Supplementary Materials for Calorie restriction in humans inhibits the PI3K/AKT pathway and induces a younger transcription profile Evi M. Mercken,

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Supplementary Materials for

Calorie restriction in humans inhibits the PI3K/AKT pathway and induces a younger transcription profile

Evi M. Mercken,

^1†

Seth D. Crosby,

^2†

Dudley W. Lamming,

^3,4,5

Lellean JeBailey,

⁶

Susan Krzysik- Walker,

⁷

Dennis Villareal,

⁸

Miriam Capri,

^9,10

Claudio Franceschi,

^9,10

Yongqing Zhang,

¹¹

Kevin Becker,

¹¹

David M. Sabatini,

^3,4,5

Rafael de Cabo,

^1*

Luigi Fontana

^8,12,13*

†

These authors contributed equally to this research.

*

Corresponding authors: lfontana@dom.wustl.edu (L.F.); decabora@grc.nia.nih.gov (R.D).

This pdf file includes:

Fig. S1

Tables S1 to S5

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Table S1. Z-scores of the top 100 pathways significantly changed by either WD or CR.

PathwayName

(Zscore) WD:Y

(Zscore) CR:WD STRIATED_MUSCLE_CONTRACTION -18.83 27.60

IGF_VS_PDGF_UP -18.05 26.23

MYOD_BRG1_UP -14.35 22.87

ELECTRON_TRANSPORT_CHAIN -12.21 17.48

RIBOSOMAL_PROTEINS -10.38 9.08

MOOTHA_VOXPHOS -9.82 15.61

MYOD_NIH3T3_UP -7.99 14.11

HUMAN_MITODB_6_2002 -7.15 15.69

VENTRICLES_UP -6.93 14.27

OXIDATIVE_PHOSPHORYLATION -6.56 10.45

MITOCHONDRIA -6.16 14.19

MUSCLE_MYOSIN -5.95 8.11

ROME_INSULIN_2F_UP -5.06 8.42

GLYCOLYSIS_AND_GLUCONEOGENESIS -4.64 7.43

PGC -3.44 9.33

NADLER_OBESITY_DN 5.16 -7.47

FLECHNER_KIDNEY_TRANSPLANT_WELL_UP 5.19 -8.99

VEGF_MMMEC_ALL_UP 5.39 -7.32

DIAB_NEPH_DN 5.84 -7.71

TAKEDA_NUP8_HOXA9_10D_DN 5.95 -8.11

TNFALPHA_TGZ_ADIP_DN 5.96 -8.58

TGZ_ADIP_UP 6.01 -9.09

ROS_MOUSE_AORTA_DN 6.05 -7.29

JNK_DN 6.16 -7.28

LEE_E2F1_UP 6.26 -8.36

CARIES_PULP_HIGH_UP 6.26 -8.93

MANALO_HYPOXIA_UP 6.34 -8.23

YAO_P4_KO_VS_WT_UP 6.37 -7.32

TAKEDA_NUP8_HOXA9_8D_UP 6.38 -7.71

CMV_HCMV_TIMECOURSE_24HRS_DN 6.39 -8.58

TGFBETA_EARLY_UP 6.40 -7.77

LEE_ACOX1_UP 6.41 -7.27

ZHANG_EFT_EWSFLI1_UP 6.41 -8.94

ADIPOCYTE_PPARG_UP 6.57 -8.97

TNFALPHA_ADIP_DN 6.57 -9.56

TAKEDA_NUP8_HOXA9_8D_DN 6.58 -8.13

VERHAAK_AML_NPM1_MUT_VS_WT_UP 6.64 -8.63

ADIP_VS_PREADIP_UP 6.82 -8.30

ALZHEIMERS_INCIPIENT_UP 6.88 -7.24

RADAEVA_IFNA_UP 6.93 -8.11

HOHENKIRK_MONOCYTE_DEND_UP 7.00 -9.04

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HOHENKIRK_MONOCYTE_DEND_DN 7.02 -7.88

YAGI_AML_PROG_FAB 7.07 -7.76

LEE_MYC_E2F1_UP 7.10 -8.54

HTERT_DN 7.15 -8.77

TAKEDA_NUP8_HOXA9_3D_UP 7.16 -7.66

LINDSTEDT_DEND_DN 7.21 -8.14

HSC_LATEPROGENITORS_ADULT 7.24 -5.90

DIAB_NEPH_UP 7.32 -6.81

BYSTRYKH_HSC_TRANS_GLOCUS 7.36 -3.97

SANA_IFNG_ENDOTHELIAL_UP 7.42 -7.41

ADIP_DIFF_UP 7.43 -10.30

REOVIRUS_HEK293_DN 7.46 -4.85

AGEING_BRAIN_UP 7.49 -8.58

PENG_GLUTAMINE_UP 7.52 -3.98

LEE_DENA_UP 7.52 -8.82

HSIAO_LIVER_SPECIFIC_GENES 7.56 -6.97

TARTE_PC 7.59 -7.57

BRCA_ER_POS 7.61 -4.91

VERHAAK_AML_NPM1_MUT_VS_WT_DN 7.72 -6.83

IRITANI_ADPROX_VASC 7.72 -6.89

SERUM_FIBROBLAST_CORE_DN 7.72 -6.14

JECHLINGER_EMT_UP 7.75 -8.41

NFKB_TARGET_REFERENCE 7.80 -8.10

GILDEA_BLADDER_UP 7.91 -8.77

TGFBETA_ALL_UP 7.91 -9.15

EMT_UP 7.93 -8.52

CMV_24HRS_DN 7.94 -10.10

APPEL_IMATINIB_UP 8.04 -7.69

HSC_HSCANDPROGENITORS_FETAL 8.06 -5.47

HSC_HSCANDPROGENITORS_SHARED 8.06 -5.47

CMV_ALL_DN 8.10 -10.42

HSC_HSCANDPROGENITORS_ADULT 8.15 -5.46

ADIPOGENESIS_HMSC_CLASS3_UP 8.22 -9.87

STEMCELL_NEURAL_UP 8.37 -5.22

LI_FETAL_VS_WT_KIDNEY_UP 8.46 -9.91

RUTELLA_HEPATGFSNDCS_UP 8.49 -10.05

DAC_PANC_UP 8.59 -8.66

BAF57_BT549_UP 8.66 -10.73

ELONGINA_KO_UP 8.87 -8.29

SANSOM_APC_5_DN 8.94 -6.79

BROWN_GRAN_MONO_DIFFERENTIATION 8.98 -10.42

NADLER_OBESITY_UP 9.45 -10.67

LEE_TCELLS2_UP 9.52 -8.69

ATRIA_UP 9.55 -10.65

ICHIBA_GVHD 9.82 -10.05

POD1_KO_DN 10.06 -11.80

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LEI_MYB_REGULATED_GENES 10.09 -9.18

WIELAND_HEPATITIS_B_INDUCED 10.14 -10.92

FLECHNER_KIDNEY_TRANSPLANT_REJECTION_UP 10.91 -12.93

AGEING_KIDNEY_SPECIFIC_UP 10.92 -11.38

CARIES_PULP_UP 11.47 -14.15

IGLESIAS_E2FMINUS_UP 11.47 -16.27

BRCA_ER_NEG 12.07 -12.19

STEMCELL_HEMATOPOIETIC_UP 12.42 -8.13

RUTELLA_HEMATOGFSNDCS_DIFF 12.98 -14.16

ALZHEIMERS_DISEASE_UP 13.62 -9.64

BOQUEST_CD31PLUS_VS_CD31MINUS_DN 14.72 -18.13 BOQUEST_CD31PLUS_VS_CD31MINUS_UP 16.89 -19.97

AGEING_KIDNEY_UP 18.29 -19.24

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Table S2

. RT-qPCR/QuantiGene based assay validation of micro-array data

Z ratio (Array) Fold change (qRT-PCR/quantiGene) CR:WD

HUMAN

CR:AL RAT

CR:WD HUMAN

CR:AL RAT

HSPB6 2.11 6.24 1.32 -1.13

MID1IP1 2.57 6.00 2.24 2.21

TPI1 3.82 4.46 2.21 1.24

ATP5G1 4.64 4.18 3.24 1.06

PKM2 3.94 4.26 3.86 -2.04

NFIX 1.50 4.22 -1.16 1.27

PPARGC1A 3.94 3.83 3.75 2.45

SCN3B 1.51 3.65 2.04 5.29

PTPN3 4.10 3.61 4.10 -

TMEM43 -2.32 -2.64 -2.69 -1.30

DDX39 -1.65 -3.33 -2.08 -2.10

BCAP31 -3.11 -3.44 -4.23 -4.90

SAT1 -4.37 -4.21 -6.99 -1.19

TMEM140 -1.57 -4.83 -2.02 -1.96

LCP1 -3.60 -5.04 -4.54 -2.20

ACSL4 -2.15 -5.60 1.33 -2.12

RUNX1 -1.62 -6.58 -1.08 -2.40

TUBB6 -3.66 -9.66 -8.40 -6.74

RNA from vastus lateralis muscle samples from human on CR versus Western diet (WD) and

vastus lateralis muscle from AL versus 40% CR-fed rat were characterized by Quantigene or

qPCR, respectively. Targets were selected based on the micro-array data which are shown for

comparison. Note that numbers reflect statistical confidence and do not relate directly to fold-

change. The fold changes marked in red did not match the Z-scores of the micro-array data.

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Table S3

. Z-scores of common pathways between humans and rats.

HUMAN RAT

PathwayName (MSigDB) Zscore

CR:WD

Zscore CR:AL

STRIATED_MUSCLE_CONTRACTION 34.49 23.15

IGF_VS_PDGF_UP 32.43 10.44

HUMAN_MITODB_6_2002 22.23 5.05

ELECTRON_TRANSPORT_CHAIN 21.74 12.50

VENTRICLES_UP 20.26 6.63

MITOCHONDRIA 20.21 4.65

MOOTHA_VOXPHOS 19.38 12.72

PGC 14.34 7.39

RIBOSOMAL_PROTEINS 14.03 3.77

OXIDATIVE_PHOSPHORYLATION 12.96 8.42

GLYCOLYSIS_AND_GLUCONEOGENESIS 9.59 9.44

KREBS_TCA_CYCLE 8.78 7.65

TCA 8.66 6.29

HIPPOCAMPUS_DEVELOPMENT_POSTNATAL 8.47 7.21

UBIQUINONE_BIOSYNTHESIS 8.34 6.71

GAY_YY1_UP 7.75 4.73

ETCPATHWAY 7.65 6.38

KREBPATHWAY 7.50 3.43

PGC1APATHWAY 7.24 3.36

UVB_NHEK1_C1 5.59 3.09

CITRATE_CYCLE_TCA_CYCLE 5.32 5.11

IDX_TSA_UP_CLUSTER5 4.73 3.45

NO2IL12PATHWAY -1.68 -1.79

STAT3PATHWAY -1.74 -1.99

CHEMICALPATHWAY -2.01 -2.42

PLCDPATHWAY -2.10 -1.61

IDX_TSA_DN_CLUSTER6 -2.13 -2.19

NKCELLSPATHWAY -2.70 -1.88

IL22BPPATHWAY -2.75 -2.27

IFNGPATHWAY -3.10 -1.95

AMINOSUGARS_METABOLISM -3.12 -1.83

GOLDRATH_CYTOLYTIC -3.14 -2.71

HOFMANN_MANTEL_LYMPHOMA_VS_LYMPH_NODES_

UP

-3.34 -2.18

SANSOM_APC_LOSS5_UP -3.50 -4.09

ZHAN_MMPC_EARLYVS -3.57 -1.90

TUMOR_SUPRESSOR -3.58 -2.53

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BECKER_IFN_INDUCIBLE_SUBSET_1 -3.60 -3.97

IFN_GAMMA_UP -3.64 -2.30

UVC_TTD_ALL_DN -3.67 -2.43

TCYTOTOXICPATHWAY -3.72 -1.65

GALE_FLT3ANDAPL_UP -3.86 -3.21

HIVNEFPATHWAY -3.90 -3.83

UVC_XPCS_8HR_DN -4.00 -3.63

VANTVEER_BREAST_OUTCOME_GOOD_VS_POOR_DN -4.02 -2.45

HSC_MATURE_SHARED -4.05 -2.82

GH_GHRHR_KO_24HRS_UP -4.06 -2.50

UVC_XPCS_ALL_DN -4.06 -3.35

ZHAN_MMPC_SIMAL -4.40 -4.12

TFF2_KO_UP -4.51 -1.84

TPA_SENS_LATE_DN -4.56 -2.64

ZHAN_MM_MOLECULAR_CLASSI_DN -4.58 -2.13

LINDSTEDT_DEND_UP -4.59 -3.99

HSC_LATEPROGENITORS_FETAL -4.70 -4.54

DAC_IFN_BLADDER_UP -4.77 -3.27

APOPTOSIS -4.80 -3.30

COMPLEMENT_ACTIVATION_CLASSICAL -4.91 -2.23

ROSS_MLL_FUSION -4.91 -4.54

IFN_ALL_UP -5.01 -3.03

VANASSE_BCL2_TARGETS -5.22 -3.77

HSC_LATEPROGENITORS_SHARED -5.27 -4.84

STEMCELL_HEMATOPOIETIC_UP -5.28 -5.61

BRENTANI_DEATH -5.38 -3.66

IFNALPHA_NL_HCC_UP -5.44 -2.33

UVB_NHEK2_DN -5.44 -3.36

AGED_MOUSE_CEREBELLUM_UP -5.48 -4.21

HSC_MATURE_ADULT -5.48 -3.16

CLASSICPATHWAY -5.50 -2.23

HSC_LATEPROGENITORS_ADULT -5.51 -4.99

CELLCYCLEPATHWAY -5.53 -3.19

YAGI_AML_PROGNOSIS -5.68 -2.15

OKUMURA_MC_LPS -5.75 -3.83

HINATA_NFKB_UP -5.85 -5.31

KNUDSEN_PMNS_DN -5.88 -2.76

IFNALPHA_HCC_UP -6.01 -2.27

GRANDVAUX_IFN_NOT_IRF3_UP -6.10 -2.84

IFNALPHA_NL_UP -6.12 -2.20

CROMER_HYPOPHARYNGEAL_MET_VS_NON_UP -6.54 -2.85

BASSO_GERMINAL_CENTER_CD40_UP -6.56 -3.08

BLEO_HUMAN_LYMPH_HIGH_24HRS_UP -7.09 -3.75

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SANSOM_APC_5_DN -7.69 -4.06

SANA_TNFA_ENDOTHELIAL_UP -7.81 -4.13

LEE_TCELLS2_UP -7.92 -2.75

RADAEVA_IFNA_UP -8.34 -2.91

AGEING_BRAIN_UP -8.62 -3.08

SANA_IFNG_ENDOTHELIAL_UP -8.80 -3.03

CARIES_PULP_HIGH_UP -10.97 -4.29

RUTELLA_HEPATGFSNDCS_UP -11.07 -2.86

WIELAND_HEPATITIS_B_INDUCED -11.52 -6.39

ICHIBA_GVHD -11.94 -6.37

BRCA_ER_NEG -12.14 -6.75

FLECHNER_KIDNEY_TRANSPLANT_REJECTION_UP -13.50 -6.30

RUTELLA_HEMATOGFSNDCS_DIFF -14.35 -5.26

CARIES_PULP_UP -15.61 -4.91

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Table S4. Z-scores of 3 central pathways altered by CR between humans and rats.

The table lists pathways involved in insulin growth factor 1 (IGF-1) signaling (green), mitochondrial function (braun) and inflammation (blue).

HUMAN RAT

PathwayName (MSigDB) Zscore CR:WD Zscore CR:AL

IGF_VS_PDGF_UP 32.43 10.44

GH_GHRHR_KO_24HRS_UP -4.06 -2.50

ELECTRON_TRANSPORT_CHAIN 21.74 12.50

MITOCHONDRIA 20.21 4.65

MOOTHA_VOXPHOS 19.38 12.72

HUMAN_MITODB_6_2002 22.23 5.04

PGC 14.34 7.39

OXIDATIVE_PHOSPHORYLATION 12.96 8.42

GLYCOLYSIS_AND_GLUCONEOGENESIS 9.59 9.44

KREBS_TCA_CYCLE 8.78 7.65

TCA 8.66 6.29

UBIQUINONE_BIOSYNTHESIS 8.34 6.71

ETCPATHWAY 7.65 6.38

KREBPATHWAY 7.50 3.43

PGC1APATHWAY 7.24 3.36

CITRATE_CYCLE_TCA_CYCLE 5.32 5.11

IFNALPHA_NL_UP -6.12 -2.20

IFNALPHA_HCC_UP -6.01 -2.27

CLASSICPATHWAY -5.50 -2.23

IFNALPHA_NL_HCC_UP -5.44 -2.33

IFN_ALL_UP -5.01 -3.03

IFN_GAMMA_UP -3.64 -2.30

IFNGPATHWAY -3.10 -1.95

IL22BPPATHWAY -2.75 -2.27

STAT3PATHWAY -1.74 -1.99

NKCELLSPATHWAY -2.70 -1.88

LEE_TCELLS2_UP -7.92 -2.75

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Table S5. Primer sequences and probe set region used for quantitative PCR analysis or Quantigene based assays

Rats Humans

Gene Accession number Sense - Antisense Probe Set Region HSPB6 NM_144617 CGTGCTTCAGCTCCTTTACC

CATCCAGCAGCACAGAAAAA

287-792

MID1IP1 NM_021242 CCCCTCTCTTTCCTCCAAAC TTCCCACCAACAGAGTAGGC

854-1356

TPI1 NM_000365 CCTGCATTGGGGAGAAGTTA GTACTTCCTGGGCCTGTTGA

280-790

ATP5G1 NM_005175 AAAAATGCAGACCACGAAGG ACTTGGCTGCTGTGTCAATG

146-620

PKM2 NM_182470 CCTATCCATTAGGCCAGCAA TTTCCAATCCTGCATTCCTC

1828-2419

NFIX NM_002501 CGACGACAGTGAGATGGAGA GCAGAAGTCCAGCTTTCCTG

728-1171

PPARGC1A NM_013261 ATGTGTCGCCTTCTTGCTCT ATCTACTGCCTGGGGACCTT

379-826

SCN3B NM_001040151 CTGAAGGACCTCCTGTGAGC CCGTAAGCGATTTCTGAAGC

416-818

PTPN3 NM_002829 ACCTGCCTGTTTACCCACTG CAGTGACCAGCATCTCTGGA

1739-2303

TMEM43 NM_024334 GAAAGCCTTTGCCTTCTGTG GCTTCACTCCAGCTTTTTGG

395-897

DDX39 NM_005804 TGAGCGCTTCTCGAAGTACA GCTGTTCCAGCATCTTGTCA

910-1348

BCAP31 NM_005745 TTTTCCTTGCTGCTGTCCTT ACTCCCAACATCCAACTTGC

654-1103

SAT1 NM_002970 AAAGGCACTGTCTTGCCACT GTGGCTGGACGGATCTTAAA

221-807

TMEM140 NM_018295 CAGCAGACAGAACCCACTGA TGACACTTTGCCAAGACAGC

535-1162

LCP1 NM_002298 ATACCCTGCCTTGCACAAAC AGCTTGGGGTATGGAGGTCT

282-736

ACSL4 NM_203436 CAAACTGAAGGCGGCATTAT GCTTGAGTTTTCTGGCTTGG

534-1067

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RUNX1 NM_001754 ACTAAGCGGCCAGTTGCTAA GGACTCGGATCTTCTGCAAG

399-909

TUBB6 NM_032525 AATAGGGGCCGTAAGATGCT TGTATGGCCCCGTACTTAGC

1250-1784

GAPDH NM_008084.2 AGACAGCCGCATCTTCTT TGATGGCAACAATGTCCACT

-

HPRT1 NM_000194 - 102-646

ACTB NM_001101 - 1164-1762

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Fig. S1. Kaplan–Meier survival analyses of ad libitum (AL) and 40% caloric restricted

(CR) rats. n = 27 for both AL and CR-fed rats. The survival curves for the AL and CR-fed rats

differ significantly (P < 0.001), Blue, AL; red, CR.

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