1 Van Nostrand Et Al SUPPLEMENTAL

Van Nostrand et al SUPPLEMENTAL MATERIAL

In this PDF: Supplemental Figures S1 -8 Supplemental Data Table 2 Supplemental Materials and Methods

As a separate Excel File: Supplemental Data Table 1 – contains gene lists from all Figure panels

1 A B INK - Down-regulated mRNAs FC>1.5 FDR<0.05 WT Metformin WT WT Insulin WT WT Control WT Met + Ins WT WT INK WT WT Ins WT InsMet 1 INK induces, Metformin Independent (e.g. Lipid signaling, Autophagy) Met 658 2 INK and Met-repress (same) (Interferon-beta, Pyruvate 395 metabolism) 1051 InsInk Ink 62 89 3 INK induces, Met represses (opposite) (e.g. Macroautophagy) 480 93 76 876 4 INK-Independent, Insulin represses (Inflammation, Nutrient sensing) 104 16 INK and Met-induce (same) (IL-17 signaling, Lipid metabolism) 25 5 44 37 INK represses, Ins represses, Met Induces in Ins (opposite) (e.g. 365 6 Monocarboxylic acid metabolism, Amino acid biosynthesis, Steroid metabolism) 7 INK induces, Ins Induces, Met represses in Ins (opposite) (e.g. Protein localization) 8 INK and Met-repress (same) (Amino acid metabolism, Lipid Metabolism, HIF-1, ATF4) Upregulated mRNAs 9 INK-Independent, Insulin represses, Met Induces in Ins (e.g. Infection pathway) FC>1.5 FDR<0.05

10 INK and Met-repress (same) (e.g. RNA biology) Met InsMet 350 922 588 InsInk 11 INK-Independent, Met induces (Apoptosis, MAPK signaling) Ink 38 177

180 78 1192 12 INK-Independent, Met represses (e.g. Cell cycle) 41 142 22 5 64 65 475

C Ctrl vs Met Ins vs InsMet NES: -1.86 NES: -1.77 FDR: 0.0024 FDR: 0.0066

Ctrl Ins

Met InsMet

Supplemental Figure S1 A) Heatmap of genes regulated by metformin (Met) or INK-128 (0.1µM, INK) at 5 hours in the absence or with 15’ pretreatment of 1nM Insulin (Ins) with a fold change of at least 1.5. Clusters annotated for metformin (Met), INK- 128 (INK), and Insulin (Ins) responsiveness and primary biological process contained in signature according to metascape analysis. B) Venn Diagram of genes regulated in primary hepatocytes by 2mM metformin (Met) and 0.1mM INK-128 (INK) in the presence or absence of 1nM Insulin pre-treatment (Ins) as described in (A). Fold change>1.5, FDR<0.05 C) GSEA analysis of genes regulated by metformin in absence (left) or presence (right) of insulin pre-treatment as described in (A) compared with gene set for AKT-mTOR signaling showing enrichment for mTOR down upon treatment with metformin. +/+ AA/AA A B 2 hr 5 hr 2 hr 5 hr G C T Alanine G C G Alanine Met (mM) 0 0.5 1 2 0 0.5 1 2 0 0.5 1 2 0 0.5 1 2 Serine Serine P-722 RAPTOR T C C T C C P-792 RAPTOR RAPTOR AMPK Targets P-AMPK

P-T389 S6K1

S6K1 Ser722Ala Ser792Ala P-S240/244 S6

Targets P-S235/236 S6 mTORC1 mTORC1 S6 4-EBP1

ACTIN C Primary Hepatocytes, Serum-Starved Up-regulated mRNAs Down-regulated mRNAs

220 260 76 117196 83 203 201 1000 1469 1387 998 (26%) (37%) (29%) (44%) AA WT AA AA WT WT AA WT Met Met/Ink Met InsMet Met&Ink InsMet&Ink InsMet InsMet/Ink

D Genes Up-regulated with Metformin and Ink Genes Down-regulated with Metformin and Ink in WT but not in RaptorAA in WT but not in RaptorAA GO Biological Process GO Biological Process

-log(p-value) -log(p-value) -log(p-value) -log(p-value) 0 1 2 3 0 1 2 3 4 0 1 2 3 0 1 2 3 4 Regulation of transcription Signal transduction Response to ER stress Cellular amino acid biosynthetic process Response to ER stress Cilium morphogenesis Pos reg of protein phosphorylation Negative reg of cell growth Neg Reg of protein kinase activity Glucose homeostasis ER Unfolded Protein Response Pos reg of ERK1/2 cascade Potassium ion transport Aging Immune system process Response to follicle-stimulating hormone Cell adhesion Cellular response to glucose stimulus Response to hypoxia Progesterone metabolic process Intracellular signal transduction Fat cell differentiation DNA binding transcription factor Apoptotic process Regulation of Rho protein signal transduction Transmembrane Transport Lipid metabolic process Regulation of TOR signaling KEGG Pathway Analysis -log(p-value) KEGG Pathway Analysis -log(p-value) 0 1 2 3 -log(p-value) 0.0 0.5 1.0 1.5 -log(p-value) Osteoclast differentiatin 0 1 2 3 0.0 0.5 1.0 1.5 African trypanosomiasis Staphylococcus aureus infection Protein processing in ER Bile secretion Leishmaniasis O-glycan Biosynthesis Biosynthesis of amino acid Axon guidance Estrogen signaling pathway Fructose and mannose metabolism E InsINK InsINK INK INK InsMet vs Ins vs Ins InsMet vs Ins vs Ins Met vs UT vs UT of Met vs UT vs UT WT AA T AT Am WT WT AA T AT Am WT WT AA T AT Am WT WT AA T AT Am WT Mlxipl Aldoart1 Lipid Naaa Metab Irs2 Aldoa Reg Gdf9 Crls1

Vcam1 metab Hk1 Sesn2 Pafah1b2 Glucose Fructose Fructose Response Neg Cell Growth Cell WT AA T AT Am WT WT AA T AT Am WT WT AA T AT Am WT WT AA T AT Am WT Alms1 Rasgrp1 Ero1l Adcy9 Diff Aloxe3 C5ar2 Dnajc3 Prkar2a Hmga2 Spry2 ER Dnaja4 ERK1/2 Fat Cell Fat Glucagon Stress

Supplemental Figure S2 A) Chromatogram of sequence from Raptor Serine 722;Alanine 722 and Serine 792;Alanine 792 heterozygous alleles generated from CRISPR targeted mice. B) ) Immunoblot analysis of serum starved primary hepatocytes derived from wild-type (+/+) or RaptorAA mice treated with increasing doses of metformin (0, 0.5, 1, or 2mM) for 2 or 5 hours and blotted for AMPK and mTORC1 substrates C) Venn diagram depicting overlap between genes identified as being both metformin and INK-dependent and genes regulated in RaptorAA hepatocytes upon metformin in the absence or presence of insulin as described in Figure 1C. D) GO Term and KEGG pathway analysis of RaptorAA-dependent genes up-regulated (left) or down-regulated (right) by metformin and INK as described in Figure 1C by a fold change of at least 1.5 in wild-type primary hepatocytes and a fold change of less than 1.5 in RaptorAA primary hepatocytes in presence or absence of insulin. Length of Bar correlates to –log(p-value). Identified using DAVID software E) Example heatmap of fold change for genes identified as being AA-dependent (FC>1.5 with metformin and Ink in WT; FC<1.5 upon metformin in AA). A B Generation of Hepatocytes: Isolate Treat Cells Nomenclature Genotype Tam Treat Hepatocytes & Collect WT +/+ or Tsc2fl/fl or Ampka1fl/fl;Ampka2fl/fl

S722A;S792A/S722A;S792A Day 1 3 5 AA Raptor Next Day In vivo Tsc2fl/fl;Alb-CreER/+ or 7-10 days later Tsc2 Tsc2fl/fl;Alb-Cre/+ (Tsc2-null) Hepatocyte Treatments:

RaptorS722A;S792A/S722A;S792A;Tsc2fl/fl; Treat w/ Treat w/ Treat w/ Translation Transcriptome AA;Tsc2 or AT Alb-CreER/+ or Alb-Cre/+ Insulin Metformin/INK Puromycin Analysis Analysis

5h Ampk Ampka1fl/fl;Ampka2fl/fl;Alb-CreER/+ -15’ 0 1h 2h 50’

C D 1.0 1.5 1.5 1.5 **** WT **** 1.5 * * AA 0.8 *** **** **** T WT 1.0 1.0 * *** 1.0 0.6 AT AA S6 -

S6 0.4 S6K1 P-S6 - - P 0.5 S6K1 T

0.5 - 0.5 P 1.0 0.2 P P AT (Treated/Untreated) Treated/ UntreatedTreated/ 0.0 UntreatedTreated/ 0.0 0.0 0.0 Treated/ UntreatedTreated/

Treated/ UntreatedTreated/ WT AA T AT WT AA T AT WT AA T AT WT AA T AT WT AA T AT WT AA T AT WT AA T AT WT AA T AT 0.5 N.S. +Ins N.S. +Ins N.S. +Ins N.S. +Ins

0.0 WT AA T AT WT AA T AT N.S. +Ins

Supplemental Figure S3 A) Nomenclature for genotypes of mice used throughout the paper. Floxed alleles treated with tamoxifen (Tam) generates null alleles. B) Schematic of time course used to treat mice with tamoxifen prior to generation of hepatocytes (top) and time course used for treating hepatocytes for various assays used throughout the paper (bottom). C) Quantification of P-S6 and P-S6K relative to total protein in immunoblots from Figure 3C D) Quantification of P-S6K and P-S6 relative to total protein in immunoblots from Figure 3D Treat w/ Treat w/ Treat w/ Translation 2 Ink-Dependent Genes A Insulin Metformin/INK Puromycin Analysis F

1 -15’ 0 1h 2h 50’ +1nM Insulin P=0.2 B 1.0 * 0 WT AA T AA;T Ampk WT 0.8 Metformin - + - + - + - + - + Ink 0.6 -1 Anti-Puro 0.4 (Treated/Untreated) Puro Incorporation Incorporation Puro (Treated/Untreated) 0.2

ACTIN 0.0 -2 +/+ AA T AA;T Ampk +/+

Primary Hepatocytes, Insulin-Pretreatment + 2mM Metformin + Ink Fold Change Translation Efficiency + Insulin -3 **** 0.20 0.15 0.20 WT UT 80s +/+ +/+ AA T AA;T Ampk WT Met AA UT C WT Ink Tsc UT 80s 80S AA Met Tsc Met 0.15 80s 0.15 0.10 + Ink + 2mM Metformin

Polysome 40s 60s 0.10 0.10 40s 60s Polysome Abs (254nm) Abs (254nm) Genes with Ink-Dependent Translation (190 genes) Abs (254nm) Polysome 0.05 G Polysome 60s60S 4 GO Term Analysis 40S0 -log(p-value) 0.05 0.05 s 0 5 10 15 20 25 10 20 30 40 50 0.00 10 20 30 40 50 10 20 30 40 50 Translation Distance (mm) Distance (mm) Distance (mm) Transport

Oxidation-reduction process

0.06 0.15 Ribosomal small subunit assembly 80s AATsc UT 80s rRNA processing AATsc Met AMPK UT AMPK Met 60s Cytoplasmic translation 0.04 40s 0.10 Polysome 40s 60s Polysome KEGG Pathway Analysis -log(p-value) Abs (254nm) Abs (254nm) 0.02 0.05 0 10 20 30 40 Ribosome Oxidative phosphorylation

0.00 0.00 10 20 30 40 50 10 20 30 40 50 Distance (mm) Distance

D 3 E Metformin-Dependent Genes H All Genes 2 TOP-Motif Genes

2 GO Biological Processes -log(p-value) 1 0 5 10 15 1 Translation Maturation of SSU-rRNA from 0 0 tricistronic rRNA transcript Oxidation-reduction process rRNA processing -1 -1

(Treated/Untreated) Ribosomal small subunit biogenesis (Treated/Untreated) * -2 -2 ** Fold Change Translation Efficiency KEGG Pathways ** -log(p-value) Fold Change Translation Efficiency ** -3 * 0 5 10 15 20 +/+ +/+ AA T AA;T Ampk -3 *** Ribosome +/+ +/+ AA T AA;T Ampk + Ink + 2mM Metformin Oxidative phosphorylation + Ink + 2mM Metformin Parkinson's disease Alzheimer's disease Huntington's disease Non-alcoholic fatty liver disease

Supplemental Figure S4 A) Schematic of time course used to assay hepatocytes for translation. B) Sunset assay on primary hepatocytes treated with 2mM metformin (Met) or 0.1µM INK-128 (INK) for 2 hours in the presence of 1nM insulin 15’ pre-treatment. Puromycin incorporation quantified with image J (right). . T-test p-value*<0.05 C) Examples of polysome profiles generated by sucrose gradients upon metformin treatment as described in (B) in the various genotypes. D) Ratio of translational efficiency (RNA from polysome/total RNA quantity) between treated and untreated samples for all genes identified across the various genotypes. Translational efficiency was normalized to the average per genotype. E) GO Term and KEGG pathway analysis of 82 genes with decreased translation efficiency in wildtype cells treated with metformin as described in (B). F) Analysis of the fold change in translational efficiency between treated and untreated as described in (B) in genes with 1.5 fold down-regulation in translational efficiency upon INK-128 (INK) treatment in wild-type cells. Kolmogorov-Smirnov test compared to wild-type treated with metformin. n=3 G) GO Term and KEGG pathway analysis of 190 genes identified as having down-regulated translational efficiency upon INK treatment in wildtype primary hepatocytes. H) Analysis of the fold change in translational efficiency between treated and untreated in genes identified as having TOP-motifs (Thoreen, et al, 2012; Hsieh et al, 2012; Philippe, et al, 2020). Kolmogorov- Smirnov test compared to wild-type treated with metformin. n=3. p-value: *0.05, **0.01, ***0.001, ****0.0001 Ins Ins MET INK INS Trxn Factors From UT MET Ins +MET INK +INK 1 SREBP2, FOXO4, PPARα, STAT3 Figure 1D: 2 HIF, SREBP1, FOXA2, CLOCK

ChREBP1, BCL3, Nanog, 3 POU2F1, SREBP1, PPARα

4 ATF4, TEAD1, CEBPB, ATF3

5 USF1, NFκB, SMAD7)

6 RARA, CEBPA

7 NCOR, IRF8, SPI1

8 FOS, NFκB, ATF3, PPARδ, SMAD3

9 TFEB, SREBF2, CREB1, MYBL2

WT AA Tsc2 AA;Tsc2 AMPK WT Insulin - - + + - - + + - - + + - - + + - - + + - + MET INK INS Trxn Factors Met - + - + - + - + - + - + - + - + - + - + Ink

1 SREBP2, FOXO4, PPARA, STAT3

2 HIF, SREBP1, FOXA2, CLOCK

ChREBP1, BCL3, Nanog, 3 POU2F1, SREBP1, PPARA

4 ATF4, TEAD1, CEBPB, ATF3

5 USF1, NFkB, TFEB, SMAD7)

6 RARA, CEBPA

7 NCOR, IRF8, SPI1

8 FOS, NFkB, ATF3, PPARd, SMAD3

9 TFEB, SREBF2, CREB1,, MYBL2

Met and Ink-dependent gene list; Primary Hepatocytes n=3-4

Supplemental Figure S5: Heatmap of 1110 genes regulated similarly between metformin (Met) and INK-128 (0.1µM, INK) in the absence or with 15’ pretreatment of 1nM Insulin (Ins) in wildtype primary hepatocytes across all genotypes and treatments. Order of genes the same as Figure 1D (top). Clusters annotated for metformin (Met), INK-128 (INK), and Insulin (Ins) responsiveness and critical transcription factors driving gene signatures, according to Enrichr as in Figure 1D. A Up-regulated mRNAs Down-regulated mRNAs WT InsMet/InsInk 308 Tsc2 WT 456 Tsc2 WT 380 WT 528 Tsc2 Tsc2 Met/Ink InsMet Met/Ink Met InsMet/InsInk Met 39 25 InsMet 348 163 151 44 29 54 510 92 222 (75%) (55%) 1167 (48%) 96 945 (78%) 21 459 20 16 14 22 326 AATsc AATsc 506 AATsc 756 306 Met AATsc InsMet InsMet Met B Genes Up-regulated with Metformin and Ink Genes Down-regulated with Metformin and Ink in WT but not in Tsc2 or AA:Tsc2 in WT but not in Tsc2 or AA:Tsc2 GO Biological Processes

-log(p-value) -log(p-value) -log(p-value) -log(p-value) 0 1 2 3 4 5 0 2 4 6 8 0 1 2 3 4 0.0 0.5 1.0 1.5 2.0 2.5 Neg reg of transcription pos reg of protein phosphorylation Cellular response to interferon-beta cellular amino acid biosynthetic process N-acetylneuraminate catabolic process pos reg of cell migration Defense response to virus cell adhesion Neg reg of TOR signaling cellular response to hydrogen peroxide pos reg of ERK1/2 cascade autophagy SMAD protein signal transduction Neg reg of DNA binding response to hypoxia neg reg of insulin receptor signaling pathway protein phosphorylation Carbohydrate metabolic process carbohydrate metabolic process neg reg of protein kinase activity sphingolipid metabolic process reg of DNA binding transcription factor Lipid metabolic process neg reg of MAP kinase activity Response to follicle stimulating hormone lipid metabollic process angiogenesis peptidyl-serine phosphorylation response to glucose KEGG Pathways

-log(p-value) -log(p-value) -log(p-value) -log(p-value) 0.0 0.5 1.0 1.5 2.0 2.5 0 1 2 3 4 0.0 0.5 1.0 1.5 2.0 0.0 0.5 1.0 1.5 2.0 2.5 Osteoclast differentiation Amino sugar and nucleotide sugar metabolism Metabolic pathways HTLV-1 infection Lysosome bile secretion MAPK signaling pathway Axon guidance Protein processing in ER insulin signaling pathway Glucagon signaling pathway thryroid hormone synthesis TNF signalin pathway biosynthesis of amino acid Insulin resistance C Up-regulated mRNAs Down-regulated mRNAs WT 812 Met/Ink WT WT 544 Ampk WT 371 InsMet/InsInk 771 Met/Ink InsMet/InsInk Ampk 222 Ampk Met InsMet 29 Ampk 143 45 85 (78%) Met 75 110 17 312 InsMet (48%) 68 756 94 417 40 (35%) 18 (68%) 42 24 661 32 442 527 394 1167 AATsc 590 AATsc AATsc AATsc Met InsMet Met InsMet D Genes Up-regulated with Metformin and Ink Genes Down-regulated with Metformin and Ink in WT but not in AA:Tsc2 or Ampk in WT but not in AA:Tsc2 or Ampk GO Biological Processes

-log(p-value) -log(p-value) -log(p-value) -log(p-value) 0 1 2 0 2 4 6 0 2 4 6 8 0 1 2 3 4 cell adhesion neg. reg. of transcription from RNA polII promoter pos reg of protein phosphorylation defense response to virus intracellular signal transduction pos. reg. of protein phosphorylation pos reg of ERK1/2 cascade cellular response to interferon beta pos. reg. of macroautophagy regulation of transcription, DNA templated pos. reg. of viral genome replication pos. reg. of cell migration lipid metabolic process N-acetylneuraminate catabolic process DNA replication immune system process oxidation-reduction process cellular response to hydrogen peroxide negative regulation of TOR signaling apoptotic process negative regulation of DNA binding carbohydrate metabolic process non-canonical WNT signaling pathway sphingolipid metabolic process SMAD protein signal transduction protein phosphorylation HIF1a signaling pathway KEGG Pathways

-log(p-value) -log(p-value) -log(p-value) -log(p-value) 0 1 2 3 0.0 0.5 1.0 1.5 0 1 2 3 4 bile secretion 0 1 2 3 4 metabolic pathway morphine addiction amino sugar and nucleotide sugar metabolism lysosome protein processig in ER estrogen signaling pathway MAPK signaling pathway signaling pathways regulating pluripotency of stem cells HIF-1 signaling pathway HIF-1 signaling pathway microRNAs in cancer osteoclast differentiation retrograde endocannabinoid signaling bile secretion HTLV-1 infection pathways in cancer axon guidance HIF-1 signaling pathway MAPK signaling pathway AMPK signaling pathway central carbon metabolism in cancer melanogenesis toxoplasmosis amino sugar and nucleotide sugar metabolism type II diabetes mellitus Supplemental Figure S6 Supplemental Figure S6 A) Venn diagram depicting overlap between genes identified as being both Metformin and INK dependent and genes regulated in Tsc2-null (T) RaptorAA;Tsc2-null (AATsc) hepatocytes upon metformin in the absence or presence of insulin as described in Figure 1D. B) GO Term and KEGG pathway analysis of Tsc- and AATsc-dependent genes up-regulated (left, 348 genes /222 genes) or down-regulated (right, 151 genes /163 genes) by metformin and INK by a fold change of at least 1.5 in wild-type primary hepatocytes and a fold change of less than 1.5 in Tsc and AATsc primary hepatocytes in presence or absence of insulin as described in Figure 1D. Identified using DAVID software C) Venn diagram depicting overlap between genes identified as being both Metformin and INK dependent and genes regulated in RaptorAA;Tsc2-null (AATsc) and Ampk-null (Ampk) hepatocytes upon metformin in the absence or presence of insulin as described in Figure 1D. D) GO Term and KEGG pathway analysis of AATsc- and AMPK-dependent genes up-regulated (left, 312 genes /222 genes) or down-regulated (right, 110 genes /149 genes) by metformin and INK by a fold change of at least 1.5 in wild-type primary hepatocytes and a fold change of less than 1.5 in AATsc and Ampk primary hepatocytes in presence or absence of insulin as described in Figure 1D. Identified using DAVID software 0.5 InsMet vs Ins InsInk vs Ins 2 ** A InsInk vs Ins 0.0 WT AA T AA;TAmpk WT ** InsMet vs Ins Ankrd37 0 WT AA T AA;TAmpk WT -0.5 Serpine1 Fasn Pdk1 Elovl6 -1.0 Ak4 -2 Elovl1 Egln1 Agpat5 -1.5

Ero1l Acaca Fold Change Log2

Met Gpam genes) target (SREBP -2.0 (HIF genes) target Vhl Fold Change Log2 -4 Acly P4ha1 SREBP Targets SREBP HIF Targets HIF Log2 Fold Change -2.5 Cul2 T Tgfa -6 WT AA AA;TAmpk T WT INK WT AA -1 1 AA;TAmpk Log2 Fold Change WT INK + Ins + Ins InsInk vs Ins -1.5 1.5 C InsMet vs Ins 2 *** Met vs UT INK vs UT WT AA T AA;TAmpk WT *** B Atp6v0d2 **** *** WT AA T AA;TAmpk WT **** Dpp7 **** 2 NS**** * Neu1 1 Atp6v0d2 **** Vps18 **** Dpp7 **** Ctns Neu1 Atp6v1b2 Vps18 1 Vps11 Ctns Ctsa 0

Atp6v1b2 Fold Change Log2

Atg16l2 (TFEB genes) target Vps11 Sqstm1 Ctsa 0 Atg16l2 Slc6a11

Log2 Fold Change Log2 Clcn7 -1 Sqstm1 (TFEB genes) target Atp6v1a T Slc6a11 WT AA Atp6v1e1 AA;T Clcn7 Ampk -1 Clcn6 WT INK T

Atp6v1a Targets TFEB WT AA Naga + Ins Atp6v1e1 AA;TAmpk WT INK Cln3 Clcn6 Atg14 TFEB Targets TFEB Naga Log2 Fold Change Cln3 Atp6v1g1 Log2 Fold Change Ctsz Atg14 Atg10 Atp6v1g1 -1 1 Ctsz Mcoln1 Atg10 -1 1 Mcoln1

201 128 201 - - -2206- D 128 InsMet vs Ins InsInk vs Ins - RapamycinRapamycinMK 3 ** E Metformin WT AA T AA;TAmpk WT ** Ppp1r3b 2 2mM AZD8055 Serpine1 ** Untreated2mM DMSO0.1mM1mM Ink Ink1mM AZD805550nM100nM 25mM 10mM 99150mM 100mM S3I S3I Rtn4rl1 * Il22ra1 1 P-S727 STAT3 Ifnar1 ** Socs3 P-Y705 STAT3 Spred1 0 Spred2

Il1r1 Fold Change Log2 -1 STAT3 Socs5 (STAT3 genes) target Bcl2 Il17rb -2 P-AMPK Sac3d1 T WT AA Ifi47 AA;TAmpk Pias2 WT INK AMPK Ifit1 + Ins STAT3 Targets STAT3 Jak2 P-S792 RAPTOR Ptpn11 Sos1 Log2 Fold Change Cxcl12 RAPTOR Ccnd3 Bcl3 -1 1 P-S6K Ifi44 Il13ra1 S6K

P-S235/S236 S6 S6

ACTIN

Supplemental Figure S7 A) Heatmap of fold change for genes from Figure 5A involved in HIF and SREBP signaling upon metformin or INK treatment in the presence of 1nM insulin 15’ pre-treatment as described in Figure 1D. (Right) Quantification of fold change for genes (identified with fold change greater than 1.5 in wild-type in absence of insulin, Figure 5A). Box Plot with bars denoting min-to-max. Kolmogorov-Smirnov test comparing to wild-type treated with metformin in presence of insulin. B-C) Heatmap of fold change for genes involved in TFEB signaling upon metformin or INK treatment in the (B) absence or (C) presence of insulin as described in Figure 1D. (Right) Quantification of fold change for genes (identified with fold change greater than 1.5 in wild-type in absence of insulin, (B)). Box Plot with bars denoting min-to-max. Kolmogorov- Smirnov test comparing to wild-type treated with metformin in presence of insulin. D) Heatmap of fold change for genes involved in STAT3 signaling upon metformin or INK in the presence of 1nM Insulin 15’ pre-treatment. Genes with fold change >1.5 denoted in black; >1.2 denoted in blue (Right) Quantification of fold change of genes (identified with fold change greater than 1.2 in wild-type in absence of insulin (Figure 5C)). Kolmogorov- Smirnov test comparing to wild-type treated with metformin in presence of insulin. E) Immunoblot analysis of wild-type primary hepatocytes treated for 2 hours with drugs inhibiting mTOR (INK128, AZD8055, Rapamycin), AKT (MK02206), STAT3 (S31-201) or activating AMPK (991). A C KEGG Pathways -log(p-value) -log(p-value) 0 2 4 6 8 0 1 2 3 4 ECM-receptor interaction WT AA T AA;T AMPK RNA polymerase PI3K-Akt signaling pathway RNA transport Metformin Focal adhesion - + - + - + - + - + Hepatitis C FC gamma R-mediated phagocytosis Signaling pathways regulating Osteoclast differentiation pluripotency of stem cells Leukocyte transendothelial migration Pyrimidine metabolism Staphylococcous aureus infection TNF signaling pathway Hematopoietic cell lineage

D Met vs Saline

WT AA T AA;T AMPK NS Ctss*** Ctsk 1.5 *** NS Pik3cg Slc12a4 * **** Gabarapl1 1.0 Hps4 **** Arsa **** Map1lc3b 0.5 Atg14 Atp6vod2 0.0 Atp6V0c Ctsc Log2 Fold Change Log2

Npc1* (TFEB genes) target -0.5 Asah1 Slc44a2* Atp13a2 -1.0 Ulk1 T WT AA Cd63 AA;TAmpk

TFEB Targets TFEB Hexb Naga Atp6v1e1 Atg2a Cln3 Hps1 Npc2 Log2 Fold Change Hgsnat Fold change >1.5 in WT Ctns -1 1 Ctsa

* B * NS Up-regulated mRNAs Down-regulated mRNAs Met vs Saline 1 *** (FC>1.5 FDR<0.05) (FC>1.5 FDR<0.05) WT AA T AA;T AMPK 0 Fasn 168 Elovl6 AA 92 AA Pcsk9 Scd1 -1 Met vs Sal WT Met vs Sal Mvk WT 19 23 Idi1 1 1 Hmgcs1

Log2 Fold Change Log2 -2 Met vs Sal Met vs Sal Elovl1* 2 genes) target (SREBP 1 14 Me1 SREBP Targets SREBP 557 368 -3 Ampk Ampk T WT AA Met vs Sal Met vs Sal AA;TAmpk

Supplemental Figure S8 A) Heatmap of genes regulated by metformin in wild-type livers with a fold change greater than 1.5 across all genotypes. Mice on high fat diet were fasted overnight, refed for 1 hour and treated with saline or 200mpk metformin by I.P. for four hours (N=2-3). B) Venn Diagram of genes up-regulated (top left) or down-regulated (top right) by at least 1.5 fold with an FDR<0.05 in wildtype, RaptorAA, and Ampk-null livers upon metformin as described in (A). C) KEGG Pathway analysis of AMPK-dependent genes up-regulated (left, red) or down-regulated (right, green) by at least 1.5 fold with an FDR<0.05 in wild-type livers upon metformin as described in (A). D) Heatmap of fold change for genes involved SREBP signaling and TFEB signaling upon metformin treatment compared to saline treated as described in (A). Genes with fold change >1.5 in wildtype livers denoted in black; FC>1.2 denoted in blue. Asterisk represent FDR. (Right) Quantification of fold change for genes identified with fold change greater than 1.2 in wildtype liver upon metformin treatment. Box Plot with bars denoting min-to-max. Kolmogorov-Smirnov test comparing to wildtype treated with metformin. WT WT GeneSymbol Motif Function Met vs UT INK vs UT References Hamp2 -1.1247 -2.4808 Rps10 TOP Translation -1.3488 -2.0381 1,3 Rpl38 TOP Translation -1.3671 -1.9628 1,3 Rpl32 TOP/PRTE Translation -1.0910 -1.7997 1,2,3 Rps10-ps1 -1.1644 -1.6941 Rps16 TOP Translation -1.6188 -1.6588 1,3 Ttc36 -0.9057 -1.5978 Rps13-ps2 -1.1840 -1.5234 Rpl11 TOP Translation -1.0139 -1.5138 2,3 Rpl13 TOP/PRTE Translation -0.9049 -1.5013 2,3 Rps20 TOP/PRTE Translation -0.8579 -1.4466 1,2,3 Gm6030 -0.9500 -1.4089 Rpl35a TOP Translation -0.8268 -1.3958 3 H2afj -0.7100 -1.3339 Rps19 TOP Translation -1.0375 -1.3208 1,3 Rps14 TOP Translation -1.0537 -1.2995 1,3 Ndufb2 Ox Phos -0.7794 -1.2860 Gm11478 -0.8438 -1.2759 Rps24 TOP Translation -0.8699 -1.2559 1,3 Rpl37a TOP/PRTE Translation -0.6773 -1.2285 1,2,3 Krt18 -0.7167 -1.2269 Pxmp2 -0.7820 -1.2261 Atp5e Ox Phos -0.9602 -1.2238 Rplp1 TOP Translation -0.6211 -1.2150 1,3 Rpl31-ps8 -0.8598 -1.2078 Ndufb9 Ox Phos -0.7838 -1.1798 Crybb3 -0.8220 -1.1752 Pgls TOP/PRTE Ox Phos -0.6455 -1.1374 2 Gpx4-ps2 -1.2358 -1.1307 Atp5mpl -0.9552 -1.1238 Endog Mitochondrial -0.7513 -1.1041 Apoc4 -0.8299 -1.0855 Rpl36-ps12 -1.0195 -1.0669 Etfb Ox Phos -0.6479 -1.0508 Gm10275 -1.0752 -1.0315 Wdr89 -0.7936 -1.0167 Rpl37 TOP/PRTE Translation -0.6358 -0.9938 1,2,3 Pfdn5 TOP -0.8393 -0.9850 2,3 Apoa2 -0.6464 -0.9811 Eef1d TOP/PRTE Translation -0.7855 -0.9764 1,2,3 Cox4i1 Ox Phos -0.6581 -0.9322 Fam213b -1.2913 -0.9219 Psmd4 -0.7642 -0.9202 Hspa8 TOP/PRTE Translation/Ox Phos -0.9494 -0.8955 2 Uqcrq Ox Phos -0.6413 -0.8832 2410015M20Rik Ox Phos -0.7735 -0.8818 Ndufa11 Ox Phos -0.9387 -0.8156 4833422C13Rik -0.7342 -0.7834 Eif2b4 TOP Translation -0.6122 -0.7685 1 Mgst3 -0.7635 -0.7161 Mterf1a -1.0961 -0.6935 Cycs Ox Phos -0.9136 -0.6816 Gm13436 -0.6759 -0.6601 Lhpp Ox Phos -0.6233 -0.6337 Blvrb -0.8007 -0.6319 Rpl34 TOP/PRTE Translation -0.8329 -0.6309 1,2,3 Apoc1 -0.7485 -0.6278 Gm6204 -1.1740 -0.6196 Zfp449 -0.9879 -0.6136 Ndufs8 Ox Phos -0.7482 -0.6039 Supplemental Table S2 Mrpl46 TOP Translation/Mito -0.7299 -0.5952 1 82 genes identified as having decreased Ppp1r35 -0.8405 -0.5857 translation efficiency (FC>1.5 [log2FC<-0.58]) Eif3d TOP Translation -0.6102 -0.5541 1 Acot2 Ox Phos -0.7817 -0.5496 upon metformin treatment in all three Hddc2 -1.2490 -0.5189 polysome profiling experiments. Genes are Naa10 -0.7854 -0.4810 Psmb3 -0.7376 -0.4800 annotated for classification with TOP or PRTE Ndufab1 Ox Phos -0.6167 -0.4663 motif, as previously published#, or with known Mrps9 TOP Translation/Mito -0.7935 -0.3862 1 roles in translation, oxidative phosphorylation Mospd1 -0.7628 -0.3791 Utp3 Translation -0.7683 -0.3581 (Ox Phos) and mitochondria (mito). Thg1l Translation/Mito -0.7085 -0.3086 Green shading signifies value of Log2FC 0 8485 0 2818 Rttn - . - . Red line signifies FC>1.5 upon INK treatment Tbkbp1 -1.2623 -0.1834 1110059E24Rik -0.7180 -0.0708 Ptar1 -0.8568 -0.0585 # Snapc3 -0.9005 0.0902 References: Cd52 -0.7987 0.1035 1) Thoreen, et al, 2012; Ciao1 -0.6536 0.1535 2) Hsieh et al, 2012; Ccdc125 -1.1099 0.6250 Cbwd1 -0.9519 0.7803 3) Philippe, et al, 2020 Supplemental Materials and Methods

Animals: Raptor mice were generated using CRISPR in utero. In brief, gRNAs targeting Raptor at serines 722 and 792 were 5’TCCGTTCAGTGAGCTCCTATGGG’3 and 5’CGGCGAGGACTCACCTATGAGGG’3, respectively. Serine-to-alanine mutations as well as synonymous silent mutations to mutate PAM sites and generate primer-specific sequence for genotyping were generated by homologous recombination from a dsDNA oligo (IDT, Supplemental Fig. S2). In utero injection of CRISPR components including Cas9 mRNA (Thermo Fisher, A25640) into C57/Bl6 zygotes was preformed as previously described(Yang et al. 2014). Resulting pups were genotyped and DNA sequenced to confirm presence of the intact alanine mutations. Double alanine mutant mice were generated by breeding S792A mutant mice to homozygosity and subsequent reinjection of Serine722-Alanine CRISPR components. Genotyping of 792A and 722A alleles was performed with primers: 722Fwd: 5’CAAAGCATGCCTCCTTTCCG’3, 722Rev: 5’GCATAAACTGGTGGGCCTCT’3, 792Fwd: 5’TGACCAGCTGTTCTTGAGCC’3, 792Rev: 5’ACCAAACTAAGGCGTGTGCT’3. The resulting PCR products were then restriction digested with SacI restriction enzyme and resolved on an agarose gel to distinguish digested fragments, with wild-type alleles generating two bands and mutant alleles only generating one band. Positive double mutant pups were bred and crossed to Tsc2 floxed mice and Albumin-Cre or Albumin-CreER mice (Imai et al. 2000). Tsc2 floxed mice on 129sv/C57Bl6 mixed background were described previously (Hernandez et al. 2007), obtained from Jackson Laboratory (027458), and backcrossed at least two times onto a C57Bl6 background. Ampkα1(Prkaa1)fl/fl and Ampkα2(Prkaa2)fl/fl mice on C57Bl6 were previously described (Hasenour et al. 2014). To create mice with liver-specific deletion of Tsc2 or Ampk, mice were crossed to Albumin-Cre (Jackson Laboratory 003574) or Albumin-CreER mice. Wildtype controls consisted of littermate Tsc2fl/fl mice without Albumin-Cre or Albumin-CreER. The final cohorts were generated by tamoxifen (1.5mg) treatment every other day for a total of 3 i.p. injections. Primary hepatocyte isolation was carried out approximately 10-14 days post-tamoxifen injection. PCR genotyping for Tsc2fl, Ampka1fl, Ampka2fl, Alb-CreER, and Alb-Cre alleles was performed as described on JAX website. Mice were fed a normal chow diet (9% kcal from fat) prior to hepatocyte isolation. For fasting- refeeding studies, mice were fed a high fat diet (45% kcal from fat) (research diets, D12451) for at least 8 weeks prior to the experiment. Mice were fasted overnight and either euthanized with high-dose avertin or refed high fat diet for 3-5 hours before euthanasia. Vehicle (0.9% saline) or 250mg/kg metformin (Sigma, PHR1084) reconstituted in 0.9% saline was administered via intraperitoneal injection 2-4 hours prior to euthanasia with high dose avertin. Liver tissue was harvested immediately and flash frozen in liquid nitrogen. All animal procedures were approved by the Salk Institute’s Institutional Animal Care and Use Committee.

Primary Hepatocytes: Primary mouse hepatocytes were isolated as previously described (Garcia et al. 2019) from 8-16 week old mice by portal vein perfusion with collagenase (Sigma, C5138). Hepatocytes were plated at 2x106

2 cells per p60 or 5x106 cells per p100 plate in DMEM (Cellgro, MT 10-017-CV) containing 5% FBS, and allowed to adhere for 3-4h on TPP plates (Light Labs System, TC1015). Following adhesion, cells were washed with DMEM and incubated overnight in serum-free DMEM prior to indicated treatments.

Protein Extraction and Immunoblotting Liver tissue lysates were generated from 50-100 mg pieces of frozen liver tissue homogenized in CST lysis buffer (20mM Tris-HCl pH 7.5, 150 mM NaCl, 1 mM EDTA, 1 mM EGTA, 50 mM sodium fluoride, 1% Triton, 2.5 mM sodium pyrophosphate, 1 mM beta-glycerophosphate, 1 mM Na3VO4, 10 nM Calyculin A) supplemented with protease inhibitors. Hepatocytes were washed with ice-cold PBS and lysed directly on plates using CST lysis buffer. Primary hepatocytes or liver tissue homogenates were lysed on ice for 10 min with shaking in lysis buffer. Lysates were centrifuged at 16,000 x g for 10 min at 4°C. Protein concentration was determined using Pierce™ BCA protein assay kit (Thermo Scientific, #23225). Lysates were resolved on 8%–12% SDS-PAGE gels, depending on the experiment, and transferred to PVDF membranes for immunoblotting. The following primary antibodies obtained from Cell Signaling Technology, unless otherwise noted, were used for immunoblotting: P-AMPK-T172 (#2535), AMPK (#2532), TSC2 (#3612), P-S1384-TSC2 (#5584), S6K1 (#9202), P-S6K1-T389 (#9234), Raptor (#2280), P-Raptor-S792 (#2083) or -S722 (Millipore, 09-104), P-4EBP1- S65 (#9451), 4EBP1 (#9452), S6 (#2217), P-S6-S235/236 (#2211), P-S6-S240/S244 (#2215), P-4EBP1-T37/46 (#2855), P-S727-Stat3 (#9134), P-Y705-Stat3 (#9131), EIF4E (#9742), P-Y727-Stat1 (#8826), STAT1 (#14994), STAT3 (#9139), P-ACC (#11818), ACC (#3662), DEPTOR (Novus, NBP1-49674), TFE3 (#14779), P-S555 Ulk1 (#5869), P-S757 Ulk1 (#6888), Ulk1 (#8054), and β-ACTIN (Sigma, A5441). Horseradish peroxidase-conjugated secondary antibodies were anti-rabbit IgG (Millipore, #AP132P) and anti-mouse IgG (Millipore, #AP124P).

RNA Isolation and Sequencing Primary hepatocytes and liver were treated as described. Liver tissue RNA was generated from 50-100 mg pieces of frozen liver tissue homogenized in Qiazol. Cells were collected from the plate following 5 hour treatment directly into Qiazol and snap frozen. RNA was isolated using the RNeasy Lipid tissue mini kit, including a DNase treatment (Qiagen). RNA was reverse transcribed using SuperScript III (Invitrogen #18080-051) and qRT-PCR was performed on a Bio-Rad CFX384 using gene-specific primers (below) and SYBR Green (Applied Biosystmes #4309155). RNA integrity (RIN) numbers were determined using the Agilent TapeStation prior to library preparation. mRNA-seq libraries were prepared using the TruSeq RNA library preparation kit (version 2), according to the manufacturers instructions (Illumina). Libraries were quantified, pooled, and sequenced by single-end 50 base pairs using the Illumina HiSeq 2500 or NovsSeq SP platform at the Salk Next-Generation Sequencing Core. Raw sequencing data were demulitplexed and converted in the FASTQ files using CASAVA (version 1.8.2). Libraries were sequenced at an average depth of 20 million reads per sample. mTBP qRT-PCR Fwd ccttgtacccttcaccaatgac mTBP qRT-PCR Rev acagccaagattcacggtaga BCL3 qRT-PCR Fwd-1 CCGGAGGCCCTTTACTACCA BCL3 qRT-PCR Rev-1 GGAGTAGGGGTGAGTAGGCAG

3 IL22RA1 qRT-PCR Fwd-1 ATGAAGACACTACTGACCATCCT IL22RA1 qRT-PCR Rev-1 CAGCCACTTTCTCTCTCCGT mRtn4rl1 qRT-PCR Fwd CTGCCAGGCACACAACTTTG mRtn4rl1 qRT-PCR Rev TGTTGGAGTAGATCCAGAGGG IFIT1 qRT-PCR Fwd-1 CTGAGATGTCACTTCACATGGAA IFIT1 qRT-PCR Rev-1 GTGCATCCCCAATGGGTTCT mSac3d1 qRT-PCR Fwd GCGCACAGTGAAGGAGTACAG mSac3d1 qRT-PCR Rev AGATAACGCACGGTGGCTAAG mSpred1 qRT-PCR Fwd GAGATGACTCAAGTGGTGGATG mSpred1 qRT-PCR Rev TCTGAAAGGTAAGGCCAAACTTC

Protein Synthesis and Polysome Profiling For global protein synthesis analysis, we used the sunset assay as previously described (Schmidt et al. 2009). In brief, primary hepatocytes were isolated (as described above), were pre-treated with or without insulin for 15’ and then treated with metformin or INK-128 for 1 hour 50min. Cells were then treated with puromycin (10µg/ml) for 10’ before cells were washed in PBS containing cyclohexamide (CHX, 100µg/ml) and lysed in CST lysis buffer containing protease inhibitors and CHX. Protein was quantified, resolved on a 8% gel, and immunoblotted with anti-puromycin antibody (Millipore, MABE343). Puromycin incorporation was quantified with ImageJ (NIH) and normalized to control. For polysome profiling, primary hepatocytes were treated as above for 2 hours prior to collection with cycloheximide (100µg/ml). Cells were collected in PBS with CHX, pelleted at 200xg at 4C for 5 minutes, and pellet snap frozen. For lysate preparation, ~10x10^6 primary hepatocytes were prepared. Cells were lysed by trituration through a 27 gauge needle in 400L polysome lysis buffer (20mM Tris-

HCl pH7.4, 150mM NaCl, 5mM MgCl2) with 1x protease inhibitor cocktail (EMD Millipore), CHX (100µg/ml), 1mM DTT, 25U/mL DNase (Turbo DNase, Thermo Fisher), 20 U/mL RNase inhibitor (RNaseOut, Thermo Fisher), 1% Triton X, and incubated on ice for 15 min. Lysates were clarified by centrifugation at 17,500xg at 4C for 5-10 min. ~10% was reserved for inputs and the remainder used for fractionation. For fractionation, a 14mL 10-50% (w/v) sucrose gradient was prepared in polysome buffer. Samples were loaded on the sucrose gradient and centrifuged in a swinging bucket rotor at 35,000xg at 4C for 3 hours. Fractions were collected from the top and UV absorbance monitored using a Gradient Station (BioCamp) equipped with ECONO UV monitor (BioRad). Fractions (500µL each) were collected using a FC203B (Gilson) fraction collector. Fractions containing polysomes were pooled. Total RNA from the inputs and the polysome pools were extracted in Trizol-LS (Thermo Fisher) and purified with Direct-zol RNA kits (Zymo). RNA sequencing libraries were generated using the TrueSeq standard mRNA kit (Illumina). Libraries were pooled and sequenced using the Illumina HiSeq 2500 platform at the Salk Next Generation Sequencing Core. Raw sequencing data were demultiplexed and converted in the FASTQ files using CASAVA (version 1.8.2). Libraries were sequenced at an average depth of 30 million reads per sample. Polysome isolated RNA was normalized to inputs to obtain translation efficiency. Two experiments in the presence of insulin and one experiment in the absence of insulin were performed and data integrated to obtain genes with greatest change in translation efficiency.

4 For m7GTP pull-down, primary hepatocytes were treated as above for 2 hours prior to lysis on ice for 10 min in pull-down buffer (10mM Hepes, pH 7.4, 100mM NaCl, 5mM MgCl2, 0.5% NP40, 2mM DTT, protease inhibitor), vortexed, and centrifuged at 16,000 x g for 10 min. γ-Aminophenyl- m7GTP agarose beads (Jena Bioscience, AC-155) were washed 3X in wash buffer (lysis buffer with 1 mM MgCl2 instead of 5mM), blocked in 1% BSA in wash buffer for 30 min, washed 2x in wash buffer, and resuspended in an equal volume. 30µL of bead slurry was added to 400µg of protein lysate per sample and rotated for 1h at 4ºC. Beads were washed 3x in wash buffer, resuspended in 2x Laemli buffer, boiled and separated by SDS-PAGE.

Polysome Profiling Analysis

First, adapter trimming was performed with cutadapt (v1.14). Next, reads were mapped with STAR (v2.4.0i) against a database of repetitive elements, with mapping reads discarded from further analysis. Remaining reads were then mapped to the mouse genome (mm10) with STAR (v2.4.0i), and stranded reads mapping to GENCODE (vM20) genes were quantified with featureCounts (subread-1.6.4). Mitochondrial genes were discarded, and only genes with at least 0.5 reads per million across all datasets were kept for further analysis. Differential expression was quantified with edgeR (v3.26.8) with dispersion = 0.06 estimated from the subset of experiments with multiple replicates

Bioinformatics Analyses

Raw RNA sequencing reads in FASTQ files were quality-tested using FASTQC (v0.11.8) (Andrews 2010) and mapped to the mouse reference genome (mm10) with STAR (v2.5.3a) aligner with default parameters (Dobin et al. 2012). Raw or FPKM (fragments per kilobase per million mapped reads) gene expression levels were quantified across all the exons of RefSeq genes with analyzeRepeats.pl in HOMER (v4.11.1) (Heinz et al. 2010). Differential expression analysis was performed with raw gene counts using R package, edgeR (v3.26.7) (Robinson et al. 2010), using replicates to compute within- group dispersion and correcting for batch effects. Genes with false discovery rate (FDR) < 0.05 and an absolute fold-change (FC) >= 1.5 were identified as significantly different when comparing two conditions. FPKM normalized counts were log transformed, filtered, scaled, and centered prior to clustering and heatmap generation with Cluster3 (de Hoon et al. 2004), and visualized with JavaTreeView (Saldanha 2004). GSEA was carried out with the GenePattern interface, https://genepattern.broadinstitute.org) using preranked lists generated from FDR values, setting gene set permutations to 1000 and using the Hallmark collection in MSigDB version5.0. GO Term and KEGG Pathway analysis were performed with David: http://david.ncifcrf.gov/. “STAT3 targets” were identified from GSEA genelists (e.g. Hallmark_IL6_Jak_STAT3_Signaling; Dauer_STAT3_TARGETS) and CHEA Transcription factor targets (Enrichr) for STAT3-dependent genes (Lachmann et al. 2010). Area- proportional Venn diagrams were plotted using BioVenn (Hulsen et al. 2008). Enrichr: http://amp.pharm.mssm.edu/Enrichr.

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