Glucocorticoid receptor crosstalk with NF-kB in airway cells – analyzing the cistromes

BIOS6660 Genomic Data Analysis with R and Bioconductor

Anthony Gerber MD, Ph.D.October 20, 1015

• Transcription factors• Many are ligand activated• Only class of transcription factors that can be

targeted by small molecules in the clinic• Clinical targets include estrogen, androgen,

mineralocorticoid, Vitamins D, glucocorticoid and thyroid receptors, RXR, PPAR

• Major interest in developing selective ligands/modulators to enable improved therapeutic windows

The Nuclear Receptor family

Glucocorticoids in the clinic: a large footprint

10-20 million annual prescriptions for oral glucocorticoids in USA

> 50 million prescriptions for localized delivery (inhaled, topical, eye drops)

Major targets are diverse immune- mediated diseases

CNS: Anxiety, insomniaOcular: Glaucoma

Muscle: Atrophy

Endocrine: Diabetes, obesity

Skin: Fragility

Bone: Osteoporosis

Cardiovascular: Hypertension

•Rheumatoid arthritis•Inflammatory bowel disease•COPD•Asthma•Other lung diseases

o Hypersensitivity pneumonitis

o BOOPo NSIPo vasculitis

•Organ transplants•RDS of prematurity

“Off target” effects

Balancing disease symptoms with glucocorticoid side effects in the clinic:A 50 year old female with severe, persistent asthma

No oral glucocorticoid use

• lung function < 50% of normal• short of breath after walking 2 blocks• unable to go up a flight of stairs• frequent coughing episodes• 1-2 ER visits per quarter• 2-3 hospitalizations per year

Taking oral glucocorticoids

• lung function ~80% of normal• no shortness of breath after 10 blocks• able to go up 2 flights of stairs• no hospitalizations or ED visits• 20 pound weight gain• lower extremity edema• irritability• high blood sugars• increased risk of osteoporosis

There is a major unmet need for improved glucocorticoid-based therapies

Background: Glucocorticoids bind to the glucocorticoid receptor (GR), causing it to regulate gene expression

Image from http://brainimmune.com/the-glucocorticoid-receptor/

Glucocorticoids GR is a basic model of metazoan transcriptional regulation-> Recent example: DNA implicated as regulating GR activity through allosteric mechanisms (Hudson et al, Nat Struct Mo Bio, 2013, Meijsing et al, Science 2009)

Therapeutic effects of GR activation are also intensely studied-> >10000 Pubmed citations for “asthma and glucocorticoid”

“Transprepression” typically implicated in mediating therapeutic effects

Structural considerations

Steve Bilodeau et al. Genes Dev. 2006;20:2871-2886

-6

-4

-2

0

2

4

6

TNFAIP3

TNIP1

TNIP2

NFᴋBIA

DUSP1012345678

Chan

ge in

mRN

A le

vel (

log 2)

Pro-inflammatory

Anti-inflammatory

TNFDexDex+TNF

How do glucocorticoids work?

β-actin

HBEGF

TNFAIP3

TNFαDex

‒‒

+‒

‒+

++

Glucocorticoids “spare” the expression of negative

feedback targets of TNF (a major inflammatory signal)

How do glucocorticoids actually work?

VehTNF

Dex

Dex+TNF

0

500

1000

1500

2000

2500 pTNFAIP3I2

Rela

tive

luci

fera

se a

ctivi

ty

VehTNF

Dex

Dex+TNF

0

50

100

150

200

250pIL8

3’5’

NFᴋB-BS1(CTTGGAAAGTCCAGG) NFᴋB-BS2(CTGGGGAATTCCAGA) GR-BS(CCAGAACAAAAAGTACAAT)

TNFAIP3 reporter

(821 bP)(+5,670 — +6,491)

2

1

TNFAIP3 Intron 2

1 2

Hela cell GR/NF-kB ChIP-seqRao et al, Genome Biology, 2011

TNFAIP3

Β-actin

70 kDa

42 kDa

TNFαDex

——

+—

++

——

+—

++

siTNFAIP3siCtrl

B

TN

Fα

Dex

Dex+

TN

Fα

-2

-1

0

1

2

3

4

5 siCtrl

siTNFAIP3C

hange in IL1

a m

RN

A leve

l (l

og2)

TNFAIP3 contributes to glucocorticoid-mediated cytokine

repression in airway epithelial cells

How do glucocorticoids actually, actually work?

How do glucocorticoids work and what prevents them from working in asthma?

Since GR interactions with DNA define GR activity

study GR interactions with DNA in airway cellsSince GR interactions with inflammatory factors are important for GC efficacy Study DNA-based interactions between GR and NF-kB

No current data on GR cistrome in airway cells…

ChIP - overview

Cross-link Chromatin shear and prep IP Purify DNA

ChIP- downstream assays

ChIP-Seq example summary dataGR PEAKS

Treatment (1 hr)

IP Antibody

control

GRdex

TNF+dex

controlNFkB-p65

TNF

TNF+dex

control

RNAP2dex

TNF

TNF+dex

Cells: Beas-2B

Treatments: dexamethasone (dex; 100 nM) tumor necrosis factor-α (TNF; 20 ng/ml)

Sequencing: Illumina Hi-Seq; performed in biological duplicate

Airway epithelial ChIP-Seq experimental design

Conditions:

Pattern 1: GR+NFkB co-occupancy & reduced RNAP2

dexGR IP

TNFp65 IP

TNFRNAP2 IPTNF+dexRNAP2 IP

TNF+dexGR IP

TNF+dexp65 IP

dexRNAP2 IP

75

125

125

50

75

125

50

IL8locus

dexGR IP

TNFp65 IP

TNFRNAP2 IPTNF+dexRNAP2 IP

TNF+dexGR IP

TNF+dexp65 IP

dexRNAP2 IP

55

80

80

45

55

80

45

CCL2locus

Pattern 1: GR+NFkB co-occupancy & reduced RNAP2

Pattern 1 summary

• GR binds pro-inflammatory gene in absence of TNF• GR occupancy is maintained/enhanced in presence

of NFkB• GR+NFkB co-occupancy reduces RNAP2 recruitment

NET EFFECT = repression of pro-inflammatory transcription

Pattern 2: NFkB-mediated GR occupancy & reduced RNAP2

dexGR IP

TNFp65 IP

TNFRNAP2 IPTNF+dexRNAP2 IP

TNF+dexGR IP

TNF+dexp65 IP

dexRNAP2 IP

ICAM1

locus

50

75

75

20

50

75

20

Pattern 2 summary

• GR binds pro-inflammatory gene only in presence of TNF

• Role of NFkB in GR recruitment unclear, possibly indirect

• GR+NFkB co-occupancy reduces RNAP2 recruitment

NET EFFECT = repression of pro-inflammatory transcription

Pattern 3: GR+NFkB co-occupancy & enhanced RNAP2

dexGR IP

TNFp65 IP

TNFRNAP2 IPTNF+dexRNAP2 IP

TNF+dexGR IP

TNF+dexp65 IP

dexRNAP2 IP

40

10

10

165

40

10

165

SERPINA3

locus

dexGR IP

TNFp65 IP

TNFRNAP2 IPTNF+dexRNAP2 IP

TNF+dexGR IP

TNF+dexp65 IP

dexRNAP2 IP

35

35

35

60

35

35

60

TNFAIP3

locus

Pattern 3: GR+NFkB co-occupancy & maintained RNAP2

Pattern 3 Summary

• GR binds anti-inflammatory genes with dex+TNF

• GR+NFkB co-occupancy does not appear antagonistic

• GR+NFkB co-occupancy enhances or maintains RNAP2 recruitment

NET EFFECT = activation (or sparing) of anti-inflammatory transcription

What do we want from our ChIP data?

BASIC

1. Identification of peaks for GR and p65 under each condition and r values

2. Identification of differential GR binding vehicle vs. dex

3. Identification of differential binding p65 binding vehicle vs. TNF treatment

What do we want from our ChIP data?

BASIC

1. Identification of peaks for GR and p65 under each condition and r values

2. Identification of differential GR binding vehicle vs. dex

3. Identification of differential binding p65 binding vehicle vs. TNF treatment

What do we want from our ChIP data?

ADVANCED

1. Differential GR binding (dex vs dex + TNF)

2. Differential p65 binding (TNF vs TNF + dex)

3. RNAP2 patterns1. Increased at TSS with dex vs vehicle

2. Closest GR peak

3. Increased at TSS with TNF and TNF + dex > TNF

4. Increased at TSS with TNF and TNF + dex < TNF

5. Closest p65 peak to TSS for patterns 3 and 4

6. Closest GR peak to TSS for patterns 3 and 4

What do we want from our ChIP data?

Collaboration Level!

1. Compare GR binding between Gerber lab data set and paper from Rao et al (Genome Biology, 2011)

2. Compare p65 binding between Gerber lab data set and paper from Rao et al (Identification of differential GR binding vehicle vs. dex

3. Compare regulatory outcomes – i.e. correlate with RNAP2 occupancy

QUESTIONS?