Supporting InformationBellet et al. 10.1073/pnas.1120636110SI Materials and MethodsAnimals. All experiments were approved by the Institutional An-imal Care and Use Committee at the University of California,Irvine. For the generation of Clockmutant mice, see ref. 1. Clock-deficient (Clock−/−) mice were a gift from S. Reppert (Universityof Massachusetts Medical School, Worchester, MA) (2). For ex-periments in Fig. S3, we usedC57BL/6J wild-type (WT)mice of 8–12 wk of age. All experiments were conducted a minimum of twotimes with similar results, even though some degree of variabilitybetween WT mice was found, depending on mice housing con-ditions (different vivaria, different degree of sterility of cages, andfood). For the microarray study, Clockmutant mice and their WTlittermates were used.

Bacterial Strains and Culture Conditions. We used Salmonella en-terica serovar Typhimurium (S. Typhimurium) IR715, a fully vir-ulent, nalidixic acid-resistant derivative of isolate ATCC14028 (3).Mutants in invA, fliC fljB, msbB, and iroN were described (4, 5).All strains were cultured aerobically in Luria Bertani (LB) broth at37 °C, with the exception of themsbBmutant, which was grown inlow-salt LB medium (4). In the cfu counts, outliers were detectedwith the Grubbs outlier test. All outliers with α confidence levelof ≤0.01 were removed from the counts.

RNA Extraction and Real-Time PCR. For gene expression analysis byreal-time PCR, total RNA was extracted with TRIzol Reagentand processed according to the instructions of the manufacturer.Next, 2 μg of RNA from each sample was retrotranscribed (Su-perScript II Reverse Transcriptase; Invitrogen), and fourfold di-luted cDNA was used for each real time reaction. For 20 μL ofPCR, 50 ng of cDNA was mixed with primers to a final concen-tration of 150 nM and 4 μL of RT2 SYBR Green Fluor Fast mastermix (QIAGEN). The reaction was first incubated at 95 °C for 3 min,followed by 40 cycles at 95 °C for 30 s and 60 °C for 1 min. Eachquantitative real-time PCR was performed by using the Chromo4real time detection system (Bio-Rad). All values are relative tothose ofGapdh or β-actinmRNA levels at each time point. A list ofthe real-time primers used in this study is provided in Table S1.Analysis was performed in Fig. 4B by calculating the geometricmeans of fold changes in gene expression of infected compared withuninfected mice killed at the same time during the day. In Fig. 4C,values in uninfected WT day were set to 1. Bars represent mean ±SEM (n = 7–14 for infected mice; n = 3–5 for uninfected mice).

Bone Marrow-Derived Macrophage Preparations. Three Clock mu-tantmice and three isogenicWTmicewere killed between zeitgebertime (ZT) 4 andZT10, and bonemarrowwas extracted from femursof each animal. Differentiation of macrophages was obtained byculturing the bone marrow in RPMI (GIBCO) supplemented with10% (vol/vol) L-929 conditionedmedium, 10% (vol/vol) FBS, 2mMglutamine, and antibiotics. After 7 d, cells were counted and platedfor the experiment. Bone marrow-derived macrophages (BMDMs)were plated for the experiment and treated with lipopolysaccharide(LPS) at a concentration of 1 μg/mL (Ultrapure LPS; Invivogen) orinfected with S. Typhimurium by using a gentamicin protectionassay as described (4). Cells were harvested, and samples wereprocessed for RNA extraction. For circadian experiments using thedexamethasone (DEX) method, BMDMs were synchronized bytreatment with 100 nM DEX (Sigma) for 2 h. For circadian ex-periments using the serum shock method, after 2 h of serum shockwith medium containing 50% (vol/vol) horse serum, cells were in-

cubated with serum-free medium for the indicated time. LPStreatment (1 μg/mL) was performed at the indicated time points.

Enzyme-Linked ImmunoSorbent Assay. Supernatant from BMDMswas collected 24 h poststimulation with LPS or after in vitro infectionwith S. TyphimuriumWT or mutants. Secretion of TNF-α, IL-6, and-1β was detected by using commercially available kits (eBioscience).

Histopathology. Tissue samples were fixed in formalin, processedaccording to standardprocedures for paraffinembedding, sectionedat 5 μm, and stained with hematoxylin and eosin. The pathologyscore of cecal samples was determined by blinded examinations ofcecal sections from a board-certified pathologist. Each section wasevaluated for the presence of neutrophils, mononuclear infiltrate,submucosal edema, surface erosions, inflammatory exudates, andcryptitis. Inflammatory changes were scored from 0 to 4 accordingto the following scale: 0, none; 1, low; 2, moderate; 3, high; 4, ex-treme. The inflammation score was calculated by adding up all ofthe scores obtained for each parameter and interpreted as follows:0–2, within normal limits; 3–5, mild; 6–8, moderate; 8+, severe.

Gene Expression Profiling and Statistical Analysis. RNA extractedfrommice cecumwas isolatedbyusing theRNeasyMiniCleanupkit(Qiagen). Amplification and labeling of mRNA, hybridization toMouse Gene 1.0 ST GeneChip arrays (Affymetrix), staining, andscanning were performed according to protocols in the AffymetrixGene Expression Analysis Technical Manual. Analyses of micro-array data were performed by using BRB Array tools (Version4.1.0 Stable Release) developed by Richard Simon and the BRBDevelopmental Team. For each condition, RNA from three or fourmice was analyzed. A minimum 2.0-fold difference (P ≤ 0.05) be-tween groups in the following comparisons was used as criteria foridentifying differentially expressed genes for hierarchical clustering:(i) WT infected vs. WT uninfected (day); (ii) WT infected vs. WTuninfected (night); (iii) Clock mutant infected vs. Clock mutantuninfected (day); (iv) Clock mutant infected vs. Clock mutant un-infected (night); (v) Clock mutant infected vs. WT infected (day);and (vi) Clock mutant infected vs. WT infected (night). Genespassing fold-change criteria were subjected to hierarchical cluster-ing analysis, a nonbiased method of sorting the genes based onsimilar patterns of expression. Pathway analysis was then performedon each pattern of expression or subcluster. Ingenuity PathwayAnalysis software was used to identify pathways and processesstatistically overrepresented in subclusters of differentially ex-pressed genes. The microarray dataset has been deposited in theGene Expression Omnibus database. (accession no. GSE46356).

Regulatory Network Analyses.Our network was initialized with theproteins identified as belonging to cluster 1 from the analysis ofthe microarray data using the BRB Array tools, together with theclock protein aryl hydrocarbon receptor nuclear traslocator-like(ARNTL) and the NF-κB proteins NF-kB1, -kB2, v-rel retic-uloendotheliosis viral oncogene homolog A (RelA), and retic-uloendotheliosis oncogene (cRel). The MotifMap (6) system wasused to search for putative transcription factor binding siteswithin an 8-kb region centered on the translation start site ofeach gene in our network, excluding exons. Using known posi-tional-weight matrices for clock and NF-κB proteins, as well ashypoxia inducible factor 1, alpha subunit (HIF1-α) (which wasalready present in cluster 1), we assigned to every site the fol-lowing two scores: (i) a motif matching score (Z-score); and (ii)a conservation score [Bayesian Branch Length Score; BBLS (6)]calculated by using a multiple alignment of 30 genomes from

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mouse to zebrafish. We filtered these sites by using a Z-scorethreshold of 4.27 (P = 0.00001), along with a modest amount ofconservation by using a BBLS cutoff of 1.0. Directed edges weredrawn between the transcription factors and the proteins whosegene had at least one binding site satisfying the above criteria. Theresulting network was also further pruned (Fig. 4D) by pro-gressively removing nodes that were not annotated as transcriptionfactors in either the JASPAR (7) or TRANSFAC 9.4 (8) data-bases, which jointly comprise>800 bindingmatrices correspondingto >400 distinct transcription factors in mouse. All networks werevisualized by using Cytoscape Web (Version 0.8) (ref. 9; www.ics.uci.edu/~baldig/CLOCK/salmonella/).

Identification of Genotype- and Time-Dependent Genes. For theexpression analysis of genotype- and time-dependent genes

within cluster 1, we ran CyberT (10) across all pairs of treatmentsto identify differentially expressed genes (Benjamini–Hochbergmultiple test corrected, P < 0.05). Time-dependent genes weredefined as genes that were significantly differentially expressedin both (i) WT uninfected day vs. WT uninfected night and (ii)WT infected day vs. WT infected night. Genotype-dependentgenes were defined as genes that were significantly differentiallyexpressed in all four of the following comparisons: (i) WT un-infected day vs. CLOCK mutant uninfected day; (ii) WT un-infected night vs. CLOCK mutant uninfected night; (iii) WTinfected day vs. CLOCK mutant infected day; and (iv) WT infectednight vs. CLOCKmutant infected night. A third gene list was createdby taking the intersection of the genotype- and time-dependent genelists (Datasets S1, S2, and S3).

1. King DP, et al. (1997) Positional cloning of the mouse circadian clock gene. Cell 89(4):641–653.

2. Debruyne JP, et al. (2006) A clock shock: Mouse CLOCK is not required for circadianoscillator function. Neuron 50(3):465–477.

3. Stojiljkovic I, Bäumler AJ, Heffron F (1995) Ethanolamine utilization in Salmonellatyphimurium: Nucleotide sequence, protein expression, and mutational analysis ofthe cchA cchB eutE eutJ eutG eutH gene cluster. J Bacteriol 177(5):1357–1366.

4. Raffatellu M, et al. (2005) The Vi capsular antigen of Salmonella enterica serotypeTyphi reduces Toll-like receptor-dependent interleukin-8 expression in the intestinalmucosa. Infect Immun 73(6):3367–3374.

5. Raffatellu M, et al. (2009) Lipocalin-2 resistance confers an advantage to Salmonellaenterica serotype Typhimurium for growth and survival in the inflamed intestine. CellHost Microbe 5(5):476–486.

6. Xie X, Rigor P, Baldi P (2009) MotifMap: A human genome-wide map of candidateregulatory motif sites. Bioinformatics 25(2):167–174.

7. Bryne JC, et al. (2008) JASPAR, the open access database of transcription factor-binding profiles: New content and tools in the 2008 update. Nucleic Acids Res36(Database issue):D102–D106.

8. Matys V, et al. (2006) TRANSFAC and its module TRANSCompel: Transcriptional generegulation in eukaryotes. Nucleic Acids Res 34(Database issue):D108–D110.

9. Lopes CT, et al. (2010) Cytoscape Web: An interactive web-based network browser.Bioinformatics 26(18):2347–2348.

10. Baldi P, Long AD (2001) A Bayesian framework for the analysis of microarrayexpression data: Regularized t -test and statistical inferences of gene changes.Bioinformatics 17(6):509–519.

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Fig. S1. Time-dependent variations of the inflammatory response in WT mice infected with S. Typhimurium. (A) Recovery of S. Typhimurium from Peyer’spatches, mesenteric lymph nodes, and spleens of WT mice at 48 and 72 h following infection at different circadian times (10:00 AM, day or ZT4; 10:00 PM, nightor ZT16). Each circle represents bacterial numbers recovered from an individual animal, normalized for milligrams of tissue. Red bars indicate the geometricmeans (n ≥ 7). Statistically significant (P < 0.05) differences are indicated. Outliers were detected with the Grubbs outlier test. All outliers with a α confidencelevel of ≤0.01 were removed from the counts. (B) Histopathology score of WT mice from experiment shown in Fig. 1B. Each bar represents the score of oneindividual animal. Each group was divided in subgroups (WNL, within normal limits; mild; moderate; and severe) based on the severity of the inflammation(score from 0 to 8+).

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Fig. S2. Cecal inflammation after Salmonella infection at day or night. Representative images (40× magnification) of cecal inflammation in WT mice 48, 60,72, and 78 h after infection (Salmonella) or not (control), at day (ZT4) or night (ZT16).

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Fig. S3. Circadian synchronization of BMDMs. (A) Bone marrow and ceca from WT mice were collected at four different times of the circadian cycle. Bonemarrow was cultured in vitro with differentiating medium for BMDM isolation. After 1 wk, BMDMs derived from each mouse were collected at four differenttimes of the day. Per2 mRNA expression profile was analyzed by quantitative PCR in both BMDMs and ceca. The values are relative to those of β-actin mRNAlevels at each circadian time. Bars represent mean ± SD (n = 2). (B) Time course of Il-6 mRNA expression after 1, 2, or 4 h of LPS stimulation (1 μg/mL) ofmacrophages derived from bone marrow of WT mice collected as in A, measured by quantitative real-time PCR. The values are relative to those of β-actinmRNA levels at each circadian time. Bars represent mean ± SD (n = 2). (C) Period 2 (Per2), cryptochrome 1 (Cry1), and brain and muscle ARNT-like protein 1(Bmal1) mRNA expression profiles in BMDMs synchronized by DEX treatment (10 μM) were analyzed by quantitative PCR. The values are relative to those ofGapdh mRNA levels at each circadian time. All of the values are the mean ± SD (n = 2). (D) BMDMs from WT mice were synchronized by high-serum treatment,and RNA was collected at different circadian times. Per2 mRNA expression profile (Left) was analyzed by quantitative PCR. Colored arrows indicate differenttimes of treatment with LPS. Time course of Il-6 mRNA expression (Right) after LPS stimulation (1 μg/mL) started at different times of the circadian cycle inBMDMs after serum shock synchronization, measured by quantitative real-time PCR. The values are relative to those of β-actin mRNA levels at each circadiantime. Bars represent mean ± SD (n = 2).

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Fig. S4. Altered inflammatory response following Salmonella infection in Clock mutant mice. (A) Recovery of S. Typhimurium from colon content of Clock+/+

and Clock−/− mice 72 h following infection at different circadian times (day or ZT4; night or ZT16). Each circle represents bacterial numbers recovered from anindividual animal, normalized for milligrams of tissue. Red bars indicate the geometric means (n = 7). Statistically significant (P < 0.05) differences are in-dicated. (B) Tissues from WT and Clock mutant mice were collected 72 h after S. Typhimurium infection and weighed. Data represent means ± SEM (n = 28 forWT; n = 17 for Clockmutant). (C) Histopathology score of Clockmutant mice from experiment shown in Fig. 3B. Each bar represents the score of one individualanimal. Each group was divided in subgroups (WNL, within normal limits; mild; moderate; and severe) based on the severity of the inflammation (score from0 to 8+). (D) Representative images (40× magnification) of cecal inflammation in Clock mutant mice 72 h after infection (Salmonella) or not (control) with S.Typhimurium, at day (ZT4) or night (ZT16).

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Fig. S5. Microarray analysis reveals major circadian differences in antimicrobial response and acute inflammation. Changes detected by microarray analysis inthe expression of genes involved in antimicrobial response (A) and acute inflammation (B) in WT and Clock mutant mice infected at two different circadiantimes with S. Typhimurium, compared with uninfected mice.

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Fig. S6. Basal gene expression in the cecum reveals a strong circadian regulation. (A) Heat diagram showing changes in gene expression detected by mi-croarray analysis in the ceca of uninfected WT and Clockmutant mice at day (10:00 AM or ZT4) and night (10:00 PM or ZT16). Three samples in each group wereused for statistical analysis. Relative increase (red) or decrease (green) of mRNA level is shown. A list of the most represented subcategories of genes, thenumber of genes included in each subcategory (istograms), and the relative P value (solid lines) are shown. (B) Diagram showing the number of genes whosebasal levels are up- or down-regulated at night in WT and Clock mutant mice, identified from the microarray analysis. (C) Examples of genes of the defenseresponse category with differential basal levels of expression between day and night in WT mice and no changes in Clock mutant mice, identified from themicroarray analysis. Statistically significant differences are indicated. *P < 0.05; **P < 0.01.

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Fig. S7. Time- or genotype-dependent changes in cytokines’ basal levels influence their expression during infection. Transcriptional profiles as in Fig. 4 B and Care shown. Analyses were performed by calculating the geometric means of gene expression values ± SEM (n = 7–14). Value of uninfected WT mice killed atZT4 was set to 1 during the analysis. Significant day–night changes are shown. *P < 0.05; **P < 0.01; ***P < 0.001.

Fig. S8. Clock genes’ transcription is down-regulated during acute infection. (A) Changes detected by microarray analysis in the expression of circadian genesin WT and Clock mutant mice left uninfected or infected with S. Typhimurium at two different circadian times (day, ZT4; night, ZT16). (B) Per2 and nuclearreceptor subfamily 1, group D, member 1 mRNA expression profile in cecum from WT and Clockmutant mice, infected or not with S. Typhimurium at day (ZT4)or night (ZT16), 72 h after infection. Data are represented as geometric means of fold increases compared with uninfected WT day ± SEM (for infected mice n =14 wt day; n = 13 wt night; n = 9 Clock mutant day; n = 8 Clock mutant night; for uninfected mice n = 3–5 in each condition). **P < 0.01; ***P < 0.001.

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Fig. S9. Computational networks of transcription factors reveal a central role for NF-κB, HIF1α, and Arntl. (A) Network containing all genes, included in cluster 1,with significant correlations in WT infected vs. uninfected during the day. Significant changes (P < 0.05) are shown as colored circles (blue, WT infected vs.uninfected day; green, WT infected vs. uninfected night; brown, Clockmutant infected vs. uninfected day; orange, Clockmutant infected vs. uninfected night).(B) Network of transcription factors possibly involved in the regulation of subsets of genes included in clusters 2, 3, and 4. Significant changes (P < 0.05) areshown as colored circles (blue, WT infected vs. uninfected day; green, WT infected vs. uninfected night; brown, Clock mutant infected vs. uninfected day;orange, Clock mutant infected vs. uninfected night).

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Table S1. List of real-time RT-PCR primers used in this study

Gene Primers

Lcn2 5′-ACATTTGTTCCAAGCTCCAGGGC-3′5′-CATGGCGAACTGGTTGTAGTCCG-3′

Cxcl1 5′-TGCACCCAAACCGAAGTCAT-3′5′-TTGTCAGAAGCCAGCGTTCAC-3′

S100A8 5′-TGTCCTCAGTTTGTGCAGAATATAAA-3′5′-TCACCATCGCAAGGAACTCC-3′

Il-6 5′-TTCCATCCAGTTGCCTTCTT-3′5′-CAGAATTGCCATTGCACAAC-3′

Tnf-α 5′-CCCATATACCTGGGAGGAGTCTTC-3′5′-CATTCCCTTCACAGAGCAATGAC-3′

Il-1β 5′-CTCTCCAGCCAAGCTTCCTTGTGC-3′5′-GCTCTCATCAGGACAGCCCAGGT-3′

Ifnβ 5′-CCCTATGGAGATGACGGAGA-3′5′-CTGTCTGCTGGTGGAGTTCA-3′

Ccl2 5′-CTTCTGGGCCTGCTGTTCA-3′5′-CCAGCCTACTCATTGGGATCA-3′

Il-17 5′-GCTCCAGAAGGCCCTCAGA-3′5′-AGCTTTCCCTCCGCATTGA-3′

Ifnγ 5′-TCAAGTGGCATAGATGTGGAAGAA-3′5′-TGGCTCTGCAGGATTTTCATG-3′

Reg3β 5′-ATGGCTCCTACTGCTATGCC-3′5′-GTGTCCTCCAGGCCTCTTT-3′

Reg3γ 5′-ATGGCTCCTATTGCTATGCC-3′5′-GATGTCCTGAGGGCCTCTT-3′

β-actin 5′-GGCTGTATTCCCCTCCATCG-3′5′-CCAGTTGGTAACAATGCCATGT-3′

Gapdh 5′-TGTAGACCATGTAGTTGAGGTCA-3′5′-AGGTCGGTGTGAACGGATTTG-3′

Per2 5′-CGCCTAGAATCCCTCCTGAGA-3′5′-CCACCGGCCTGTAGGATCT-3′

Nr1d1 5′-GGGCACAAGCAACATTACCA-3′5′-CACGTCCCCACACACCTTAC-3′

Cry1 5′-CAGACTCACTCACTCAAGCAAGG-3′5′-TCAGTTACTGCTCTGCCGCTGGAC-3′

Bmal1 5′-GCAGTGCCACTGACTACCAAGA-3′5′-TCCTGGACATTGCATTGCAT-3′

Lcn2, lipocalin 2; Cxcl1, chemokine (C-X-C motif) ligand 1; S100a8, S100calcium binding protein; Ccl2, chemokine (C-C motif) ligand 2; Reg3β, regen-erating islet-derived 3 β; Reg3γ, regenerating islet-derived 3 γ.

Dataset S1. Hierarchical clustering table with list of genes depicted in each cluster (Fig. 4A)

Dataset S1

Fold change differences between groups were calculated through comparisons of different conditions [WT infected day (wtid) vs. WT uninfected day (wtud);WT infected night (wtin) vs. WT uninfected night (wtun); Clock infected day (ckid) vs. Clock uninfected day (ckud); Clock infected night (ckin) vs. Clockuninfected night (ckun)]. P values for the different comparisons are also shown. Both fold changes and P values are color-coded. Fluorescence intensitiesare shown but not color-coded.

Dataset S2. List of cluster 1 genes showing a time–main effect

Dataset S2

Dataset S3. List of cluster 1 genes showing a genotype–main effect

Dataset S3

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Dataset S5. Hierarchical clustering table with list of genes depicted in each cluster (Fig. S6A)

Dataset S5

Fold change differences between groups were calculated through comparisons of different conditions [WT night vs. day; Clockmutant (CK) night vs. day; CKday vs. WT day; CK night vs. WT night]. P values for the different comparisons are shown. Both fold changes and P values are color-coded.

Dataset S4. List of cluster 1 genes showing both a time–main and a genotype–main effect

Dataset S4

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