of SLC1A5_var fragments fused to the NT of EGFP with Mitotracker. (D) Quantification of colocalization between SLC1A5_var fragments and MitoTracker. (E) Schematic of the steps for mitochondria isolation (P4) from cell homogenates. (F) Mitochondrial fractionation of SLC1A5_var fragments fused to the NT of EGFP. (G) Immunofluorescence of SLC1A5_var or SLC1A5_var_2A (R44A/K45A). (H) Quantification of colocalization in (G) (n = 15). (I) The fluorescence intensity profile across the line in (G). (J) Mitochondria fractionation of SLC1A5_var and SLC1A5_var_2A (R44A/K45A). (K) [3H]glutamine uptake into mitochondria purified from HeLa cells expressing Con, SLC1A5_var, or SLC1A5_var_2A (R44A/K45A). The error bars represent mean ± SD (*p < 0.05; **p < 0.01; ***p < 0.005; n.s., not significant).

Cell Metabolism 31, 1–17, February 4, 2020 5

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

A

0.5 0.0

0

10

0

si-HIF-1α

si-c-Myc

si-con

si-HIF-2α H

N

H

1

2.75 1.28

2.92

0.60

0.31 1.33 3.04

1

1.63 0.80 1.83

0.67

0.65 0.99 1.76

si-c-Myc

si-HIF-2α

si-HIF-1α

PDK1

HIF-1α

0.5

HIF-2α c-Myc

NHNHNHNH si-con

5

N

CCND1

si-c-Myc

si-HIF-2α ***

H

1A5

1.0

0.0

***

15

N

SLC38A1

HIF-2α

Con HIF-2α

Con HIF-2α

Relative mRNA level

si-con

***

NHNHNHNH

20

NHNHNHNH

3

β-actin

si-c-Myc

2

0

si-HIF-2α

** *

H

1A5_var

si-HIF-1α

4

N

*

1

1.5

***

***

2

Relative mRNA level

6

***

***

3

si-c-Myc

si-HIF-2α

si-HIF-1α

si-con

*

1.0

D

c-Myc

8

***

4

CCND1 *** ***

2

1

0

Con HIF-2α

SLC38A1

PDK1

1.5

Relative mRNA level

0

Con HIF-2α

NHNHNHNH

5

Relative mRNA level

1

0

1A5 ***

***

2

si-con

NHNH NHNH

1.5

***

si-HIF-1α

0.5

2.0

4

CCND1

Relative mRNA level

***

Relative mRNA level

1.0

0.0

***

si-c-Myc

HIF-2α

1.5

Relative mRNA level

***

si-HIF-2α

NHNH NHNH

si-c-Myc

si-HIF-2α

si-con Relative mRNA level

1A5_var

2

0

si-con

NHNH NHNH

3

*

1

Relative mRNA level

0.5

C

2

6

Relative mRNA level

Relative mRNA level

1.0

0.0

3

si-c-Myc

si-HIF-2α

HIF-1α

1.5

***

si-con

NHNH NHNH si-con

0

**

***

PDK1

si-c-Myc

2

***

4

si-HIF-2α

4

5

si-HIF-1α

***

1A5

si-HIF-1α

***

***

6

si-HIF-1α

Relative mRNA level

Relative mRNA level

8

si-HIF-1α

Relative mRNA level

B 1A5_var

1.0

0.5

0.0

Con HIF-2α

E

1.5

1.0

0.5

0.0

Con HIF-2α

F

HIF-2α 0.6

1 amplicon

0.2

2 amplicon

si-con

β-actin

4 amplicon

amplicon :

0.1% Input

Control IgG anti-HIF-2α Ab

% of total input

1.0

***

0.8 0.6 0.4

1A5_var WT HRE

*** 200 *** 150

* n.s

100 50

0

N

1A5_var mtHRE

250

3

4

1A5_var WT HRE

n.s

800

1A5_var mtHRE

*** 600

***

***

400

200

0

CoCl2 – + – + – +

0

HIF-2α – HIF-1α

0.2

2

– –

–

H

– + – + – + si-HIF-1α

IgG

1

I

si-con

IP

H 1 amplicon

HIF-2D

Ratio of Fire-luc / Renila-luc

G

H

Ratio of Fire-luc/Renila-luc

N

si-con

0

3 amplicon

si-HIF-2α

CCND1

si-con

HIF-2α

si-HIF-2α

amplicons

si-HIF-2α

1.52

si-con

0.96

si-con

0.83

anti-HIF-2α Ab

0.4

si-HIF-2α

1

1A5

Control IgG

si-HIF-1α

4.13

si-HIF-2α

3.02

*** ***

si-HIF-2α

1.11

4

% of total input

1

3

IgG anti-HIF-2D

1A5_var

2

0.1% Input

1

IgG anti-HIF-2D 0.1% Input

si-con si-HIF-2α

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Figure 3. HIF-2a Mediates Hypoxia-Induced SLC1A5 Variant Expression (A) Real-time PCR analysis of the expression of SLC1A5 variant, HIF-a target genes. N, normoxia; H, hypoxia. (B) Effect of HIF-2a knockdown on SLC1A5_var and SLC1A5 protein levels. N, normoxia; H, hypoxia. (legend continued on next page)

6 Cell Metabolism 31, 1–17, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

contained a mutant HRE (hypoxia response element) sequence (Semenza et al., 1996) (Figure S3D). Hypoxia and cobalt chloride induced an approximately 20% and 50% increase in WT promoter activity, respectively. However, the mutant HRE reporter showed a 70% decrease in promoter activity in normoxia compared to the WT HRE reporter and did not show significant increase in promoter activity even in hypoxia or cobalt chloride treatment (Figures S3E and S3F), indicating that the gene expression of SLC1A5_var is controlled by hypoxia. Hypoxic Activation of the SLC1A5 Variant Is HIF-2a Dependent Next, we identified the underlying mechanism of hypoxia-induced SLC1A5_var expression. Interestingly, downregulation of HIF-2a specifically impaired the normoxia- or hypoxia-induced expression of SLC1A5_var, SLC1A5, and CCND1, which is known to be a HIF-2a target gene (Cho et al., 2016). Downregulation of HIF-1a or c-Myc had little impact on the gene expression of SLC1A5_var (Figure 3A). Furthermore, downregulation of HIF-2a impaired the hypoxia-induced protein expression of SLC1A5_var and SLC1A5 (Figure 3B). Overexpression of HIF-2a enhanced the gene and protein expression of SLC1A5_var and SLC1A5 in a dose-dependent manner (Figures 3C and 3D). Next, we determined whether SLC1A5_var was a direct target of HIF-2a. In chromatin immunoprecipitation (ChIP) assay, four different PCR amplicons covering predicted HREs within the promoter of SLC1A5_var were selected (Figure 3E). Even in normoxia, HIF-2a crosslinked with amplicon 1 (Figures 3E and 3F). Furthermore, amplicon 1 was amplified more in hypoxia than in normoxia (Figure 3G), indicating that HIF-2a specifically binds the promoter region of SLC1A5_var. Additionally, we observed that the increased gene expression of both SLC1A5_var and SLC1A5 induced by cobalt chloride was suppressed by the HIF-2a inhibitor PT-2385 (Figures S3G and S3H). Overexpression or knockdown of HIF-2a, but not HIF-1a, affected the reporter activity of WT HRE but not the mutant HRE of SLC1A5_var (Figures 3H and 3I). These results indicate that HIF-2a binds to the HRE within the promoter of SLC1A5_var to control its gene expression. The SLC1A5 Variant Mediates Glutaminolysis and Redox Regulation in Cancer Cells We investigated whether SLC1A5_var expression could increase TCA cycle metabolites through mitochondrial glutaminolysis. The purified mitochondria from cells downregulating SLC1A5_ var decreased the concentration of glutamine-derived TCA cycle metabolites (Figures 4A–4E). Downregulation of SLC1A5_var, but not SLC1A5, concomitantly decreased the concentration of glutamine-derived metabolites (Figures S4A–S4K), indicating that SLC1A5_var is critical for mitochondrial glutaminolysis.

Given that the amount of citrate derived from reductive carboxylation was minor compared to that from oxidative pathway, glutamine-supported oxidative phosphorylation is a major direction of glutaminolysis to generate ATP in pancreatic cancer cells. Since mitochondrial glutamine ends its fate in oxidization, producing ATP (Fan et al., 2013), we compared the portion of ATP production from glucose or glutamine in normoxia and hypoxia respect to SLC1A5_var. In normoxia, glutamine was not significant for ATP production when glucose was present, but ATP was produced from glutamine when glucose was not present. However, in hypoxia, glutamine contributed to ATP production, with or without glucose (Figure 4F). We then examined the effect of SLC1A5_var expression on glutamine-derived ATP production under glucose depletion. In both normoxia and hypoxia, glutamine re-supplementation after the depletion of glucose and glutamine increased cellular ATP production in control or SLC1A5 downregulated cells. However, glutamine-derived ATP production was significantly suppressed in SLC1A5_var downregulated cells (Figure 4G). Conversely, overexpression of SLC1A5_var increased glutamine-derived ATP production (Figure 4H). These data indicate that ATP production via glutaminolysis is highly dependent on SLC1A5_var. Glutamine regulates reactive oxygen species (ROS) through glutathione (GSH) synthesis (Altman et al., 2016). GSH is a tripeptide (Glu-Cys-Gly), and glutamine has been shown to be a crucial source for GSH synthesis, which provides glutamate in cancer cell lines (Sappington et al., 2016). Glutamine increased cellular GSH levels in a concentration-dependent manner (Figure 4I) and suppressed cellular ROS levels (Figures 4J and 4K). Inhibition of glutamine-derived GSH synthesis by BPTES, a glutaminase GLS1 inhibitor, and GPNA, a SLC1A5 blocker, significantly increased cellular ROS levels (Figures 4I–4K), indicating that glutamine is responsible for cellular ROS homeostasis. Next, we examined the effect of SLC1A5_var levels on GSH synthesis and cellular ROS levels. Knockdown of SLC1A5_var, but not SLC1A5, reduced cellular GSH levels, and overexpression of SLC1A5_var, but not SLC1A5, increased cellular GSH levels (Figure 4L). In contrast, knockdown of SLC1A5_var increased ROS levels, but its overexpression suppressed ROS levels (Figures 4M and 4N). These results indicate that SLC1A5_ var mediates glutamine-derived GSH synthesis for cellular redox regulation. Pancreatic cancer cells also generate NADPH from glutamine for maintenance of redox homeostasis (Son et al., 2013). We therefore measured the NADPH/NADP+ ratio and found that knockdown of SLC1A5_var markedly altered the NADPH/NADP+ ratio (Figure S4L), suggesting that SLC1A5_var is a critical mediator for glutamine regulation of the cellular redox state.

(C) Real-time PCR analysis of the expression of SLC1A5 variant, HIF-a target genes. (D) Effect of HIF-2a overexpression on SLC1A5_var and SLC1A5 protein levels. N, normoxia; H, hypoxia. (E) Schematic diagram of the human SLC1A5_var promoter and amplicons used in the ChIP assay (left). HIF-2a ChIP assay of the human SLC1A5_var gene in normoxia (right). (F) Quantification of HIF-2a binding to regions 1 to 4. (G) HIF-2a ChIP assay (upper) and quantification (lower). (H) Effects of exogenous HIF-2a on SLC1A5_var promoter activity. (I) Knockdown effects of HIF-2a or HIF-1a on SLC1A5_var wild-type or mutant HRE promoter construct. The error bars represent mean ± SD (*p < 0.05; **p < 0.01; ***p < 0.005; n.s., not significant).

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8 Cell Metabolism 31, 1–17, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

Glutamine activates mTORC1 signaling pathway through a-KG production (Dura´n et al., 2012). Since SLC1A5_var controls cellular a-KG levels (Figures 1N and 1O), we investigated whether SLC1A5_var mediates glutamine-induced mTORC1 activation. Downregulation of SLC1A5_var, but not SLC1A5, impaired glutamine-induced S6K phosphorylation (Figure S4M). Addition of a cell-permeable a-KG analog rescued this impairment, suppressed by SLC1A5_var downregulation (Figure S4N). However, neither SLC1A5_var nor SLC1A5 is related to the cellular leucine uptake (Figure S4O) and leucine-induced mTORC1 activation (Figure S4P). Overexpression of SLC1A5_ var, but not SLC1A5, enhanced glutamine-induced S6K phosphorylation (Figure S4Q). Repression of glutamine-induced S6K phosphorylation by BPTES (Figure S4R) or GLS1 downregulation was rescued by cell-permeable a-KG (Figure S4S). These results indicate that SLC1A5-var mediates glutaminolysis-induced mTORC1 activation. The SLC1A5 Variant Is Critical for Metabolic Reprogramming in Cancer Cells We investigated MiaPaCa2 cell dependency on oxidative phosphorylation (OXPHOS) with a real-time metabolite analyzer measuring the oxygen consumption rate (OCR) and the extracellular acidification rate (ECAR). The basal OCR was higher under glutamine regardless of the glucose level, implying that MiaPaCa2 cells use glutamine rather than pyruvate derived from glucose (Figures 5A and 5B). Furthermore, the maximal OCR was increased by glutamine with or without glucose (Figures 5A and 5B). However, the basal and maximal OCR was not affected by glutamate (Figure 5C). These data demonstrate that glutamine metabolism is increased under glucose depletion and that mitochondrial glutaminolysis is still important for TCA cycle under glucose supplementation. The ECAR was also higher under glutamine supplementation (Figures 5D and 5E). These data support that glutamine addiction drives the metabolic reprogramming. To examine the role of SLC1A5_var in energy use, we measured OCR and ECAR in MiaPaCa2 cells downregulating (Figure 5F) or overexpressing SLC1A5_var (Figure 5K). Knockdown of SLC1A5_var, but not SLC1A5, exhibited a more quiescent and glycolytic cell type, corresponding to cells that generate their energy predominantly from glycolysis (Figure 5F). Knockdown of SLC1A5_var, but not SLC1A5, impaired the basal and maximal OCR, implying defective mitochondrial respiration (Figures 5G and 5H). Knockdown of SLC1A5_var suppressed the ECAR (Figures 5I and 5J). Conversely, overexpression of SLC1A5_var exhibited a more aerobic and energetic cell type, corresponding to cells that generate their energy predominantly

from OXPHOS (Figure 5K). Overexpression of SLC1A5_var increased the basal and maximal OCR (Figures 5L and 5M) and the ECAR (Figures 5N and 5O). However, BPTES treatment suppressed the basal and maximal OCR increased by SLC1A5_var overexpression (Figures 5P and 5Q), further supporting the importance of SLC1A5_var in mitochondrial respiration. Since downregulation or overexpression of SLC1A5 did not affect the OCR and ECAR (Figures 5F–5O) and MiaPaCa2 cells expressed several plasma membrane glutamine transporters (Figure S2G), we hypothesized that suppression of only one of several plasma membrane glutamine transporters did not significantly affect cellular glutamine uptake and glutamine-derived OCR. Indeed, downregulation of SLC1A5, SLC38A1, or SLC38A2 did not affect the basal and maximal OCR (Figures 5R and 5S), but downregulation of both SLC38A1 and SLC38A2, dominant plasma membrane glutamine transporters in MiaPaCa2 cells, or downregulation of SLC1A5_var alone significantly inhibited the basal and maximal OCR (Figures 5R and 5S). Overexpression of SLC1A5_var but not SLC1A5 or mitochondrial targeting mutant (SLC1A5_var_2A) increased glucose-derived 6-phosphogluconate and ribulose 5-phosphate via pentose phosphate pathway, fructose 1,6-bisphosphate and lactate via glycolysis pathway, and TCA cycle metabolites including a-KG, succinate, fumarate, and malate (Figures S5A–S5I). These data indicate that SLC1A5_var contributes to mitochondrial respiration and glycolysis via enhanced glutamine influx. Hypoxia Confers Gemcitabine Resistance via SLC1A5_var-Mediated Glutamine Metabolism Since hypoxia is a critical determinant of drug resistance in pancreatic cancer cells (Yokoi and Fidler, 2004), we also confirmed gemcitabine resistance in hypoxia using pancreatic cancer cell lines and human patient-derived pancreatic cancer cells. In normoxia, gemcitabine significantly suppressed cancer cell growth. In hypoxia, however, gemcitabine was ineffective in inhibiting cancer cell growth (Figures 6A and 6B), increasing the GI50 of gemcitabine in MiaPaCa2 (Figure 6C) and patient-derived YPAC-02 (Figure 6D) cells. In these two cell types, gemcitabine induced cell death significantly in normoxia but only marginally in hypoxia (Figure 6E). Since SLC1A5_var transcription is regulated by hypoxia (Figures S3A and S3B), we hypothesized that SLC1A5_var caused the hypoxia-induced gemcitabine resistance. Interestingly, in hypoxia, knockdown of SLC1A5_var rescued gemcitabine-induced cell death, suppressed by SLC1A5_var overexpression (Figure 6F), while overexpression of SLC1A5_var suppressed gemcitabine-induced cell death (Figure 6G), suggesting the inhibitory role of SLC1A5_var on gemcitabine-induced cell death. To address its inhibitory role,

Figure 4. The SLC1A5 Variant Mediates Glutaminolysis and Redox Regulation in Cancer Cells (A) Diagram of 13C isotopomer patterns with [U-13C]glutamine as tracer. The incorporation of 13C atoms is denoted as m + n, where n is the number of 13C atoms. (B–E) Metabolic abundance of [U-13C]glutamine-derived TCA metabolites in the purified mitochondria from MiapaCa2 cells (B) a-KG, (C) succinate, (D) fumarate, and (E) malate. (F) ATP generation from either glutamine or glucose in normoxia or hypoxia. (G and H) Effect of SLC1A5_var knockdown (G) or overexpression (H) on ATP generation in the presence or absence of glutamine (2 mM) and either normoxia or hypoxia in glucose-depleted condition. (I–K) Effects of glutamine and inhibitors on cellular glutathione levels (I), cellular ROS levels (J), and mitochondrial ROS levels (K). (L–N) Dependence of cellular glutathione (L), cellular ROS (M), and mitochondrial ROS (N) levels on SLC1A5_var expression. The error bars represent mean ± SD (*p < 0.05; **p < 0.01; ***p < 0.005; n.s., not significant).

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Figure 5. The SLC1A5 Variant Is Critical for Metabolic Reprogramming in Cancer Cells (A and B) Effects of glutamine and/or glucose on the OCR in MiaPaCa2 cells plotted over time (A) or bar graph (B). gluc, glucose; Gln, glutamine. (C) Effect of glutamine or glutamate on the OCR in MiaPaCa2 cells. (legend continued on next page)

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we checked the cellular ROS levels in normoxia and hypoxia because SLC1A5_var controls glutamine-derived GSH synthesis and ROS scavenging (Figures 4L–4N). Hypoxia increased basal ROS levels compared to normoxia, but gemcitabineinduced ROS levels were much higher in normoxia than in hypoxia (Figure 6H). To examine whether SLC1A5_var inhibits gemcitabine-induced cell death via mitochondrial glutaminolysis, we used BPTES to inhibit glutaminolysis and found that its treatment rescued the inhibitory effect of SLC1A5_var on gemcitabine-induced cell death (Figure 6I). We further investigated the association of gemcitabine resistance and SLC1A5_var expression in pancreatic cancer cells. In MiaPaCa2 and Panc1 cells, overexpressing SLC1A5_var increased the GI50 of gemcitabine, and knockdown of SLC1A5_ var sensitized these cells (Figures S6A–S6D). Overexpression of SLC1A5_var significantly suppressed gemcitabine-induced cell death (Figure S6E), but its knockdown enhanced it (Figure S6F). Similarly, SLC1A5_var overexpression decreased cellular ROS levels (Figure 6J), but its knockdown increased ROS levels (Figure 6K). To examine whether SLC1A5_var inhibits gemcitabineinduced cell death via glutamine-derived GSH synthesis and ROS scavenging, we used buthionine sulfoximine (BSO), a glutamylcysteine synthetase inhibitor, to inhibit GSH synthesis or glutathione monoethyl ester (GME) to supply cellular GSH and found that BSO treatment rescued gemcitabine-induced cell death suppressed by SLC1A5_var overexpression (Figure 6L), while GME treatment suppressed gemcitabine-induced cell death enhanced by SLC1A5_var knockdown (Figure 6M). In addition, we found that gemcitabine-resistant (Gem.R) MiaPaCa2 cells triggered the expression of SLC1A5_var and other enzymes regulating the cellular redox state (Figure S6G). In these gemcitabine-resistant cells, knockdown of SLC1A5_var improved gemcitabine resistance (Figure S6H). These data demonstrate that SLC1A5_var confers gemcitabine resistance in pancreatic cancer cells through the suppression of ROS production by glutamine-derived GSH synthesis. The SLC1A5 Variant Is Essential for Pancreatic Cancer Growth Since pancreatic cancer cells are highly dependent on glutamine (Figure S7A), we assessed the role of SLC1A5_var on pancreatic cancer cell growth. Knockdown of SLC1A5_var strongly suppressed oncogenic growth (Figures 7A and 7B) and cell growth in these cell lines (Figure 7C). Furthermore, knockdown of SLC1A5_var strongly induced cell death (Figure S7B). However, SLC1A5 knockdown itself had little impact on these cell lines. In MiaPaCa2 cells carrying the HRE mutation of the SLC1A5_var promoter, oncogenic cell growth was dramatically suppressed but rescued by SLC1A5_var overexpression (Figure 7D). Further-

more, re-expression of SLC1A5_var in SLC1A5_var-downregulated cells rescued cell growth, cell death, and anchorage-independent cell growth compared to that of control cells (Figures 7E and S7C, and S7D), implying that SLC1A5_var is critical for pancreatic cancer cell growth. Mitochondrial oxidative stress can cause mitochondrial fragmentation (Wu et al., 2011), and SLC1A5_var controls mitochondrial ROS (Figure 4N). Therefore, we examined the mitochondrial shape and found fragmented mitochondria in a larger proportion of cells with SLC1A5_var knockdown than in control or SLC1A5 knockdown cells (Figures S7E and S7F). Moreover, mitochondrial membrane potential was significantly altered by SLC1A5_ var knockdown (Figure S7G), indicating that SLC1A5_var function is linked to mitochondrial dynamics in the cells. Previous studies have identified several metabolites that restore growth inhibition by depleting glutamine (Pavlova et al., 2018; Son et al., 2013). We found that N-acetylcysteine (NAC) and asparagine synergistically rescued cell viability under glutamine depletion, although supplementation of cell-permeable a-KG, glutamate, or aspartate also partially rescued cell viability suppressed by glutamine depletion (Figure S7H). We then investigated whether NAC and asparagine could rescue pancreatic cancer cell growth under SLC1A5_var knockdown and found that NAC and asparagine partially rescued it (Figures 7F and 7G). In MiaPaCa2 cells carrying the HRE mutation of the SLC1A5_var promoter, cell growth was dramatically suppressed but partially rescued by NAC and asparagine (Figure 7H). To examine the role of SLC1A5_var on pancreatic cancer growth in vivo, we injected MiaPaCa2 cells transfected with small hairpin RNA (shRNA) targeting control or SLC1A5_var into the subcutaneous scapular region of nude mice. Interestingly, SLC1A5_var knockdown completely inhibited tumor growth in vivo (Figure 7I). Furthermore, the combination of SLC1A5_var knockdown and 2-deoxyglucose (2-DG) profoundly suppressed pancreatic cancer growth (Figure 7J), indicating the additive effects of glutamine and glucose metabolism. Together, these data suggest that targeting the mitochondrial glutamine transport and the subsequent glutamine metabolism by SLC1A5_var provides a new therapeutic strategy for fighting cancer. DISCUSSION Although numerous studies have emphasized the plasma membrane SLC1A5 in cancer metabolism, inhibition of SLC1A5 failed to affect cell proliferation (Bothwell et al., 2018, Bro¨er et al., 2019). Our data also showed that plasma membrane SLC1A5 had little impact on mitochondrial glutaminolysis and cancer cell growth, while mitochondrial SLC1A5_var substantially affected them in pancreatic cancer. Moreover, GPNA and

(D and E) Effects of glutamine and/or glucose on the ECAR in MiaPaCa2 cells plotted over time (D) or bar graph (E). gluc, glucose; Gln, glutamine. (F) Effect of SLC1A5_var knockdown on the metabolic phenotype in MiaPaCa2 cells. (G and H) Effect of SLC1A5_var knockdown on the OCR plotted over time (G) or bar graph (H). (I and J) Effect of SLC1A5_var knockdown on the ECAR plotted over time (I) or bar graph (J). (K) Effect of SLC1A5_var overexpression on the metabolic phenotype in MiaPaCa2 cells. (L and M) Effect of SLC1A5_var overexpression on the OCR plotted over time (L) or bar graph (M). (N and O) Effect of SLC1A5_var overexpression on the ECAR plotted over time (N) or bar graph (O). (P and Q) Effect of BPTES on the glutamine-derived OCR in MiaPaCa2 cells plotted over time (P) or bar graph (Q). (R and S) Effect of plasma membrane glutamine transporters (SLC1A5, SLC38A1, and SLC38A2) or SLC1A5_var knockdown on the OCR plotted over time (R) or bar graph (S). The error bars represent mean ± SD (*p < 0.05; **p < 0.01; ***p < 0.005; n.s., not significant).

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Figure 6. Hypoxia Confers Gemcitabine Resistance via the SLC1A5 Variant (A) Pancreatic cancer cell lines (MiaPaCa2 and Panc1) and patient-derived pancreatic cancer cells (YPAC-02, YPAC-16, and YPAC-26) were treated with gemcitabine for 96 h. (legend continued on next page)

12 Cell Metabolism 31, 1–17, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

benzylserine, known inhibitors of SLC1A5 (Liu et al., 2018), also inhibit the mitochondrial glutamine transport activity of SLC1A5_var (Figure 1M). Therefore, previous studies using inhibitors or siRNAs targeting SLC1A5 might have overlooked the possibility that SLC1A5_var was also suppressed. Since GPNA also blocks other glutamine transporters including SLC38A1, SLC38A2, and SLC7A5 (Bro¨er et al., 2018), there will be a possibility that unknown mitochondrial glutamine transporters, as well as SLC1A5_var, are also suppressed. However, SLC1A5_var downregulation completely abolished the mitochondrial glutamine transport (Figure 1J). Our data indicate that SLC1A5_var is an exclusive mitochondrial glutamine transporter and that targeting mitochondrial SLC1A5_var is critical for cancer treatment. There have been several efforts to develop SLC1A5 inhibitors. GPNA is not specific for SLC1A5 (Bro¨er et al., 2018). In the earlier studies, compound 12 and V-9302 were identified as SLC1A5 inhibitors (Schulte et al., 2016, 2018). However, these are inhibitors for SLC38A2 and SLC7A5, but not for SLC1A5 (Bro¨er et al., 2018). Specific inhibitors that distinguish plasma membrane SLC1A5 and mitochondrial SLC1A5_var will be essential for the study of their own functions. Since there are several plasma membrane glutamine transporters, it is not surprising that cancer cells are not affected by targeting one of them (Bro¨er et al., 2019). Pancreatic cancer cells express several plasma membrane glutamine transporters at the same time (Figure S2G) and downregulation of both SLC38A1 and SLC38A2 only affected the OCR (Figures 5R and 5S). The combined block of plasma membrane glutamine transporters will be needed to significantly suppress cellular glutamine transport and cancer cell growth. Hypoxia has been associated with drug resistance in numerous cancers, including pancreatic cancer (Yokoi and Fidler, 2004). A recent study demonstrated that disrupting glutaminolysis increased gemcitabine sensitivity in gemcitabineresistant pancreatic cancer cells (Chen et al., 2017). These studies, together with our results, suggest a model in which hypoxia induces both HIF-1a and HIF-2a and concomitantly alters cellular GSH synthesis through increased glutaminolysis mediated by SLC1A5_var, generating gemcitabine resistance in pancreatic cancer cells. A recent study reported that gemcitabine resistance was associated with increased glucose metabolism in pancreatic adenocarcinoma (Shukla et al., 2017). Hypoxia upregulates deoxycytidine triphosphate (dCTP) through the pentose phosphate pathway (PPP) of glucose metabolism, and the increased dCTP competes with a deoxycytidine analog, gemcitabine. SLC1A5_var can control glucose-derived PPP products (Figures S5B and S5C), perhaps through increased PPP-related gene expression. Therefore, SLC1A5_var-mediated

glutaminolysis can confer gemcitabine resistance via at least two routes: the decreased cell death caused by the increased glutamine-derived GSH synthesis and the molecular competition due to increased glucose-derived pyrimidine synthesis. Protein glycosylation has been involved in a variety of cellular processes, including protein folding, localization, and cell signaling (Helenius and Aebi, 2001). Recent reports have suggested that mitochondrial proteins are N- or O-glycosylated (Burnham-Marusich and Berninsone, 2012; Hu et al., 2009). For example, Lpe10p, a mitochondrial inner membrane magnesium transporter, is N-glycosylated and its glycosylation is important for the mitochondrial localization (Kung et al., 2009). Our results also show that glycosylation is required for mitochondrial localization of SLC1A5_var (Figures S2H–S2K), supporting the role of glycosylation of mitochondrial protein. Despite its functional importance, the mitochondrial glutamine transporter has been unknown for many decades. Here, we demonstrate that the mitochondrial glutamine transporter SLC1A5_var is a gatekeeper for glutamine metabolism and metabolic reprogramming in cancer cells. Our data also suggest that targeting mitochondrial amino acid transporters could be a new cancer starvation strategy for controlling tumor growth. Limitations of Study While we observed that glutaminolysis via SLC1A5_var significantly affects glucose metabolism, at present it is difficult to ascertain the mechanism by which glutamine facilitates glycolysis and the PPP. It will be interesting to study the role that SLC1A5_var might have on metabolic changes under hypoxia. We believe further studies will be required to understand the relevant crosstalk between glucose and glutamine metabolism. STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: d d d

d

KEY RESOURCES TABLE LEAD CONTACT AND MATERIALS AVAILABILITY EXPERIMENTAL MODEL AND SUBJECT DETAILS B Cell Lines B Mice B Generation of Pancreatic Cancer Patient-Derived Cell Lines METHOD DETAILS B Cell Lysis and Immunoblotting B Antibodies and Inhibitors

(B) MiaPaCa2 cells (left) and YPAC-02 cells (right) were cultured in normoxia or hypoxia with gemcitabine for 7 days. (C and D) GI50 values of gemcitabine in MiaPaCa2 (C) and YPAC-02 (D) cells. (E) Effect of hypoxia on gemcitabine-induced cell death. (F) Effect of SLC1A5_var knockdown on gemcitabine-induced cell death. (G) Effect of SLC1A5_var overexpression on gemcitabine-induced cell death. (H) Effect of hypoxia on gemcitabine-induced cellular ROS generation. (I) Effect of BPTES on gemcitabine-induced cell death in SLC1A5_var-overexpressed cells. (J and K) Effects of SLC1A5_var overexpression (J) or knockdown (K) on gemcitabine-induced cellular ROS generation. (L) Effect of buthionine sulfoximine (BSO) on gemcitabine-induced cell death in SLC1A5_var overexpression cell lines. (M) Effect of glutathione monoethyl ester (GME) on gemcitabine-induced cell death in SLC1A5_var downregulated cells. The error bars represent mean ± SD (*p < 0.05; **p < 0.01; ***p < 0.005; n.s., not significant).

Cell Metabolism 31, 1–17, February 4, 2020 13

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

A

si-con

si-1A5

B

si-1A5_var

Colonies per well

Colonies per well

* 100

*** 50

***

*** ***

si-con si-1A5 si-1A5_var

150

150

100

50

***

***

***

***

***

***

YPAC-16

YPAC-26

0

0

AsPC1

BxPC3

SU.86.86

Panc10.05

Panc1

MiaPaCa2 CFPAC-1

HPAF-II

si-con

si-1A5

si-1A5_var

600 400 200 0

800 600 400 200 0

0 1 2 3 4 5 6

SU.86.86

1000

Cell growth (%)

800

BxPC3 Cell growth (%)

1000

Cell growth (%)

Cell growth (%)

AsPC1 1000

800 600 400 200 0

0 1 2 3 4 5 6

D

si-1A5_var

si-1A5

600

Panc10.05

400 200

***

800 600 400 200 0

0

0 1 2 3 4 5 6

150

YPAC-16 1000

Colonies per well

si-con

Cell growth (%)

C

0 1 2 4

0 1 2 3 4 5 6

days

days

days

days

Panc1

MiaPaCa2

CFPAC-1

HPAF-II

6 8

days

100

50

***

0

400 200 0

600 400 200 0

600 400 200 0

YPAC-26

800 600 400 200

0 1 2 3 4 5 6

0 1 2 4 6 8

0 1 2 4 6 8

0 1 2 4 6 8

days

days

days

days

days

MiaPaCa2

F

*** ***

***

50 *

0

0 0 1 2 3 4 5 6

days

0

NAC : – + – +

– + – +

Asn : – Ě + +

– Ě + +

– Ě + +

Asn : – Ě + +

– Ě + +

– Ě + +

si-1A5

si-1A5_var

si-1A5

si-1A5_var

0

NAC/Asn :

–

+

–

– + – +

J sh-con

***

sh-1A5_var

*** 500

sh-1A5_var *** *** *** ***

+

***

0

10

*** *** 100

50

0

2-DG : – +

0

sgCon sg1A5_var HRE

si-Con

Cell viability (Relative to si-con, %)

*** 50

*

– + – +

sh-con

1000

100

***

50

– + – +

I ***

150

Tumor volume (mm3)

Colonies per well

200

100

NAC : – + – +

si-con

H

***

100

Cell viability (%)

500

Cell viability (%)

Cell growth (%)

MiaPaCa2 si-con/Con si-1A5_var_#1/Con si-1A5_var_#2/Con si-con/1A5_var si-1A5_var_#1/1A5_var si-1A5_var_#2/1A5_var

1A5_var

Panc1

G

***

1000

Con

0

0 1 2 3 4 5 6

E

sgCon sg1A5_var HRE

300

600

1000

sgCon sg1A5_var HRE

600

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800

Cell growth (%)

900

800

Cell growth (%)

1200

Cell growth (%)

1000

Cell growth (%)

Cell growth (%)

0 1500

20

30

days

–

+

–

+

si-con si-1A5 si-1A5_var

Figure 7. The SLC1A5 Variant Is Essential for Pancreatic Cancer Growth (A and B) Clonogenic growth of pancreatic cancer cells (A) and patient-derived pancreatic cancer cells (B) transfected with si-SLC1A5_var. (C) Relative proliferation of pancreatic cancer cell lines and patient-derived pancreatic cancer cells transfected with si-SLC1A5_var. (legend continued on next page)

14 Cell Metabolism 31, 1–17, February 4, 2020

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B

Subcellular and Submitochondrial Fractionation Cellular Amino Acid Uptake Assay B Purification of Mitochondria from Cells and Measurement of Mitochondrial Amino Acids Uptake B LC/MS-based Metabolomics and Quantification of Metabolite Abundance B Immunofluorescence Staining and Analysis B Live-Cell Imaging and Analysis B Expression Constructs and Mutagenesis B Hypoxia Treatment B Gene Expression Analysis B Luciferase Promoter Activity Assay B siRNA and shRNA Expression B Generation of Cells Stably Expressing cDNAs and shRNAs B CRISPR/Cas9 Knockout B Generation of Gemcitabine Resistant MiaPaCa2 Cells B Chromatin Immunoprecipitation (ChIP) B OCR / ECAR Analysis B ATP Assay B Measurement of GSH, ROS and Mitochondrial ROS + B Measurement of NADP /NADPH B Measurement of Cell Viability, Growth and Death B Clonogenic Assay B In Vivo Xenograft Tumor Assay B Analysis of Mitochondrial Morphology B Measurement of Mitochondrial Membrane Potential B Expression of SLC1A5 Isoform in Normal and Cancer Tissue B Survival Analysis B In Silico Analysis QUANTIFICATION AND STATISTICAL ANALYSIS DATA AND CODE AVAILABILITY B

d d

of data; S.B., conception and design; J.M.H., supervision, manuscript writing, and final approval of manuscript.

DECLARATION OF INTERESTS The authors declare no competing interests. Received: March 6, 2019 Revised: August 5, 2019 Accepted: November 27, 2019 Published: December 19, 2019 REFERENCES Altman, B.J., Stine, Z.E., and Dang, C.V. (2016). From Krebs to clinic: glutamine metabolism to cancer therapy. Nat. Rev. Cancer 16, 619–634. Bothwell, P.J., Kron, C.D., Wittke, E.F., Czerniak, B.N., and Bode, B.P. (2018). Targeted suppression and knockout of ASCT2 or LAT1 in epithelial and mesenchymal human liver cancer cells fail to inhibit growth. Int. J. Mol. Sci. 19, E2093. Bro¨er, A., Fairweather, S., and Bro¨er, S. (2018). Disruption of Amino Acid Homeostasis by Novel ASCT2 Inhibitors Involves Multiple Targets. Front. Pharmacol. 9, 785. Bro¨er, A., Gauthier-Coles, G., Rahimi, F., van Geldermalsen, M., Dorsch, D., Wegener, A., Holst, J., and Bro¨er, S. (2019). Ablation of the ASCT2 (SLC1A5) gene encoding a neutral amino acid transporter reveals transporter plasticity and redundancy in cancer cells. J. Biol. Chem. 294, 4012–4026. Burnham-Marusich, A.R., and Berninsone, P.M. (2012). Multiple proteins with essential mitochondrial functions have glycosylated isoforms. Mitochondrion 12, 423–427. Cassago, A., Ferreira, A.P., Ferreira, I.M., Fornezari, C., Gomes, E.R., Greene, K.S., Pereira, H.M., Garratt, R.C., Dias, S.M., and Ambrosio, A.L. (2012). Mitochondrial localization and structure-based phosphate activation mechanism of Glutaminase C with implications for cancer metabolism. Proc. Natl. Acad. Sci. USA 109, 1092–1097.

SUPPLEMENTAL INFORMATION

Chacinska, A., Koehler, C.M., Milenkovic, D., Lithgow, T., and Pfanner, N. (2009). Importing mitochondrial proteins: machineries and mechanisms. Cell 138, 628–644.

Supplemental Information can be found online at https://doi.org/10.1016/j. cmet.2019.11.020.

Chen, W.W., Freinkman, E., Wang, T., Birsoy, K., and Sabatini, D.M. (2016). Absolute quantification of matrix metabolites reveals the dynamics of mitochondrial metabolism. Cell 166, 1324–1337.e11.

ACKNOWLEDGMENTS This work was supported by the Global Ph.D. Fellowship Program (NRF-2015H1A2A1031134), the Global Frontier Project Grant (NRF-2013M3A6A4072536), the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (2018R1A6A1A03023718), and the Korea Basic Science Institute (T39720). AUTHOR CONTRIBUTIONS H.C.Y., conception and experimental design, collection and analysis of data, and manuscript writing; S.J.P., M.N., J.K., K.K., J.H.Y., J.-K.K., Y.H., H.S.L., M.Y.L., C.W.L., J.S.K., Y.-H.K., J.L., J.C., and G.S.H., collection and analysis

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(D) Single guide RNA targeting the HRE motif of the SLC1A5_var promoter (SLC1A5_var HRE mutant) impaired cell clonogenicity. (E) Relative cell growth of SLC1A5_var downregulated cells. (F and G) Cell viability rescue of SLC1A5_var downregulated MiaPaCa2 (F) and Panc1 (G) cells by NAC and Asn. NAC, N-acetylcysteine; Asn, asparagine. (H) Effect of NAC and Asn on the clonogenic growth of SLC1A5_var HRE mutant cells. (I) Xenograft growth of MiaPaCa2 cells expressing Con or SLC1A5_var shRNA in mice. (J) The combination of SLC1A5_var knockdown and 2-DG suppressed cancer cell growth. The error bars represent mean ± SD (*p < 0.05; **p < 0.01; ***p < 0.005; n.s., not significant).

Cell Metabolism 31, 1–17, February 4, 2020 15

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STAR+METHODS KEY RESOURCES TABLE

REAGENT or RESOURCE

SOURCE

IDENTIFIER

Rabbit polyclonal anti-Tim23 (WB: 1:250)

Abcam

Cat#ab116329; RRID: AB_10903878

Rabbit monoclonal anti-GLS1 (WB: 1:1000, IF 1:50)

Abcam

Cat#ab156876; RRID: AB_2721038

Antibodies

Rabbit polyclonal anti-GLS2 (WB: 1:1000, IF 1:50)

Abcam

Cat#ab113509; RRID: AB_10866157

Rabbit monoclonal anti-GAC (WB: 1:1000, IF 1:50)

Abcam

Cat#ab202027

Normal rabbit IgG

Cell Signaling Technology

Cat#2729; RRID: AB_1031062

Rabbit monoclonal anti-COX4 (WB: 1:1000, IF 1:50)

Cell Signaling Technology

Cat#4850; RRID: AB_2085424

Rabbit monoclonal anti-Na,K-ATPase (WB: 1:1000, IF 1:50)

Cell Signaling Technology

Cat#23565; RRID: AB_2798866

Rabbit monoclonal anti-ERp72 (WB: 1:1000, IF 1:50)

Cell Signaling Technology

Cat#5033; RRID: AB_10622112

Rabbit monoclonal anti-GM130 (WB: 1:1000, IF 1:50)

Cell Signaling Technology

Cat#12480; RRID: AB_2797933

Rabbit monoclonal anti-Rab7 (WB: 1:1000, IF 1:50)

Cell Signaling Technology

Cat#9367; RRID: AB_1904103

Rabbit polyclonal anti-CCND1 (WB: 1:1000)

Cell Signaling Technology

Cat#2922; RRID: AB_2228523

Rabbit polyclonal anti-phoshpo-p70 S6 kinase (Thr389) (WB: 1:1000)

Cell Signaling Technology

Cat#9205; RRID: AB_330944

Rabbit polyclonal anti-p70 S6 kinase (WB: 1:1000)

Cell Signaling Technology

Cat#9202; RRID: AB_331676

Alexa488-conjugated 2nd goat anti-mouse (IF: 1:500)

Invitrogen

Cat#A-11001; RRID: AB_2534069

Alexa594-conjugated 2nd goat anti-rabbit mouse (IF: 1:500)

Invitrogen

Cat#A-11012; RRID: AB_141359

Goat anti-mouse IgG, HRP (WB: 1:10000)

Invitrogen

Cat#31430; RRID: AB_228307

Goat anti-rabbit IgG, HRP (WB: 1:10000)

Invitrogen

Cat#31460; RRID: AB_228341

Rabbit polyclonal anti-HIF-2a (WB: 1:500)

Novus biologicals

Cat#NB100-122; RRID: AB_10002593

Rabbit polyclonal anti-HIF-1a (WB: 1:500)

Novus biologicals

Cat#NB100-105; RRID: AB_10001154

Mouse monoclonal anti-HA-probe (IF: 1:50)

Santa Cruz Biotechnology

Cat#sc-7392; RRID: AB_627809

Rabbit polyclonal anti-LAMP2 (WB: 1:1000, IF 1:50)

Santa Cruz Biotechnology

Cat#sc-5571; RRID: AB_647855

Rabbit polyclonal anti-SLC1A5 (WB: 1:1000)

Santa Cruz Biotechnology

Cat#sc-99002; RRID: AB_2239446

Mouse monoclonal anti-b-actin (WB: 1:2000)

Santa Cruz Biotechnology

Cat#sc-47778; RRID: AB_2714189

Rabbit polyclonal anti-TOM20 (WB: 1:1000)

Santa Cruz Biotechnology

Cat#sc-11415; RRID: AB_2207533

Mouse monoclonal anti-MnSOD2 (WB: 1:1000)

Santa Cruz Biotechnology

Cat#sc-133134; RRID: AB_2191814

Mouse monoclonal anti-GFP (WB: 1:1000)

Santa Cruz Biotechnology

Cat#sc-9996; RRID: AB_627695

Mouse monoclonal anti-PDK1 (WB: 1:500)

Santa Cruz Biotechnology

Cat#sc-293160

Mouse monoclonal anti-GLUT1 (WB: 1:500)

Santa Cruz Biotechnology

Cat#sc-377228

Chemicals, Peptides, and Recombinant Proteins ECL (EzWestLumi)

ATTO

Cat#AE-1495

13

Cambridge Isotope Laboratories

Cat#CLM-1822

13

Cambridge Isotope Laboratories

Cat#CLM-1396

Y-27632

Enzo

Cat#ALX-270-333

AgeI

Enzynomics

Cat#R063S

Gentamicin

GIBCO

Cat#15750-06

Dialyzed FBS

GIBCO

Cat#26400044

Opti-MEM I Reduced Serum Medium

GIBCO

Cat#31985062

EGF

Invitrogen

Cat#PHG0313

H2DCFDA

Invitrogen

Cat#D399

MitoTracker Red CMXRos

Invitrogen

Cat#M7512

MitoSOX Red

Invitrogen

Cat#M36008

TMRE, Tetramethylrhodamine

Invitrogen

Cat#T669

C-Glutamine (99%) C-Glucose (99%)

(Continued on next page)

e1 Cell Metabolism 31, 1–17.e1–e12, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

Continued REAGENT or RESOURCE

SOURCE

IDENTIFIER

Lipofectamine RNAiMAX reagent

Invitrogen

Cat#13778075

Lipofectamine 2000 reagent

Invitrogen

Cat#11668500

PT2385

Med Chem Express

Cat#HY-12867

PNGase F

NEB

Cat#P0704L

Luciferase Cell Culture Lysis 5X Reagent

Promega

Cat#E1500

Gemcitabine

Sigma

Cat#G6423

Hydrocortisone

Sigma

Cat#H-0135

AmphotericinB

Sigma

Cat#A2942

Cholera toxin

Sigma

Cat#C-8052

Insulin

Sigma

Cat#I-9278

Adenine

Sigma

Cat#A2786

Monobromobimane

Sigma

Cat#69898

WST-1

Sigma

Cat#05 015 944 001

Crystal violet

Sigma

Cat#C0775

Alanine

Sigma

Cat#A4349

Serine

Sigma

Cat#S4311

Glutamine

Sigma

Cat#G5792

Glutamate

Sigma

Cat#49621

Asparagine

Sigma

Cat#A4159

Aspartate

Sigma

Cat#A6558

Di-methyl-aKG

Sigma

Cat#349631

N-acetylcysteine

Sigma

Cat#A9165

Mercury chloride

Sigma

Cat#215465

GPNA, L-g-glutamyl-p-nitroanilide

Sigma

Cat#G6133

Benzylserine

Sigma

Cat#S635022

Cobalt chloride

Sigma

Cat#C8661

Deferoxamine

Sigma

Cat#D9533

BPTES

Sigma

Cat#SML0601

BSO

Sigma

Cat#B2515

GME, glutathione reduced monoethyl ester

Sigma

Cat#G1404

2-Deoxyglucose

Sigma

Cat#D6134

Puromycin

Sigma

Cat#P8833

Polybrene (hexadimethrine bromide)

Sigma

Cat#H9268

DAPI

Sigma

Cat#D9542

Hoechst (bisBenzimide H)

Sigma

Cat#B1155

Optiprep

Sigma

Cat#D1556

Digitonin

Sigma

Cat#D141

Poly-L-lysine solution

Sigma

Cat#P8920

Tunicamycin

Sigma

Cat#T7765

3

Perkin Elmer

Cat#NET-460

3

Perkin Elmer

Cat#NET-551

3

Perkin Elmer

Cat#NET-248

H-Leucine H-Glutamine H-Serine

3

Perkin Elmer

Cat#NET-490

14

H-Glutamate C-Alanine

Perkin Elmer

Cat#NEC266E0

Microscint PS

Perkin Elmer

Cat#6013631

Anti-c-Myc Magnetic Beads

Pierce

Cat#88843

c-Myc Peptide

Pierce

Cat#20170

EcoRI

TAKARA

Cat#1040A

NotI

TAKARA

Cat#1166A (Continued on next page)

Cell Metabolism 31, 1–17.e1–e12, February 4, 2020 e2

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

Continued REAGENT or RESOURCE

SOURCE

IDENTIFIER

KpnI

TAKARA

Cat#1068A

EcoRV

TAKARA

Cat#1042A

BglII

TAKARA

Cat#1021A

ChIP kit

Abcam

Cat#ab500

a-Ketoglutarate (a-KG) Assay kit

Abcam

Cat#ab83431

NADP+/NADPH Assay kit

Abcam

Cat#ab65349

Critical Commercial Assays

Seahorse XF Cell Mito Stress Test kit

Agilent Technologies

Cat#103592-100

GSH/GSSG Assay Kit

Abcam

Cat#ab138881

Seahorse XF Glycolytic Rate Assay kit

Agilent Technologies

Cat#103344-100

Seahorse XF Cell Energy Phenotype Test Kit

Agilent Technologies

Cat#103325-100

FITC Annexin V Apoptosis Detection kit I

BD PharMingen

Cat#51-65874X

Deproteinizing Sample Preparation kit

BioVision

Cat#K808

Succinate Colorimetric Assay kit

BioVision

Cat#K649

Fumarate Colorimetric Assay kit

BioVision

Cat#K633

Malate Colorimetric Assay kit

BioVision

Cat#K637

Citrate Colorimetric/Fluorometric Assay kit

BioVision

Cat#K655

Glutamine assay kit

BioVision

Cat#K556

Serine assay kit

BioVision

Cat#K743

Alanine assay kit

BioVision

Cat#K652

Glutamate assay kit

BioVision

Cat#K629

Q5 Site-Directed Mutagenesis kit

NEB

Cat#E0554S

Lysosome Enrichment kit

Pierce

Cat#89839

NE-PER kit

Pierce

Cat#78833

CellTiter-Glo Luminescent Cell Viability Assay

Promega

Cat#G7570

CellTox Green Cytotoxicity Assay

Promega

Cat#G8742

Dual-Luciferase Reporter Assay System

Promega

Cat#E1910

MiniBEST Universal RNA Extraction Kit

TAKARA

Cat#9767A

PrimeScript 1st strand cDNA Synthesis Kit

TAKARA

Cat#6110A

EmeraldAmp GT PCR Master Mix

TAKARA

Cat#RR310B

AsPC1 (human, female)

ATCC

Cat#CRL1682

BxPC3 (human, female)

ATCC

Cat#CRL1687

SU.86.86 (human, female)

ATCC

Cat#CRL1837

Panc10.05 (human, male)

ATCC

Cat#CRL2547

Panc1 (human, male)

ATCC

Cat#CRL1469

Experimental Models: Cell Lines

MiaPaCa2 (human, male)

ATCC

Cat#CRL1420

CFPAC-1 (human, male)

ATCC

Cat#CRL1918

HPAF-II (human, male)

ATCC

Cat#CRL1997

Capan2 (human, male)

ATCC

Cat#HTB80

SW1990 (human, male)

ATCC

Cat#CRL2172

HeLa (human, female)

ATCC

Cat#CCL2

SW480 (human, male)

ATCC

Cat#CCL228

SW620 (human, male)

ATCC

Cat#CCL227

LS1034 (human, male)

ATCC

Cat#CRL2158

LS174T (human, female)

ATCC

Cat#CL188

COLO205 (human, male)

ATCC

Cat#CCL222

HT29 (human, female)

ATCC

Cat#HTB38

H508 (human, male)

ATCC

Cat#CCL253 (Continued on next page)

e3 Cell Metabolism 31, 1–17.e1–e12, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

Continued REAGENT or RESOURCE

SOURCE

IDENTIFIER

HCT116 (human, male)

ATCC

Cat#CCL247

DLD-1 (human, male)

ATCC

Cat#CCL221

A549 (human, male)

ATCC

Cat#CCL185

H460 (human, male)

ATCC

Cat#HTB177

H596 (human, male)

ATCC

Cat#HTB178

H226 (human, male)

ATCC

Cat#CRL5826

H358 (human, male)

ATCC

Cat#CRL5807

H441 (human, male)

ATCC

Cat#HTB174

H1299 (human, male)

ATCC

Cat#CRL5803

FHC (human, male)

ATCC

Cat#CRL1831

BJ (human, male)

ATCC

Cat#CRL2522

HPDE (human, female)

Dr. Ming-Sound Tsao

Ouyang et al., 2000

YPAC-02 (human, male)

Dr. Seungmin Bang

N/A

YPAC-16 (human, male)

Dr. Seungmin Bang

N/A

YPAC-26 (human, male)

Dr. Seungmin Bang

N/A

HEK293T (human, female)

Korean Cell Line Bank

Cat#21573

HCC15 (human, male)

Korean Cell Line Bank

Cat#70015

HCC44 (human, female)

Korean Cell Line Bank

Cat#70044

HCC2108 (human, female)

Korean Cell Line Bank

Cat#72108

16HBE (human, male)

Merck

Cat#SCC150

Nara Biotech

N/A

Experimental Models: Organisms/Strains Female BALB/c nude mice Oligonucleotides pLKO.1-puro-shGFP

Broad Institute

TRCN0000072187

siRNA (HIF-1a, HIF-2a, c-Myc)

Dharmacon

SMART POOL: ON-TARGETplus siRNA

siRNA (GLS1, SLC38A1, SLC38A2)

IDT

Predesigned Dicer-Substrate siRNA

control siRNA (si-con)

Invitrogen

Cat#AM4611

SLC1A5 siRNA (NM_005628.2) #1: CCAGAGAAACUCUCGUAUU #2: GCUGACAGUGGUGGCCGUG

This paper

N/A

SLC1A5_var siRNA (NM_001145145.1) #1: GCUGCCCUCCCACUAUGUA #2: GCUAGCACGCCAGCCUCUU

This paper

N/A

sgSLC1A5_var HRE:CCCCCACACCACGTGTCACT

This paper

N/A

pLKO.1-puro-shSLC1A5_var: CTATGTACTCTAC CACCTATG

This paper

N/A

Primers for RT-PCR analysis, see Table S1

This paper

N/A

Primers for ChIP analysis, see Table S1

This paper

N/A

Primers for cloning, see Table S1

This paper

N/A

pLKO.1 puro

Dr. Jinu Lee

N/A

pmTFP1-C vector

Allele Biotechnology

Cat#ABP-FP-TCNCS10

pLKO.1-puro-shGFP

Broad Institute

TRCN0000072181

pIRESpuro3 vector

Clontech

Cat#631619

pCMV-HA-N vector

Clontech

Cat#631604

pLJM60-FLAG-SLC38A9.1

Dr. David Sabatini

Addgene 71858, Wang et al., 2015

lentiCRISPRv2

Dr. Feng Zhang

Addgene 52961, Sanjana et al., 2014

Recombinant DNA

Lentiviral packaging and envelope plasmids

Dr. Jinu Lee

N/A

HA-HIF-2a pcDNA3

Dr. William Kaelin

Addgene 18950, Kondo et al., 2002 (Continued on next page)

Cell Metabolism 31, 1–17.e1–e12, February 4, 2020 e4

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

Continued REAGENT or RESOURCE

SOURCE

IDENTIFIER

HA-HIF-1a pcDNA3

Dr. William Kaelin

Addgene 18949, Kondo et al., 2002

pMXs-3XMyc-EGFP-OMP25

Dr. David Sabatini

Addgene 83355 Chen et al., 2016

pOTB7-human SLC1A5

Medical Genomics KRIBB

hMU006775

pCMV-SPORT6-human SLC38A1

Medical Genomics KRIBB

hMU000738

pCMV-SPORT6-human SLC38A2

Medical Genomics KRIBB

hMU003377

pCMV-SPORT6-human SLC7A5

Medical Genomics KRIBB

hMU005138

pGL4.10 vector

Promega

Cat#E6651

pGL4.70 vector

Promega

Cat#E6881

pIRESpuro3-SLC1A5

This paper

N/A

pIRESpuro3-SLC1A5_var-WT, D186A, R44A/K45A

This paper

N/A

pmTFP1-C-NT_WT, NT_3A, NT_2A, middle, CT

This paper

N/A

pIRESpuro3-HA-SLC38A1, HA-SLC38A2, HA-SLC38A9

This paper

N/A

pCMV-HA-N-SLC7A5

This paper

N/A

pGL4.10-SLC1A5_var-WT-HRE promoter construct

This paper

N/A

pGL4.10-SLC1A5_var-mutant-HRE promoter construct

This paper

N/A

pLKO.1-puro-shSLC1A5_var

This paper

N/A

Software and Algorithms WAVE software

Agilent Technologies

Agilent Technologies

Zen colocalization

Carl ZEISS

Carl ZEISS

PrediSi

open source

http://www.predisi.de/

TMHMM

open source

http://www.cbs.dtu.dk/services/ TMHMM/

ImageJ

open source

https://imagej.nih.gov/ij/download.html

Prism

GraphPad

GraphPad

Protter

open source

http://wlab.ethz.ch/protter/start/

COBALT

open source

https://www.st-va.ncbi.nlm.nih.gov/ tools/cobalt/

Firehose Broad GDAC

open source

http://gdac.broadinstitute.org/

Genotype-Tissue Expression (GTEx) portal

open source

https://gtexportal.org/

Survminer R package

open source

http://www.sthda.com/english/

LEAD CONTACT AND MATERIALS AVAILABILITY Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Jung Min Han ([email protected]). The described plasmids used in this study are deposited in plasmid repository of Korea Human Gene Bank (genebank.kribb.re.kr). Additional data and materials related to this paper may be requested from the authors. EXPERIMENTAL MODEL AND SUBJECT DETAILS Cell Lines Pancreatic cancer cell lines (AsPC1, BxPC3, SU.86.86, Panc10.05, Panc1, MiaPaCa2, CFPAC-1, HPAF-II, Capan2, and SW1990), colon cancer cell lines (SW480, SW620, LS1034, LS174T, COLO205, HT29, H508, HCT116, and DLD-1), lung cancer cell lines (A549, H460, H596, H226, H358, H441, and H1299), FHC, BJ and HeLa were obtained from ATCC. HEK293T, HCC15, HCC44 and HCC2108 cells were obtained from the Korean Cell Line Bank. 16HBE cells were obtained from Merck. Cells were grown in the following media at 37 C with 5% CO2 unless otherwise stated. MiaPaCa2 cells were used to generate Gem.R (gemcitabine resistant) cells as previously described (Davidson et al., 2004). MiaPaCa2 and Panc1 cells were used to generate cell lines stably expressing each SLC1A5 variant. Patient-derived pancreatic adenocarcinoma cells, YPAC-02, YPAC-16, and YPAC-26 were provided by Dr. Seungmin Bang (Yonsei University College of Medicine). The human pancreatic duct epithelial cell line (HPDE) was provided from Dr. Ming-Sound Tsao. The HPDE cell line was grown in serum-free media supplemented with bovine pituitary extract and EGF. MiaPaCa2, Panc1, HEK293T and HeLa cells were cultured in DMEM with 10% FBS. AsPC1, BxPC3, SU.86.86, Panc10.05, SW480. SW620, LS1034, LS174T, COLO205, HT29, H508, HCT116, DLD-1, A549, H460, H596, H226, H358, H441, and H1299 cells were cultured in RPMI e5 Cell Metabolism 31, 1–17.e1–e12, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

with 10% FBS. CFPAC-1 cells were cultured in Iscove’s modified Dulbecco’s medium (IMDM). HPAF-II and BJ cells were cultured in MEM with 10% FBS. Capan2 and SW1990 cells were cultured in McCoy’s 5A Medium and Leibovitz’s L-15 Medium with 10% FBS, respectively. 16HBE cells were cultured in DMEM/F12 medium with 10% FBS. FHC cells were cultured in complete growth media (DMEM:F12 nutrient mix = 1:1; 10% FBS, extra HEPES final 25 mM; cholera toxin, 10 ng/mL; insulin, 5 mg/mL; transferrin, 5 mg/mL; hydrocortisone, 100 ng/mL; EGF, 20 ng/mL). YPAC-02, YPAC-16, and YPAC-26 cells were cultured in F-media (DMEM:F12 nutrient mix = 3:1; insulin, 5 mg/mL; amphotericin B, 250 ng/mL; gentamicin, 10 mg/mL; cholera toxin, 0.1 nM; EGF, 0.125 ng/mL; hydrocortisone, 25 ng/mL; ROCK inhibitor Y-27632, 10 mM; adenine, 24 mg/mL) (Liu et al., 2017). Mice All animal work was performed in accordance with protocols approved by the Institutional Animal Care and Use Committee at Korea Research Institute of Bioscience and Biotechnology. For in vivo xenograft tumor assay, five-week-old female BALB/c nude mice (Nara Biotech Co., Seoul, Republic of Korea) were used. For gene expression analysis in mouse tissue, five-week-old female and male C57BL/6 mice were used. Mice were housed at 4 mice per cage at 24 C and at a 12 h light/dark cycle, and were allowed access to food (38057, purina) and water ad libitum in a specific pathogen-free facility monitoring health status with culture, serum and microscopic examination. Generation of Pancreatic Cancer Patient-Derived Cell Lines Patients who were diagnosed with PDAC (pancreatic ductal adenocarcinoma) were enrolled for establishment of a tumor model and genetic analysis. Tumor specimens (%1 cm) were obtained from resected specimens of patients who underwent surgery for PDAC. For patients with unresectable PDAC, endoscopic ultrasound (EUS)-guided biopsy or percutaneous biopsy were performed to obtain the tumor specimens. Tumor tissues and paired peripheral blood samples were collected simultaneously in the present study. All tissues were placed into medium with antibiotics. Using forceps and a scalpel, residual fat tissue was removed. Tumor tissues were minced into 1-2 mm small fragments with sterile scissors. Dissected specimens were placed in medium. Primary cell line isolation was conducted within 1–2 h of tumor resection. If specimens could not be processed immediately to prepare CRCs (conditionally reprogrammed cells), the tumor cells were frozen in liquid nitrogen for long-term storage. Tissue was resuspended in collagenase (1 mg/mL, Sigma) in culture medium and incubated for 30 min at 37 C with agitation to dissociate the tumor tissue from the collagenous stroma. We added 5x F-medium for neutralization, followed by centrifugation at 1500 rpm for 3 min. The supernatant was filtered through a cell strainer (70-mm nylon, Falcon). The filtered tumor cells were resuspended in F-media consisting of Keratinocyte-SFM (Life Technologies) supplemented with prequalified recombinant epidermal growth factor and bovine pituitary extract (Life Technologies), 2% fetal bovine serum (Sigma), and 1% antibiotic-antimycotic (Life Technologies). The cells were cultured on plates preplated with irradiated 3T3-J2 (mouse fibroblast cells). Cells were incubated at 37 C with 5% CO2. Tumor cells on the plates were readily apparent by morphology relative to stromal elements (e.g., fibroblasts). Contaminating stromal cells were removed by differential trypsinization or selective scraping of the plates as necessary. The cell lines were pretreated with 500 ng/mL mycoplasma removal agent (MP Biomedicals). The generated cell lines were regularly checked to ensure that they were not infected with mycoplasma. All patients signed consent forms for sample collection and molecular analysis. The study was approved by the institutional review board of Severance Hospital, Seoul, Korea (IRB number 4-2015-0297). METHOD DETAILS Cell Lysis and Immunoblotting For immunoblotting, cells were washed twice with DPBS and sonicated on ice in lysis buffer (40 mM HEPES pH 7.4, 0.5% Triton X-100, 10mM b-glycerol phosphate, 10 mM pyrophophate, 2.5 mM MgCl2) supplemented with protease inhibitors (5 mg/mL aprotinin, 10 mg/mL leupeptin, 250 mM PMSF). The whole lysed fraction was carefully subjected to sonication on ice to avoid heat and air bubbles. It was critical that the samples containing SLC1A5_var were neither boiled (or heated above 40 C) or frozen prior to resolution by immunoblotting except incubation with PNGase F (NEB) at 37 C for 4 h with nondenatured conditions. Protein concentration was measured by BCA assay (Intron), and proteins were denatured in a sample buffer immediately before SDS-PAGE. Then, 30 mg of protein was applied to SDS-PAGE and transferred to PVDF membrane (Merck) using a Trans-Blot Turbo Blotting System (BioRad). After blocking in TBST buffer containing 2% BSA, the membranes were incubated with individual primary antibodies overnight. The next day, the membranes were subsequently incubated with either anti-mouse or anti-rabbit IgG conjugated with horseradish peroxidase (Invitrogen). Immunoblot signals were detected by MicroChemi (DNR Bioimaging system) with enhanced chemiluminescence, EzWestLumi (ATTO), and quantified by densitometry analysis of protein bands using ImageJ. Immunoblot images are representative of three independent experiments. Antibodies and Inhibitors Antibodies were obtained from the following sources: COX4, Na,K-ATPase, ERp72, GM130, Rab7, CCND1, phospho-S6 kinase (T389) and S6 kinase from Cell Signaling Technology; SLC1A5, LAMP2, b-actin, TOM20, MnSOD2, GFP, HA, PDK1, and GLUT1 from Santa Cruz Biotechnology; Tim23 from Abcam; HIF-1a and HIF-2a from Novus Biologicals. Reagents were obtained from

Cell Metabolism 31, 1–17.e1–e12, February 4, 2020 e6

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

the following sources: alanine, serine, glutamine, glutamate, asparagine, aspartate, di-methyl aKG, N-acetylcysteine, mercury chloride, GPNA, benzylserine, cobalt chloride, deferoxamine, gemcitabine, BPTES, BSO, GME, Tunicamycin and 2-DG from Sigma; PT2385 from Med Chem Express. Subcellular and Submitochondrial Fractionation Mitochondria were isolated from cells as previously described (Wieckowski et al., 2009) with slight modifications. All experiments were performed on ice or at 4 C with prechilled buffers and equipment. Cells cultured in 10 cm dishes (> 90% confluence) were rapidly washed twice with KPBS (136 mM KCl, 10 mM KH2PO4, pH 7.2 in deproteinized and sterilized water. The pH of the buffer was adjusted with KOH because of the sensitivity of isolated mitochondria to sodium) (Chen et al., 2016) and then gently scraped into 1 mL KPBS. The cell suspension was spun down at 900 g for 3 min, the supernatant was discarded, and the cells were resuspended in 1 mL KPBS with protease inhibitors (5 mg/mL aprotinin, 10 mg/mL leupeptin, 250 mM PMSF). Cells were carefully homogenized with 30-50 strokes of a 2 mL Dounce homogenizer to avoid introducing air bubbles into the samples (cell integrity was observed under a phase-contrast microscope to confirm that damaged cells were 80%–90% of total cells). The homogenate was spun down at 600 g for 5 min, and the pellet was discarded (intact cells and nuclei). The supernatant was spun down at 7,000 g for 10 min at 4 C, and the supernatant was discarded. Next, the pellet was resuspended using a Dounce homogenizer (not pipetting). The mitochondrial suspension was centrifuged with KPBS at 7,000 g for 10 min at 4 C. The supernatant was discarded, and the mitochondrial pellets were resuspended using a Dounce homogenizer. Finally, the mitochondrial suspension was centrifuged at 10,000 g for 10 min at 4 C. Total mitochondrial protein contents were determined using a BCA assay kit (intron). Isolation of lysosomes from cells was performed using a Lysosome Enrichment kit (Pierce) according to the manufacturer’s protocol. Briefly, cells cultured in 10 cm dishes (> 90% confluence) were quickly rinsed with DPBS and gently scraped into 3 mL DPBS. The cell suspension was centrifuged at 900 g for 3 min, and the supernatant was discarded. According to the protocol, reagents were sequentially added to the samples with homogenization with a Dounce homogenizer (Sigma), and the samples were subjected to ultracentrifugation at 145,000 g for 2 h at 4 C. After centrifugation, the lysosome band was carefully transferred and analyzed by immunoblotting. Isolation of cytosolic proteins from cells was performed using the NE-PER kit (Pierce) according to the manufacturer’s protocol. Isolation of plasma membrane proteins from cells was performed using Optiprep (Sigma) according to the manufacturer’s protocol (Alere Technologies, Application sheet S62, Isolation of plasma membrane from cultured cells by flotation through a discontinuous gradient). Briefly, cells were washed twice in PBS and then once in homogenization buffer (0.25M sucrose, 1 mM EDTA, 2 mM MgCl2, 20 mM HEPES-NaOH, pH 7.4). Then, the cells were suspended in homogenization buffer and homogenized using a Dounce homogenizer. Next, the sample was centrifuged at 2000 g for 10 min, and the supernatant was subjected to ultracentrifugation at 100,000 g for 1 h. The pellet was resuspended with 30% Optiprep. Next, a discontinuous gradient was prepared by mixing sucrose solution and Optiprep solution and then, overlaying on the resuspended sample. The gradient was subsequently centrifuged at 165,000 g for 3.5 h. The upper gradient was collected by tube puncture and analyzed by immunoblotting. Submitochondrial fractionation was performed as described (Hovius et al., 1990) with slight modifications. Briefly, purified mitochondria were resuspended in 500 mL swelling buffer (10 mM KH2PO2, pHm7.4) with digitonin (2 mg/mL) using a Dounce homogenizer (Sigma) and allowed to swell on ice for 1 h with tapping every 10 min. Then, 1 volume of iso-osmotic solution (32% sucrose, 30% glycerol, and 10 mM MgCl2) was added. The mix was spun at 10,000 g and 4 C for 10 min. Supernatant S1 contained the outer membrane. The pellet P1 was mitoplasts (matrix surrounded by intact inner membrane). P1 was resuspended in 500 mL swelling buffer with a Dounce homogenizer (Sigma) and allowed to swell on ice for 1 h. Then, 1 volume of iso-osmotic solution was added. S1 and the resuspended P1 were spun at 17,000 g and 4 C for 1 h. The supernatant from S1 contained the outer membrane. The supernatant from P1 contained the matrix, and the pellet was the inner membrane. Each fraction was analyzed by immunoblotting with the indicated antibodies. Cellular Amino Acid Uptake Assay MiaPaCa2 cells were seeded in 12-well culture plates and allowed to grow 50% confluence. Radiolabeled glutamine (L-[3H]Gln) and leucine (L-[3H]Leu) (Perkin Elmer), each at a 3 mCi/mL were used to assess amino acid uptake. All measurements were carried out at 37 C and were terminated after brief wash with DPBS solution. Transported amino acids were extracted with lysis buffer (0.2% SDS) and mixed with Microscint PS (Perkin Elmer). All measurements were analyzed by scintillation spectrophotometry Microbeta2 (Perkin Elmer). The lysate was used to measure the cellular protein concentration of each sample by BCA assay kit (Intron). The uptake of radiolabeled glutamine and leucine were calculated from the counts per min (cpm) per sample and specific activity of each labeled amino acid, and these measurements were normalized to cellular protein content. Purification of Mitochondria from Cells and Measurement of Mitochondrial Amino Acids Uptake Mitochondria were prepared according to Wieckowski et al. (2009) with slight modifications. For each experiment, MiaPaCa2 cells expressing 3XMyc-EGFP-OMP25 were immunoprecipitated with anti-Myc antibody. 100ul of anti-c-Myc magnetic beads (Pierce) were pre-washed three times with KPBS (136 mM KCl, 10 mM KH2PO4, pH 7.2 in deproteinized and sterilized water). All washes were done by gentle pipetting using a wide-bore pipette tip and collecting beads using a magnetic stand, DynaMag Spin Magnet (Invitrogen). Cells cultured in 15 cm dishes with 90% confluence were rapidly washed twice with DPBS and then gently scraped into 1 mL KPBS. The pH of the buffer was adjusted with KOH because of the sensitivity of isolated mitochondria to sodium e7 Cell Metabolism 31, 1–17.e1–e12, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

(Chen et al., 2016). The cell suspension was spun down at 900 g for 3 min and the pellet was resuspended in 1 mL KPBS. The cells were carefully homogenized with 30-50 strokes of a 2 mL Dounce homogenizer to avoid introducing air bubbles into the samples. The homogenate was spun down at 1000 g for 2 min and the supernatant was immunoprecipitated with anti-c-Myc antibody-conjugated magnetic beads for 20 min. The c-Myc-tagged mitochondria were eluted with 250 mL of 0.25 mg/mL c-Myc peptide (Pierce). To measure the mitochondrial amino acid uptake, purified mitochondria were diluted with KPBS solution and 50 mL of mitochondrial suspension was delivered to each well of 96-well plate coated with poly-L-lysine (Sigma). The microplate was then transferred to a centrifuge equipped with a swinging bucket microplate adaptor, and spun at 2,000 g for 20 min. After centrifugation, the supernant was discarded and then 100 mL of prewarmed KPBS solution was added to each well. Radiolabeled alanine (L-[14C]Ala), serine (L-[3H] Ser), glutamine ([L-[3H]Gln), and glutamate ([L-3H]Glu) (Perkin Elmer) (3 mCi/mL) were used to assess mitochondrial amino acid uptake by adding labeled amino acids into each well. For the experiment using SLC1A5 inhibitors, GPNA (100 mM L-g-glutamyl-p-nitroanilide), Benzylserine (100 mM), and HgCl2 (20 mM mercury chloride), these inhibitors were added 2 h before the assay and included continuously during amino acid uptake assay. All measurements were carried out at 37 C and were terminated after brief wash with DPBS solution. Transported amino acids were extracted with lysis buffer (0.2% SDS) and mixed with Microscint PS (Perkin Elmer). All measurements were analyzed by scintillation spectrophotometry Microbeta2 (Perkin Elmer). The lysate was used to measure the mitochondrial protein concentration of each sample by BCA assay kit (Intron). The uptake of radiolabeled amino acid was calculated from the counts per min (cpm) per sample and specific activity of each labeled amino acid, and these measurements were normalized to mitochondrial protein content. LC/MS-based Metabolomics and Quantification of Metabolite Abundance Whole cell metabolite or mitochondrial metabolite profiling was performed on ice with ice-cold buffers. 1x107 cells were quickly washed two times with DPBS and briefly washed with Optima LC/MS water and then scraped into 1 mL of 80% methanol in water. Samples were vortexed vigorously for 1min, spun down at 17,500 g for 15 min, and the supernatants analyzed with LC/MS as described above to determine the total moles of metabolite in each sample. Whole cell metabolites were calculated using the total moles of metabolite in samples and normalized to the total number of cells per sample. For measurement of mitochondrial metabolite, mitochondria were isolated from 3x107 cells and purified as described above. For extraction, beads were collected and incubated for 5 min with 200 mL 80% methanol in water. Mitochondrial metabolites were calculated using the total moles of metabolite in samples and normalized to the total mass of mitochondrial protein of each sample. For the ultra-performance liquid chromatography-triple-quadrupole mass spectrometry (UPLC-TQ-MS) analysis, the metabolite extract was diluted with 20% (v/v) acetonitrile. An Agilent 1290 Infinity II LC and Agilent 6495 Triple Quadrupole MS systems equipped with an Agilent Jet Stream ESI source (Agilent Technologies) was used for analysis. The MassHunter Workstation (Ver B.06.00, Agilent Technologies) software was used for data acquisition and analysis. To quantify the level of glutamine, glutamate and glutathione, LC separations were carried out on Intrada Amino acids column (50 mm x 3 mm, particle size 3 mm, Imtakt). To quantify the level of TCA cycle intermediates, LC separations were carried out on Kinetex C18 column (100 mm x 2.1 mm, particle size 1.7 mm, Phemomenex) and Kinetex Polar C18 column (100 mm x 2.1 mm, particle size 2.6 mm, Phemomenex). To quantify the level of palmitate, LC separations were carried out on Acquity UPLC BEH T3 column (100 mm x 2.1 mm, 1.7 mm; Waters). The MS was operated with following parameter settings: gas temperature of 220 C, nebulizer gas of nitrogen at 40 psi, sheath gas temperature of 300 C, and sheath gas flow rate of 12 L/min. Quantification was performed in multiple reaction monitoring (MRM) mode and the optimized condition of each metabolite was performed using flow injection of individual standard compound solutions (100 ng/mL) into the mass. Immunofluorescence Staining and Analysis HeLa cells were seeded onto coverslips and fixed with 100% ice-cold methanol for 1 min at
20 C. After incubation with PBS blocking buffer containing 1% BSA, cells were incubated with anti-HA (Santacruz, 1:50), anti-COX4, anti-Na,K-ATPase, anti-ERp72, antiGM130, and anti-LAMP2 (Cell Signaling, 1:50) antibodies for 4 h at room temperature. The samples were incubated with Alexa 488- or Alexa 594-conjugated secondary antibodies (1:1000) in blocking buffer containing 1% BSA for 30 min. Nuclei were stained with DAPI (300 nM, 5 min). After washing with PBS, cells were mounted and observed by confocal laser scanning microsopy (ZEISS). The index of colocalization was calculated via the colocalization module in Zen imaging software (ZEISS). After ROIs (regions of interest) were defined according to the localization of HA-tagged SLC1A5, SLC1A5_var, SLC38A1, SLC38A2, SLC38A9, or SLC7A5, the localization of other components was measured within the defined ROIs. The index of colocalization corresponds to the mean ± SD of the overlap coefficient (R) 3 100 obtained for more than 10 cells for each colabeling. Intensity profile was generated using the image profile module in Zen imaging software (ZEISS). All samples were blinded, to avoid an experimenter-caused bias in the results. Live-Cell Imaging and Analysis HeLa cells were seeded onto confocal dishes (SPL) and probed with MitoTracker Red (Invitrogen). After incubation with 20 nM MitoTracker Red for 10 min, cell images were captured with an objective lens (60X/1.40 oil) at a resolution of 1024 X 1024 using digital zooming (LSM710, ZEISS). The index of colocalization was calculated via the colocalization module in Zen imaging software (ZEISS). After ROIs were defined according to the localization of MitoTracker, the localization of other components was measured within the defined ROIs. The index of colocalization corresponds to the mean ± SD of the overlap coefficient (R) 3 100 obtained for more than 10 cells for each colabeling. Cell Metabolism 31, 1–17.e1–e12, February 4, 2020 e8

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

Expression Constructs and Mutagenesis Human SLC1A5, SLC38A1, SLC38A2, SLC7A5 cDNA were provided from the Korea Human Gene Bank (Medical Genomics Research Center, KRIBB), and SLC38A9 cDNA was provided from Addgene. For expression studies, the coding sequences of human SLC1A5 (NM_005628.2) and SLC1A5_var (NM_001145145.1) were cloned into the pIRESpuro3 vector (EcoRI/NotI). For immunofluorescence analysis, SLC1A5, SLC1A5_var, SLC38A1, SLC38A2, SLC38A9, and SLC7A5 were subcloned into the pCMV-HA-N vector (EcoRI/NotI). To generate EGFP-fused SLC1A5_var protein for identification of the MTS, 1-46, 47-234, and 235-339 peptide sequences of SLC1A5_var were cloned into the pmTFP1-C vector (EcoRI/NotI), whose fluorescence protein mTFP was substituted with EGFP (AgeI/BglII). The human SLC1A5_var mutant (D186A) was generated using a site-directed mutagenesis kit (NEB). The human SLC1A5_var mutant (R44A/K45A), NT_3A, and NT_2A were generated using primers including point mutations followed by PCRs. To generate the WT SLC1A5_var HRE promoter construct for the transcriptional activity assay, the intron region (2342 bp) between exon 2 and exon 3 within the SLC1A5 gene locus from MiaPaCa2 cell was cloned into the pGL4.1 vector (KpnI/EcoRV). The SLC1A5_var mutant HRE promoter was generated using a site-directed mutagenesis kit (NEB). Hypoxia Treatment Cells were placed in a hypoxia chamber (STEMCELL Technologies) flushed with 100 L of a gas mixture containing 1% O2 and 5% CO2 balanced with N2 and then incubated at 37 C. Gene Expression Analysis RNA was isolated using the MiniBEST Universal RNA Extraction kit (TAKARA) according to the manufacturer’s instructions. Reverse transcription of 1,000 ng RNA was performed using the PrimeScript 1st strand cDNA Synthesis kit (TAKARA). The complete reaction mix was incubated at 42 C for 45 min, and the reverse transcriptase was inactivated at 90 C for 5 min. For qRT-PCR, the resulting cDNA was diluted in nuclease-free water (1:1) followed by PCR using EmeraldAmp GT PCR Master Mix (TAKARA). Then, the PCR products were analyzed by 1% agarose gel electrophoresis. Gene expression levels were determined by ImageJ and normalized to the expression level of the housekeeping genes, b-actin or GAPDH. For quantitative real-time PCR analysis, cDNA was diluted in nuclease-free water (1:5) and gene expression levels are analyzed using Step One Plus (Applied Biosystems). Expression levels were normalized to the expression level of the housekeeping genes POLR2A. The primers used for PCR are listed in Table S1. Luciferase Promoter Activity Assay Cells plated in 12-well plates were cotransfected with 0.8 mg of Firefly luciferase construct containing the SLC1A5_var promoter and 0.2 mg of control Renilla construct (Promega) using Lipofectamine 2000 transfection reagent (Invitrogen). After transfection, the cells were incubated for the desired time or condition, and the luciferase activity was measured using the Dual-Luciferase Reporter Assay System (Promega) and a microplate reader (Infinite 200 PRO, TECAN). Firefly luciferase activity was normalized to Renila luciferase activity. siRNA and shRNA Expression For siRNA experiments, cells were transfected with siRNAs using Lipofectamine RNAiMAX reagent (Invitrogen) in Opti-MEM Reduced Serum Medium (GIBCO) as described by the manufacturer. The SLC1A5 and SL1A5_var siRNA sequences are listed in Key resources table (Unless otherwise noted, #1 siRNA was used in all experiments). The pLKO.1 shRNA vector was provided by Dr. Jinu Lee. The shSLC1A5_var sequence was 50 -CTATGTACTCTACCACCTATG-30 generated from SLC1A5_var exon 2 and the exon 3 junction sequences. Control shRNA sequence was provided by the Broad Institute (TRCN0000072187, 50 -CTCTCGGCATG GACGAGCTGT-30 ). Generation of Cells Stably Expressing cDNAs and shRNAs MiaPaCa2 or Panc1 cells were transfected with pIRESpuro3 including SLC1A5 or SLC1A5_var cDNA using Lipofectamine 2000 reagent (Invitrogen) according to the manufacturer’s protocol. Forty-eight h after transfection, cells were subcultured in medium containing puromycin (MiaPaCa2, 5 mg/mL; Panc1, 10 mg/mL). After two weeks, surviving cells were observed and isolated from large, healthy colonies using a cloning cylinder (Sigma) and continually maintained in medium containing puromycin (Sigma). Single cells from resistant colonies were transferred into 96-well plates to confirm that they could grow as puromycin-resistant colonies. For the experiments in Figure 5, two different overexpressing cells from different isolated colonies were selected and averaged (1A5, SLC1A5 #1 and #2; 1A5_var, SLC1A5_var #1 and #2). To generate stable knockdown cell lines, HEK293T cells were transfected with shGFP or shSLC1A5_var with packaging and envelope plasmids (Addgene) using Lipofectamine 2000 reagent (Invitrogen). Virus-containing supernatants were collected at 48 h after transfection. MiaPaCa2 cells were infected with 0.45 mm-filtered viral supernatant in the presence of 10 mg/mL polybrene (Sigma) for 24 h. Infected MiaPaCa2 cells were selected with 5 mg/mL puromycin. CRISPR/Cas9 Knockout Guide RNA sequence targeting the human SLC1A5_var promoter (50 -CCCCCACACCACGTGTCACT-30 ) was cloned into the lentiCRISPRv2 vector (Addgene). HEK293T cells were transfected with sgCon or sgSLC1A5_var-HRE with packaging and envelope plasmids (Addgene) using Lipofectamine 2000 reagent. Virus-containing supernatants were collected at 48 h after transfection.

e9 Cell Metabolism 31, 1–17.e1–e12, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

MiaPaCa2 cells were infected with 0.2 mm-filtered viral supernatant in the presence of 10 mg/mL polybrene for 24 h. Infected MiaPaCa2 cells were selected with 5 mg/mL puromycin for one week and used in the experiment. Generation of Gemcitabine Resistant MiaPaCa2 Cells Gemcitabine resistant MiaPaCa2 cells (Gem.R cells) were generated by exposure to gradually increasing concentrations of the drug for 3 months as described previously (Davidson et al., 2004). Parental MiaPaCa2 cells were exposed to gemcitabine at an initial concentration of 1 nM, and the gemcitabine concentration was increased with every subculture passage (passage 1, 1 nM; passage 2, 4.5 nM; passage 3, 8 nM; passage 4, 11.5 nM; passage 5, 15 nM; passage 6, 18.75 nM, passage 7, 22.5 nM; passage 8 26.25 nM; passage 9, 30 nM). Subculture was performed when cell confluence reached 90% in the dishes. The Gem.R cell line was cultured in gemcitabine (30 nM) to maintain resistance. Chromatin Immunoprecipitation (ChIP) Cells were cultured in normoxia or hypoxia for 24 h, and ChIP assays were performed using the ChIP kit (Abcam) according to the protocol described by the manufacturer. Briefly, 2 3 106 cells were fixed with 1.1% formaldehyde for 10 min. Cell nuclei were isolated, and DNA from 120 mg nuclear extract was sheared to 200-1,000 bp by sonication. Proper conditions to obtain the desired fragment size had been determined prior to the experiment by performing a sonication time course. The resulting fragmented chromatin was divided into two ChIP reactions (HIF-2a or control IgG ChIP). DNA was enriched by immunoprecipitation using 5 mg of either the anti-HIF-2a (Novus) or normal rabbit IgG control antibodies (Cell Signaling) complexed to Protein A agarose beads. The formaldehyde crosslinks from the immunoprecipitated DNA were dissociated with heat (95 C, 10 min). Proteins were removed by protein K treatments. Nonenriched DNA samples were treated in the same manner to serve as control input. The resulting ChIP and input DNAs were subjected to PCR using primers for several promoter regions of SLC1A5_var bearing HRE motifs. OCR / ECAR Analysis The OCR and ECAR were determined with an XFe24 extracellular flux analyzer (Agilent Technologies) as described in the manufacture’s protocol. A total of 2.5x104 cells were seeded per well in 24-well micro cell culture plates (Agilent Technologies) in DMEM with 10% FBS and incubated at 37 C overnight in a 5% CO2 incubator. The next day, the growth medium was replaced with phenol red and bicarbonate-free, pH 7.4, DMEM, and the cells were incubated at 37 C in a non-CO2 incubator to equilibrate the CO2 level in the atmosphere. Using the XFe24 analyzer, OCR and ECAR were measured under baseline conditions and under the treatment of several metabolic drugs, such as glutamine (Gln, 2mM), glucose, (gluc, 25mM), oligomycin (2 mM), FCCP (carbonyl cyanide-p-trifluoromethoxyphenylhydrazone, 0.5 mM), Rotenone/Antimycin A (0.5 mM/0.5 mM), 2-DG (2-deoxyglucose, 50 mM) (These drugs were included in the Cell Mito Stress Test kit, Glycolytic Rate Assay kit, Phenotype Test Kit, Agilent Technologies). For metabolic phoenotype assay, cells were used to measure the basal OCR and ECAR (Basal). Subsequently, cells were exposed to oligomycin (2 mM) and FCCP (0.5 mM) to measure the OCR and ECAR in metabolic stress conditions (Maximal). Each measurement cycle consisted of 3 min of mixing, 3 min of waiting, and 4 min of measuring. The OCR and ECAR values were normalized to cell number and analyzed using WAVE software (Agilent Technologies) ATP Assay Cells in a 24-well format were treated with either glucose or glutamine and incubated in normoxia or hypoxia for 4 h. After incubation, cells were washed using 500 mL PBS and lysed using 250 mL lysis reagent for luciferase assay (Promega) and briefly centrifuged at 13000 g for 1 min. ATP was measured by mixing each 50 mL supernatant of lysed sample and 50 mL of CellTiter-Glo (Promega), the plate was incubated in the dark for 10 min, and the luminescence was quantified by a plate reader (Infinite 200 PRO, TECAN). Measurement of GSH, ROS and Mitochondrial ROS Intracellular reduced glutathione contains a thiol group that was derivatized with monobromobimane, a fluorescent tag (Ex/Em: 394/490 nm) (Hedley and Chow, 1994). Cells were incubated with monobromobimane (40 mM, 15 min), and stained cells were analyzed using a flow cytometer (BD FACS ARIA III). The reduced glutathione (GSH) to oxidized gluathione (GSSG) ratio was measured using the GSH/GSSH assay kit (Abcam) according to the manufacturer’s instructions. The fluorescence at Ex/Em = 490/520 nm were recorded, and the GSH/GSSG ratio was calculated based on the formula described in the manufacturer’s instructions. Intracellular ROS were determined by staining cells with 1 mM of 5-(and-6)-carboxy-20 ,70 -dichlorodihydrofluorescein diacetate (H2DCFDA, Invitrogen) for 15 min according to the manufacturer’s protocol (Ex/Em: 492/517 nm). Stained cells were analyzed using a flow cytometer (BD FACS ARIA III). Mitochondrial ROS were determined by staining cells with 5 mM MitoSOX Red mitochondrial superoxide indicator (Ex/Em: 510/580 nm). Cells were incubated with MitoSOX Red, and stained cells were analyzed using a flow cytometer (BD FACS ARIA III). Measurement of NADP+/NADPH NADPH/NADP+ ratio was determined using NADP+/NADPH Assay kit (ab65349) according to the manufacturer’s instruction. Briefly, 1x106 cells were collected on ice with extraction buffer and subjected to two rounds of freeze-thaw at
80 C. NADP+ and NADPH concentrations were determined by comparison to standard curves and normalized using calculated protein concentration. Cell Metabolism 31, 1–17.e1–e12, February 4, 2020 e10

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

Measurement of Cell Viability, Growth and Death To eliminate the effects of serum-derived trace glutamine, dialyzed FBS (GIBCO) was used. For cell viability assays, cells were seeded into 96-well culture plates at a density of 5,000 cells per well and initially kept in proper media with 10% dialyzed FBS. After cell attachment, the medium was replaced with conditioned medium. Cell viability was measured using a WST-1 assay after 72 h. The WST-1 assay is based on utilizing the highly sensitive water-soluble tetrazolium salt to produce a water-soluble formazan dye upon reduction in the presence of mitochondrial dehydrogenases. Absorbance at 450 nm was measured using a microplate reader (Infinite 200 PRO, TECAN) for each sample and normalized to the control. (reference wavelength 625 nm). Cell proliferation was measured using an IncuCyte system (Sartorius). IncuCyte data are shown as cell confluence (mean ± SEM) at set intervals. The cell number was counted using an automated cell counter (ADAM-MC, NanoEntek). Cell death was measured using CellTox green dye (Promega). After the desired duration of cell culture in either the presence or absence of gemcitabine, cells were stained with CellTox green dye for 1 h. Stained cells were measured with a flow cytometer (BD FACS ARIA III) to quantify the number of dead cells. To determine the percentage of cells undergoing apoptosis induced by SLC1A5_var knockdown, annexin V assay was performed according to the protocol described by the manufacturer. A total of 5X105 cells were stained with FITC-annexin V and incubated for 30 min at room temperature in the dark, followed by analysis using flow cytometry (BD FACS ARIA III). Clonogenic Assay Cells were plated in 6-well plates at 600 cells per well in 3 mL of media. To prevent evaporation of the cell culture medium during the experimental period, the culture plates were placed into a humidified chamber with sterile deionized water. After 2-3 weeks, colonies were fixed in 100% methanol and stained with 0.5% crystal violet and counted. The data are representative of three independent experiments with similar results. In Vivo Xenograft Tumor Assay All animal experiments were conducted in accordance with the Guide for the Care and Use of Laboratory Animals, published by the Korea National Institute of Health (BEC-CAN-2016-001 and 002). Xenografts were performed on 8-week-old female BALB/c nude mice. After subcutaneous injection with MiaPaCa2 shCon or shSLC1A5_var 1.0 3 107 cells in 250 mL PBS, tumor volumes were measured by electronic calipers at every other day and calculated using the formula (length 3 width 3 height)/2. Analysis of Mitochondrial Morphology Cells were divided as previously described (Karbowski et al., 2006) into three categories: ‘‘Elongated/tubular’’ with > 90% of mitochondria forming elongated interconnected networks, ‘‘Intermediate’’ with mixed tubular and short mitochondria, and ‘‘Fragmented’’ with > 90% short puncti-form mitochondria. The percentage of cells with elongated/tubular, intermediate, or fragmented mitochondria was measured, and over 100 cells per condition were quantified in samples from three biologically independent experiments. Measurement of Mitochondrial Membrane Potential Changes in mitochondrial membrane potential were detected by incubation of living cells with tetramethylrhodamine ethyl ester (TMRE 20 nM, Invitrogen) for 15 min and analyzed by flow cytometry (BD FACS ARIA III). Expression of SLC1A5 Isoform in Normal and Cancer Tissue The expression of each tissue transcript of SLC1A5 isoform from normal and cancer tissue was acquired from Firehose of The Broad Insitutue (http://gdac.broadinstitute.org/) and the Genotype-Tissue Expression (GTEx) portal (https://gtexportal.org/). After transformation of transcription IDs into those of ensemble, normalization of each tissue samples was performed. Log2 transformation of expression value was visualized by boxplot and comparison of normal and cancer tissue was performed by Student’s t test and p < 0.005 was considered as statistically significant. Survival Analysis Kaplan-Meier overall survival of the TCGA cohort patients of each cancer group stratified according to expression level (high/low) was generated and log rank test was performed, using R packages of Survminer (version 0.4.4) and Survival Analysis (version2.44). In Silico Analysis To analyze putative transmembrane domains, the protein sequence of SLC1A5_var was uploaded to the web server for predicting transmembrane domains (http://www.cbs.dtu.dk/services/TMHMM/). To analyze the signal peptide in the amino-terminal region of SLC1A5_var, the protein sequence of SLC1A5_var was uploaded to the web server (http://www.predisi.de/). To identify conserved amino acid sequence in putative SLC1A5_var genes in different species, amino acid sequence was uploaded to the COBALT for predicting amino acid similarity (https://www.st-va.ncbi.nlm.nih.gov/tools/cobalt/).

e11 Cell Metabolism 31, 1–17.e1–e12, February 4, 2020

Please cite this article in press as: Yoo et al., A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells, Cell Metabolism (2019), https://doi.org/10.1016/j.cmet.2019.11.020

QUANTIFICATION AND STATISTICAL ANALYSIS All statistical analyses were performed using GraphPad Prism 7 software. Data obtained from the RT-PCR, immunofluorescence staining, clonogenic assay, and OCR/ECAR were statistically analyzed using Student’s t test, and the graphs show the mean ± SD. Detailed methods and p values for the statistical significance are described in the figure legends and method details. We did not include additional statistical tests for data distributions. DATA AND CODE AVAILABILITY This study did not generate any unique datasets or code.

Cell Metabolism 31, 1–17.e1–e12, February 4, 2020 e12