www.sciencemag.org/cgi/content/full.1233665/DC1

Supplementary Materials for

Type I Interferon Suppresses Type II Interferon–Triggered Human

Anti-Mycobacterial Responses

Rosane M. B. Teles, Thomas G. Graeber, Stephan R. Krutzik, Dennis Montoya, Mirjam

Schenk, Delphine J. Lee, Evangelia Komisopoulou, Kindra Kelly-Scumpia, Rene Chun,

Shankar S. Iyer, Euzenir N. Sarno, Thomas H. Rea, Martin Hewison, John S. Adams,

Stephen J. Popper, David A. Relman, Steffen Stenger, Barry R. Bloom, Genhong Cheng,

Robert L. Modlin*

*To whom correspondence should be addressed. E-mail: rmodlin@mednet.ucla.edu Published 28 February 2013 on Science Express

DOI: 10.1126/science.1233665

This PDF file includes:

Materials and Methods

Figs. S1 to S22

References

1

Supplementary Materials for

Type I interferon suppresses Type II interferon-triggered human anti-

mycobacterial responses

Rosane M.B. Teles, Thomas G. Graeber, Stephan R. Krutzik, Dennis Montoya, Mirjam

Schenk, Delphine J. Lee, Evangelia Komisopoulou, Kindra Kelly-Scumpia, Rene Chun,

Shankar S. Iyer, Euzenir N. Sarno, Thomas H. Rea, Martin Hewison, John S. Adams,

Stephen J. Popper, David A. Relman, Steffen Stenger, Barry R. Bloom, Genhong Cheng

and Robert L. Modlin

correspondence to: rmodlin@mednet.ucla.edu

This PDF file includes:

Materials and Methods

Figs. S1 to S22

Materials and Methods

Patients and clinical specimens

Patients with leprosy were classified according to the criteria of Ridley and

Jopling (30). The designation of tuberculoid leprosy (T-lep) included patients that were

classified clinically as borderline tuberculoid, “BT”, and the designation of lepromatous

leprosy (L-lep) only included patients classified as “LL”. All T-lep and L-lep skin biopsy

specimens were taken at the time of diagnosis, prior to initiating treatment. Reversal

reaction (RR) skin biopsy specimens were considered upgrading reactions; consistent

with activation of cell-mediated immune responses against M. leprae towards the

2

tuberculoid pole (usually this reaction occurs during treatment, but can also occur

spontaneously). Specimens were embedded in OCT medium (Ames, Elkhart, IN), snap

frozen in liquid nitrogen and stored at -80C. All leprosy patients were recruited with

approval from the Institutional Review Board of University of Southern California

School of Medicine and the Institutional Ethics Committee of Oswald Cruz Foundation,

as well as the University of California, Los Angeles.

Antibodies and cytokines

Antibodies used for immunohistochemistry were as follows: CD3, CD163 and

CD209 (BD Pharmingen, Franklin Lakes, NJ), IFN-β and IFNAR1 (PBL Interferon

Source, Piscataway, NJ), CD14 and IL-10 (Invitrogen, Carlsbad, CA and BD

Biosciences, San Diego, CA) and IgG controls (Sigma, St. Louis, MO). The following

human recombinant cytokines were used for in vitro assays, IFN- β (PBL Interferon

Source), IFN-γ (BD Biosciences) and IL-10 (R&D Systems, Minneapolis, MN).

Blocking antibodies included anti-IL-10 (BD Pharmingen) and anti-IFNAR2

(Calbiochem, San Diego, CA).

Microarray data analysis

Gene expression profiles of mRNAs derived from skin biopsy specimens of 24

leprosy patients (T-lep, n = 10; L-lep, n = 6; RR, n = 7) were determined using

Affymetrix Human U133 Plus 2.0 microarrays and analyzed as previously described (31).

Principal component analysis (PCA) was performed using Partek v6.4. Unsupervised

clustering analysis of genes with coefficient of variance ≥ 1.0 and intensity average ≥100

3

was performed using Cluster and Treeview (32) and further biofunctional analyses were

performed using Ingenuity Pathways Analysis Software (IPA). The raw gene expression

data analyzed in this study are available online through the Gene Expression Omnibus

database (http://www.ncbi.nlm.nih.gov/geo/) accession number GSE17763.

In a separate experiment, CD14+ monocytes were enriched by negative selection

of PBMC from four healthy donors using EasySep (Stem Cell Technologies, Vancouver,

Canada). The negatively selected cells were analyzed by flow cytometry and found to be

>90% CD14+. The monocytes were cultured in the presence or absence of lL-10

(10ng/ml) for 24h. Gene expression profiles of mRNAs derived from the untreated or

treated monocytes were determined as described above. Expression Omnibus database

(http://www.ncbi.nlm.nih.gov/geo/) accession number is GSE43700.

Identification of IFN regulated genes

Supervised analyses were performed to identify Type I and Type II IFN regulated

genes. Differentially expressed genes between T-lep and L-lep leprosy groups were

identified by pairwise comparison using the criteria of a p ≤ 0.05 and fold change (FC) ≥

1.5. A list of genes specifically induced or repressed by only IFN-, IFN-β or IFN-γ was

derived from the gene expression profile data of IFN-treated PBMC (6). These IFN

downstream gene targets were then integrated with the leprosy lesion microarray data to

determine the differential expression of IFN-regulated genes in different disease forms.

A second IFN-oriented analysis was performed using the IFN target genes as defined by

the interferome database (7). Two microarrays using peripheral blood of patients with

tuberculosis, active and latent tuberculosis (TB1) (3) and active tuberculosis patients and

4

healthy donors (TB2) (12) were also compared with the microarray data derived from

IFN-stimulated PBMC (6). Type I interferon suppresses Type II interferon-triggered

human anti-mycobacterial responses. Enrichment analysis of the overlap in IFN target

genes between the different leprosy and TB datasets was performed using the

hypergeometric distribution to control for differences in the overall number of

differentially expressed genes. The hypergeometric distribution (hypergeometric test) is

equivalent to the one-tailed version of Fisher's exact test. These tests determine the

degree the observed amount of enrichment is greater than expected, and together these

are two of the most common enrichment statistics used in bioinformatic analyses (33,

34). For the IFN-specific enrichment statistical analysis of Figure 1C and 1E, IFN-

induced and -repressed genes were individually analyzed for each group (as shown in

Supplemental Figure 2 and 6) and statistical analysis was performed using a one-tailed

Fisher’s exact test and Bonferroni multiple hypothesis testing correction. The IFN

summation score was calculated using a gene voting approach based on the sum of the

signed log ratio relative expression of the IFN-β specific and IFN-γ specific induced

(positive in the summation) and repressed (negative) genes in each individual lesion.

Noisy and non-discriminatory genes were excluded from the IFN summation scores,

namely genes that did not show differential expression in either direction between the

patient subtypes (ANOVA p-value > 0.05). IFN-β specific genes in common between L-

lep lesions and active TB blood, TB1 and TB2, were integrated with the IL-10 vs. media

monocyte gene expression profile. A flow diagram for the gene expression profile and

integrative genomics analyses is shown in Supplemental Figure 1.

5

Immunoperoxidase labeling and confocal microscopy.

Frozen tissue sections were blocked with normal horse serum before incubation

with monoclonal antibodies (mAbs) for 60 min, followed by incubation with biotinylated

horse anti-mouse IgG for 30 min. Slides were counterstained with hematoxylin and

mounted in crystal mounting medium (Biomeda, Foster City, CA) and were visualized

using the ABC Elite system (Vector Laboratories, Burlingame, CA).

To colocalize cytokines with specific cell markers two-color immunofluorescence

with confocal microscopy was used. Immunofluorescence was performed by serially

incubating cryostat tissue sections with mouse anti-human mAbs of different isotypes,

anti-CD3 (IgG1), anti-CD14 (IgG1), anti-CD163 (IgG1), anti-CD209 (IgG2b), anti-IFN-

β (IgG1 and IgG2a) and anti-IL-10 (IgG1) followed by incubation with isotype-specific,

fluorochrome (A488 or A568)-labeled goat anti-mouse immunoglobulin antibodies

(Molecular Probes, Carlsbad, CA). Controls included staining with isotype-matched

antibodies as described previously (35). Nuclei were stained with DAPI (4',6'-diamidino-

2-phenylindole). Double immunofluorescence of skin sections was examined using a

Leica-TCS-SP MP inverted single confocal laser-scanning and a two-photon laser

microscope (Leica, Heidelberg, Germany) at the Advanced Microscopy/Spectroscopy

Laboratory Macro-Scale Imaging Laboratory, California NanoSystems Institute,

University of California at Los Angeles.

Bacterial and human cell culture and treatment

M. leprae was grown in the footpad of nu/nu mice, as described previously (36)

and was provided by Dr. James L. Krahenbuhl of National Hansen's Disease Programs,

6

Health Resources Service Administration, Baton Rouge, LA. Sonicated M. leprae was

provided by Patrick Brennan of the Department of Microbiology, Immunology &

Pathology, Colorado State University, Fort Collins, CO.

Whole blood from healthy donors was obtained with informed consent (UCLA

I.R.B. #92-10-591-31). PBMCs were isolated using Ficoll (GE Healthcare, Piscataway,

NJ) gradient centrifugation. Monocytes were purified by plastic adherence for two hours

in RPMI 1640 (Invitrogen) supplemented with 1% fetal calf serum (Omega Scientific,

Tarzana, CA). Non-adherent cells were removed via vigorous washing and adherent cells

were cultured in RPMI supplemented with antibiotics and 10% fetal calf serum, or 10%

vitamin D-sufficient (100 nM) human serum for antimicrobial peptide gene expression

studies or M. leprae infection studies. Human adherent monocytes were cultured in

RPMI with 10% FCS (Omega Scientific) in the presence or absence of live M. leprae

(MOI 10:1), sonicated M. leprae (10μg/ml) for 6h and 24h for IFN-β mRNA detection by

qPCR and IFN-β and IL-10 protein detection by ELISA, respectively. In addition,

neutralizing anti-human IFNAR2 (10μg/ml; Calbiochem) or a isotype control were used

in combination with live M. leprae (MOI 10:1) or sonicated M. leprae (10μg/ml) for 24h,

then supernatants were collected for measurement of IL-10 by ELISA. Human adherent

monocytes were cultured in RPMI with 10% FCS (Omega Scientific) in the presence or

absence of IFN-β (200U/ml) for 24h and supernatants were collected for IL-10 detection

by ELISA. In a separate set of experiments, monocytes were stimulated with IFN-β

(200U/ml), IFN-γ (273U/ml) or IL-10 (10ng/ml). After stimulation the cells were

cultured for 3h or 24h. In addition, neutralizing anti-human IL-10 (10μg/ml; BD

7

Pharmingen) or isotype control was used in combination with IFN-γ and IFN-β for 24h

and total RNA was isolated to measure antimicrobial pathway gene expression levels.

Real-time quantitative PCR (qPCR)

Total RNA was isolated from 10 L-lep, 10 T-lep and 10 RR skin lesions, and

cDNA was prepared as described previously (37). TaqMan gene expression assays were

used for detection of IFN-β, IFN-γ, IFNAR1, IL-10, OAS1, OAS2 and GAPDH

(glyceraldehyde-3-phosphate dehydrogenase; Applied Biosystems, Foster City, CA).

The relative quantities of the gene tested per sample were calculated against the GAPDH

mRNA using the CT formula as previously described (11).

To analyze cytokine and antimicrobial peptide mRNA levels of human

monocytes, total RNA was isolated, cDNA synthesized and qPCR performed to measure

IFN-β, cathelicidin (CAMP), CYP27B1, DEFB4, VDR and h36B4 as previously reported

(15). The relative quantities of the gene tested per sample were calculated against h36B4

using the delta cycle threshold formula as previously described (38). The data were

normalized to the media control samples.

Antimicrobial assays

To measure IFN-induced antimicrobial activity in M. leprae-infected monocytes,

we adapted the previously described real time PCR based method for the assessment of

bacterial viability, which compares 16S RNA levels to genomic DNA levels (15, 21).

Given that M. leprae itself induced IFN-β, monocytes were pre-treated with IFN-γ, and

then infected with M. leprae at an MOI of 10:1 overnight. This resulted in the infection

8

of approximately 80% of the monocytes at 2.1 ± 0.4 bacteria per cell. Subsequently, the

monocytes were treated with various cytokines and M. leprae viability was measured

after five days. Monocytes were isolated as described above, pre-treated with IFN-γ

(273U/ml) for 24 h and infected overnight with M. leprae at an MOI of 10:1 followed by

stimulation with IFN-β (200U/ml), IFN-γ (273U/mL), IL-10 (10ng/ml), VDR antagonist

ZK 159 222 (VAZ) (10−8

M) or medium for three days. We have used VAZ previously

to establish the role of the VDR in the host antimicrobial response (1, 11, 16). Monocyte

viability was measured before infection and five days after infection by Trypan blue

exclusion and was always ≥90%. In addition, neutralizing anti-human IL-10 antibody

was added before M. leprae infection and in combination with IFN-γ and IFN-β post-

treatment. Total RNA and DNA was isolated as previously described (15). cDNA was

synthesized from the total RNA as described (11) for both human and bacterial mRNAs.

The bacterial 16S rRNA and genomic element DNA (RLEP) levels were then assessed

using real time PCR. In order to normalize for the total number of monocytes present in

the culture, 36B4 was also evaluated. Comparison of the bacterial DNA to the

mammalian 36B4 levels was used to monitor infectivity between all the conditions in the

assay as well as PCR quality. The 16S rRNA and genomic DNA values were calculated

using the CT analysis, with the bacterial DNA value serving as the housekeeping

gene. The M. leprae 16S rRNA and M. leprae repetitive genomic element (RLEP)

primers used were as previously described (15, 21).

ELISA

9

Secreted IFN-β and IL-10 proteins in the supernatant were measured using

VeriKineTM

Human Interferon-Beta ELISA Kit (PBL Interferon Source), and IL-10

antibody pair (Invitrogen) following manufacturer protocols.

Measurement of vitamin D metabolism

Human monocytes were treated with IFN-γ (500U/ml), IL-10 (10ng/ml) and IFN-

γ+ IL-10 in 10% FCS for 48h, followed by incubation with a radiolabeled metabolite of

cholecalciferol (D3), 25 (OH)D3 for 5h in serum-free media. The measurement of

25(OH)D3 bioconversion to 1,25(OH)2D3 or 24,25(OH)2D3 was performed by HPLC as

previously described (17).

Statistical analysis

Results are reported as pooled data from an entire series of experiments, and

described as mean ± the SEM unless otherwise indicated. GraphPad Prism 5 software

was used for testing of parametric distribution and statistical analysis. We applied the log

transformation (log(x+1)) and performed Kolmogov Smirnov normality test and equality

of variances test (Bartlett's test) on the transformed values to verify whether the data were

parametrically distributed. For comparison between three different groups found to have

a parametric distribution, statistical analysis was performed by one-way analysis of

variance ANOVA followed by the Newman-Keuls multiple comparison post test. For

comparison between three different groups found to have a nonparametric distribution,

statistical analysis was performed by Kruskal-Wallis analysis of variance by ranks test

followed by Dunn's multiple comparison test. The two-tailed student’s t-test was used

10

when individual comparisons between two groups were performed. Individual details of

statistical analyses are explained in the figure legends.

11

Fig. S1.

Leprosy test set23 leprosy skin biopsies10 T-lep, 6 L-lep and 7 RR

GSE17763

L-lep vs. T-lep vs. RRdifferential gene expression

(p < 0.05, fold > 1.5)

PCA and clustering analysisFigure 1A and 1B

IFN-induced gene expression profiles in PBMCWaddell et al., 2010

GSE17762

Determined genes that were specifically modulated by IFN- , IFN-b and IFN-g

and examined their expression in

leprosy lesionsFigures 1C and 1D

TB patients whole blood gene expression profiles

TB 1: active vs. latent (Berry et al., 2010)

GSE19491

TB 2: active vs. normal (Maertzdorf et al. 2012)

GSE 34608

Determined genes that were specifically modulated by IFN- , IFN-b

and IFN-g and examined their expression in TB patients blood

Figure 1E

Published TB gene expression datasets

Identification of IFN-b specific genes in blood in common between L-lep, and active tuberculosis (TB1 and TB2) profiles

Integrative genomics

CD14+ monocytesIL-10 gene expression profile

IL-10 vs. media

GSE 43700

Determined which of the IFN-b specific genes expressed in common between L-lep, active

TB1, and TB2, were also induced by IL-10

Figure 1F

Integrative genomics

Validation leprosy lesions

qPCR10 T-lep, 10 L-lep and 10 RR

Figure 2A and 3A

Immunohistochemistry4 T-lep, 4 L-lep and 4 RR

Figure 2B, 2C, 3B, 3C and 3D

Integrative genomics

Supplemental Figure 1. Flow diagram for analysis of gene expression profiles.

12

Fig. S2

0

10

20

30

40

IFN-

induced genes in PBMC repressed genes in PBMC

# g

en

es

ex

pre

ss

ed

in

le

sio

ns

# g

en

es r

ep

ressed

in

lesio

ns

Sig

ne

d lo

g1

0 e

nri

ch

me

nt

p-v

alu

e

IFN-b IFN-g IFN- IFN-b IFN-g

IFN-

induced genes in PBMC repressed genes in PBMC

IFN-b IFN-g IFN- IFN-b IFN-g

L-lep

T-lep

L-lep

T-lep

L-lep

T-lep

L-lep

T-lep

0

10

20

30

40

Sig

ned

lo

g10 e

nri

ch

men

t

p-v

alu

e

Supplemental Figure 2. Type I and Type II IFN specific genes had

a differential distribution in leprosy skin lesions. IFN-, IFN-b and

IFN-g -specif ic genes (induced or repressed) identif ied in healthy

human PBMC were integrated with leprosy lesion transcripts (6 L-lep

and 10 T-lep; fold change ≥ 1.5 and p ≤ 0.05). Dotted lines indicate

hypergeometric enrichment p-value of 0.05 (log p=1.3). Bonferroni

multiple hypothesis test correction was applied for each group.

-2

-1

0

1

2

3

4

5

6

I FNa I FNb I FNg

0

1

2

3

4

5

6

I FNa I FNb I FNg

13

Fig. S3

IFN-b (only) IFN- (only)

IFN-g (only)

L-lep33

13 76

100

00

0

3

1 1 1

3

7 10

00

0

T-lep

RR

Inducible genes

IFN-b (only) IFN- (only)

IFN-g (only)

L-lep24

6 34

000

00

0

0

0 0 0

5

9 52

00

0

T-lep

RR

Repressed genes

Supplemental Figure 3. Venn Diagram of IFN-, IFN-b and

IFN-g specific genes in leprosy lesions. IFN-, IFN-b and IFN-g

specif ic genes induced or repressed in L-lep, T-lep and RR

lesions (6 L-lep, 10 T-lep and 7 RR; FC≥ 1.5, p≤ 0.05).

14

Fig. S4.

>4 4-2.5 >4 4-2.5

L-lep/T-lep T-lep/L-lep

*

0

2

4

6

*

Interferome data baseF

old

en

ric

hm

en

t in

le

sio

n

(ob

serv

ed

/exp

ecte

d)

FC:

IFN type I

IFN type I/II

L-lep T-lep

IFN type I

IFN type I/II

L-lep T-lep

>4 4-2.5 >4 4-2.5

L-lep/T-lep T-lep/L-lep

Supplemental Figure 4. Type I regulated genes upregulated in

L-lep lesions. Type I and Type II regulated genes were classif ied in

the leprosy lesion transcripts using Interferome database (6 L-lep

and 10 T-lep; fold change ≥ 2.5 and p ≤ 0.05). Dotted lines indicate

either the expected fold enrichment of one (upper panel), or the

hypergeometric enrichment p-value of 0.05 (log p=1.3, lower panel).

Bonferroni multiple hypothesis test correction was applied for each

group.

-8

-6

-4

-2

0

2

4

6

8

>4 >2. 5 >4 >2. 5

L- l ep T- l ep

Fo

ld e

nri

ch

me

nt/

de

-en

ric

hm

en

t(l

og

p-v

alu

e)

15

Fig. S5.

IFN-g

IFN-b

MS4A7IFNGR1GLIPR1ALOX5IGHG1CYBAGPR35IGF2BP3SERPINB6KRR1MAN1A2

Expression in leprosy lesions

Repressed by IFN in control PBMC

IFN-b

T-lep L-lep RR

Expression in leprosy lesions

Induced by IFN in control PBMC

MS4A7CCRL2LILRB1CD163MARCKSITGAXCCR1MXL1CENTA2GNPDA1LYNC3AR1NEK4RRBP1SNX2CD59ALOX5B3GNT2NBNTANKRIPK3ANXA4PFKFB3SDSFPRL1CCL4, TLR1CEP110TARP

T-lep L-lep RR

NLRP1GSTM5UBDMMP25VSNL1LTMK2GBP1GBP2GBP6CYP24A1CYP27B1VDRCCL21CXCL2CXCL11

Regulatory cytokines

Antimicrobial

chemokines

IFN-g GBP family

Vit D genes

PRR receptors

Type I IFN

signature genes

B cell genes

OAS1OAS2MX2IFNAR1TLR4TLR7IL-10IL-27CD80CD83CD86TGFBR1BCL2L1XIAPBLNKBAFFVAV1

Costimulatory

molecules

IFN-b

Supplemental Figure 5. IFN-b and IFN-g specific genes distribution in leprosy lesions. IFN-b and IFN-g

induced and repressed specif ic genes distribution in 6 L-lep, 10 T-lep and 7 RR lesions (FC≥ 1.5, p≤ 0.05).

Genes listed in black are common between T-lep and RR lesions. IFN-b induced genes upregulated in L-lep

include Type I interferon genes, PRR receptors, regulatory cytokines and B cells genes. IFN-g induced genes

upregulated in T-lep and RR include GBP family, vitamin D (Vit D) genes and antimicrobial chemokines.

16

Fig. S6

0

5

10

15

20

25

30

I FNa onl y I FNb onl y I FNg onl y

TB ACT

TB LTN

repressed genes in PBMC# g

en

es r

ep

ressed

in

lesio

ns

IFN- IFN-b IFN-gIFN-

induced genes in PBMC

# g

en

es

ex

pre

ss

ed

in

le

sio

ns

IFN-b IFN-g0

5

10

15

20

25

30

I FNa onl y I FNb onl y I FNg onl y

TB ACT

TB LTN

Supplemental Figure 6. Type I and Type II IFN specific genes

distribution in the blood of active and latent tuberculosis. IFN-,

IFN-b and IFN-g -specif ic genes (inducible or repressed) identif ied in

healthy human PBMC were integrated with tuberculosis whole blood

transcripts (fold change ≥ 1.5 and p ≤ 0.05). Dotted lines indicate

hypergeometric enrichment p-value of 0.05 (log p=1.3). Bonferroni

multiple hypothesis test correction was applied for each group.

Sig

ned

lo

g10 e

nri

ch

men

t p

-valu

e

IFN-

induced genes in PBMC

IFN-b IFN-g-2

0

2

4

6

8

10

12

I FNa I FNb I FNg

TB ACT

TB LTN

repressed genes in PBMC

IFN- IFN-b IFN-gSig

ned

lo

g10 e

nri

ch

men

t p

-valu

e

-2

0

2

4

6

8

10

12

I FNa I FNb I FNg

TB ACT

TB LTN

17

Fig. S7

IFN- IFN-b IFN-g

Fo

ld e

nri

ch

me

nt

(ob

se

rve

d/e

xp

ec

ted

)

IFN- IFN-b IFN-gSig

ne

dlo

g1

0 e

nri

ch

me

nt p

-valu

e

0

0.5

1

1.5

2

2.5

3

I FNa I FNb I FNg

TB LTN

TB ACT

-2

0

2

4

6

8

10

12

I FNa I FNb I FNg

TB LTN

TB ACT

Induced IFN-b specific genes

L-lep TB1

20

20

TB2

14 16

14

16

3

Total induced genes

L-lep TB1

790

3205

TB2

888 720

254

470

977

ELF1

IL-27

MS4A7

NBN

OAS2

SSB

USP15

CCR1

CD59

CD163

FPR2

PFKFB3

TANK

TLR1

TLR4

TLR7

IL-1

0 p

rofi

le

(A) (B)

Supplemental Figure 7. Common Type I IFN signature in the blood of active TB patients and L-lep

lesions. (A) Enrichment analysis of overlap between IFN-specif ic genes and tuberculosis whole blood

transcripts associated with disease state (active (ACT), latent (LTN); fold change ≥ 1.5 and p ≤ 0.05).

Dotted lines indicate either the expected fold enrichment of one (upper panel), or the hypergeometric

enrichment p-value of 0.05 (log p=1.3, lower panel). Bonferroni Multiple HypothesisTest correction was

applied for each group. (B) Venn diagrams show the total number of signif icantly (p < 0.05) induced genes

and IFN-b-specif ic induced genes between L-lep, TB1 (UK cohort) and TB2 (Germany cohort) datasets.

Hypergeometric distribution-based enrichment analysis was performed to determine signif icance of IFN-b

genes induced in all three datasets; p < 0.007. Common genes between the three datasets were

compared with genes induced by IL-10 in a human monocyte dataset. Genes in red are also induced by

IL-10, and this overlap with IL-10 is greater than expected (9 of 16 common IFN-b- specif ic induced genes,

compared to 138 of 470 total common induced genes, hypergeometric p-value = 0.02).

18

Fig. S8

Supplemental Figure 8: Controls for immunoperoxidase detection.

Isotype control for IFN-b and IL-10 (IgG2a), isotype control for IFNAR1 (IgG1),

and the macrophage marker CD68 as a positive control. Data are

representative of four biopsy specimens for each group.

IgG2a

IgG1

CD68

T-lep L-lep RR

19

Fig. S9

CD14

IFN-b

Merge

CD209

Merg

e

IFN-b

Merge Merge

IFN-b

IFN-b

CD163

CD3

Supplemental figure 9. IFN-b colocalize with macrophage markers in L-lep

lesions. Co-expression of IFN-b (green) with M markers (CD14, CD163 and

CD209; red) and T cell marker (CD3; red), cellular nuclei were visualized using

DAPI. Data are representative of four individual L-lep biopsy specimens.

20

Fig. S10

Supplemental Figure 10. Isotype controls for IFN-b and cell markers

in L-lep lesions. Co-expression of isotype control for IFN-b (IgG2a, green)

with isotype control for CD14,CD3 and CD163 (IgG1, red) or isotype control

for CD209 (IgG2b, red). Cellular nuclei were visualized using DAPI. Data

are representative of four L-lep biopsy specimens.

IgG1

IgG2a

Merge

IgG2b

IgG2a

Merge

21

Fig. S11

CD163

IFN-b

Merge

IFN-b

CD209

Merge

Supplemental Figure 11. IFN-b and cell markers colocalization in T-lep lesions. CD3+, CD163+ and

CD209+ cells were detected, but few IFN-b+ cells. Co-expression of IFN-b (green) with T cells marker (CD3, red)

and M markers (CD163 and CD209, red). Cellular nuclei were visualized using DAPI. Data are representative

of four T-lep biopsy specimens.

Merge

CD3

IFN-b

22

Fig. S12

Supplemental Figure 12. mRNA levels of Type I IFN genes

are higher in L-lep vs. T-lep. Total mRNA was isolated f rom

10 L-lep, 10 T-lep and 10 RR skin lesions, and OAS1 and

OAS2 mRNA levels were analyzed by TaqMan qPCR. The

mRNA levels were normalized to GAPDH levels. Statistical

signif icance was calculated using one–way ANOVA followed

by Newman-Keuls multiple comparison Test for OAS1 and

Kruskal-Wallis followed by Dunn's multiple comparison test for

OAS2. ** p≤ 0.01; * p≤ 0.05.

OAS1 mRNA

T-lep L-lep RR

0

20

40

60

Rela

tive Q

uan

tifi

cati

on

** *

OAS2 mRNA

T-lep L-lep RR0

50

100

150

200

250

Rela

tive Q

uan

tifi

cati

on

** *

23

Fig. S13

CD163

IL-10

Merge

CD209

IL-10

Merge

FCD3

Merge

IL-10

Supplemental figure 13. IL-10 colocalize with macrophage markers in L-lep lesions. Co-expression

of IL-10 (green) with M markers (CD14, CD163 and CD209; red) and the T cell marker (CD3; red).

Cellular nuclei were visualized using DAPI. Data are representative of four individual L-lep biopsy

specimens.

24

Fig. S14

IgG1

IgG2a

IgG2b

IgG2a

Supplemental Figure 14. Isotype controls for IL-10 and cell markers in

L-lep lesions. Co-expression of isotype control for IL-10 (IgG2a, green)

with isotype control for CD3 and CD163 (IgG1, red) or isotype control for

CD209 (IgG2b, red). Cellular nuclei were visualized using DAPI. Data are

representative of four L-lep biopsy specimens.

MergeMerge

25

Fig. S15

Supplemental Figure 15. Isotype controls

for IL-10 and IFN-b in L-lep lesions. Co-

expression of isotype control for IL-10 (IgG2a,

red) with isotype control for IFN-b (IgG1,

green). Cellular nuclei were visualized using

DAPI. Data are representative of four L-lep

biopsy specimens.

IgG1

IgG2a

Merge

26

Fig. S16

Supplemental Figure 16. IFN-b

induces IL-10 in human monocytes.

Cells were stimulated with IFN-b

(200U/ml) for 24h and IL-10 protein

levels were detected by ELISA. Data

are represented as mean SEM, n=6.

Statistical signif icance was calculated

by two-tailed Student’s t-test. ** p≤ 0.01.

0

20

40

60

80

100

120

media IFN-b

IL-10 (pg/ml)**

27

Fig. S17

IL-10 (pg/ml)

IFNAR2 IgG2a_

IFNAR2IgG2a_

mLEP live IFN-b

0

20

40

60

80

100

120

140

mLEP 10: 1 mLEP 10: 1+aI FNAR2 mLEP 10: 1+IgG2a I FNB I FNB+aI FNAR2 I FNB+I gG 2a

Donor 1 Donor 2

Supplemental Figure 17. Blocking of IFNAR2 decreased the ability of live

M. leprae to induce IL-10. Human monocytes were stimulated with live mLEP

(MOI 10:1) alone or in combination with anti-human IFNAR2 antibody or isotype

control for 24h. IL-10 protein levels were detected by ELISA. Graphs show

results f rom two dif ferent donors.

0

20

40

60

80

100

120

140

mLEP 10: 1 mLEP 10: 1+aI FNAR2 mLEP 10: 1+IgG2a I FNB I FNB+aI FNAR2 I FNB+I gG 2a

IL-10 (pg/ml)

IFNAR2 IgG2a_

IFNAR2 IgG2a_

mLEP live IFN-b

28

Fig. S18

0

500

1000

1500

2000

0 5000 10000 15000

R = -0.43

0

500

1000

1500

2000

0 4000 8000 12000

R = -0.64

IL-1

0(A

U)

IL-1

0(A

U)

L-lep

T-lep

RR

CYP27B1 (AU) VDR (AU)

Supplemental Figure 18. Vitamin D associated gene

mRNA levels inversely correlate with IL-10 mRNA levels.

Correlation of CYP27B1 or VDR and IL-10 detected by

microarray (arbitrary units) for individual samples in three

leprosy groups (L-lep, n=6; T-lep, n=10 and RR, n=7)

29

Fig. S19

CYP27B1 mRNA (FC)

IFN-g

+IFN-b

IFN-g

+IL-10 IFN-g + IFN-b

0

0.5

1

1.5

2

2.5

3

M edi a I FNG G +I FNB G +I L- 10 aI L- 10+G +I FNB I gG 1+G +IFNB

media IFN-g IgG1 IL-10

* *

*

*

VDR mRNA (FC)*

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

M edi a I FNG G +I FNB G +I L- 10 aI L- 10+G +I FNB I gG 1+G +IFNB

media IFN-g IFN-g

+IFN-b

IFN-g

+IL-10

IgG1 IL-10

IFN-g + IFN-b

* **

Supplemental Figure 19 . IFN-b and IL-10 antagonize the ability of IFN-g to induce

vitamin D genes. Human monocytes were stimulated with IFN-g alone or in

combination with IFN-b or IL-10, anti-human IL-10 antibody was added in the monocyte

culture in combination with IFN-g and IFN-b for 24h. RNA was isolated and the CYP27B1

and VDR mRNA levels were detected by qPCR. Data are represented as mean SEM,

n=7. Statistical signif icance between two groups was calculated by two -tailed Student’s

t-test. * p≤ 0.05.

30

Fig. S20

0.0

0.5

1.0

1.5

2.0

media IL-10 IFN-g IFN-g+ IL-10

25D3→24,25D3 (fmol / 106 cells / hr)

**

*

Supplemental Figure 20. IFN-g reduces the inactive

form of Vitamin D3. Human monocytes were treated

with IL-10, IFN-g and IFN-g + IL-10 for 48h followed by

incubation with radiolabeled metabolite cholecalciferol

(D3), 25(OH)D3 for 5 h in serum-free media. The

ability to convert 25(OH)D3 to 24,25(OH)2D3 was

measured by HLPC. Enzymatic conversion data are

represented as mean SEM and shows three separate

donors, each studied in triplicate. Statistical

signif icance was calculated by one-way ANOVA

repeated measures test and comparison between two

groups was conf irmed by the post test, Newman-Keuls

Multiple Comparison Test. * p≤ 0.05.

31

Fig. S21

IL-10IFN-bmedia

M.leprae viability (AU)

Supplemental Figure 21. IFN-b and IL-10

do not affect M. leprae viability. Human

monocytes were infected overnight with live

mLEP (MOI 10:1), followed by treatment

with IFN-b (200U/ml) or IL-10 (10ng/ml) for

4 days. Viability of mLEP was calculated by

the ratio of bacterial 16S RNA and DNA

(RLEP) by qPCR. Data are represented as

mean SEM, n=7.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

32

Fig. S22

CYP27b1

25D

1,25D

Cath. DEFB4

Antimicrobial

activity

VDR

IFN-g

CYP27b1

25D

1,25D

Cath. DEFB4

Pathogenesis

VDR

IFN-g IFN-b

IL-10

Supplemental Figure 22 :IFN-b suppresses IFN-g induced

antimicrobial activity. A summary diagram indicating i) the

IFN-g-inducible antimicrobial pathway (blue), ii) the IFN-b

inducible pathway (red), and iii) parts of the IFN-g-inducible

antimicrobial pathway that are blocked by IFN-b (grey).

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