And Stimulation-Dependent Transcriptional Programs

Cell Type− and Stimulation-Dependent Transcriptional Programs Regulated by Atg16L1 and Its Crohn's Disease Risk Variant T300A This information is current as of September 29, 2021. Mukund Varma, Motohiko Kadoki, Ariel Lefkovith, Kara L. Conway, Kevin Gao, Vishnu Mohanan, Betsabeh Khoramian Tusi, Daniel B. Graham, Isabel J. Latorre, Andrew C. Tolonen, Bernard Khor, Aylwin Ng and Ramnik J. Xavier Downloaded from J Immunol published online 10 June 2020 http://www.jimmunol.org/content/early/2020/06/09/jimmun ol.1900750 http://www.jimmunol.org/

Supplementary http://www.jimmunol.org/content/suppl/2020/06/09/jimmunol.190075 Material 0.DCSupplemental

Why The JI? Submit online.

• Rapid Reviews! 30 days* from submission to initial decision by guest on September 29, 2021

• No Triage! Every submission reviewed by practicing scientists

• Fast Publication! 4 weeks from acceptance to publication

*average

Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts

The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2020 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published June 10, 2020, doi:10.4049/jimmunol.1900750 The Journal of Immunology

Cell Type– and Stimulation-Dependent Transcriptional Programs Regulated by Atg16L1 and Its Crohn’s Disease Risk Variant T300A

Mukund Varma,* Motohiko Kadoki,*,†,‡ Ariel Lefkovith,* Kara L. Conway,† Kevin Gao,† Vishnu Mohanan,*,†,‡ Betsabeh Khoramian Tusi,*,†,‡ Daniel B. Graham,*,‡,x Isabel J. Latorre,*,†,‡ Andrew C. Tolonen,* Bernard Khor,† Aylwin Ng,*,x and Ramnik J. Xavier*,†,‡,x

Genome-wide association studies have identified common genetic variants impacting human diseases; however, there are indica- tions that the functional consequences of genetic polymorphisms can be distinct depending on cell type–specific contexts, which Downloaded from produce divergent phenotypic outcomes. Thus, the functional impact of genetic variation and the underlying mechanisms of disease risk are modified by cell type–specific effects of genotype on pathological phenotypes. In this study, we extend these concepts to interrogate the interdependence of cell type– and stimulation-specific programs influenced by the core autophagy gene Atg16L1 and its T300A coding polymorphism identified by genome-wide association studies as linked with increased risk of Crohn’s disease. We applied a stimulation-based perturbational profiling approach to define Atg16L1 T300A phenotypes in dendritic cells and T lymphocytes. Accordingly, we identified stimulus-specific transcriptional signatures revealing T300A- http://www.jimmunol.org/ dependent functional phenotypes that mechanistically link inflammatory cytokines, IFN response genes, steroid biosynthesis, and lipid metabolism in dendritic cells and iron homeostasis and lysosomal biogenesis in T lymphocytes. Collectively, these studies highlight the combined effects of Atg16L1 genetic variation and stimulatory context on immune function. The Journal of Immunology, 2020, 205: 000–000.

merging insights into immune pathologies identify key autophagy targets intracellular pathogens and regulates inﬂam- cell types controlling cell stress pathways and inﬂam- matory cytokine production (10–14). mation (1–7). In particular, the genetic association of The Atg16L1 gene is broadly expressed across cell types, and

E by guest on September 29, 2021 Atg16L1 with increased risk of inflammatory bowel diseases the functional effects of the T300A allele conferring increased risk (IBD) implicated autophagy in the dysregulation of immune ho- of Crohn’s disease are incompletely understood. At the molecular meostasis (4, 8–11). Autophagy is a cellular disposal system that level, the T300A substitution introduces a caspase cleavage site on directs cytoplasmic cargo into lysosomes for proteolytic degra- Atg16L1 (1, 3). Cell stress associated with caspase activation dation. In addition to recycling biomass, such as organelles, potentiates autophagy defects in the T300A genetic background (1, 3). In response to infection and starvation, Ulk1-mediated phosphorylation of wild-type (WT) Atg16L1 enhances antibacterial autophagy and, importantly, promotes cleavage of Atg16L1 *Broad Institute of MIT and Harvard, Cambridge, MA 02142; †Center for Compu- tational and Integrative Biology, Massachusetts General Hospital, Harvard Medical T300A (15). These findings are consistent with the observation School, Boston, MA 02114; ‡Department of Molecular Biology, Massachusetts Gen- that Atg16L1 T300A renders mice susceptible to infection with x eral Hospital, Harvard Medical School, Boston, MA 02114; and Gastrointestinal Yersinia enterocolitica, and caspase inhibition ameliorates intes- Unit and Center for the Study of Inflammatory Bowel Disease, Massachusetts Gen- eral Hospital, Harvard Medical School, Boston, MA 02114 tinal pathology in this model (3). Thus, cell-extrinsic stress ORCIDs: 0000-0002-9254-1247 (M.V.); 0000-0002-0124-7406 (M.K.); 0000-0001- pathways prime genetic susceptibility to intestinal pathology. 6313-1348 (K.L.C.); 0000-0001-5855-1006 (K.G.); 0000-0001-7072-2162 (B.K.T.); Additionally, T300A disrupts protein–protein interactions medi- 0000-0001-5907-4504 (A.C.T.); 0000-0003-4689-5092 (B.K.); 0000-0002-5630- ated by the Atg16L1 WD40 repeat domain (16), which provides a 5167 (R.J.X.). docking site for interaction with TMEM59 and subsequent recruit- Received for publication July 3, 2019. Accepted for publication May 6, 2020. ment of the autophagy machinery to intracellular vesicles (17). This work was funded by the National Institutes of Health (R01DK097485 and Binding of the anti-inflammatory protein A20 to the WD40 repeat U19AI142784). domain regulates intestinal epithelial cell death, but this physical in- Address correspondence and reprint requests to Dr. Aylwin Ng at the current address: Casma Therapeutics, Inc., 400 Technology Square, Suite 201, Cambridge, MA teraction is not affected by the presence of T300A (18). As new in- 02139, or Dr. Ramnik J. Xavier, Massachusetts General Hospital, 185 Cambridge nate defense mechanisms are described, the importance of autophagy Street, 7th Floor, Boston, MA 02114. E-mail addresses: [email protected] becomes increasingly clear. Atg proteins, including Atg16L1, were (A.N.) or [email protected] (R.J.X.) recently shown to mediate the release of exomes that neutralize pore- The online version of this article contains supplemental material. forming toxins produced by pathogens such as methicillin-resistant Abbreviations used in this article: Aoah, acyloxyacyl hydrolase; cKO, conditional knockout; CLEAR, Coordinated Lysosomal Expression and Regulation; Ctse, cathepsin Staphylococcus aureus (19). It remains unclear how Atg16L1 T300A E; DC, dendritic cell; Faah, fatty acid amide hydrolase; IBD, inflammatory bowel affects disparate cell types in differing environmental contexts and disease; mTOR, mammalian target of rapamycin; TFEB, transcription factor EB; tSNE, how this cumulatively impacts disease pathogenesis. t-distributed stochastic neighbor embedding; WT, wild-type. Generation of Atg16L1 T300A knock-in mice has facilitated Copyright Ó 2020 by The American Association of Immunologists, Inc. 0022-1767/20/$37.50 discoveries of cell type–specific programs that control immune

www.jimmunol.org/cgi/doi/10.4049/jimmunol.1900750 2 Atg16L1 T300A CELL TYPE– AND STIMULATION-DEPENDENT PROGRAMS homeostasis. In epithelial cells, Atg16L1 T300A is associated with XP beads (Beckman Coulter). Each sample was then tagmented using the defective antibacterial autophagy, Paneth and goblet cell granule Nextera XT DNA Library Preparation Kit (Illumina) and the Nextera XT morphology, and secretory function (1, 3, 6, 20, 21). Additionally, Index Kit (Illumina). Postreaction purification was performed with Agencourt AMPure XP beads. Samples were then pooled, prepared, and Atg16L1 T300A knock-in mice exhibit a variety of pathological loaded onto a MiSeq (Illumina) and NextSeq (Illumina) per the manu- phenotypes throughout the immune system. Macrophages derived facturer’s instructions. from T300A mice produce elevated levels of IL-1b in response to Mast cells. Cell lysis was performed with TCL buffer (Qiagen) con- pathogen-associated molecular pattern stimulation (1, 22). These taining 1% 2-ME. Full length cDNA libraries were prepared with lysate ∼ results are consistent with previous reports of elevated IL-1b in from 2000 cells per sample, using template switching and whole transcriptome amplification in a modified version of the SmartSeq2 Atg16L1 knockout mice (23). Autophagy has been implicated in protocol described (36). After SmartSeq2, double-stranded cDNA was Ag presentation by dendritic cells (DCs) and priming CD4 T cells cleaned and purified with Agencourt AMPure XP beads (Beckman (24–26). Moreover, autophagy controls T cell homeostasis and Coulter). Each sample was then tagmented using the Nextera XT DNA attrition (27–29), and Atg16L1 is specifically required for regu- Library Prep Kit (Illumina) and the Nextera XT Index Kit (Illumina). latory T cell maintenance of peripheral tolerance (30, 31). Taken Postreaction purification was performed with Agencourt AMPure XP beads. The samples were pooled and run on a 2% E-Gel EX Agarose together, these data identified a range of host pathways that im- Gel (Thermo Fisher Scientific) and the gel was extracted with a pinge on selective autophagy and implicated a number of func- Zymoclean Gel DNA Recovery Column (Zymo Research). Samples tional connections by which Atg16L1 T300A may contribute to were prepared and loaded onto a MiSeq (Illumina) per the manufac- diverse pathological phenotypes. It is increasingly apparent that turer’s instructions. the extent to which Atg16L1 T300A might influence specific DCs. Cell lysis was performed with Lysis/Binding Buffer for Dynabeads (catalog no. A33562; Thermo Fisher Scientific), and mRNA isolation was pathways triggered in response to different stimuli in one cell type performed with the Dynabeads mRNA Direct Kit (Life Technologies). Full Downloaded from cannot be directly inferred from another cell type, as this may not length cDNA libraries were prepared with mRNA from ∼26,250 cells using be representative or generalizable across different cell types, nor template switching and whole transcriptome amplification in a modified across stimulation or perturbation states. In this study, we define version of the Smart-Seq2 protocol (36). After Smart-Seq2, double- T300A-specific transcriptional profiles in T cells, DCs, and mast stranded cDNA was cleaned and purified with Agencourt AMPure XP beads (Beckman Coulter). Each sample was then tagmented using the cells to demonstrate that the Atg16L1 T300A allele conspires Nextera XT DNA Library Prep Kit (Illumina) and the Nextera XT Index with environmental triggers to induce several cell type– and Kit (Illumina). Postreaction purification was performed with Agencourt http://www.jimmunol.org/ stimulation-specific phenotypes associated with inflammatory AMPure XP beads. The samples were pooled and run on a 2% E-Gel EX pathology. Agarose Gel (Thermo Fisher Scientific) and gel extracted with Zymoclean Gel DNA Recovery Column (Zymo Research). Samples were prepared and loaded onto a MiSeq (Illumina) and NextSeq (Illumina) per the manu- Materials and Methods facturer’s instructions. Cells and stimulation RNA sequencing analysis pipeline and data preprocessing DCs. Splenic DCs were isolated from C57BL/6J (WT), CD11c-Cre+ 3 Reads were aligned to the Mus musculus 10 transcriptome using TopHat2 Atg16L1flox/flox conditional knockout (cKO), and Atg16L1T300A/T300A mu- plus Bowtie (37). Transcripts were quantified using htseq-count (38), tant (T300A) (3) mice with mouse CD11c MicroBeads UltraPure (catalog

and read alignment quality control was performed using RSeQC (39). by guest on September 29, 2021 no. 130-108-338; Miltenyi Biotec). For each genotype, the cells were Trimmed mean of M values (TMM) normalization as implemented in prepared independently from three mice as biological replicates. The cells the edgeR package (40) was used for between-sample normalization. were then cultured overnight in RPMI 1640 medium containing 10% FBS, TMM-normalized counts were used as input for further analysis. Genes MEM Non-Essential Amino Acids, GlutaMAX, 1 mM sodium pyruvate, with zero counts across the board were excluded from downstream 55 mM 2-ME, penicillin and streptomycin (all from Thermo Fisher Sci- analysis. entific). On the next day, the cells were stimulated with 1 mg/ml LPS for 0, 4, and 12 h. These time points were selected based on published cytokine Differential expression analysis and pathway enrichment responses (32). ∼ T cells. CD4+ CD62L+ naive T cells were isolated from C57BL/6J (WT), The data were modeled with a generalized linear model of the form y Lck Cre+ 3 Atg16L1flox/flox (cKO), and Atg16L1T300A/T300A mutant Genotype + Stimulation + Genotype:Stimulation for the DCs and T cells (T300A) mice using CD4-Negative Enrichment Kits (STEMCELL Tech- individually. A likelihood ratio test was used to test for differential ex- nologies, Vancouver, BC, Canada) and CD62L MicroBeads (Miltenyi pression between conditions. A false discovery rate–adjusted p value cutoff Biotec, San Diego, CA). For each genotype, the cells were prepared in- of 0.05 was used to select genes for pathway enrichment. Pathway en- dependently from three mice as biological replicates. T cells isolated per richment was performed using the goana and kegga functions in edgeR genotype each received no stimulation, CD3/CD28 Dynabeads (for 4 or (41) and the clusterProfiler package (42). The KEGG (43), Gene On- 20 h), or 1 mM Torin treatment (for 4 h). Peak T cell activation, as defined tology (44), and Reactome (45) databases were queried to find enriched by the number of differentially expressed genes after CD3/CD28 stimu- categories. lation, was observed at 20 h; the 4-h time point allowed us to perform a time-varying analysis of transcriptional programs in response to CD3/ CAMERA gene set enrichment analysis of transcription CD28 stimulation. A 4-h Torin treatment activated autophagy in T cells. factor targets Mast cells. Bone marrow–derived mast cells were isolated from WT, Gene sets for targets of known transcription factors were tested for dif- + flox/flox T300A/T300A Mcpt5-Cre 3 Atg16L1 (cKO), and Atg16L1 mice. For ferential expression under the interaction model y ∼ Genotype 3 Stimu- each genotype, cells were isolated from four different mice in two different lation. The Correlation Adjusted MEan RAnk (CAMERA) test (46) as batches (three mice and one mice). All cells were treated with 100 ng/ml implemented in edgeR was used to set differences in the expression of anti-DNP IgE sensitization for 2 h, followed by either no further stimu- these gene sets. The CAMERA test accounts for intergene correlation, lation, 10 ng/ml DNP–BSA Ag for 30 min, or 10 ng/ml DNP–BSA Ag for which makes it particularly suitable for testing differential expression of 1 h. These time points were selected based on previously published studies gene sets that have a common biological phenomenon (such as a shared on the kinetics of mast cell degranulation (33–35). transcription factor in this case) driving their gene expression. Fig. 3 shows transcription factor enrichment based on target gene expression in T cells. RNA sequencing Each point in that plot is a gene set (e.g., the point labeled Hsf1 is the set of T cells. Cell lysis and mRNA isolation was performed with the Dynabeads all genes regulated by Hsf1). The plot thus represents the transcription mRNA DIRECT Kit (Life Technologies). mRNA from ∼150,000 cells was factor target gene sets double-differentially expressed under the interaction reverse-transcribed in a poly(dT)-primed reaction with template switch model described above (i.e., genes that show a higher or lower change in oligo and Maxima H Minus Reverse Transcriptase (Thermo Fisher Sci- expression upon stimulation between two different genotypes). Similarly, entific). NEBNext Ultra II Non-Directional RNA Second Strand Synthesis Supplemental Fig. 3 shows transcription factors whose targets are enriched Module (New England Biolabs) was used to generate double-stranded for in the double-differential comparisons under LPS stimulation for cDNA. The cDNA was cleaned and purified with Agencourt AMPure splenic DCs. The Journal of Immunology 3

Protein network perturbation inference model, TLR4 engagement by LPS in splenic DCs induces an inflammatory response characterized by robust cytokine production A change in topology due to genotypic perturbations was tested for in the + f/f BioPlex network (47), an established, experimentally verified protein in- (50). CD11c splenic DCs were isolated from WT, Atg16L1 3 teraction network. The algorithm used was the DeMAND algorithm (48). CD11c Cre+ (cKO), and Atg16L1T300A/T300A knock-in (T300A) DeMAND, although originally developed to study chemical perturbations mice. Stimulation time points (4 and 12 h) were selected based on through small molecules, can be applied equally well to study genetic cytokine responses (32), and they allowed us to perform a time- perturbations such as cKOs (Atg16L1) or single-nucleotide polymorphisms (T300A). DeMAND uses a Gaussian kernel to estimate the interaction varying analysis of LPS-induced transcriptional programs that are probability density and compares it across two conditions to estimate dependent on Atg16L1 and the T300A variant. network dysregulation. Because the algorithm works best with larger Stimulation of WT splenic DCs with LPS elicited a strong group sizes, samples from across all stimulations (i.e., nonbaseline transcriptional response, peaking at 4 h, with many of the genes samples) were grouped and then compared across genotypes to find stimulation-independent genetic perturbations. enriched in discrete biological processes. Enriched categories associated with immunity, including TLR and pattern-recognition Variance partition analysis genes, cytokines and chemokines, type I and II IFNs and IFN- The variancePartition (49) was used to quantify the variance attributable regulated genes, signal transduction, and transcription factors in the different factors in our experiment. Briefly, a linear model was com- immune regulation (Fig. 1A), served as confirmation of the fidelity puted for the expression of each gene individually, and the fraction of and integrity of LPS stimulation. More importantly, we found that variance attributable to the different factors (cell type, stimulation, and the absence of Atg16L1 dramatically altered this LPS-induced genotype) in our dataset after batch correction was computed. Each factor was treated as a random effect by virtue of being a categorical variable. transcriptional response in splenic DCs, affecting the expression Because we were using this analysis to find the relative strength of the of 1039 genes at 4 h. A vast majority (88%; 916/1039) of the genes Downloaded from different factors, interaction terms were not included in the model at this impacted were more substantially altered by Atg16L1 deficiency stage. in the LPS-stimulated state than in the unstimulated baseline state. Abs and compounds Thus, LPS stimulation accentuated genotype-associated differences and provided the context dependence in which the loss of Abs used for immunoblot are as follows: Egr1 (4154, 1:1000; Cell Signaling Technology); cMyc (5605, 1:1000; Cell Signaling Technology); Rb1cc1 Atg16L1 was able to manifest its effect.

(12436, 1:1000; Cell Signaling Technology); Wnt10a (sc-376028, 1:500; During LPS stimulation, we found the expression of many http://www.jimmunol.org/ 2 Santa Cruz Biotechnology); Ulk1 (8054T, 1:1000; Cell Signaling Tech- immune response genes (enrichment p =13 10 8) substantially nology); Akt1 (2938, 1:1000; Cell Signaling Technology); CD28 (38774S, reduced in the absence of Atg16L1 compared with WT. Inhibited 1:1000; Cell Signaling Technology); Lamp2 (L0668, 1:1000; Sigma- genes include cytokines (Il6, Il1b, Il15, Il18, Il27), chemokines Aldrich); cathepsin C (74590, 1:500; Santa Cruz Biotechnology); clathrin (2410, 1:1000; Cell Signaling Technology). (Ccl3, Ccl4, Ccl7, Ccl12, Cxcl1, Cxcl2, Cxcl9, Cxcl11), Tnf, Tnfsf10,TLRs(Tlr3, Tlr8, Tlr9), and the inflammasome component Immunoblotting Nlrp3. Strikingly, the strong LPS induction of IFN genes (Ifna2, Cells were lysed in standard lysis buffer (50 mM Tris–HCl [pH 7.5], Ifna5, Ifnb1, Ifna4) was inhibited almost completely in splenic 150 mM NaCl, 0.5 mM EDTA, 1% Nonidet P-40, Halt Phosphatase In- DCs lacking Atg16L1 (Fig. 1A, 1B). In contrast, splenic DCs hibitor Single-Use Mixture [Pierce], and Protease Inhibitor Tablets expressing the Atg16L1 T300A variant exhibited diametrically by guest on September 29, 2021 [Roche]) at 4˚C for 30 min. Lysates were centrifuged at 18,000 3 g at 4˚C for 15 min, and the supernatant was collected for protein concentration opposing trends when compared with Atg16L1 cKO cells; after estimation using a Bradford assay. Samples were prepared using 53 LPS stimulation of T300A DCs, many of the altered immune loading buffer (250 mM Tris–HCl [pH 6.8], 10% SDS, 30% glycerol, genes (e.g., Ifna5) showed expression enhanced beyond the 0.02% bromophenol blue, 5% 2-ME) and boiled for 5 min. Samples were induction level observed in WT splenic DCs (Fig. 1A, 1B). electrophoresed in 4–20% Mini-PROTEAN TGX polyacrylamide gels In striking contrast to the transcriptional profile of immune (Bio-Rad Laboratories) and transferred onto PVDF using wet transfer at 80 V for 1 h. Five percent BSA in TBST was used to block the membrane response genes, key steroid biosynthesis pathway genes (Fdft1, for 1 h. Blots were incubated overnight at 4˚C with Ab prepared in 1% Cyp51, Hmgcs1, Pmvk, Idi1) were upregulated in LPS-stimulated BSA. After three washes with TBST, the membrane was incubated with cKO but not WT or T300A DCs (Fig. 1A, 1C), suggesting that HRP-conjugated secondary Ab for 60 min at room temperature. Following Atg16L1 plays important dual roles in promoting inflammation secondary incubation, the blot was washed three times in TBST and incubated with Chemiluminescent HRP Substrate (Millipore). All Western and dampening anti-inflammatory processes in the LPS response blots were performed at least three independent times. by inhibiting genes involved in steroid biosynthesis. Thus, LPS stimulation not only accentuated but also polarized genotype- Results associated differences, namely enhanced expression of inflam- Autophagy controls multiple immune functions, and genetic matory cytokines and IFN response genes in T300A DCs. knockout of core autophagy proteins exerts pleiotropic effects on Compared with cytokine responses, LPS-activated metabolic immune homeostasis. However, it remains unclear how genetic programs that participate in inflammation, autophagy, and im- variants of Atg16L1 impact immune function in different cell types munity are incompletely understood, but new insights into these and how environmental context modifies these phenotypes. In this processes are beginning to emerge (51–53). Cellular metabolites study, we applied a stimulation-based perturbational profiling can serve as danger signals that trigger proinflammatory responses approach in DCs, T lymphocytes, and mast cells to define Atg16L1 following LPS stimulation (54). LPS can shift core metabolism in T300A phenotypes relative to Atg16L1 knockout. Accordingly, we DCs from oxidative phosphorylation to glycolysis, which en- sought to identify transcriptional signatures that reveal T300A- hances fatty acid metabolism needed for endoplasmic reticulum dependent functional phenotypes associated with immune cell and Golgi expansion (55), demonstrating the importance of lipid type and activation status. metabolism to innate immunity and potentially revealing a role in regulating autophagy. In this study, we highlight three lipid LPS stimulation reveals Atg16L1 genotype-dependent metabolism genes (fatty acid amide hydrolase [Faah], acyloxyacyl responses in DCs hydrolase [Aoah], and Ch25h) that we identified as transcrip- First, we employed an endotoxin-elicited immune response model tionally induced by LPS and dependent on Atg16L1 or its T300A in mouse CD11c+ splenic DCs to assess alteration of the tran- variant (Fig. 1D–F). Both Faah and Aoah encode hydrolases, whereas scriptional landscape in the context of Atg16L1 genotype. In this Ch25h is a hydroxylase. Faah participates in the degradation of 4 Atg16L1 T300A CELL TYPE– AND STIMULATION-DEPENDENT PROGRAMS Downloaded from http://www.jimmunol.org/ by guest on September 29, 2021

FIGURE 1. LPS stimulation reveals Atg16L1 genotype-dependent responses in splenic DCs. (A) Heatmap shows unstimulated (No stim) and LPS- induced transcriptional proﬁles of CD11c+ splenic DCs isolated from Atg16L1f/f 3 CD11c Cre+ (cKO), Atg16L1T300A/T300A (T300A), and WT mice.

Expression values (log2CPM from biological triplicates) were z-score–transformed and represented by color intensity transitions shown in the color bar. The expression of these genes was strongly influenced by LPS stimulation and genotype and was enriched in pathways and processes associated with immune responses, lipid and steroid metabolism, Wnt signaling, and mitochondrial and Golgi function. (B–F) Boxplots showing expression profiles of key genes [(B) Ifna5,(C) Idi1,(D) Faah,(E) Aoah, and (F) Ch25h] in splenic DCs for which LPS stimulation (for 4 and 12 h) and genotype exert a strong effect. endocannabinoids anandamide and palmitoylethanolamine, which Aoah. At baseline, Aoah was expressed at low levels (Fig. 1E), are involved in intestinal inflammation (56). Induction of the Faah and no significant difference across WT, cKO, and T300A was gene by LPS was diminished in the absence of Atg16L1 and in observed. Upon LPS stimulation, expression levels of Aoah were the presence of the T300A variant (Fig. 1D). Aoah selec- markedly upregulated at 4 h and further increased at 12 h. This is tively inactivates bacterial LPS by specifically hydrolyzing the consistent with the role of Aoah in LPS inactivation, establishing acyloxyacyl-linked fatty acyl chains in the lipid A moiety (57). a functional feedback loop that senses LPS levels. The absence Our transcriptomic analysis revealed a feedback loop involving of Atg16L1 reduced Aoah expression compared with WT when The Journal of Immunology 5 stimulated with LPS at 4 and 12 h. Conversely, the T300A var- deleted suggests a response to elevated ferritin levels, which is iant exhibited even higher Aoah induction levels compared with indicative of a disruption in the iron transport and metabolism WT at both LPS-stimulated time points, reminiscent of the ex- network. Importantly, this elevated transcriptional response to pression profile observed for immune response genes in which Atg16L1 genotype differences is cell type–dependent. The ex- genotypic differences were polarized by LPS stimulation. pression increase observed for these iron-associated genes in From our analysis, we found a striking concordance between the cKO T cells (Atg16L1f/f 3 Lck Cre+) was not seen in cKO expression profiles of Ch25h and immune response genes (Fig. 1A, splenic DCs (Atg16L1f/f 3 CD11c Cre+) relative to Atg16L1 1F); the dependence of Ch25h expression on Atg16L1 became T300A and WT cells (Fig. 2B). Altered expression of genes in evident only under LPS stimulation. Similar to immune response the iron transport pathway is consistent with impaired selective genes, the induction of Ch25h expression by LPS was significantly ferritinophagy. diminished in the absence of Atg16L1 compared with WT. At To define altered stimulation-dependent transcriptional pro- the later time point of LPS stimulation (12 h), Ch25h induction grams in T cells, we profiled expression changes in Torin-induced was higher in the T300A variant than in WT. As a choles- T cells and CD3/CD28–stimulated T cells across genotypes terol hydroxylase, Ch25h catalyzes the formation of 25-hydroxy- (Atg16L1f/f 3 Lck Cre+ cKO, T300A, and WT). Torin, a small cholesterol, an intermediate in the biosynthesis of oxysterol, which molecule mTOR inhibitor, mimics cellular starvation and induced is a ligand for the lymphoid cell chemotactic receptor Gpr183/EBI2. autophagy after 4 h in T cells. Given that autophagy is essential Intriguingly, 25-hydroxycholesterol promotes a robust NLRP3 for T cell activation, we first evaluated the efficacy of these inflammasome assembly, production of IL-1b (58), and mitochon- stimulations by examining differential expression of autophagy- drial reactive oxygen species–mediated pathways, which is con- related genes and T cell activation-related genes for Torin and Downloaded from sistent with TLR4 engagement (59). Transcriptionally, we observed CD3/CD28 stimulation, respectively. Consistent with Torin stim- that these components are coordinately upregulated by LPS and are ulation in WT T cells, we observed downregulation of Mtor ex- Atg16L1 dependent. pression and upregulation of core autophagy complex components We detected an enrichment of genes associated with the Wnt (68), including Ulk1 (Atg1), Atg13, Rb1cc1 (Fip200), Atg13, pathway that shared similar expression profiles with the immune Atg14, Wipi1/2 (Atg18), Atg2b, Map1lc3a (a member of the LC3/

response genes. The expression of these genes was induced by LPS Atg8 complex), and genes encoding autophagy adaptors Sqstm1 http://www.jimmunol.org/ in WT and T300A but inhibited in the absence of Atg16L1. Protein (p62), Ncoa4, Optn, and Tax1bp1 (Fig. 2C). After CD3/CD28 levels of Wnt10a, Egr1, and c-myc confirmed that LPS increased stimulation, we observed peak T cell activation as defined by expression of Wnt pathway genes in WT and T300A but not cKO number of genes being differentially expressed at 20 h and used DCs (Supplemental Fig. 1). The Wnt pathway is not only essential this time point for subsequent analyses. Including an intermediate for embryonic development and homeostasis but has more re- (4 h) time point again allowed us to evaluate time-varying tran- cently been recognized to be important in exerting immunomod- scriptional responses to CD3/CD28 stimulation. As expected, ulatory influence in inflammation, infection, and autophagy genes associated with T cell activation were induced in CD3/ (60–62). Recently, the intracellular bacterium Ehrlichia was found CD28–stimulated WT T cells (Fig. 2D). We validated a subset of to induce and exploit the Wnt pathway to evade destruction in the these changes in T cells, observing increased Ulk1 and Rb1cc1 by guest on September 29, 2021 autophagolysosome. The Wnt pathway inhibited lysosomal fusion protein expression following Torin treatment as well as ele- and the autolysosomal destruction of Ehrlichia (62). There is vated Akt1 and CD28 levels following CD3/CD28 stimulation additional evidence that the Wnt pathway can inhibit autophagy (Supplemental Fig. 2). by regulating the activation of the mammalian target of rapamycin Next, we modeled our data with a full factorial design matrix, (mTOR) pathway (63–65) through Akt-mediated GSK3 phos- including interaction terms, and evaluated the stimulation– phorylation (66). These findings, together with our identification genotype factor interaction (or double-differential) terms to find of key Wnt pathway genes induced by LPS in splenic DCs in an transcriptional programs that change in response to stimulation Atg16L1-dependent manner, highlights the importance of Wnt- between cKO, T300A, and WT T cells. This allowed us to identify mediated regulation in antibacterial autophagy and innate im- a change in response upon stimulation between the different ge- mune defense response. notypes. We identified genes associated with lysosomal processes Taken together, LPS stimulation in splenic DCs strongly alters, and pathways to be the most highly enriched (Fig. 2E). These accentuates, and polarizes the genotypic impact of Atg16L1 or its lysosomal genes exhibited stimulation-dependent response shifts T300A variant on the transcriptional landscape. In the absence of that were altered by genotype. Most of the deregulated lysosome- LPS stimulation, the transcriptional differences between geno- associated genes showed a downregulation in their response to types in splenic DCs were less marked. Torin (i.e., Torin versus baseline) in cKO compared with WT (Fig. 2E). These include Lamp2 (69), Cltc (70), and Litaf (71), Distinct Atg16L1- and T300A-dependent transcriptional which have been implicated in autophagosome formation, con- signatures in T cells sistent with the role of Atg16L1 in the formation and maturation of By profiling naive CD4+ CD62L+ T cells from WT, Atg16L1f/f 3 the autophagosome. Other lysosomal genes dysregulated by Lck Cre+ (cKO), and Atg16L1T300A/T300A (T300A) mice, we Atg16L1 loss include Ctsh, Ctsc, Dnase2, Galc, Acp2, Cd68, identified transcriptional signatures that are both genotype- and Pcyox1, and Creg1, which constitute the Coordinated Lysosomal T cell type–dependent. At baseline, we found genes associated Expression and Regulation (CLEAR) gene network regulated by with iron binding, transport, and metabolism (67) to be upregu- transcription factor EB (TFEB), the master regulator of lysosome lated in Atg16L1 knockout cells. The ferritin gene Ftl1, genes biogenesis and degradation of glycosaminoglycans and sphingo- involved in iron homeostasis (Slc46a1, Slc4a1, Slc40a1, Slc25a37, lipids (72). Consistent with this observation, we identified glyco- Trf, Hmox1), and the entire heme complex (Hbb-b1, Hbb-b2, Hba- sphingolipid metabolism genes (St8sia1, Ggta1, B4galt4, B3galnt1, a1, Hba-a2) were upregulated when Atg16L1 was disrupted A4galt) that were enriched, nearly all of which exhibited a re- (Fig. 2A). In fact, we found the heme complex genes to be among sponse to Torin that was dampened in the absence of Atg16L1 the most highly differentially upregulated genes between cKO and (Fig. 2E). Additionally, we found cholesterol metabolism, ether WT T cells (Fig. 2B). The upregulation of Ftl1 when Atg16L1 was lipid metabolism, and arachidonic acid metabolism to be strongly 6 Atg16L1 T300A CELL TYPE– AND STIMULATION-DEPENDENT PROGRAMS Downloaded from http://www.jimmunol.org/ by guest on September 29, 2021

FIGURE 2. Atg16L1 genotype shapes transcriptional programs and activation responses in T cells. (A) Heatmap showing expression profiles of naive CD4+ CD62L+ T cells from Atg16L1f/f 3 Lck Cre+ (cKO) and WT mice. Atg16L1 genotype- and stimulation-independent genes were associated with iron binding, transport, and metabolism. Expression values (log2CPM) were z-score–transformed and represented by color intensity transitions shown in the color bar. (B) As a representative gene from the heme/iron cluster shown in (A), Hbb-b1 expression profiles of T cells (top) and splenic DCs (bottom) are contrasted in boxplots. T cells were stimulated for 4 or 20 h with CD3/CD28 and for 4 h with Torin. DCs were stimulated for 4 or 12 h with LPS. The expression of Hbb-b1 in T300A T cells was intermediate between WT and cKO. Hbb-b1 expression was upregulated in T300A splenic DCs compared with both WT and cKO. Expression values are presented as log2CPM of the gene transcripts for each cell type. (C) Volcano plot shows that autophagy genes were significantly induced by Torin stimulation in WT T cells, whereas Mtor was downregulated. Red and blue dots denote significantly upregulated and downregulated genes, respectively (false discovery rate , 0.05 and fold change . 1.5). Gray dots indicate insignificant change in gene expression. (D) Volcano plot of T cell activation genes significantly induced by stimulation with CD3/CD28 for 20 h in WT T cells. (E and F) Bar plots showing pathway enrichment analysis of stimulation- and genotype-dependent transcriptional shifts in responses to (E) Torin and (F) 20-h CD3/CD28 stimulation. Response to stimulus was captured with a factorial design model that evaluates stimulation–genotype factor interactions (double differentials). Dumbbell plots show these double-differential shifts of genes [log2(fold change between stimulated and unstimulated)] driving the enrichment of the respective key pathways and also exhibiting an Atg16L1-dependent response to Torin or CD3/CD28 stimulation. Each node on the dumbbell represents a response. Each pair of nodes connected in a dumbbell indicates the two genotypes being compared (Atg16L1f/f 3 Lck Cre+ cKO and WT). The distance between each pair of nodes shows the shift in response between WT and cKO. enriched and impacted in an Atg16L1-dependent manner (Fig. 2E), following CD3/CD28 stimulation in cKO T cells relative to WT revealing an important regulatory influence by Atg16L1 on lipid- (Supplemental Fig. 2). associated metabolic pathways and lysosome-associated catabolic To identify transcriptional mechanisms controlling the deregu- processes. We also observed an enrichment of genes functioning lated expression states defined by genotype differences, we adopted in cholesterol metabolism and lysosomal pathways that were an approach to infer the potential contribution of transcription downregulated in the absence of Atg16L1 in T cell responses to factor activity. We applied a competitive gene set test that accounts CD3/CD28 stimulation (Fig. 2F), but it was not as extensive as for intergene correlation (46) to assess differences in the expres- seen in response to Torin stimulation (Fig. 2E). Selecting from sion of transcription factor targets across cKO, T300A, and WT the most highly enriched stimulation- and genotype-dependent T cells. Hsf1 was associated with the differential response be- lysosomal genes, we confirmed decreases in protein expression tween both cKO versus WT and T300A versus WT. In this context, of Cltc and Lamp2 following Torin treatment as well as Ctsc Hsf1 target genes showed a positive fold change under Torin The Journal of Immunology 7 stimulation in the two mutant samples compared with WT Lgals3 (galectin-3) node was the most dysregulated in cKO T cells (Fig. 3A). Hsf1 was previously shown to have an opposing compared with WT (Fig. 3B). Galectin-3 is a member of the function relative to Nrf2-Keap1 in regulating autophagy (73), and b-galactoside–binding protein family that has been implicated in upregulation of its targets suggests that autophagy may be sup- inflammation (74), metastasis (75), and apoptosis (76) among pressed in Atg16L1 knockout or T300A, which is consistent with other immune-related processes. Notably, galectin-3 is thought to previous studies (1). Additionally, activation of Hsf1 upon CD3/ be regulated by MITF (a paralog of TFEB) in certain cell types CD28 stimulation shows a time dependence, with targets of its and has been reported to play a role in iron trafficking in associ- paralog Hsf2 being more differentially expressed at the 4-h time ation with transferrin (77–79). Transferrin itself is the second- point and with Hsf1 activity dominating at the 20-h time point most dysregulated node in the T300A versus WT comparison of when T cell activation is higher. Under Torin stimulation, Hsf1 network disruption, with the most dysregulated node being Zbtb9, target enrichment was found to be higher. a predicted transcriptional regulator with incomplete functional Transcription factors whose targets were downregulated upon annotation. Other notable genes common to T300A and cKO Torin stimulation included Tcf4, which has been linked to auto- T cells that were associated with disrupted network modules in- phagosome formation (63). A decrease in signal for Tcf4 target cluded the enzyme Rnase3, which regulates antibacterial function genes is consistent with defective autophagosome formation in the (80), and Ifna21, a paralog of Ifna4 that we showed to be regulated cKO context. In Atg16L1 T300A cells, we identified Notch3 as the at the transcriptional level in a genotype-dependent manner in transcription factor whose targets were most significantly down- splenic DCs (Fig. 1A, Supplemental Fig. 3). regulated, consistent with the immunosuppression observed in the mutant cells. Cell type and stimulation exert strong influences on Downloaded from A similar analysis identified differentially regulated transcription genotype differences factors between cKO, T300A, and WT splenic DCs under LPS We observed not only stimulation-dependent but also cell type– stimulation. Transcription factors related to the NF-kB pathway dependent programs regulated by the Atg16L1 genotype in T cells (Nfkb1, Nfkbia, Rel, Ikbkb) show consistent dysregulation, with and splenic DCs. Subsequently, we sought to quantify the extent to targets of inhibitory transcription factors (Ikbkb, Nfkbia) upregu- which each of these factors influenced the transcriptional land-

lated and those of activating transcription factors (Rel, Nfkb1, scape. Toward this end, we expanded the cell types proﬁled to http://www.jimmunol.org/ Rela) downregulated in cKO and T300A versus WT under the include bone marrow–derived mast cells obtained from WT, double-differential comparisons. This is consistent with a damp- Atg16L1f/f 3 Mcpt5 Cre+ (cKO), and Atg16L1T300A/T300A (T300A) ened response of immune-related genes in the absence of mice. Mast cells were stimulated with DNP–BSA for 30 min and Atg16L1. In stark contrast to T cells, in which we highlighted a 1 h to induce degranulation. These time points were selected based positive fold change in targets of Hsf1 (an inhibitor of Nrf3)in on previously published studies on the kinetics of mast cell de- both cKO and T300A relative to WT, targets of Nrf3 (Nfe2l2) were granulation (33–35). As with the previous experiments, splenic enriched in Atg16L1 knockout and T300A DCs (Supplemental DCs were stimulated with LPS at 4 and 12 h time points to initiate Fig. 3). immune responses. T cells were activated by CD3/CD28 stimu- Next, we analyzed the BioPlex protein interaction network (47), lation for 4 and 20 h and also stimulated with Torin for 4 h to by guest on September 29, 2021 with the objective of identifying key nodes in the gene networks of activate autophagy. All RNA sequencing libraries were rese- T cells that are disrupted by perturbation of autophagy. We used quenced at a comparable depth to minimize the confounding ef- the DeMAND algorithm for network dysregulation (48), treating fects from quality control differences. the Atg16L1f/f 3 Lck Cre+ cKO as a genetic perturbation of To ascertain the relative importance of the three factors driving WT cells. We compared all the nonbaseline samples in each ge- the transcriptional differences observed across the immune cell notype group and found that the subnetwork surrounding the types and under their respective stimulations, we adopted a tiered

FIGURE 3. Network dysregulation and transcription factor enrichment analyses identify hidden targets of Atg16L1 genetic perturbation in T cells. (A)To uncover the activity of transcription factors that were not expressed at high levels themselves, the targets of transcription factors in the transcriptional regulatory relationships unravelled by sentence-based text-mining (TRRUST) database (95) were tested for enrichment by applying the competitive gene set test that accounts for intergene correlation (46). Transcription factors Hsf1, Notch3, Nr1h2, and Tcf4 were identified as top hits with functionally relevant known annotations. Term size refers to the number of genes in each associated term in TRRUST. (B) To infer gene modules that are significantly dysregulated by Atg16L1f/f 3 Lck Cre+ and Atg16L1T300A/T300A, we applied the DeMAND algorithm (48) and compared all stimulation samples (nonbaseline) from either group to WT. The submodule centered at galectin-3 (Lgals3) was found to be most dysregulated in the Atg16L1f/f 3 Lck Cre+ versus WT comparison, with genes involved in lysosome and trafficking contributing to the phenotype. 8 Atg16L1 T300A CELL TYPE– AND STIMULATION-DEPENDENT PROGRAMS dimensionality reduction approach. We first reduced the dimen- shaped by cellular states triggered by environmental cues. Work sionality of our dataset using principal component analysis. from previous studies suggests that environment–gene and gene– Principal components (except those most correlated with batch) gene interactions can modify Atg16L1 genotype-dependent were then subjected to a second dimensionality reduction step by processes involved in antibacterial autophagy (1, 81) and Paneth applying spectral t-distributed stochastic neighbor embedding cell function (82). In splenic DCs, we found that LPS stimulation (tSNE). tSNE provided a high-level visual summary of the tran- dramatically altered or polarized the Atg16L1 genotype effect on scriptomic landscape and revealed that cell type differences transcriptional responses to an extent not observed in the unsti- dominated over other factors (Fig. 4A). In the tSNE, samples mulated baseline state. Without LPS stimulation, transcriptional cluster most strongly by cell type, followed by stimulation, and changes owing to genotype differences were unremarkable. Thus, then by genotype, indicating that genotype-dependent programs LPS stimulation provided the context dependence or regulatory owing to Atg16L1 deficiency or the T300A variant are highly cell landscape that allowed genotype differences to manifest. Upon type–specific. LPS stimulation, immune response genes in DCs were particularly We next conducted variance partition analysis (49) to further impacted by genotype differences. The extent of downregulation quantify the effect of the different factors on the transcriptional of immune response genes (including cytokines, chemokines, profile. A linear model was computed for the expression of each IFN-regulated genes, TLRs, and inflammasome components) in gene individually in the dataset after batch correction, which the absence of Atg16L1 was striking. Steroid biosynthesis genes, allowed us to establish the fraction of variance attributable to however, were upregulated in the absence of Atg16L1. Others have genotype, cell type, and stimulation state. Each factor was treated also linked autophagy to innate inflammatory signaling by dem- as a random effect by virtue of being a categorical variable. onstrating that Atg16L1 is necessary in myeloid (83) and epithelial Downloaded from Variance partition analysis also pointed to cell type as the major (84) cells to prevent overproduction of type I IFNs. Myeloid cell– contributor to variance, followed by stimulation, and then geno- specific loss of Atg16L1 increased IFN-b and IL-1b production type (Fig. 4B). Strikingly, we found only one gene (cathepsin and enhanced intestinal immunity to Salmonella typhimurium E[Ctse]) that was predominantly genotype-dependent, with over through an IFNR-dependent mechanism. Moreover, overproduc- 60% of its variance attributable to genotype (Fig. 4C). Ctse tion of IFN-b and IL-1b was observed in human macrophages

showed significantly elevated expression in Atg16L1 cKO and carrying Atg16L1 T300A, and an IFN response gene signature was http://www.jimmunol.org/ T300A splenic DCs and T cells compared with WT (Supplemental elevated in IBD patients resistant to anti-TNF therapy (83). To- Fig. 4). For the other top genes exhibiting a substantial genotype gether, these observations indicate that Atg16L1 is required for the dependence, we found that their transcriptional profiles were all proinflammatory responses of DCs. Our findings contrast with a markedly influenced by cell type and stimulation factors (Fig. 4C). previous study in which Atg16L1-deficient macrophages were With the exception of Ctse, we have observed that cell type and found to produce higher levels of IL-18 when stimulated with LPS stimulation states strongly influence the transcriptional landscape (23). Instead, we observed a very strong suppression of IL-18 and alter the context in which genotype differences can manifest. expression in Atg16L1-deficient DCs, suggesting that Atg16L1- driven programs are cell type–specific. After LPS stimulation, the Discussion T300A variant was associated with an enhanced expression of by guest on September 29, 2021 Our results support the growing recognition that the impact of immune response genes, representing a shift toward an inflam- Atg16L1 genotype differences on autophagy and immunity is matory state. At baseline, however, there were no significant ex- strongly dependent on cell type–specific contexts and is further pression differences detected for immune response and steroid

FIGURE 4. Transcriptional responses depend on contexts of cell type, stimulation condition, and genotype. We examined the extent to which cell type, stimulation, and genotype influence the transcriptional profile of CD11c+ splenic DCs, naive CD4+ CD62L+ T cells, and bone marrow–derived mast cells across genotypes as labeled. Atg16L1f/f 3 CD11c Cre+ for DCs and Atg16L1f/f 3 Lck Cre+ for T cells (cKO). Atg16L1T300A/T300A (T300A). Cells were unstimulated (No Stim) or subjected to different cell type–relevant stimulations as indicated. An additional summary is available in Supplemental Fig. 2. (A) High-level visual summary of the transcriptomic landscape using tandem principal component analysis and tSNE suggests that cell type differences dominate over other factors. (B) Variance partition analysis provides a quantitative assessment of the extent to which the variance of each gene can be attributed to cell type, genotype, and stimulation state, showing that cell type represents the major contributor to this variance, followed by stimulation and then genotype. This illustrates the importance of context-specific analysis of transcriptomic data and the need to study the effects of Atg16L1 and the T300A variant in each specific cell type separately. (C) Ranking of the 20 top-most genotype-dependent genes. Residuals show the rest of the genes that do not significantly vary between groups. Ctse is the only gene that has most of its variance (.60%) explained by genotype. Ctse expression profiles in splenic DCs and T cells are shown in Supplemental Fig. 4. The Journal of Immunology 9 biosynthesis genes between genotypes, reinforcing the notion that factors that behave similarly in the context of Atg16L1 deficiency genotype- and allele-specific differences are only revealed in ap- (Nfkbia) as well as those with opposing behaviors (Nfe2l2)in propriate functional contexts. these cell types. Together, these results provide starting points for Compared with DCs, we observed distinct transcriptional pro- understanding the cross-talk between autophagy, inflammation, grams in T cells under the control of the Atg16L1 genotype. and immunometabolism that maintains tissue homeostasis. IBD is Specifically, iron metabolism machinery was dysregulated in a model disease in this context, as risk genes control inter- Atg16L1f/f 3 Lck Cre+ cKO T cells in a stimulation-independent connected functional pathways in cell type–dependent manners; manner. Upregulation of ferritin and heme complex genes in the assigning variants pathway risk scores may help define disease absence of Atg16L1 suggests that a deficiency in Atg16L1 might subtypes, biomarkers, and targeted therapeutic strategies (89). be associated with an accumulation of iron in the cell. Many genes Indeed, genomic and transcriptional profiles have been combined involved in iron transport were also differentially expressed, with computational approaches to position variants affecting the suggesting that the mechanism underlying this phenotype might responsiveness of genes to stimuli (responsiveness quantitative be a disruption of intracellular iron handling at the level of im- trait loci) within molecular circuits (90). paired ferritinophagy. Transcriptional alterations associated with Collectively, our studies in DCs and T cells provide a more lysosomal and autophagosome dynamics were more pronounced quantitative estimate of the influences of cell type, stimulation, and upon Torin stimulation compared with CD3/CD28 stimulation, genotype on transcriptional profiles. Our findings from variance indicating a predominant mTOR signaling dependence. This is partition analysis demonstrated that cell type and stimulation also consistent with TFEB regulation because many of the dys- effects predominate over transcriptional alterations owing to regulated lysosomal genes constitute the TFEB-regulated CLEAR genotype differences. Although expression of many genes showed Downloaded from network that is important for lysosomal biogenesis. Deregulation strong genotype dependence, expression of very few genes of the CLEAR network is linked to lysosomal diseases (85). exhibited independence from cell type and stimulation state. In Further, we identified additional transcription factors that drive fact, we found only one gene (Ctse) whose expression was pre- gene expression changes in cKO and T300A T cells through dominantly genotype-specific across cell types and stimulation transcription factor target enrichment approaches. Notably, Hsf1 states examined. Ctse is a nonlysosomal aspartic protease, with a

targets were upregulated upon both stimulations (Torin and CD3/ structure that is almost identical to that of Ctsd (91), a lysosomal http://www.jimmunol.org/ CD28) and both genotypes (cKO and T300A). Hsf1 is known to gene previously reported to be upregulated in IBD (92, 93). Ctse function in suppression of autophagy and antagonize Nrf2-Keap1. has been implicated in MHC class II presentation (94), suggesting Additionally, targets of Nr1h3 (LXRA), a transcription factor that it could also play an important role in IBD development through implicated in induction of lethal autophagy, were downregulated the disruption of Ag presentation in the context of the T300A risk after CD3/CD28 stimulation. This effect was observed after CD3/ variant. Ctse had most of its variance attributable to genotype and CD28 but not Torin stimulation, suggesting that regulation of showed elevated expression in Atg16L1 T300A compared with both Nr1h3 target genes occurs in an mTOR-independent manner. WT and Atg16L1 knockout cells. Thus, Ctse transcription appears to Lastly, we tested for the disruption of the BioPlex protein–protein track inversely with the T300A variant and could serve as a useful interaction network and found key nodes galectin-3 and transfer- candidate marker. Our finding that Ctse represents the sole exception by guest on September 29, 2021 rin, both of which have roles in iron trafficking, to be affected by rather than the rule reinforces the concept that cell type and stimu- Atg16L1 deficiency. lation states establish the context in which genotype differences can Insights from genetics, particularly polymorphisms in Atg16L1 manifest. These observations strongly suggest that studies into and IRGM, helped to define the complex role for autophagy in disease-associated genotypes and variants be performed and inter- IBD. Conditional Atg16L1 knockout and T300A knock-in mice preted in the context of each specific cell type and stimulation state. revealed cell type–specific phenotypes that could be described relative to WT as more mild or severe. The cumulative effects Acknowledgments of these cell type–specific phenotypes contribute to IBD patho- We thank Elizabeth Creasey and Abdifatah Omar for technical assistance physiology. In this study, we extend Atg16L1 genotype- and cell and Theresa Reimels for editorial assistance. type–dependent observations and report on stimulation-specific programs in splenic DCs, T cells, and mast cells. LPS-induced Ifna5 expression in DCs was abrogated by Atg16L1 loss but en- Disclosures hanced beyond WT levels by the T300A substitution. We identi- R.J.X. cofounded Jnana Therapeutics and Celsius Therapeutics and is a con- sultant to Novartis. A.N. is currently employed by Casma Therapeutics, Inc. fied genotype- and stimulation-dependent metabolism genes in Work was performed when A.N. was at Massachusetts General Hospital, both DCs and T cells that impair mucosal immunity. Our analysis Harvard Medical School. The other authors have no financial conflicts of revealed a feedback loop in DCs in which LPS induced expression interest. of Aoah, a lipid metabolism gene with a known role in LPS inactivation. Altered LPS inactivation in Aoah knockout DCs leads to decreased IL-6 production, which results in inhibition of Th17 References cell polarization and induction of regulatory T cells (86). We 1. Lassen, K. G., P. Kuballa, K. L. Conway, K. K. Patel, C. E. Becker, J. M. Peloquin, E. J. Villablanca, J. M. Norman, T. C. Liu, R. J. Heath, et al. identified a second genotype- and stimulation-dependent lipid 2014. Atg16L1 T300A variant decreases selective autophagy resulting in altered metabolism gene, Ch25h, that was shown to function as part of an cytokine signaling and decreased antibacterial defense. Proc. Natl. Acad. Sci. axis regulating osteoarthritis (87). This mechanism may have a USA 111: 7741–7746. 2. Kaser, A., A. H. Lee, A. Franke, J. N. Glickman, S. Zeissig, H. Tilg, E. E. Nieuwenhuis, broader role in the gut. Last, we observed enrichment of choles- D. E. Higgins, S. Schreiber, L. H. Glimcher, and R. S. Blumberg. 2008. XBP1 links ER terol metabolism genes in an Atg16L1-dependent manner in Torin- stress to intestinal inflammation and confers genetic risk for human inflammatory bowel stimulated T cells. Atg16L1 deficiency and Atg16L1 T300A cause disease. Cell 134: 743–756. 3. Murthy, A., Y. Li, I. Peng, M. Reichelt, A. K. Katakam, R. Noubade, M. Roose- cholesterol accumulation in lysosomes that contributes to defec- Girma, J. DeVoss, L. Diehl, R. R. Graham, and M. van Lookeren Campagne. tive plasma membrane repair, linking membrane integrity to IBD 2014. A Crohn’s disease variant in Atg16l1 enhances its degradation by caspase 3. Nature 506: 456–462. (88). Comparing transcription factor enrichment analyses of DCs 4. Rioux, J. D., R. J. Xavier, K. D. Taylor, M. S. Silverberg, P. Goyette, A. Huett, and T cells in response to stimulation, we revealed transcription T. Green, P. Kuballa, M. M. Barmada, L. W. Datta, et al. 2007. Genome-wide 10 Atg16L1 T300A CELL TYPE– AND STIMULATION-DEPENDENT PROGRAMS

association study identifies new susceptibility loci for Crohn disease and im- 30. Chu, H., A. Khosravi, I. P. Kusumawardhani, A. H. Kwon, A. C. Vasconcelos, plicates autophagy in disease pathogenesis. Nat. Genet. 39: 596–604. L. D. Cunha, A. E. Mayer, Y. Shen, W. L. Wu, A. Kambal, et al. 2016. Gene- 5. Adolph, T. E., M. F. Tomczak, L. Niederreiter, H. J. Ko, J. Bo¨ck, E. Martinez- microbiota interactions contribute to the pathogenesis of inflammatory bowel Naves, J. N. Glickman, M. Tschurtschenthaler, J. Hartwig, S. Hosomi, et al. disease. Science 352: 1116–1120. 2013. Paneth cells as a site of origin for intestinal inflammation. Nature 503: 31. Kabat, A. M., O. J. Harrison, T. Riffelmacher, A. E. Moghaddam, C. F. Pearson, 272–276. A. Laing, L. Abeler-Do¨rner, S. P. Forman, R. K. Grencis, Q. Sattentau, et al. 6. Cadwell, K., J. Y. Liu, S. L. Brown, H. Miyoshi, J. Loh, J. K. Lennerz, C. Kishi, 2016. The autophagy gene Atg16l1 differentially regulates Treg and TH2 cells to W. Kc, J. A. Carrero, S. Hunt, et al. 2008. A key role for autophagy and the control intestinal inflammation. Elife 5: e12444. autophagy gene Atg16l1 in mouse and human intestinal Paneth cells. Nature 32. Jovanovic, M., M. S. Rooney, P. Mertins, D. Przybylski, N. Chevrier, R. Satija, 456: 259–263. E. H. Rodriguez, A. P. Fields, S. Schwartz, R. Raychowdhury, et al. 2015. Im- 7. Deuring, J. J., G. M. Fuhler, S. R. Konstantinov, M. P. Peppelenbosch, munogenetics. Dynamic profiling of the protein life cycle in response to path- E. J. Kuipers, C. de Haar, and C. J. van der Woude. 2014. Genomic ATG16L1 ogens. Science 347: 1259038. risk allele-restricted Paneth cell ER stress in quiescent Crohn’s disease. Gut 63: 33. Deng, Z., T. Zink, H. Y. Chen, D. Walters, F. T. Liu, and G. Y. Liu. 2009. Impact 1081–1091. of actin rearrangement and degranulation on the membrane structure of primary 8. McCarroll, S. A., A. Huett, P. Kuballa, S. D. Chilewski, A. Landry, P. Goyette, mast cells: a combined atomic force and laser scanning confocal microscopy M. C. Zody, J. L. Hall, S. R. Brant, J. H. Cho, et al. 2008. Deletion polymor- investigation. Biophys. J. 96: 1629–1639. phism upstream of IRGM associated with altered IRGM expression and Crohn’s 34. Qin, S., X. Wang, H. Wu, P. Xiao, H. Cheng, X. Zhang, and Y. Ke. 2016. Cell- disease. Nat. Genet. 40: 1107–1112. based phenotypic screening of mast cell degranulation unveils kinetic pertur- 9. Kuballa, P., A. Huett, J. D. Rioux, M. J. Daly, and R. J. Xavier. 2008. Impaired bations of agents targeting phosphorylation. Sci. Rep. 6: 31320. autophagy of an intracellular pathogen induced by a Crohn’s disease associated 35. Xiang, Z., M. Block, C. Lo¨fman, and G. Nilsson. 2001. IgE-mediated mast cell ATG16L1 variant. PLoS One 3: e3391. degranulation and recovery monitored by time-lapse photography. J. Allergy 10. Kuballa, P., W. M. Nolte, A. B. Castoreno, and R. J. Xavier. 2012. Autophagy Clin. Immunol. 108: 116–121. and the immune system. Annu. Rev. Immunol. 30: 611–646. 36. Picelli, S., A. K. Bjo¨rklund, O. R. Faridani, S. Sagasser, G. Winberg, and 11. Kuballa, P., and R. J. Xavier. 2010. Failure and exploitation of autophagy in R. Sandberg. 2013. Smart-seq2 for sensitive full-length transcriptome profiling human pathologies-cellular integrity between inflammation, infection, and cell in single cells. Nat. Methods 10: 1096–1098. survival. Semin. Immunopathol. 32: 319–322. 37. Kim, D., G. Pertea, C. Trapnell, H. Pimentel, R. Kelley, and S. L. Salzberg. 2013. Downloaded from 12. Paulus, G. L., and R. J. Xavier. 2015. Autophagy and checkpoints for intracel- TopHat2: accurate alignment of transcriptomes in the presence of insertions, lular pathogen defense. Curr. Opin. Gastroenterol. 31: 14–23. deletions and gene fusions. Genome Biol. 14: R36. 13. Levine, B., N. Mizushima, and H. W. Virgin. 2011. Autophagy in immunity and 38. Anders, S., P. T. Pyl, and W. Huber. 2015. HTSeq—a Python framework to work inflammation. Nature 469: 323–335. with high-throughput sequencing data. Bioinformatics 31: 166–169. 14. Virgin, H. W., and B. Levine. 2009. Autophagy genes in immunity. Nat. 39. Wang, L., S. Wang, and W. Li. 2012. RSeQC: quality control of RNA-seq ex- Immunol. 10: 461–470. periments. Bioinformatics 28: 2184–2185. 15. Alsaadi, R. M., T. T. Losier, W. Tian, A. Jackson, Z. Guo, D. C. Rubinsztein, and 40. Robinson, M. D., and A. Oshlack. 2010. A scaling normalization method for

R. C. Russell. 2019. ULK1-mediated phosphorylation of ATG16L1 promotes differential expression analysis of RNA-seq data. Genome Biol. 11: R25. http://www.jimmunol.org/ xenophagy, but destabilizes the ATG16L1 Crohn’s mutant. EMBO Rep. 20: 41. Robinson, M. D., D. J. McCarthy, and G. K. Smyth. 2010. edgeR: a Bio- e46885. conductor package for differential expression analysis of digital gene expression 16. Boada-Romero, E., I. Serramito-Go´mez, M. P. Sacristań, D. L. Boone, data. Bioinformatics 26: 139–140. R. J. Xavier, and F. X. Pimentel-Muinõs. 2016. The T300A Crohn’s disease risk 42. Yu, G., L. G. Wang, Y. Han, and Q. Y. He. 2012. clusterProfiler: an R package for polymorphism impairs function of the WD40 domain of ATG16L1. Nat. Com- comparing biological themes among gene clusters. OMICS 16: 284–287. mun. 7: 11821. 43. Kanehisa, M., and S. Goto. 2000. KEGG: kyoto encyclopedia of genes and 17. Boada-Romero, E., M. Letek, A. Fleischer, K. Pallauf, C. Ramoń-Barros, and genomes. Nucleic Acids Res. 28: 27–30. F. X. Pimentel-Muinõs. 2013. TMEM59 defines a novel ATG16L1-binding motif 44. Ashburner,M.,C.A.Ball,J.A.Blake,D.Botstein,H.Butler,J.M.Cherry,A.P.Davis, that promotes local activation of LC3. EMBO J. 32: 566–582. K. Dolinski, S. S. Dwight, J. T. Eppig, et al; The Gene Ontology Consortium. 2000. 18. Slowicka, K., I. Serramito-Go´mez, E. Boada-Romero, A. Martens, M. Sze, Gene ontology: tool for the unification of biology. Nat. Genet. 25: 25–29. I. Petta, H. K. Vikkula, R. De Rycke, E. Parthoens, S. Lippens, et al. 2019. 45. Fabregat, A., K. Sidiropoulos, P. Garapati, M. Gillespie, K. Hausmann, R. Haw, Physical and functional interaction between A20 and ATG16L1-WD40 domain B. Jassal, S. Jupe, F. Korninger, S. McKay, et al. 2016. The Reactome pathway by guest on September 29, 2021 in the control of intestinal homeostasis. Nat. Commun. 10: 1834. Knowledgebase. Nucleic Acids Res. 44(D1): D481–D487. 19. Keller, M. D., K. L. Ching, F. X. Liang, A. Dhabaria, K. Tam, B. M. Ueberheide, 46. Wu, D., and G. K. Smyth. 2012. Camera: a competitive gene set test accounting D. Unutmaz, V. J. Torres, and K. Cadwell. 2020. Decoy exosomes provide for inter-gene correlation. Nucleic Acids Res. 40: e133. protection against bacterial toxins. Nature 579: 260–264. 47. Huttlin, E. L., L. Ting, R. J. Bruckner, F. Gebreab, M. P. Gygi, J. Szpyt, S. Tam, 20. Liu, T. C., T. Naito, Z. Liu, K. L. VanDussen, T. Haritunians, D. Li, K. Endo, G. Zarraga, G. Colby, K. Baltier, et al. 2015. The BioPlex network: a systematic Y. Kawai, M. Nagasaki, Y. Kinouchi, et al. 2017. LRRK2 but not ATG16L1 is exploration of the human interactome. Cell 162: 425–440. associated with Paneth cell defect in Japanese Crohn’s disease patients. JCI 48. Woo, J. H., Y. Shimoni, W. S. Yang, P. Subramaniam, A. Iyer, P. Nicoletti, Insight 2: e91917. M. Rodrı´guez Martıńez, G. Lo´pez, M. Mattioli, R. Realubit, et al. 2015. Elu- 21. Bel, S., M. Pendse, Y. Wang, Y. Li, K. A. Ruhn, B. Hassell, T. Leal, S. E. Winter, cidating compound mechanism of action by network perturbation analysis. Cell R. J. Xavier, and L. V. Hooper. 2017. Paneth cells secrete lysozyme via secretory 162: 441–451. autophagy during bacterial infection of the intestine. Science 357: 1047–1052. 49. Hoffman, G. E., and E. E. Schadt. 2016. variancePartition: interpreting drivers of 22. Kuo, S. Y., A. B. Castoreno, L. N. Aldrich, K. G. Lassen, G. Goel, V. Dancı´k, variation in complex gene expression studies. BMC Bioinformatics 17: 483. P. Kuballa, I. Latorre, K. L. Conway, S. Sarkar, et al. 2015. Small-molecule 50. Luger, R., S. Valookaran, N. Knapp, C. Vizzardelli, A. M. Dohnal, and enhancers of autophagy modulate cellular disease phenotypes suggested by T. Felzmann. 2013. Toll-like receptor 4 engagement drives differentiation of human genetics. Proc. Natl. Acad. Sci. USA 112: E4281–E4287. human and murine dendritic cells from a pro- into an anti-inflammatory mode. 23. Saitoh, T., N. Fujita, M. H. Jang, S. Uematsu, B. G. Yang, T. Satoh, H. Omori, PLoS One 8: e54879. T. Noda, N. Yamamoto, M. Komatsu, et al. 2008. Loss of the autophagy protein 51. Palsson-McDermott, E. M., A. M. Curtis, G. Goel, M. A. Lauterbach, Atg16L1 enhances endotoxin-induced IL-1beta production. Nature 456: 264– F. J. Sheedy, L. E. Gleeson, M. W. van den Bosch, S. R. Quinn, R. Domingo- 268. Fernandez, D. G. Johnston, et al. 2015. Pyruvate kinase M2 regulates Hif-1a 24. Lee, H. K., L. M. Mattei, B. E. Steinberg, P. Alberts, Y. H. Lee, A. Chervonsky, activity and IL-1b induction and is a critical determinant of the warburg effect in N. Mizushima, S. Grinstein, and A. Iwasaki. 2010. In vivo requirement for Atg5 LPS-activated macrophages. [Published erratum appears in 2015 Cell Metab. 21: in antigen presentation by dendritic cells. Immunity 32: 227–239. 347.] Cell Metab. 21: 65–80. 25. Zhang, H., L. Zheng, D. P. McGovern, A. M. Hamill, R. Ichikawa, Y. Kanazawa, 52. Krawczyk, C. M., T. Holowka, J. Sun, J. Blagih, E. Amiel, R. J. DeBerardinis, J. Luu, K. Kumagai, M. Cilluffo, M. Fukata, et al. 2017. Myeloid ATG16L1 J. R. Cross, E. Jung, C. B. Thompson, R. G. Jones, and E. J. Pearce. 2010. Toll- facilitates host-bacteria interactions in maintaining intestinal homeostasis. like receptor-induced changes in glycolytic metabolism regulate dendritic cell J. Immunol. 198: 2133–2146. activation. Blood 115: 4742–4749. 26. Hubbard-Lucey, V. M., Y. Shono, K. Maurer, M. L. West, N. V. Singer, 53. O’Neill, L. A., and D. G. Hardie. 2013. Metabolism of inflammation limited by C. G. Ziegler, C. Lezcano, A. C. Motta, K. Schmid, S. M. Levi, et al. 2014. AMPK and pseudo-starvation. Nature 493: 346–355. Autophagy gene Atg16L1 prevents lethal T cell alloreactivity mediated by 54. Mills, E. L., B. Kelly, A. Logan, A. S. H. Costa, M. Varma, C. E. Bryant, dendritic cells. Immunity 41: 579–591. P. Tourlomousis, J. H. M. Da¨britz, E. Gottlieb, I. Latorre, et al. 2016. Succinate 27. Xu, X., K. Araki, S. Li, J. H. Han, L. Ye, W. G. Tan, B. T. Konieczny, dehydrogenase supports metabolic repurposing of mitochondria to drive in- M. W. Bruinsma, J. Martinez, E. L. Pearce, et al. 2014. Autophagy is essential flammatory macrophages. Cell 167: 457–470.e13. for effector CD8(+) T cell survival and memory formation. Nat. Immunol. 15: 55. Everts, B., E. Amiel, S. C. Huang, A. M. Smith, C. H. Chang, W. Y. Lam, 1152–1161. V. Redmann, T. C. Freitas, J. Blagih, G. J. van der Windt, et al. 2014. TLR-driven 28. Stephenson, L. M., B. C. Miller, A. Ng, J. Eisenberg, Z. Zhao, K. Cadwell, early glycolytic reprogramming via the kinases TBK1-IKKe supports the ana- D. B. Graham, N. N. Mizushima, R. Xavier, H. W. Virgin, and W. Swat. 2009. bolic demands of dendritic cell activation. Nat. Immunol. 15: 323–332. Identification of Atg5-dependent transcriptional changes and increases in mito- 56. Shamran, H., N. P. Singh, E. E. Zumbrun, A. Murphy, D. D. Taub, M. K. Mishra, chondrial mass in Atg5-deficient T lymphocytes. Autophagy 5: 625–635. R. L. Price, S. Chatterjee, M. Nagarkatti, P. S. Nagarkatti, and U. P. Singh. 2017. 29. Pua, H. H., I. Dzhagalov, M. Chuck, N. Mizushima, and Y. W. He. 2007. A Fatty acid amide hydrolase (FAAH) blockade ameliorates experimental colitis by critical role for the autophagy gene Atg5 in T cell survival and proliferation. altering microRNA expression and suppressing inflammation. Brain Behav. J. Exp. Med. 204: 25–31. Immun. 59: 10–20. The Journal of Immunology 11

57. Gorelik, A., K. Illes, and B. Nagar. 2018. Crystal structure of the mammalian 77. Carlsson, M. C., P. Bengtson, H. Cucak, and H. Leffler. 2013. Galectin-3 guides lipopolysaccharide detoxifier. Proc. Natl. Acad. Sci. USA 115: E896–E905. intracellular trafficking of some human serotransferrin glycoforms. J. Biol. 58. Jang, J., S. Park, H. Jin Hur, H. J. Cho, I. Hwang, Y. Pyo Kang, I. Im, H. Lee, Chem. 288: 28398–28408. E. Lee, W. Yang, et al. 2016. 25-hydroxycholesterol contributes to cerebral in- 78. Vankrunkelsven, A., K. De Ceulaer, D. Hsu, F. T. Liu, P. De Baetselier, and flammation of X-linked adrenoleukodystrophy through activation of the NLRP3 B. Stijlemans. 2010. Lack of galectin-3 alleviates trypanosomiasis-associated inflammasome. Nat. Commun. 7: 13129. anemia of inflammation. Immunobiology 215: 833–841. 59. West, A. P., I. E. Brodsky, C. Rahner, D. K. Woo, H. Erdjument-Bromage, 79. Franco, P. G., L. A. Pasquini, M. J. Pe´rez, M. V. Rosato-Siri, L. Silvestroff, and P. Tempst, M. C. Walsh, Y. Choi, G. S. Shadel, and S. Ghosh. 2011. TLR sig- J. M. Pasquini. 2015. Paving the way for adequate myelination: the contribution nalling augments macrophage bactericidal activity through mitochondrial ROS. of galectin-3, transferrin and iron. FEBS Lett. 589: 3388–3395. Nature 472: 476–480. 80. Rosenberg, H. F. 1995. Recombinant human eosinophil cationic protein. Ribo- 60. Oderup, C., M. LaJevic, and E. C. Butcher. 2013. Canonical and noncanonical nuclease activity is not essential for cytotoxicity. J. Biol. Chem. 270: 7876–7881. Wnt proteins program dendritic cell responses for tolerance. J. Immunol. 190: 81. Begun, J., K. G. Lassen, H. B. Jijon, L. A. Baxt, G. Goel, R. J. Heath, A. Ng, 6126–6134. J. M. Tam, S. Y. Kuo, E. J. Villablanca, et al. 2015. Integrated genomics of 61. Gatica-Andrades, M., D. Vagenas, J. Kling, T. T. K. Nguyen, H. Benham, Crohn’s disease risk variant identifies a role for CLEC12A in antibacterial R. Thomas, H. Ko¨rner, B. Venkatesh, J. Cohen, and A. Blumenthal. 2017. WNT autophagy. Cell Rep. 11: 1905–1918. ligands contribute to the immune response during septic shock and amplify 82. Cadwell, K., K. K. Patel, N. S. Maloney, T. C. Liu, A. C. Ng, C. E. Storer, endotoxemia-driven inflammation in mice. Blood Adv. 1: 1274–1286. R. D. Head, R. Xavier, T. S. Stappenbeck, and H. W. Virgin. 2010. Virus-plus- 62. Lina, T. T., T. Luo, T. S. Velayutham, S. Das, and J. W. McBride. 2017. Ehrlichia susceptibility gene interaction determines Crohn’s disease gene Atg16L1 phe- activation of Wnt-PI3K-mTOR signaling inhibits autolysosome generation and notypes in intestine. Cell 141: 1135–1145. autophagic destruction by the mononuclear phagocyte. Infect. Immun. 85: 83. Samie, M., J. Lim, E. Verschueren, J. M. Baughman, I. Peng, A. Wong, Y. Kwon, e00690-17. Y. Senbabaoglu, J. A. Hackney, M. Keir, et al. 2018. Selective autophagy of the 63. Petherick, K. J., A. C. Williams, J. D. Lane, P. Ordoń˜ez-Morań, J. Huelsken, adaptor TRIF regulates innate inflammatory signaling. Nat. Immunol. 19: 246– T. J. Collard, H. J. Smartt, J. Batson, K. Malik, C. Paraskeva, and 254. A. Greenhough. 2013. Autolysosomal b-catenin degradation regulates Wnt- 84. Martin, P. K., and K. Cadwell. 2020. Regulation of interferon signaling in re- autophagy-p62 crosstalk. EMBO J. 32: 1903–1916. sponse to gut microbes by autophagy. Gut Microbes 11: 126–134. 64. Fu, Y., H. Chang, X. Peng, Q. Bai, L. Yi, Y. Zhou, J. Zhu, and M. Mi. 2014. 85. Palmieri, M., S. Impey, H. Kang, A. di Ronza, C. Pelz, M. Sardiello, and Downloaded from Resveratrol inhibits breast cancer stem-like cells and induces autophagy via A. Ballabio. 2011. Characterization of the CLEAR network reveals an integrated suppressing Wnt/b-catenin signaling pathway. PLoS One 9: e102535. control of cellular clearance pathways. Hum. Mol. Genet. 20: 3852–3866. 65. Bailis, W., and W. S. Pear. 2012. Notch and PI3K: how is the road traveled? 86. Janelsins, B. M., M. Lu, and S. K. Datta. 2014. Altered inactivation of com- Blood 120: 1349–1350. mensal LPS due to acyloxyacyl hydrolase deficiency in colonic dendritic cells 66. Ma, T., N. Tzavaras, P. Tsokas, E. M. Landau, and R. D. Blitzer. 2011. Synaptic impairs mucosal Th17 immunity. Proc. Natl. Acad. Sci. USA 111: 373–378. stimulation of mTOR is mediated by Wnt signaling and regulation of glycogen 87. Choi, W. S., G. Lee, W. H. Song, J. T. Koh, J. Yang, J. S. Kwak, H. E. Kim, synthetase kinase-3. J. Neurosci. 31: 17537–17546. S. K. Kim, Y. O. Son, H. Nam, et al. 2019. The CH25H-CYP7B1-RORa axis of

67. Davis, M., and S. Clarke. 2013. Inﬂuence of microRNA on the maintenance of cholesterol metabolism regulates osteoarthritis. Nature 566: 254–258. http://www.jimmunol.org/ human iron metabolism. Nutrients 5: 2611–2628. 88. Tan, J. M. J., N. Mellouk, S. E. Osborne, D. A. Ammendolia, D. N. Dyer, R. Li, 68. Yang, Z., and D. J. Klionsky. 2010. Mammalian autophagy: core molecular D. Brunen, J. M. van Rijn, J. Huang, M. A. Czuczman, et al. 2018. An machinery and signaling regulation. Curr. Opin. Cell Biol. 22: 124–131. ATG16L1-dependent pathway promotes plasma membrane repair and limits 69. Saftig, P., W. Beertsen, and E. L. Eskelinen. 2008. LAMP-2: a control step for Listeria monocytogenes cell-to-cell spread. Nat. Microbiol. 3: 1472–1485. phagosome and autophagosome maturation. Autophagy 4: 510–512. 89. Graham, D. B., and R. J. Xavier. 2020. Pathway paradigms revealed from the 70. Rong, Y., M. Liu, L. Ma, W. Du, H. Zhang, Y. Tian, Z. Cao, Y. Li, H. Ren, genetics of inﬂammatory bowel disease. Nature 578: 527–539. C. Zhang, et al. 2012. Clathrin and phosphatidylinositol-4,5-bisphosphate reg- 90. Gat-Viks, I., N. Chevrier, R. Wilentzik, T. Eisenhaure, R. Raychowdhury, ulate autophagic lysosome reformation. Nat. Cell Biol. 14: 924–934. Y. Steuerman, A. K. Shalek, N. Hacohen, I. Amit, and A. Regev. 2013. Deci- 71. Bertolo, C., S. Roa, A. Sagardoy, M. Mena-Varas, E. F. Robles, J. I. Martinez- phering molecular circuits from genetic variation underlying transcriptional re- Ferrandis, X. Sagaert, T. Tousseyn, A. Orta, I. S. Lossos, et al. 2013. LITAF, a sponsiveness to stimuli. Nat. Biotechnol. 31: 342–349. BCL6 target gene, regulates autophagy in mature B-cell lymphomas. Br. J. 91. Chou, K. C. 2005. Modeling the tertiary structure of human cathepsin-E. Bio-

Haematol. 162: 621–630. chem. Biophys. Res. Commun. 331: 56–60. by guest on September 29, 2021 72. Settembre, C., and D. L. Medina. 2015. TFEB and the CLEAR network. 92. Hausmann, M., F. Obermeier, K. Schreiter, T. Spottl, W. Falk, J. Scho¨lmerich, Methods Cell Biol. 126: 45–62. H. Herfarth, P. Saftig, and G. Rogler. 2004. Cathepsin D is up-regulated in in- 73. Dayalan Naidu, S., D. Dikovskaya, E. Gaurilcikaite, E. V. Knatko, Z. R. Healy, flammatory bowel disease macrophages. Clin. Exp. Immunol. 136: 157–167. H. Mohan, G. Koh, A. Laurell, G. Ball, D. Olagnier, et al. 2017. Transcription 93. Menzel, K., M. Hausmann, F. Obermeier, K. Schreiter, N. Dunger, F. Bataille, factors NRF2 and HSF1 have opposing functions in autophagy. Sci. Rep. 7: W. Falk, J. Scholmerich, H. Herfarth, and G. Rogler. 2006. Cathepsins B, L and 11023. D in inflammatory bowel disease macrophages and potential therapeutic effects 74. Henderson, N. C., and T. Sethi. 2009. The regulation of inflammation by of cathepsin inhibition in vivo. Clin. Exp. Immunol. 146: 169–180. galectin-3. Immunol. Rev. 230: 160–171. 94. Zaidi, N., and H. Kalbacher. 2008. Cathepsin E: a mini review. Biochem. Bio- 75. Takenaka, Y., T. Fukumori, and A. Raz. 2002. Galectin-3 and metastasis. Gly- phys. Res. Commun. 367: 517–522. coconj. J. 19: 543–549. 95. Han, H., H. Shim, D. Shin, J. E. Shim, Y. Ko, J. Shin, H. Kim, A. Cho, E. Kim, 76. Nakahara, S., N. Oka, and A. Raz. 2005. On the role of galectin-3 in cancer T. Lee, et al. 2015. TRRUST: a reference database of human transcriptional apoptosis. Apoptosis 10: 267–275. regulatory interactions. Sci. Rep. 5: 11432.