A B C * 2 2.5 Aβ 1.8 n.s Aβ sAPPβ * Aβ 1.6 sAPPβ 2 n.s * 1.2 1.4 * 1 1.2 1.5 n.s n.s n.s 0.8 1 n.s 0.8 1 n.s 0.6 0.6 0.4 0.4 0.5

Normalized ECL Counts Normalized ECL 0.2

0.2 *** Counts Normalized ECL

Normalized ECL Counts Normalized ECL *** 0 0 0 *** MEDGC APP BACE1 Pen2 STX 7 VAMP-7 VAMP-5 PCDNA TFEB TFEB dNLS CONTROL 50uM 100uM Overexpression Chloroquine siRNA

1.2 D 1.2 E F AAV-TFEB injection into the brain cortical regions of WT mice

1 1 * 0.8 0.8 *

0.6 0.6

0.4 0.4 Normalized ECL counts Normalized ECL Normalized ECL counts Normalized ECL 0.2 0.2

0 0 PCDNA TFEB S211A/ PCDNA TFE3 S142A G H I

1.2 Aβ x-40 1.2 Aβ x-42 1.2 n.s 1 1

1 0.8 ** 0.8 *** 0.8 0.6 0.6 0.6 Values ed E CL

0.4 0.4 0.4 Normalized ECL counts Normalized ECL 0.2 0.2 0.2

Normali z *** 0 0 0 No CathepsinD+ CathepsinD+ Aß Heat inactivated Aß CathepsinD+ Aß GFP TFEB GFP TFEB

Mondal et al, SFig.1 1.4

1.2 Aß

1 sAPPß

0.8

0.6

0.4

0.2 Normalized ECL counts Normalized ECL 0 MEDGC EIF2AK1 APP BACE1 siRNA

Mondal et al., SFig.2 HeLa-swAPP cells A B 1.2 1.2 Aβ 1 1 sAPPβ Aβ 0.8 0.8 *

0.6 0.6 **

0.4 0.4

0.2 0.2 Normalized ECL counts Normalized ECL Normalized ECL counts Normalized ECL *** 0 0 MEDGC AKT1 AKT2 APP MEDGC AKT1 AKT2 APP siRNA siRNA

Mondal et al, SFig.3 B sAPPβ A Actin Synaptic Infection/ Endocytosis Lipid Metabolism Cytoskeleton Function

NRK NRK ROR1 HGS HGS STK35 WNK3 PLXNA3 CSK CSK MPP3 ROR1 RIPK3 CDK5 CDK5 STK11 CSK CSK PIP5K1B PIP5K1B CDK5 RYK EIF2AK1 CDK5 IRAK1

hsa04722:Neurotrophin signaling pathway hsa04910:Insulin/Nutrient pathway hsa04010:MAPK signaling pathway NRK STK32B CDC2L1 hsa04340:Hedgehog signaling pathway CNKSR1 VRK2 AKDH18A1 CMPK1 hsa04062:Chemokine signaling pathway NTRK2 CNKSR1 WNK3 BRSK1 HIPK2 hsa04620:Toll-like receptor signaling pathway CSK ROR1 CSK STK11 MPP3 EIF2AK1 hsa04070:Phosphatidylinositol signaling system RIPK3 CSK AURKA STRADB EIF2AK4 hsa04150:mTOR signaling pathway IRAK1 CDK5 hsa05200:Pathways in cancer Energy RNA processing/ hsa04360:Axon guidance NFB signaling Cancer Mental Health metabolism Translation hsa04920:Adipocytokine signaling pathway β hsa04370:VEGF signaling pathway APP hsa00230:Purine metabolism hsa00561:Glycerolipid metabolism hsa04916:Melanogenesis hsa04310:Wnt signaling pathway hsa04720:Long-term potentiation hsa00564:Glycerophospholipid metabolism Aβ hsa05020:Prion diseases hsa04810:Regulation of actin cytoskeleton Neurotrophin MAPK Hedgehog Synaptic PhosphatidylInositol hsa04110:Cell cycle Signaling Signaling Signaling Function Signaling hsa00983:Drug metabolism MAPKSP1 NTRK2 hsa00240:Pyrimidine metabolism IRAK2 NTRK2 TAOK2 TAOK2 PLXNA3 PIK3CG hsa00562:Inositol phosphate metabolism PIK3CG MAPK9 CSNK1A1 STK36 MAPK2 MAPK9 PTK2 DGKE hsa04020:Calcium signaling pathway IRAK1 MAPK7 CSNK1G1 CSNK1A1L MAP4K2 PRKACA PAK3 PIP5K1B hsa04140:Regulation of autophagy MAP2K2 CSK CSNK1D PRKACA STK3 MAPK7 PLXNA2 DGKH hsa00330:Arginine and proline metabolism PRKCD CALM1 GSK3B PRKACB MAP4K3 PRKACB GSK3B DGKI AKT1 AKT2 hsa00010:Glycolysis / Gluconeogenesis AKT1 MAP2K6 CDK5 PI4KB GSK3B MAP2K5 hsa04115:p53 signaling pathway MAP3K6 AKT2 CALM1 hsa04622:RIG-I-like receptor signaling pathway hsa04630:Jak-STAT signaling pathway hsa04740:Olfactory transduction NME2 PIK3CG AKT2 PIK3CG CSNK1A1 GK PIK3CG PRKACA PKM2 AKT1 MAPK9 AKT1 CSNK1A1L DGKE AKT1 PRKAA1 AK5 MAP2K2PRKACA AKT2 GSK3B ETNK2 AKT2 CSK DGUOK PHKG1 PRKAA1 STK11 MAPK9 DGKH GSK3A PRKCD AK7 GSK3B PRKACB ULK2 PRKACA DGKI GSK3B HCK PAPSS2 PRKC1 CALM1 PRKAA1 PRKACB PI4KB PRPS1 Insulin /Nutrient mTOR Chemokine Wnt Purine/ Signaling Signaling Signaling Signaling Glycerolipid/ Glycerophosholipid metabolism C

Mondal et al., SFig.4 AKT2 siRNA

1.4 oligo1 oligo2 oligo3 APP MedGC 1.2 Aβ 60 AKT2 1 GAPDH 0.8 38 kDa * 0.6 **

0.4 ** 0.2 *** *** *** Normalized ECL counts Normalized ECL *** 0 MED GC APP BACE1 PEN2 AKT2 AKT2 AKT2 AKT2 Oligo1 Oligo2 Oligo3 Pool

siRNA

Mondal et al., SFig.5 1.4 Aβ

1.2

1

0.8

0.6

0.4

0.2 Normalized ECL Counts Normalized ECL 0 MEDGC APP AKT1 AKT2 siRNA

Mondal et al, SFig.6 Mondal et al., SFig. 7 A B siRNA C Inhibitors MedGC APP BACE1 PEN2 AKT2 AKT1 DMSO C3 DAPT AKTinh1 Lo AKTinh 1 Hi AKT2inhII Lo AKTinhII Hi DMSO DAPT AKT inh

98 APP 98 APP

β-CTF β-CTF (C99) 14 14 -CTF -CTF (C83)

38 GAPDH 38 GAPDH kDa kDa

Mondal et al, SFig.8 C 1.4 1.4 B 1.4 Aβ n.s A Aβ Aβ sAPPβ n.s 1.2 n.s n.s 1.2 1.2 1 1 1 0.8 ** * 0.6 0.8 0.8 ** 0.4 ***

0.6 0.6 ** Normalized to DMSO 0.2 ****** ** 0.4 0 0.4 ****** *** *** DMSO AKT pathway AKT pathway AKT pathway inhibitor 10 M inhibitor 5 M inhibitor 1 M

Normalized ECL counts Normalized ECL 0.2 Normalized ECL counts Normalized ECL 0.2 *** *** 0 0 C3 DAPT DAPT PI-103 DMSO Torin-1 Torin-1 DMSO AZD2014 Everolimus KU-0063794 AKT-Inh. VIII AKT-Inh. Perifosine-Hi Perifosine-Lo Miltefosine-Hi Miltefosine-Lo AKT pathway Inhibitors PH-domain targeting AKT Inhibitors SH-SY5Y Cells expressing endogenous APP Aβ D 1.2 E 1.2 Aβ

1 1

0.8 0.8 *** 0.6 0.6 *** 0.4 0.4

0.2 0.2 *** Normalized ECL counts Normalized ECL Normalized ECL counts Normalized ECL *** 0 0 DMSO AKT Inhibitor DAPT DMSO AKT Inhibitor DAPT

Mondal et al, SFig.9 A

B

NESTIN/ DACH1 PHASE CONTRAST

SOX2 beta III-tubulin/ GFAP

Mondal et al, SFig.10 4000 Aβ 40 3500 * WT AKT2 -/- 3000 2500 60 2000 AKT2 1500 1000 Normalized ECL counts Normalized ECL 500 38 GAPDH 0 kDa WT AKT2 -/-

Mondal et al, SFig.11 Aβ A sAPPβ

Supernatants from Cells that Supernatants from Cells that overexpress APP do not overexpress APP

AKT inhibitor 1.2 1.4 DMSO

AKT pathway Inhibitor 1.2 1

1 0.8

0.8 0.6 0.6

0.4 DMSO Normalized ECL counts Normalized ECL Normalized ECL counts Normalized ECL 0.4 Aβ sAPPβ 0.2 AKT pathway Inhibitor 0.2

0 0 0 Hr 2 Hr 4 Hr 6 Hr 0 Hr 2 Hr 4 Hr 6 Hr

Time of incubation Time of incubation

B Aβ sAPPβ C

Supernatants from Cells that do not Cells that overexpress APP 1.4 Aβ overexpress APP 1.4 sAPPβ AKT inhibitor SEAP 1.2 1.2

1 1

0.8 0.8

0.6 0.6

0.4 0.4 Normalized ECL Counts Normalized ECL 0.2 0.2 Norm. Luminescence counts

0 0 DMSO AKTinh I Lo AKTinh I Hi AKT inh II Lo AKT inh II Hi MEDGC AKT1 AKT2 AKT inhibitor or DMSO treatment on cells that do not overexpress APP siRNA

Mondal et al., SFig.12 A B

1.4 * 1.2 DMSO 0.5 Insulin 1 Insulin 1 98 APP (Low exposure) 0.8

0.6 * * * * 98 APP (High exposure) 0.4

0.2 Normalized ECL counts Normalized ECL 0 38 GAPDH DMSO AKT pathway DMSO+Insulin AKT pathway inhibitor Inhibitor+Insulin kDa

C DMSO pathway inhibitor AKT pathway inhibitor AKT + Insulin DMSO + Insulin

98 APP

38 GAPDH

kDa

Mondal et al, SFig. 13 A B C

Insulin + DAPI TFEB Merge Amino acids - + - + AKT inhibitor - - + + AKT pathway inhibitor - + DMSO TFEB S211-P

Lamp2 TFEB GFP

Tubulin AKT Inhibitor AKT

mTOR *** Merge

+ DMSO AKT AKT- pathway Pathway inhibitor Inhibitor

Mondal et al. SFig.14

6

5

4 Control

3 AKT 2 pathway inhibitor Fold changes (mRNA) relative to GAPDH 1

0 Lamp1 Lamp2 CatD vATPase

Mondal et al, SFig.15 A B Insulin/IGF-1/Nutrient Signaling

Protein synthesis degradation (Autophagic/ Lysosomal)

Protein accumulation

In division competent cells, Failure to dilute through this leads to cell division division in postmitotic neurons (Cancer)

Protein aggregation (amyloid formation in Neurodegeneration) C

Nutrient+Insulin Starvation 10-5 10-10 Pa nPa 10-11

10-12 Pa 10-10 nM nM nPa 10-13

10-14

10-15 10-15 0123 4 5 0123 4 5 time (days) time (days)

105 1.2 P P 1 m 104 m Pa Pa nPa nPa 0.8 103 0.6 102 0.4 fold change fold change 1 10 0.2

100 0 0123 4 5 0123 4 5

Mondal et al, SFig.16 A B C CHO wt NPC1 null NPC1 null_hNPC1 CHO wt NPC1 null NPC1 null_hNPC1 CHO wt NPC1 null NPC1 null_hNPC1 LysoTracker ThioS Filipin DMSO DMSO DMSO AKT-pathway inhibitor AKT-pathway inhibitor AKT-pathway inhibitor

Mondal et al, SFig.17 A B

CHO wt NPC1 nullNPC1 null_hNPC1CHO wt NPC1 nullNPC1 null_hNPC1

Mondal et al, SFig.18 HeLa sw APP cells

Supernatant

Measure Aβ from the supernatant Seeding of Treatment 12h incubation Medium change BV2 microglia

Mondal et al, SFig.19 A No metabolic disorder Hyperlipidemia T2D Control AD

Synapsin-1, CD68, Iba1, DAPI

B AD Hyperlipidimia Synapsin-1, CD68, Iba1, DAPI

AD T2D Synapsin-1, CD68, Iba1, DAPI

Mondal et al, SFig.20 High Insulin/ Nutrient Low Insulin/ Nutrient conditions conditions

Amino Insulin APP BACE Insulin Amino acids γ-secretase acids

Insulin Receptor Insulin Receptor

PI3K PI3K

AKT AKT

Phospho- Aβ Phospho- TSC1/2 TSC1/2 TSC1/2 Early endosomes mTOR mTOR TSC1/2 Amino Amino TFEB-P/ acids acids TFE3 (Cytoplasm) TFEB/ TFE3 (nucleus)

More functional Lysosomes Less functional Lysosomes

More clearance of Less clearance of endosomally generated Aβ endosomally generated Aβ

High Aβ Low Aβ High amyloid levels Low amyloid levels

High Autophagolysosome Cholesterol ?

? Autophagosome

Cathepsin D

Golgi

Mondal et al, SFig.21 Reactome(Pathway(Enrichment(Analysis( Pathway(name( FDR( Signaling'by'Interleukins' 3.75E612' Diseases'of'signal'transduction' 1.72E610' Signaling'by'SCF6KIT' 2.59E610' Insulin'receptor'signalling'cascade' 3.04E610' Signaling'by'VEGF' 3.04E610' Signaling'by'EGFR' 3.04E610' PIP3'activates'AKT'signaling' 3.04E610' IRS6mediated'signalling' 3.04E610' Negative'regulation'of'the'PI3K/AKT'network' 3.04E610' Signaling'by'Insulin'receptor' 3.05E610' IRS6related'events'triggered'by'IGF1R' 3.05E610' PI3K/AKT'activation' 3.05E610' GAB1'signalosome' 3.05E610' IGF1R'signaling'cascade' 3.05E610' Signaling'by'Type'1'Insulin6like'Growth'Factor'1'Receptor'(IGF1R)' 3.19E610' Downstream'signal'transduction' 3.90E610' VEGFA6VEGFR2'Pathway' 4.34E610' Signaling'by'PDGF' 4.34E610' DAP12'signaling' 4.34E610' Downstream'signaling'events'of'B'Cell'Receptor'(BCR)' 6.34E610' PI5P,'PP2A'and'IER3'Regulate'PI3K/AKT'Signaling' 6.34E610' DAP12'interactions' 9.63E610' MAPK1/MAPK3'signaling' 1.22E609' PI3K/AKT'Signaling'in'Cancer' 1.22E609' ' ' ! ! ! ! ! Mondal!et!al,!STable!1! Legends to Supplementary Figures

Supplementary Figure 1: Replication and validation of Aβ clearance by lysosomes A. Cells treated with two different concentrations of Chloroquine and probed for Aβ (black bars) or sAPPβ levels (grey bars). *p<0.05. n.s indicates not significant. B. Aβ and sAPPβ levels after silencing of Vamp-7, Syntaxin-7 and Vamp-5 using specific siRNAs along with controls (MedGC scrambled oligos, APP, BACE1 and Pen-2 specific siRNAs). C. HeLa- sweAPP cells transfected with TFEB and TFEB dNLS and assayed for Aβ levels. PCDNA used as a negative control *p<.05. D. HeLa-sweAPP cells transfected with TFEB and TFEB S211A/S142A and assayed for Aβ levels. PCDNA used as a negative control *p<.05. E. HeLa- sweAPP cells transfected with TFE3 and assayed for Aβ levels. PCDNA used as a negative control *p<.05. F. Cortex of WT mice transduced with an AAV-TFEB (red, top row) and AAV- GFP vector (green, bottom row, used as negative control). Nuclei are stained with DAPI (blue). G. Aβ extracted from cortex of WT mice injected with AAV-TFEB and AAV-GFP and assayed for Aβ levels. **p<.005, ***<.0005. H. Cortical tissue from control, AAV-GFP- injected and AAV-TFEB-injected mice was analysed by western blot to confirm the expression of the transgenes as well as the increased lysosomal biogenesis (assessed by LAMP-1 expression) induced by TFEB overexpression. CathepsinD and LC3-II levels were also determined. GAPDH was used as a loading control. I. Recombinant human Cathepsin D (0.625ng/µl) was incubated with synthetic Aβ. Following the incubation electrochemiluminescence assay was performed to determine the amount of degraded Aβ. Synthetic Aβ without Cathepsin D treatment was used as a negative control. Heat inactivated Cathepsin D was also incubated with synthetic Aβ. Heat inactivated Cathepsin D did not degrade Aβ. Error bars indicate S.D.

Supplementary Figure 2: Silencing of EIF2AK1 reduces both sAPPβ and Aβ levels. HeLa- sweAPP cells were transfected with siRNA pools against EIF2AK1, APP or BACE1 (positive controls) or with a control-siRNA (MEDGC) and the conditioned media were assayed for Aβ (black) and sAPPβ (grey) by ECL-multiplex assay. Error bars indicate SEM.

Supplementary Figure 3: A. HeLa-sweAPP cells transfected with siRNA pools against AKT1, AKT2 and APP (positive control) along with a scrambled MEDGC oligo as negative control and assayed for Aβ (black) and sAPPβ (grey) levels. B. HeLa-sweAPP cells transfected with siRNA pool against AKT1, AKT2 and APP (positive control) along with scrambled MEDGC oligo as negative control and assayed for Aβ42 *p<.05,** <.005, ***<.0005. Error bars indicate S.D.

Supplementary Figure 4: A, B. Bioinformatics analysis of siRNA screen hits identifies various signalling networks. Insulin/nutrient signalling pathway are seen as one of the top clusters. C. Reactome pathway enrichment analysis of the aging-similar showed a prominent contribution from the IIN-AKT pathways.

Supplementary Figure 5: HeLa-sweAPP cells transfected with siRNA pool against APP, BACE1, PEN2, AKT2 or individual siRNA against AKT2 or MEDGC as negative control and probed for Aβ levels. AKT2 levels were analyzed using AKT2 specific antibodies. GAPDH was used as a protein loading control. Error bars indicate S:D.

Supplementary Figure 6: Silencing of AKT1 and AKT2 reduces Aβ levels in cell lysates. HeLa-sweAPP cells were transfected with siRNA pool against AKT1, AKT2 or APP (positive control) or with a control-siRNA (MEDGC) and lysates of transfected cells were assayed for Aβ by ECL-assay (Error bars indicate SEM).

Supplementary Figure 7: Silencing of AKT2 does not influence APP or BACE1 levels. HeLa-sweAPP cells were transfected with siRNA pool against AKT2 or APP (positive control) or with a control-siRNA (MEDGC) and lysates of transfected cells were immunoblotted against APP and BACE1. GAPDH was used as a protein loading control.

Supplementary Figure 8: A. HeLa-sweAPP cells treated with β-secretase inhibitor (C3), γ- secretase inhibitor (DAPT) and AKT inhibitors (AKT inh I, AKT inh II. Lo-1µM and Hi-10 µM) and probed for APP cleavage products. DAPT treatment leads to a specific accumulation of C-terminal fragments of APP, which is not seen when the cells are treated with AKT inhibitors, C3 or DMSO (negative control). B. RNAi silencing of AKT1, AKT2 and as controls scrambled (MedGC), APP, BACE1 or PEN2 were performed in HeLa-sweAPP cells and probed for APP cleavage products using the C-terminal antibody of APP. The γ-secretase subunit, PEN2 silencing leads to a specific accumulation of C-terminal fragments of APP, which is not seen when the cells are treated with AKT1 or AKT2 siRNAs. GAPDH is used as a loading control. C. HeLa-sweAPP cells transfected with C99-GFP plasmid were treated for 12 h with either AKT inhibitor VIII, DMSO (negative control) or DAPT, the γ-secretase inhibitor as positive control. Cell lysates were analysed by Western blot probed with anti-GFP antibody. AICD-GFP levels are not reduced upon AKT-inhibitor treatment. Alternatively, DAPT treatment reduced the formation of AICD-GFP but instead produces C83-GFP due to the µ-cleavage of C99-GFP. Error bars are S.D.

Supplementary Figure 9: A. HeLa-sweAPP cells treated with different AKT pathway inhibitors and assayed for Aβ levels. DMSO treatment was used as negative control. γ- Secretase inhibitor DAPT and β-secretase inhibitor C3 treatment were used as positive controls.*p<.05,** <.005, ***<.0005. B. HeLa-sweAPP cells treated with FDA approved AKT inhibitors (Miltefosine and Perifosine) using different concentrations (lo-10µM, and Hi- 25µM for Miltefosine and 50µM for Perifosine) and assayed for Aβ levels. C. HeLa-sweAPP cells treated with different concentrations of AKT pathway inhibitor and probed for Aβ (black bars) or sAPPβ (grey bars). DMSO was used as a negative control. D. SH-SY5Y cells treated with AKT inhibitor and assayed for Aβ levels. ***p<.0005. DMSO and DAPT treatment were used as negative and positive controls respectively. E. HeLa-sweAPP cells treated with AKT inhibitor and assayed for Aβ42 levels. DMSO and DAPT treatment were used as negative and positive controls respectively. ***p<.0001. Error bars are S.D.

Supplementary Figure 10: A. Skin fibroblasts were derived from a healthy donor and iPS cells were established using the reprogramming factors OCT4, SOX2, KLF4 and c-MYC. From iPS cells, neuro epithelial stem cells, a long-term, self-renewing neural stem cell population, were established. Terminal differentiation into neuronal cultures was initiated by growth factor withdrawal and neurons terminally differentiated for 4 weeks before applying compounds for Aβ measurements. The cartoon was produced using Servier Medical Art (www.servier.com). B. Human iPSC-derived neuro epithelial stem cells express the neural stem cell-associated transcription factors SOX2 and DACH1 as well as the intermediate filament NESTIN. IPSC-derived differentiated neuronal cultures mainly consist of neurons expressing beta III-tubulin and MAP2ab. A smaller fraction of GFAP-expressing astrocytes is also present in the cultures.

Supplementary Figure 11: Cortical extract of wild type (WT) mice or mice lacking AKT2 assayed for Aβ levels *p<.05. Westen blot image of cortical extracts shows the absence of AKT2 in AKT2-/- mice compared to WT mice. GAPDH was used as a loading control.

Supplementary Figure 12: A. Untransfected HeLa cells that do not overexpress APP were treated with AKT pathway inhibitor. Conditioned medium obtained from AKT pathway inhibited HeLa cells were mixed with conditioned medium from HeLa-sweAPP cells (cells that overexpress APP and have robust levels of Aβ and sAPPβ) for different time points and incubated at 37°C. The Aβ and sAPPβ levels that remained after incubation were measured using electrochemiluminescence detection and normalized to the values from DMSO treated conditions. B. Untransfected HeLa cells that do not overexpress APP and hence have no detectable Aβ and sAPPβ were treated with either AKT inh I or AKT inh II at two different concentrations (Lo-1µM and Hi-10µM) followed by replacement of medium with conditioned medium from HeLa-sweAPP cells (cells that over ever express APP and have robust levels of Aβ and sAPPβ) for 3 h. The Aβ/ sAPPβ levels that remain after the incubation were measured using electrochemiluminescence detection and normalized to the values from DMSO treated conditions. C. HeLa-sweAPP cells transfected with siRNA pool against AKT1, AKT2, MEDGC followed by transfection with SEAP and assayed for released SEAP.

Supplementary Figure 13: A. iPSC treated with two different concentrations of insulin and probed for APP levels. DMSO treatment was used as negative control. GAPDH was used as a loading control. B. Hela-sweAPP cells treated with insulin in the presence or absence of AKT pathway inhibitor and probed for intracellular Aβ levels. DMSO treatment was used as negative control. *p<.05,**<.005 C. Hela-sweAPP cells treated with insulin in the presence or absence of AKT pathway inhibitor and probed APP levels. DMSO treatment was used as negative control. GAPDH was used as a loading control.

Supplementary Figure 14: A. HEK293 cells were serum starved for 10 h followed by amino acid starvation for 1h. Cells were then treated with AKT pathway inhibitor (10 µM) for 2.5 h. For insulin treatment, cells were pretreated (2 h) with AKT pathway inhibitor, and stimulated with medium containing insulin (1 µM) and AKT pathway inhibitor for 30 min. DMSO treatment was used as negative control. Cells were co-labeled for Lamp2 (green) and mTOR (red). Scale bar is 10 µm. B. Immunoblot analysis of TFEB-S211 phosphorylation (HeLa TFEB-GFP stable cell line) following 2 hour treatment with vehicle (DMSO) or 10µM Akt inhibitor (n=3, mean+/-SEM, p=0.002, t-test). Quantification of TFEB S211-P in the presence or absence of AKT pathway inhibitor. C. HeLa TFEB-GFP cells serum deprived (starved) treated with insulin in the presence of AKT inhibitor or DMSO (negative control). Cells were imaged for GFP (TFEB), DAPI (Nucleus) and lysotracker (red). Scale bar is 20 µm.

Supplementary Figure 15: RT-PCR analysis of Lamp1, Lamp2, CatD and v-ATPase after treatment with AKT pathway inhibitor (black bars) DMSO treatment (grey bars) was used as a negative control.

Supplementary Figure 16: A. Measurement of proteasomal activity in the presence of AKT pathway inhibitor or insulin. DMSO treatment was used as negative control and epoxomicin treatment was used as positive control. NM-Normal medium. SM-Starvation medium (devoid of serum). B. Hypothetical scheme for protein aggregation in post-mitotic cells (neurons). C. Simulated effects of increased nutrition and insulin (left column) and of starvation (right column) on the aggregation of WT Aβ. The treatment simulations started at the beginning of day 2. The simulations were performed using protein aggregation kinetics of Aβ42 (Meisl et al., 2014).

Supplementary Figure 17: A, B, C. WT, NPC1 null and NPC1 null cells stably expressed human NPC1 were treated with AKT-pathway inhibitor and stained for (A) Lysotracker (red), (B) ThioS (green) and (C) Filipin (blue).

Supplementary Figure 18: A. Western blot analysis of SQSTM1/P62 and LC3-I/LC3-II were performed on cell lysates from CHO wt, NPC1 knockout CHO cells and NPC1 knockout CHO cells stably expressing human NPC1. β-actin and GAPDH were used as loading controls. B. siRNA based knock down of NPC1 and NPC2 were performed on HeLa cells and Cathepsin D levels were analyzed by western blot. β-actin and GAPDH were used as loading controls.

Supplementary Figure 19: Schematic representation of Aβ uptake assay in microglia.

Supplementary Figure 20: A. Imaris 3D reconstructions of confocal images. Microglia are represented by Iba1 (magenta) and CD68 (yellow), and pre-synaptic marker Synapsin-1 (cyan), counterstained with DAPI for nuclei (grey). Scale bar 3 microns. B. Magnified representative confocal images showing 20x20x4 micron regions of interest stained with Iba1 (magenta) and CD68 (yellow), and pre-synaptic marker Synapsin-1 (cyan), counterstained with DAPI for nuclei (grey). Synapsin-1 inclusions can be seen in microglial cells of AD individuals by orthogonal view.

Supplementary Figure 21: Schematic representation of regulation of amyloid levels depends on insulin signalling/Nutrient sensing pathway.

STable 1: Bioinformatics analysis of human tissue-specific transcriptome analysis of the ageing-similar genes showed a prominent contribution from the IIN-AKT pathways among the 25 most enriched pathways