www.sciencemag.org/cgi/content/full/342/6161/967/DC1

Supplementary Materials for

Commensal Bacteria Control Cancer Response to Therapy by Modulating the Tumor Microenvironment

Noriho Iida, Amiran Dzutsev, C. Andrew Stewart, Loretta Smith, Nicolas Bouladoux, Rebecca A. Weingarten, Daniel A. Molina, Rosalba Salcedo, Timothy Back,

Sarah Cramer, Ren-Ming Dai, Hiu Kiu, Marco Cardone, Shruti Naik, Anil K. Patri, Ena Wang, Francesco M. Marincola, Karen M. Frank, Yasmine Belkaid,

Giorgio Trinchieri,* Romina S. Goldszmid*

*Corresponding author. E-mail: trinchig@mail.nih.gov (G.T.); rgoldszmid@mail.nih.gov (R.S.G.)

Published 22 November 2013, Science 342, 967 (2013)

DOI: 10.1126/science.1240527

This PDF file includes:

Materials and Methods Figures S1 to S20 References

Iida et al. 2

MATERIALS AND METHODS

Mice. Tnf−/− Rag1−/−, Cybb−/−, Tlr4−/−, Tlr2−/− and C57B6LY5.2Cr mice were bred and

maintained in a specific pathogen-free (both Helicobacter spp and parvovirus-free) environment,

and generally used between 7 and 14 weeks of age. All strains were backcrossed to obtain at least

98% congenicity to either C57BL/6J or C57BL/6NCr background. Animal studies were

approved by the Institutional Animal Care and Use Committee (IACUC) of National Cancer

Institute (Frederick, Maryland) and were conducted in accordance with the IACUC guidelines

and the National Institutes of Health Guide for the Care and Use of Laboratory (National

Institutes of Health Publication No. 86–23, 1985). Germ-free C57BL/6 mice were bred at

Taconic Farms (Germantown, NY) and maintained in the NIAID gnotobiotic facility in

accordance with the procedures outlined in the Guide for the Care and Use of Laboratory

Animals under an animal study proposal approved by the NIAID Animal Care and Use

Committee.

Cell culture and reagents. MC38 cells were provided by Dr. Jon Wigginton (NCI, Frederick,

MD). EL4 cells were purchased from American Type Culture Collection (ATCC, number TIB-

39; Manassas, VA), and both were cultured in RPMI1640 containing 10% fetal bovine serum,

penicillin/streptomycin, L-glutamine, sodium pyruvate, non-essential amino acids (Lonza,

Walkersville, MD). B16F10 cells were obtained from National Cancer Institute Repository and

cultured in DMEM containing 10% fetal bovine serum, penicillin/streptomycin, L-glutamine,

sodium pyruvate, non-essential amino acids. CpG-ODN 1668, control ODN and ultrapure LPS

derived from E. coli O111:B4 were purchased from Invivogen (San Diego, CA). Antibiotics and

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cytotoxic drugs were purchased from the following companies: vancomycin (Hospira, Lake

Forest, IL), imipenem/cilastatin (brand name is Primaxin, Merck, Bethesda, MD), neomycin

(Med-Pharmex, Pomona, CA), ampicillin (Sigma, St. Louis, MO), oxaliplatin (Sanofi-Aventis,

Bridgewater, NJ), cisplatin (APP Pharmaceuticals, Schaumburg, IL), and N-acetylcysteine

(Hospira, Lake Forest, IL).

CpG-ODN based immunotherapy. Mice were injected in the flank subcutaneously with 2 × 105

MC38 or 2 × 105 B16F10 cells. When tumor sizes reached around 6 mm diameter, mice were

injected intratumorally with 10 μg CpG-ODN 1668 or control ODN. To augment anti-tumor

effect, 250 μg anti–IL-10R antibody (clone 1B1.3a) or isotype IgG (clone GL113) was injected

intraperitoneally in some experiments one day prior to CpG injection. Tumor sizes were

monitored every other day and volume was calculated using the following formula:

Volume (mm3) = (longest diameter) × (shortest diameter)2/2

Mice were euthanized when tumor volume reached 4000 mm3 or when they became moribund.

Chemotherapy of established tumors in mice. Mice were injected in the flank subcutaneously

with 5 × 105 EL4 or 2 × 105 MC38 cells. Around seven days after the tumor inoculation the mice

were treated with intraperitoneal oxaliplatin injection (10 mg per kg body weight) or cisplatin

injection (5 mg per kg body weight). To deplete Gr-1+ cells, tumor-bearing mice received 250 µg

anti-Gr-1-antibody (RB6-8C5) or isotype control (GL113) intraperitoneally on days 2, 5 and 8

after tumor injection.

Real-time PCR. cDNA was prepared from 1000 ng of total RNA according to the protocol for

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SuperScript II Reverse transcription (Invitrogen, Grand Island, NY). For each sample, real-time

quantitative RT-PCR was then performed using the SYBR Green PCR Master Mix (Qiagen,

Valencia, CA), with forward and reverse primers at a final concentration of 0.3 µM, in a sample

volume of 25 µL. The primers were designed using Primer 3.0 software from mRNA sequences

submitted to GenBank and checked in BLAST to confirm the total gene specificity. The

sequences of primers are: Tnf (forward) GCC TCT TCT CAT TCC TGC TT and (reverse) AGG

GTC TGG GCC ATA GAA CT; Hprt (forward) TGC CGA GGA TTT GGA AAA AGT G and

(reverse) CAC AGA GGG CCA CAA TGT GAT G. In several experiments, TaqMan gene

expression assay (Tnf, Mm00443258_m1; Hprt, Mm01545399_m1) and Fast Universal PCR

Master Mix (Applied Biosystems, Foster City, CA) were used. PCR was performed using a

StepOnePlus machine (Applied Biosystems) under the cycling conditions required in the

protocol for SYBR Green PCR Master Mix. The expression of candidate genes in each group of

mice was normalized to Hprt to obtain a ΔCt value and to calculate a 2^−(mean ΔCt).

Nanostring. The nCounter analysis system (NanoString Technologies, Seattle, WA) was used to

screen for the expression of signature genes associated with inflammation pathway as previously

described (26). Two specific probes (capture and reporter) for each gene of interest were

employed. Briefly, 5ul of RNA (the concentration is higher than 33 ng/µL) was hybridized with

customized Reporter CodeSet and Capture ProbeSet as Mouse Inflammation Panel including 150

selected genes (NanoString Technologies) according to the manufacturer’s instructions for direct

labeling of mRNAs of interest with molecular barcodes without the use of reverse transcription

or amplification. The hybridized samples were then recovered in the NanoString Prep Station

and the mRNA molecules were counted with the NanoString nCounter. For analysis of

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expression, each sample profile was normalized to geometric mean of 5 housekeeping genes

including Gapdh, Hprt, Rpl19, Rpl27 and Rpl30. The data was analyzed using one-way ANOVA

and p-values were corrected for multiple comparisons using q-value method.

DNA extraction, quantification and sequencing of fecal bacteria. Fecal DNA was extracted

with DNA Stool kit (Qiagen) according to manufacturer’s instruction. The abundance of

eubacteria in feces was measured by qPCR using a StepOnePlus instrument (Applied

Biosystems) with the fecal DNA and 16S rRNA gene primers for eubacteria as previously

described. The sequences of the primers are ACT CCT ACG GGA GGC AGC AGT (UniF340)

and ATT ACC GCG GCT GCT GGC (UniR514). The real-time PCR program started with an

initial step at 95°C for 10 min, followed by 40 cycles of 30 s at 95°C and 1 min at 60°C and 1

cycle of 15 s at 95°C. The real-time PCRs were done using SYBR green Mastermix (Qiagen).

Bacterial numbers were determined using standard curves constructed with DNA of E. coli strain

K12-MG1655 or DH5α as reference bacteria. qPCR measures the number of 16S rRNA gene

copies per gram feces, not actual bacterial numbers or CFU. Number of 16S gene copies varies

between different species, however due to large number of different species in the gut, 16S gene

copies could be used as a measure of relative numbers of the bacteria in the sample (27). For 16S

sequencing analysis, PCR amplicon was prepared using V1 (5’-

AGAGTTTGATCCTGGCTCAG-3’) and V3 (primer 534R; 5’-ATTACCGCGGCTGCTGG-3’)

primers with barcodes and 454 sequencing primers. PCR reaction was done using Accuprime

High Fidelity Taq Polymerase (Invitrogen), PCR reaction was done with an initial step at 95°C

for 2 min, followed by 25 cycles of 30 sec at 95°C, 30 sec at 56°C and 5 min at 72 °C. PCR

product was purified from oligo DNA contaminants using AMPure (Beckman Coulter),

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quantified using Agilent’s Bioanalyzer, DNA 1000 kit and Kappa QPCR kit (KAPA

Biosystems) ; all samples were pooled in equimolar concentrations. Emultion PCRs were made

using Roche 454 emPCR Lib-A kit (Roche). Sequencing was done using Roche 454 FLX-Ti

protocol. Downstream sequence processing was performed using Mothur v1.22.0 (28).

Sequences were assigned to corresponding barcodes; trimmed and low quality sequences were

removed using shhh.flows pipeline. A minimum length of sequences used was 400 bp long.

Chimeras were removed using UChime algorithm (Mothur plugin). Sequences were aligned to

SILVA bacterial reference dataset. For OTU analysis sequences were clustered and sequences

with more than 97% similarity were binned into the same OTUs. Both types of data (aligned to

reference dataset) and clustered based on similarity were used in downstream analysis for

comparisons between the groups and correlation analysis. A phylogenetic tree was calculated

using Clearcut algorithm (a plugin in Mothur software package), which was used to calculate

unweighted Unifrac distances. Bacterial diversity indexes (Chao and Inverse Simpson Index)

were also calculated using Mothur software. All sequence analysis was done on Biowulf NIH

cluster. Taxonomically assigned or OTU-clustered reads were imported into Partek 6.0 software

and normalized to number of bacteria per gram of feces. Groups indicated in the figures or the

text were compared to each other either using unpaired t-test or multi-way ANOVA analysis.

Correlation between bacterial phylogenetic groups and Tnf (obtained by RT-PCR analysis) was

done at every taxonomic level separately using Spearman's rank correlation coefficient, p-values

were corrected for multiple comparisons using q-value method. Taxonomic trees were made

using Cytoscape 2.8.1 software. The sequence data has been deposited in the Sequence Read

Archive (SRA) (bioproject accession number PRJNA221649).

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Histology and Immunohistochemistry. Histological examination of tumors for quantification

of necrosis was performed on 10% neutralized buffered formalin-fixed paraffin-embedded

sections of subcutaneous tumors stained routinely with hematoxylin and eosin. Necrotic areas

and tumor margins were outlined using Adobe Photoshop Element. These delineated areas were

used to calculate % necrosis within individual tumors.

Gamma-H2AX immunohistochemistry was performed on formalin-fixed, paraffin-embedded

sections of subcutaneous tumors. Briefly, slides were routinely deparaffinized and stained using

an automated immunohistochemical stainer (Leica, IL). Slides were treated with endogenous

peroxidase blocking and heat-induced epitope retrieval in citrate buffer for 20 minutes. A

biotinylated mouse anti-human phospho-histone H2A.X antibody was used at a 1:100 dilution

(clone JBW301, Millipore, MA) and incubated for 60 minutes. Amplification was performed

using a streptavidin-horseradish peroxidase conjugate and visualized with diaminobenzidine

(Leica). Tissues were counterstained with hematoxylin (Leica). Positive and negative controls

were normal testis. Labeled slides were digitalized to 40x (Aperio, CA), and at least 10 high-

magnification images were taken and used to quantify nuclei. Images were selected from central

portions of each tumor in areas with minimal necrosis. Only nuclei morphologically consistent

with tumor nuclei were included in the quantification, and at least 1,000 tumor nuclei were

counted for each tumor. Nuclei with morphology consistent with apoptosis (smudged labeling,

condensed chromatin) were excluded. Nuclei were stratified into three groups: nuclei with less

than 4 foci were considered negative, and nuclei with more than 4 foci were considered positive.

Within the positive nuclei, those nuclei with confluent foci were considered to have pan-nuclear

labeling.

Iida et al. 8

Flow cytometry. For ex vivo intracellular cytokine staining (ICS) tumors were harvested 3 h

after intratumoral CpG injection. After mechanical disruption, tumors were incubated in

complete RPMI1640 in the presence of GolgiPlug (1:1000 dilution, ,BD Biosciences, San Jose,

CA) at 37°C in 5% CO2 for 2 hours and stained for surface markers followed by fixation and

permeabilization with BD Cytofix/Cytoperm kit (BD Biosciences) according to the

manufacturer's instructions. Dead cells were excluded using LIVE/DEAD Fixable Dead Cell

Stain Kit (Invitrogen). For T cells ICS, untreated tumors were harvested and digested with

collagenase D and DNase I as described above. Cells were then cultured in duplicate at 1 × 107

cells/ml in a 12-well plate and stimulated with 50 ng/ml PMA (Sigma) and 750 ng/ml ionomycin

(Sigma), in the presence of brefeldin A (1:1000) at 37°C in 5% CO2. After 5 h, cells were fixed

and permeabilized with BD Cytofix/Cytoperm kit and stained with the corresponding antibodies.

For Foxp3 staining, mouse regulatory T cell staining kit (eBioscience, San Diego, CA) was used

according to the manufacturer’s instruction. To detect ROS in EL4-infiltrating cells, EL4 tumors

on B6LY5.2 mice were harvested 24 h after oxaliplatin injection. The tumors were mechanically

disrupted on ice without enzymatic digestion to avoid further generation of ROS. Cells were

stained using ROS probe from Total ROS Detection Kit (Enzo, New York, NY) and antibodies

for surface markers. Anti- TNF (MP6-XT22), IL-17a (eBio17B7), CD45 (30-F11), CD45.1

(A20), CD11c (N418), F4/80 (BM8), FoxP3 (FJK-16s) and isotype control rat IgG2a (clone

eBR2a) were purchased from eBioscience. Anti- IL-12p40 (C15.6), IFN-γ (XMG1.2), IL-4

(11B11), Ly6G (1A8), CD4 (RM4-5), CD8α (53-6.7), Gr-1 (RB6-8C5), CD11b (M1/70), I-Ab

(25-9-17), CD86 (GL1) and isotype controls rat IgG1 (clone R3-34) were purchased from BD

Biosciences. Anti- Ly6C (HK1.4) was purchased from BioLegend (San Diego, CA). Data were

analyzed by FlowJo (Tree Star, Ashland, OR).

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Administration of antibiotics, N-acetylcysteine and LPS. The mice were treated with

vancomycin (500 mg/L), imipenem/cilastatin (500 mg/L) and neomycin (1 g/L) in drinking

water as antibiotic cocktail, and the antibiotics-containing water was changed every other day

due to the short half-life of imipenem. In a different set of experiments, animals received the

antibiotics indicated above as a single drug or ampicillin (1 g/L). N-acetylcysteine solution was

added to drinking water at final concentration 5 g/L and changed every day due to short half-life

as previously described (29). For oral LPS administration, mice were orally gavaged with 25

mg/kg of ultrapure LPS from E. coli in sterile water 3 times per week, 2 weeks before and 1

week after the tumor injection.

Colonization with bacterial inocula. Mice were inoculated by gavage with A. shahii or L.

fermentum. One hour prior to the bacterial gavage mice were injected intraperitoneally with 3

mg of cimetidine HCl ( Sigma, St. Louis, MO) and 0.02 mg of sincalide (Sigma, St. Louis, MO)

in 100 ml of phosphate-buffered saline (PBS) to inhibit stomach acid secretion and empty the

gallbladder to improve colonization with stomach acid – sensitive bacteria (30). For preparation

of bacterial inocula, A. shahii (ATCC BAA-1179) was passaged onto anaerobic blood agar CDC

formulation (Remel, Lenexa, KS) (BA) and incubated for 72 h. at 37°C in an anaerobic chamber

(Shel Lab, Cornelius, OR). The bacteria were resuspended in anaerobic PBS. C57BL/6Ncr

female mice were inoculated i. g. with 200 μl of inoculum (dose range: 2 x 108 to 5 x 109 CFU).

Mice received 5 or 8 doses during the two 10-day trials. Colonization of feces was monitored,

and the cecal contents were collected at the end of the study. Pellets or cecal content were

collected in one ml anaerobic PBS tubes and transported in an anaerobic jar (MGC, Tokyo,

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Japan) with a GasPak™ EZ Anaerobe Container System sachet (BD, Franklin Lakes, NJ). The

feces or cecal contents were streaked onto BA plates in the anaerobic chamber and incubated at

37°C anaerobically for 48-96 hours. MALDI-TOF MS (Bruker, Billerica, MA) confirmed all

four of the A. shahii inoculated mice tested were colonized. No A. shahii was detected in any of

the control mice tested. L. fermentum (ATCC 9338) was grown on MRS agar (Difco, Sparks,

MD) overnight at 37°C, 5% CO2, and resuspended in PBS. Mice were inoculated i. g. with 200

μl of inoculum (5 x 108 to 3 x 109 CFU). Mice received 9 or 13 doses of L. fermentum during the

two 19-day studies. Fecal pellets before inoculation and cecal contents were collected and diluted

in PBS and streaked onto MRS and BA plates and incubated aerobically at 37°C, 5% CO2.

Presence of L. fermentum was confirmed by MALDI-TOF MS.

Microarrays. Total RNA was extracted using RNAeasy kit (QIAGEN) according to the

manufacturer’s instructions. 300ng of total RNA was amplified into complement-strand RNA

(cRNA) using WT expression kit according to the Invitrogen protocol. The quality of both total

RNA and amplified RNA was tested using a Bioanalyzer 2000 (Agilent Technologies). Sense

DNA was converted via RT reaction and labeled with biotin using Affymetrix labeling kits and

hybridized overnight in a hybridization oven on to MouseGene 1.0 ST array according to manual

factory protocol. Posthybridization arrays were stained with fluorescence on a Genechip Fluidics

Station 450 (Affymetrix) according to the respective manufacturers' instructions. Arrays were

then scanned on a GeneChip Scanner 3000 7G (Affymetrix). CEL files were uploaded into

Partek 6.0 software (Partek Ink. St.Louis, USA. Probe set expression summaries were obtained

using the RMA method (31) that includes background subtraction, the log2 transformation,

quantile normalization, and the median polish to probe level data. Comparison between the

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groups was done using two-way ANOVA Method of Moments (32) and Fisher's Least Significant

Difference as a contrast method (33). p-values from ANOVA were used to estimate the false

discovery rate using the q-value method. Genes with q<0.1, and fold change >|1.5| or >|2| were

selected for downstream analysis and visualizations. Pathway analysis was done using IPA

(Ingenuity Systems, www.ingenuity.com). Significant Gene Ontology (GO) terms and

associated genes were used to create a gene-GO terms network to identify clusters of GO terms

with overlapping common genes. Networks were visualized using Cytoscape 8.2 software (34).

GO clusters were detected using ClusterOne plugin of Cytoscape 8.2 software (35). Most

common GO terms of the identified cluster were used to create the common name for the cluster.

The microarray data were deposited in the Gene Expression Omnibus database.

Detection of platinum bound to DNA. EL-4 tumors were harvested eight hours after oxaliplatin

injection and frozen immediately. Tumors were lysed with a lysing buffer containing 100 mM

Tris, 200 mM sodium chloride, 5 mM EDTA, 0.2%SDS, and 100 µg/ml Proteinase K (Roche)

and incubated 3 hours at 55°C. After centrifugation, DNA was precipitated from the supernatant

by adding 2.5 vol. of 95% ethanol. The tube was gently inverted for 30 s, and the DNA was

spooled out and air-dried briefly. The DNA was dissolved in TE buffer (10 mM Tris-HCl, 1 mM

EDTA, pH 7.5) and RNase A (Sigma, final concentration 100 µg/ml) was added and incubated

for 1 h at 37°C. The DNA was precipitated a second time with ethanol as described above and

redissolved in TE buffer.

Platinum analysis by inductively coupled plasma mass spectrometry (ICP-MS) analysis. A

400 L aliquot of DNA sample was transferred to a pre-weighed 30 mL LDPE sample vial. The

sample weight was recorded. The sample was then digested with 1.5% HNO3: 4% HCl to 20 mL

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volume. Elemental Analysis was completed using ICP-MS. Calibration samples were prepared

from a serial dilution of a 1 ug/g and 10 ng/g Ag (NIST SRM 3140) solution. Briefly, 10, 25, 50,

75, 100, 150, 200 pg/g standards were prepared by diluting 0.100, 0.250, 0.500, 0.750, 1.00,

1.50, and 2 mL of a 1 ng/g Pt solution and was transferred to a 18 mL LDPE sample vial. The

standards were diluted to a total of 10 mL using 1.5% HNO3: 4% HCl solution, respectively.

The weight of the empty vial, the vial containing sample, and the vial containing the final

dilution was recorded. The exact concentration in each standard was determined by difference.

The two masses analyzed were Platinum (Pt, analyte) and Indium (In, internal standard).

Samples were run in triplicate, with each one or the triplicate consisting of 10 measurement

repetitions. A calibration curve was constructed from the external calibration samples. The

Platinum signal was normalized for instrumental changes by dividing the Platinum counts

(analyte) by the Indium counts (internal standard). A calibration curve was run at the beginning

and end of the sampling sequence, and the two curves were averaged together to create the curve

used to quantify the samples. The limit of detection (LOD) was determined using the method

outlined by IUPAC utilizing a LOD = 3σ 2,3. More specifically, IUPAC lists the definition of the

limit of detection as:

In the equation, cL is the lowest detectable concentration, sB is the standard deviation of the

quantitative blanks, m is the slope of the calibration curve, and k is the numerical value chosen

for the corresponding confidence interval. For determining the limit of detection for each

sample, the value of k =3 was used. The LOD for the sample run was 0.48 pg/g. The limit of

quantitation (LOQ) was also determined using the formula above with k =10. The LOQ for the

ICP-MS run was 1.6 pg/g. Concentration of platinum was expressed as ng of platinum per gram

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DNA. No platinum was detected in the untreated control tumors.

Bioluminescence assay. Twenty-four hours after oxaliplatin injection, EL4-bearing mice were

injected with luminescent probe L-012 (Wako, Richmond, VA) and imaged with IVIS Spectrum

(Xenogen, Alameda, CA) as previously described (36). L-012 shows luminescence after

chemical reaction with ROS. To calculate bioluminescence, flux (photon counts/second)

obtained 16 min after L-012 injection was divided by tumor area.

Statistical analyses. Differences in Kaplan-Meier survival curves were assessed by the log-rank

test. Tumor volumes were analyzed with a repeated measures linear mixed model and all other

outcomes with one-way ANOVA. All p values were two-tailed and were corrected for multiple

comparisons with the Bonferroni or Holm-Sidak methods. The analysis was performed with

Prism version 5.0 (GraphPad software, La Jolla, CA) or SAS version 9.2 (SAS Institute, Inc.,

Cary, NC). Statistical analysis of microarray, nanostring and microbiome datasets was performed

using Partek 6.6 (Partek Inc., St. Louis, MO, USA) and Prism version 5.0 software using one or

two-way ANOVA Method of Moments. The p values were corrected for multiple comparisons

using q-value method.

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Fig. S1. Effect of ABX treatment on tumor gene expression. Gene Ontology (GO) analysis of differentially expressed genes (q<0.1, >1.5 fold difference) in (A) MC38 (8 mice per group) and (B) EL4 tumors (5 mice per group) from H2O- or ABX-treated mice prior to any therapeutic treatment. GO analysis is visualized as a network using Cytoscape. GO terms are displayed as nodes; size is inversely proportional to log2 of the p-value. Clusters of the GO terms were determined using ClusterOne plugin of the Cytoscape. Most common terms in the identified clusters were used to label GO terms. Analysis of genes downregulated (top, blue color) or upregulated after ABX treatment (bottom, red color) is shown.

Iida et al. 15

Fig. S2 Characterization of hematopoietic cell populations in tumor bearing animals. Flow cytometric analysis of EL4 (A) or MC38 (B) tumor-infiltrating leukocyte populations (CD45+ cells) as well as cells of spleens from MC38 bearing mice (C). Data are shown, as absolute cell number of CD45+ leukocytes per mg of tumor weight or as percentages of the Ly6C+MHCII+, Ly6ChiMHCII-, F4/80hi, Ly6Ghi, CD4+ and CD8+ T-cells among total CD45+ cells. Polarized CD4 T cell subsets in the MC38 tumors were determined after ex vivo stimulation with phorbol 12-myristate 13-acetate (PMA) and ionomycin. IFN-γ+CD4+ Th1 cells, IL-4+CD4+ Th2 cells, IL-17A+CD4+ Th17 cells and FoxP3+CD25+CD4+ T-reg cells are shown as a fraction of CD4+ T-cells and IFN-γ+CD8+ Tc1 cells are shown as a fraction of CD8+ T-cells. Data are shown as individual mice and means ±SEM. *P<0.05 and **P<0.01.

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Fig. S3. ABX treatment impairs the anti-IL-10R/CpG-ODN therapy efficacy in B16 tumor-

implanted mice and is dependent on TNF. (A) H2O- or ABX-drinking B16 tumor bearing mice were treated with anti-IL-10R/CpG-ODN or left untreated (control). (B) MC38-bearing WT or Tnf-/- mice were treated with anti-IL-10R/CpG-ODN or left untreated (control). Data are shown as means ± SEM. One experiment representative of two performed is shown. * **P<0.01 and ***P<0.001.

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Fig. S4. ABX-treatment blocks intracellular cytokine production and upregulation of

costimulatory molecules in tumor infiltrating cells following anti-IL-10R/CpG-ODN

therapy. (A) Examples of the flow cytometry gating strategies utilized (MC38 tumor infiltrating cells). Representative plots shown are gated on live CD45+ cells. (B) TNF-producing MC38 tumor infiltrating cells in H2O or ABX-drinking mice: representative flow cytometry histograms (dark lines represent staining isotype control; light lines control isotype IgG/control ODN treated mice; shadowed histograms anti-IL-10R/CpG-ODN-treated mice, green H20 and orange ABX-treated mice); (C) Percent TNF-producing cells (top panel) and mean fluorescence intensity (MFI) of intracellular TNF (bottom panel) in the indicated MC38-infiltrating cell subsets isolated from H2O- or ABX-drinking mice treated with anti-IL-10R/CpG-ODN or control isotype IgG/control ODN and harvested 3 h after ODN injection. (D) Representative plots of CD86 expression (MFI shown in upper right corner) on CD11c+MHCII+ cells in MC38 tumors harvested 12 h post anti-IL-10R/CpG-ODN or control isotype IgG/control ODN injection. Blue: isotype control; red, anti-CD86 antibody. (E) Representative plots (left, dark lines represent staining isotype control; light lines isotype IgG/control ODN treated mice; shadowed histograms anti-IL-10R/CpG-ODN-treated mice, green H20- and orange ABX-treated mice) and percentages of IL-12p40-producing cells (right) are shown. Data in panel C and E are shown as individual mice and means ±SEM. *P<0.05, **P<0.01 and ***P<0.001.

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Fig. S5. Effect of ABX-treatment on tumor gene expression induced by anti-IL-10R/CpG-

ODN therapy. mRNA expression of selected genes was determined by Nanostring nCounter gene expression assay in MC38 tumors isolated from H2O- or ABX-treated mice subjected to anti-IL-10R/CpG-ODN or not and harvested 3 h after CpG-ODN injection. Data are shown as individual mice and means ±SEM. *P<0.05, **P<0.01 and ***P<0.001.

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Fig. S6. TNF production by tumor infiltrating cells is restored by LPS gavage in ABX-

treated mice and TLR2-deficiency does not affect the effectiveness of anti-IL-10R/CpG-

ODN therapy. (A) Intracellular TNF (flow cytometry) in MC38-infiltrating CD45+ cells isolated 3 h after CpG-ODN injection from H2O- or ABX-treated mice subjected to anti-IL-10R/CpG-ODN therapy and orally gavaged or not with LPS (25 mg/kg, 3 times per week, 2 weeks before and 1 week after tumor injection). Data show individual mice and means ±SEM. (B) MC38 tumor growth in H2O or ABX-treated WT mice or Tlr2-/- mice treated or not with anti-IL-10R/CpG-ODN. *P<0.05, **P<0.01 and ***P<0.001.

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Fig. S7. Composition of fecal microbiota segregates mice with high and low intratumoral

TNF production. 16S rDNA data obtained from sequencing fecal samples from H2O-drinking mice collected prior to anti-IL-10R/CpG-ODN therapy was analyzed using unweighted Unifrac analysis and visualized using Principal Component Analysis (PCA). A gradient from blue to red represents relative mRNA Tnf levels from low to high respectively, Tnf levels were estimated using RT-PCR. Left panel shows PCA axis 1 vs axis 2 and right panel axis 1 vs axis 3. One representative of 3 experiments is shown.

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Fig. S8. Bacterial diversity analysis. Fecal bacterial 16S rDNA was sequenced in water treated only group (H2O), ABX recovery group (1, 2 and 4 weeks post ABX cessation) and in single antibiotics treated groups [ampicillin (A), imipenem (I), neomycin (N), vancomycin (V)]. Chao (A) and Inverse Simpson (B) indexes of bacterial diversity are shown for individual mice. Red lines represent means ±SD.

Log2 reads/10,000 Figure S9

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Fig. S9. Taxonomic tree of fecal bacteria identified in all 16S rDNA sequencing experiments

part of this study. Bacteria names in the boxes indicate from left to right: Kingdom, Phylum, Class, Order, Family and Genus. The same taxonomic tree was used to illustrate the microbiota changes in Fig. S10, S12, and S13. Bars on the right side indicate genus abundance (log2 transformed number of reads per 10,000) in H2O-drinking mice.

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Fig. S10. Recovery of microbiota post-ABX treatment. Fecal samples were collected prior to 3-weeks ABX treatment and 1, 2 and 4 weeks post cessation of ABX treatment. 16S rDNA of the identified bacteria was compared between the groups at every taxonomical level and displayed as taxonomical tree. Taxonomical tree branches correspond to the one displayed in Fig.S9. Size of the nodes in the tree labeled “H2O vs 1w” is proportional to number of log2 reads of bacterial phylotypes in H2O drinking mice. Red nodes indicate significantly (q<0.1) higher number of reads in H2O drinking mice compared to mice 1w post ABX cessation, and conversely, blue nodes, lower. Size of the nodes in the tree labeled “1w vs H2O” is proportional to number of log2 reads of bacterial phylotypes in feces of mice 1w post ABX cessation. Red nodes indicate significantly (q<0.1) higher number of reads 1w post ABX cessation compared to H2O drinking mice, and conversely, blue nodes indicate lower number of reads. Size of the nodes in the tree labeled “2w to 1w” is proportional to number of log2 reads of bacterial phylotypes in feces of mice 2w post ABX cessation. Red nodes indicate significantly (q<0.1) higher number of reads 2w post ABX cessation compared to 1w post ABX cessation, and conversely, blue nodes indicate lower number of reads. Size of the nodes in the tree labeled “3w to 1w” is proportional to number of log2 reads of bacterial phylotypes in feces of mice 3w post ABX cessation. Red nodes indicate significantly (q<0.1) higher number of reads 3w post ABX cessation compared to 1w post ABX cessation, and conversely, blue nodes, indicate lower number of reads.

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Fig. S11. Effect of single antibiotics on fecal microbiota composition and intratumoral Tnf

mRNA expression after anti-IL-10R/CpG-ODN therapy. Fecal microbiota and response to aIL-10R/CpG-ODN treatment was analyzed in MC38-bearing mice drinking water (H2O), water containing the antibiotic cocktail including vancomycin, imipenem and neomycin (VIN), or the single antibiotics vancomycin (V), imipenem (I), neomycin (N), and ampicillin (A) for 3 weeks. (A) The number of eubacteria 16S rRNA gene copy in feces collected before anti-IL-10R/CpG-ODN treatment was determined by real-time PCR. (B) Heatmap of OTUs (97% similarity) of fecal microbiota was normalized to copy number of 16S per gram of feces. OTUs represented by <0.1% of total reads were removed from the analysis. (C) Fecal microbiota composition was analyzed by principal component analysis of unweighted Unifrac distances. (D) Tnf mRNA expression (real-time PCR, values on Y-axis represent 2- Ct) in tumors from the same animals treated with anti-IL-10R/CpG-ODN and harvested 3 h after CpG injection. In (A) and (D) data show individual mice and means ±SEM. *P<0.05, **P<0.01 and ***P<0.001.

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Fig. S12. Changes of bacterial composition due to single antibiotic treatments. Fecal samples were collected 3-weeks after the indicated single antibiotic treatment. 16S rDNA of the identified bacteria was compared between the groups at every taxonomical level and displayed as taxonomical tree. Taxonomical tree branches correspond to the one displayed in Fig.S9. Size of the nodes in the trees is proportional to number of log2 reads of bacterial phylotypes in feces of mice treated with the indicated antibiotic. Red nodes indicate significantly (q<0.1) higher number of reads in single antibiotic treated mice compared to normal H2O drinking, and conversely, blue nodes lower reads number.

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Fig. S13. Bacterial genera correlating with intratumoral Tnf mRNA expression after anti-

IL-10R/CpG-ODN treatment in different datasets. (A) Visualization of fecal bacterial genera showing positive (red circles) or negative (green circles) correlation (Spearman's rank correlation, q<0.1) with intratumoral Tnf expression levels in water only group (H2O), antibiotic recovery group (ABX recovery) and single antibiotics treated group (Single ABX). Gram negative bacteria are labeled “G-” and gram positive bacteria “G+”. Fecal samples were collected prior to anti-IL-10R/CpG-ODN therapy and Tnf mRNA expression levels 3 h post anti-IL-10R/CpG-ODN treatment were estimated by RT-PCR. (B) The same bacteria are represented as taxonomical tree with distribution of the branches corresponding to the labels in Fig. S9. Size of the circles is proportional to log2 number of reads found for all datasets combined. Red color of the nodes indicates positive and green indicates negative correlations (q<0.1) with intratumoral Tnf expression levels.

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Fig. S14. Correlation with TNF production and recovery dynamics of selected bacteria

genera after ABX withdrawal. (A) Correlation between Alistipes, Ruminococcus and Lactobacillus abundance and anti-IL-10R/CpG induced tumor TNF production analyzed in H2O-drinking mice. (B) Abundance of Alistipes, Ruminococcus and Lactobacillus genera in H2O-drinking mice or in ABX-treated mice 1, 2 or 4 weeks after cessation of ABX treatment. Data are shown as individual mice values and mean ± SEM, counts were normalized to 10,000 reads per sample. *P<0.05, **P<0.01 and ***P<0.001.

Iida et al. 29

Fig. S15. Inoculation with individual bacterial species affects TNF production by tumor

associated myeloid cells in response to anti-IL-10R/CpG-ODN. Control H2O-drinking mice or mice one week after cessation of ABX treatment were exposed to anti-IL-10R/CpG-ODN therapy. (A) A group of ABX pre-exposed mice was subjected to oral gavage with A. shahii. (B) A group of control H20-drinking mice was subjected to oral gavage with L. fermentum. Mice in both groups were sacrificed 3 h after CpG-ODN treatment and intracellular TNF measured in the indicated tumor-associated myeloid cell subsets. Data show individual mice and means ±SEM from combined data from 2 experiments (A) or one representative experiment out of 2 performed (B). *P<0.05 and **P<0.01.

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Fig. S16. Impaired anti-tumor effect of platinum compounds in ABX-treated and in GF

mice. (A) MC38 tumor growth after oxaliplatin treatment of individual animals from experiment shown in Fig. 4A. (B) EL-4 tumor growth in specific pathogen-free (SPF) or germ-free (GF) mice treated with oxaliplatin or PBS (control). (C) H2O- or ABX-treated MC38-bearing mice were intraperitoneally injected with oxaliplatin (10 mg/kg) or PBS (control). Tumor growth (left) and survival (right) are shown. (D) Subcutaneous EL4 tumor-bearing H2O- or ABX-treated mice were treated with cisplatin (5 mg/kg) or PBS (control). Data in A, B and C are shown as mean ± SEM from one experiment with 5 to 10 mice/group representative of 2 or more experiments; tumor growth (left panels) and survival (right panels) are shown. *P<0.05, **P<0.01, ***P<0.001

Iida et al. 31

Fig. S17. ABX limit the changes in tumor gene expression induced by oxaliplatin treatment. Gene Ontology (GO) analysis of differentially expressed genes (q<0.1, >2 fold difference) in EL4 tumors from H2O- vs ABX-drinking mice 18h post Oxaliplatin treatment from the experiment shown in Fig.4C. GO analysis of genes expressed significantly higher (A) in H2O-drinking mice or in ABX-drinking mice (B). GO analysis is visualized as a network using Cytoscape. GO terms are displayed as nodes; size is inversely proportional to log2 of the p-value. Clusters of the GO terms were determined using ClusterOne plugin of the Cytoscape. Most common terms in the identified clusters were used to label GO terms.

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Fig. S18. Expression of selected genes in EL4 tumors from H2O- or ABX-exposed mice

treated or not with oxaliplatin. mRNA gene expression (Nanostring nCounter gene expression assay) was determined in EL4 tumors harvested 48 h after oxaliplatin or PBS injection. Y-axis represents normalized counts. Data are shown as individual mice and means ±SEM. *q<0.05, ** q<0.01 and ***q<0.001.

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Fig. S19. The antitumor effect of oxaliplatin is reduced by NAC and requires MyD88 but

not TLR4, IL-1R, IL-18R or TNF. (A) EL4 tumor growth in WT and Tnf-/- mice treated with oxaliplatin or PBS (control). (B) EL4-bearing H2O- or N-acetylcysteine (NAC)-drinking mice were treated with oxaliplatin or PBS (control). Tumor growth (left) and survival (right) are shown. (C) Absolute cell number and frequencies (flow cytometry) of CD11b+Ly6GhiLy6Cint and CD11b+Ly6G-Ly6Chi cells in total CD45+ cells in the blood and EL4 tumors harvested from anti-Gr-1 antibody- or isotype control-injected mice. (D) EL4-bearing WT, Myd88-/-, Tlr4-/-, l1r-/- and Il18r-/- mice were treated with oxaliplatin or PBS (control). Tumor growth (left panels) and survival (right panels) are shown. A, B and D tumor growth data are means ±SEM from one representative experiment with 5-10 mice/group out of 2 or more performed. *P<0.05, **P<0.01 and ***P<0.001.

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Fig. S20. ABX treatment decreases tumor DNA damage induced by oxaliplatin but not the

formation of platinum adducts. (A) EL4 tumors from H2O- or ABX-treated mice were analyzed for dsDNA damage after oxaliplatin treatment using gamma-H2AX immunohistochemical labeling to indicate foci of damage. Nuclei with <4 foci were considered negative and positive nuclei were grouped as having >4 foci or pan-nuclear labeling (uncountable foci) as shown in the right inset. Data (means ± SEM) are from one experiment representative of two performed. **P<0.01. (B) Platinum (Pt) bound to EL4 tumor DNA in control PBS-injected mice or 8 h post-oxaliplatin injection was measured by IPS-mass spectrometry. Data shown as individual mice and means ± SEM from 2 experiments combined.

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