A SAGE Approach to Discovery of Genes Involved in Autophagic Cell Death

Acknowledgements

Genome Sciences CentreVictor Ling

Marco Marra

Functional GenomicsSuganthi Chittaranjan

Doug FreemanCarrie AndersonShaun Coughlin

SequencingGenome Sciences Centre

Sequencing Team

BioinformaticsSteven JonesErin Garland

Richard VarholScott Zuyderduyn

SAGE team

University of MarylandBiotech InstituteEric Baehrecke

Programmed Cell Death (PCD)

Function Dysfunction

Deleting damaged cellsCancer

Culling cell number

Deleting structures

Sculpting tissues

Autoimmune diseases

Neurodegenerative diseases

Developmental abnormalities

Programmed cell death

Type I = Apoptotic

• cytoskeletal collapse

• condensation and fragmentation of chromatin and cytoplasm

• preservation of organelles

• phagocytosis by macrophages or neighbouring cells

(heterophagy)

• occurs in isolated cells

Type II = Autophagic

• preservation of cytoskeleton

• formation of vacuoles that engulf cytoplasm and

organelles

• fusion of vacuoles with lysosomes for self-degradation

• late chromatin condensation and nuclear degeneration

• occurs in groups of cells

Autophagic cell death in normal physiology

• Dictyostelium sorocarp formation

• insect metamorphosis •intersegmental muscle, gut, salivary glands

• mammalian embryogenesis •regression of interdigital webs, sexual anlagen

• mammalian adulthood •intestine, mammary gland post-weaning, ovarian atretic follicles

Autophagic cell death in disease

• human neurodegenerative diseases (Alzheimer and Parkinson)

• cardiomyocyte degeneration

• spontaneous regression of human neuroblastoma

• tamoxifen-treated mammary carcinoma cells (MCF-7)

• bcl-2 antisense treatment of human leukemic HL60 cells

• beclin-1 (apg6) promotes autophagy and inhibits tumorigenesis; expressed at decreased levels in human breast carcinoma

Aims

1. Identify the genes involved in autophagic cell death in vivo.

2. Determine which genes are necessary and sufficient for autophagic cell death.

3. Determine if genes function in mammalian autophagic cell death.

4. Identify the autophagic cell death genes associated with human disease and investigate potential as molecular markers and/or

therapeutic targets.

Experimental Approach

Gene expression profiling (SAGE):• Comprehensive• Gene Discovery

Drosophila model system: • Known cell death genes/pathways are conserved• Genetic and molecular tools• Sequence resources• FlyBase and GadFly databases• Multiple tissues undergo PCD; well-characterized

(Jiang et al., 1997)

• autophagic • stage-specific • synchronous

hr (APF, 18°C)

• known cell death genes are regulated transcriptionally

Reverse transcription - + - + - + - + - + - + 16 18 20 22 23 24

diap2

rpr

hid

RT-PCR analysis

Drosophila salivary gland PCD

Overview of SAGE tag abundance

SAGE

LibraryTotal tags analyzed

Transcripts % of transcripts seen at frequency:

1 2-10 11-100 >100

16 hr 34,989 3,126 32.7 55.7 10.4 1.2

20 hr 31,215 3,034 38.0 50.9 9.7 1.4

23 hr 30,823 2,963 33.3 54.0 11.2 1.4

Total number of different transcripts in all three libraries is 4,628.

Deriving SAGE tag abundance

Total SAGE tags analyzed: • remove linker sequences and duplicate ditags• select a quality cut-off • remove singletons i.e. found only once in all 3 libraries

•Number of different transcripts at each timepoint: • combine libraries (e.g. 16a + 16b) in SAGEspace• export to Excel and count lines/sort by tag numbers

Total number of different transcripts:• compare 16 + 20 vs 23• export to Excel and count lines

Alternate: use Unix commands, e.g. grep – c , unique

Tag-to-gene Mapping in Drosophila(E. Pleasance, M. Marra and S. Jones, in preparation)

Resources: Drosophila genomic sequence, full-length cDNAs, ESTs, salivary gland ESTs

4,628 transcripts:

2866 (61.9%) – known or predicted genes 289 ( 6.2 %) – genomic DNA and EST (but no predicted gene)1170 (25.3%) – genomic DNA and/or reverse strand of gene 303 ( 6.5%) – no match

Comparison of SAGE and real-time quantitative RT-PCR

Fold-difference by SAGE

Fo

ld-d

iffe

ren

ce b

y Q

RT

-PC

R

1.0

10.0

100.0

1000.0

1.0 10.0 100.0 1000.0

Correlation coefficient = 0.5

II. Correlation coefficient between fold-difference values (64 samples):

I. Direction of Change:

91/96 samples = 95% concordance

Real time quantitative RT-PCR analyses

• Applied Biosystems 7900 Sequence Detection System

• gene specific primers designed (near SAGE tag) using Primer Express V software

• SYBR Green One-step RT-PCR reagent kit / Melting curve analysis

• sample volume reduced to 15 μl ; n = 3

• “housekeeping” gene and known cell death gene as controls

• used to confirm expression profiles and to resolve ambiguous tag-to-gene mappings

An ecdysone induced transcriptional cascade regulates salivary gland cell death

BFTZ-F1

EcR/USP

BR-C

E74

E93

rprhidarkdronccrq

diap2

Cell Death

E75

SAGE Identifies Genes Associated Previously With Salivary Gland Death

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006B

R-C

E7

4

E7

5

E9

3

rpr

ark

dro

nc

iap

2

crq

Ta

g F

req

ue

nc

y (

tag

co

un

t/to

tal t

ag

s)

SG16

SG20

SG23BFTZ-F1

EcR/USP

BR-CE74E93

rprhidark

dronccrq

iap2

CellDeath

E75

Question: What genes didn’t

we find?

Do they contain anNlaIII site?

1244 genes are expressed differentially (p < .05) prior to salivary gland PCD

512 genes have associated

biological annotations (Flybase Gene Ontology)

R. Varhol, S. Zuyderduyn

732 genes have unknown functions

377 of thesewere unpredicted

FlyBase Gene Annotation

Automating the association of differentially expressed genes with biological annotations

Behind the scenes:Incorporation of FlyBase, GadFly, Swissprot, etc.

into DISCOVERYdb

Link database information with differential expression and tag-to-gene mapping data

6 files of pairwise comparisons with genesassociated with annotations of interest

Several trials……

Output of “flyannotation.pl”

Molecular Function SCOP id Protein Domain GO id Bio Process GO id Cell CompartmentATP-citrate (pro-S)-lyase 56059 Glutathione synthetase ATP-binding domain-like6085 acetyl-CoA biosynthesis 5737 cytoplasmactin binding 7015 actin filament organizationgram-positive antibacterial peptide 6961 antibacterial humoral responsegram-positive antibacterial peptide 6961 antibacterial humoral responseeukaryotic initiation factor 4E binding 6961 antibacterial humoral responsegram-positive antibacterial peptide 6961 antibacterial humoral responseantibacterial peptide 6961 antibacterial humoral responseantifungal peptide 57095 Scorpion toxin-like 6966 antifungal humoral responsetranscription factor, cytoplasmic sequestering 48403 Ankyrin repeat 6966 antifungal humoral response 5737 cytoplasmlysozyme 53955 Lysozyme-like 6960 antimicrobial humoral responsemacrophage receptor 52374 Nucleotidylyl transferase 6915 apoptosis 5887 integral plasma membrane proteincaspase 52129 Caspase-like 6915 apoptosis 5737 cytoplasm

6915 apoptosisubiquitin-specific protease 7412 axon target recognitionprotein serine/threonine kinase 56112 Protein kinase-like (PK-like) 7350 blastoderm segmentationprotein serine/threonine kinase 56112 Protein kinase-like (PK-like) 7350 blastoderm segmentationactin binding 7420 brain developmentcaspase activator 50978 Trp-Asp repeat (WD-repeat) 6919 caspase activationcatalase 56634 Heme-linked catalases 6802 catalase reaction 5777 peroxisomeGTPase 16288 cytokinesis 5940 septin ringactin binding 53067 Actin-like ATPase domain 7010 cytoskeleton organization and biogenesis 5869 dynactin complexstructural protein of cytoskeleton 53067 Actin-like ATPase domain 7010 cytoskeleton organization and biogenesis 5884 actin filamentstructural protein of cytoskeleton 53067 Actin-like ATPase domain 7010 cytoskeleton organization and biogenesis 5884 actin filament

49599 TRAF domain 6952 defense responsemonophenol monooxygenase activator 6952 defense responsescavenger receptor 6952 defense response 5887 integral plasma membrane proteinscavenger receptor 6952 defense response 5887 integral plasma membrane proteintransmembrane receptor 52047 RNI-like 6952 defense response 5886 plasma membranescavenger receptor 6952 defense response 5887 integral plasma membrane proteininositol-1,4,5-triphosphate phosphatase 56219 DNase I-like 16311 dephosphorylation

8340 determination of adult life spanubiquitin-specific protease 6514 deubiquitylation

SG16 vs SG23 upregulated (p < 0.05)

Secondary screening of differentially expressed genes

I. Data Mining

II. Gene expression in salivary gland cell death-defective mutant (E93)

III. Gene expression in other dying tissues

IV. Loss-of-function and gain-of-function mutant analyses

Data mining related questions

What differentially expressed Drosophila genes are similar to mammalian genes and associated previously with:

cell death?autophagy?

pathways of interest?tumorigenesis?

cancer?other diseases?

I. Data mining by sequence similarity searches and keyword queries

SAGE tag maps to Drosophila gene

Extract gene sequence from GadFly Database

GadFly – Swissprot Homology (tBLASTX)

Keyword query of Swissprot comments, keywords and identification fields

SAGE tag maps to novel EST

tBLASTX search EST vs Swissprot

Keyword query of FlyBase and PCD database

KeywordData

base

SG

16

SG

23Gene

Sim

(%)Score

Length

(aa)Swiss

Prot idDatabase Description

death

apoptosis

apoptosis

apoptosis

apoptosis

apoptosis

apoptosis

death

death

survivalautophagy

hormone

hormone

cancer

cancer

tumor

tumor

tumor

apoptosis

TNF

BH3

SP

SP

SP

SP

SP

SP

SP

SP

SP

SP

SP

SP

SP

SP

SP

SP

SP

SP

FB

FB

PCD

0

4

0

0

0

0

1

1

0

1

0

2

0

1

1

45

10

65

1

1EST only

15

0

6

5

4

4

7

61

7

7

7

73

12

7

15

1

0

0

5

102

Nc

debcl

cact

Traf1

CG4719

Ptpmeg

CG4859

CG10777

Rpn2

stck

chrw

ciboulot

CG8706

Atet

CG13907

botv

sp6

CG11335

CG10990

CG4091

CG2023

27.2

25.5

37.1

37.0

39.3

31.3

41.6

18.7

23.7

65.7

35.3

68.6

29.6

39.9

33.2

48.6

28.3

42.7

59.9

59.6

53.9

251

127

322

300

232

101

772

87

160

1276

257

114

1204

469

311

2044

427

423

592

330

247

253

133

203

179

116

80

407

444

267

321

170

34

984

240

203

838

361

182

469

188

228

ICE6_HUMAN

BCL2_HUMAN

IKBA_HUMAN

TRA1_HUMAN

BAR1_HUMAN

PTND_HUMAN

MM11_MOUSE

WRN_HUMAN

PSD2_HUMAN

PINC_HUMAN

RB24_MOUSE

TYB4_HUMAN

LRP2_HUMAN

ABG2_HUMAN

MOT1_HUMAN

EXL3_HUMAN

MASP_MOUSE

LYOX_HUMAN

 

 

 

CASPASE-6 PRECURSOR

APOPTOSIS REGULATOR BCL-2

NF-KAPPAB INHIBITOR ALPHA

TRAF1

BRCA1-ASSOCIATED RING DOMAIN

FAS-ASSOCIATED PTP-1

STROMELYSIN-3 PRECURSOR

WERNER SYNDROME HELICASE

26S PROTEASOME S2

PINCH PROTEIN

RAS-RELATED PROTEIN RAB-24

THYMOSIN BETA-4

LDL RECEPTOR-RELATED PROT

BREAST CANCER RESISTANCE

MONOCARBOXYLATE TRANSPORT

TUMOUR SUPPRESSOR EXL3-LIKE

PROTEASE INHIBITOR 5

PROT-LYSINE 6-OXIDASE PREC.

MM 'APOPTOSIS PROTEIN MA-3'

HS 'TNF-INDUCED PROTEIN GG2-1'

BH3

Data Mining - What next?

• Is it possible to include the “best” match from Swissprot?

• How can we best incorporate information from TrEMBL?

• What genes belong to the same metabolic or signal transduction pathways?

• A new release of GadFly will be available soon. How are the Drosophila databases updated?

• What differentially expressed genes are similar to mammaliangenes up/downregulated in cancer?

(e.g. compare to cancer SAGE libraries)

Secondary screening of differentially expressed genes

I. Data Mining

II. Gene expression in salivary gland cell death-defective mutant (E93)

III. Gene expression in other dying tissues

IV. Loss-of-function and gain-of-function mutant analyses

II. Analysis of differential gene expression in E93 mutant salivary glands

• E93 is a DNA binding protein required for salivary gland cell death (Lee et al. 2000)

• 65 different E93 chromosomal binding positions are known

• Expression of known cell death genes is reduced in E93 mutant salivary glands

• We tested 20 differentially expressed genes with map positions corresponding to E93 binding sites

Gene expression is reduced in E93 mutant salivary glands

19/20 upregulated genes showed a reduction in relative levels of transcription.

Gene Cytological

location

OreR SAGE (16:23)

OreR RT-PCR (16:23)

E93 RT-PCR (16:23)

E93 RT-PCR (16:30)

CecB

CG4091

CecA1

Doa

CG4859

CG14995

BACR19J1.2

CG3845

Ptpmeg

CG9321

Cp1

CG12789

CG1216

larp

CG7860

Cyp1

Phm

Sox14

CG13448

CG8149

ark (control)

3R 99E4-99E4

2R 59F5-59F5

3R 99E4-99E4

3R 98F1-98F2

2R 60D10-60D10

3L 64A7-64A8

X 1B10-1B10

2R 49E1-49E1

3L 61C1-61C1

2L 29E4-29E4

2R 50C20-50C20

2L 28A1-28A1

3L 61A6-61A6

3R 98C3-98C3

X 13E3-13E3

X 14B15-14B15

2R 60A14-60A14

2R 60A14-60A14

3L 71E1-71E1

3R 85D25-85D25

N/A 

> 30

105

> 106

> 38

12

> 22

34

25

> 4

23

12

7

> 4

> 11

10.5

11

> 4

> 7

7.2

6

15

2765.7

206.7

177.5

71.9

47.2

40.8

34.6

29.6

14.2

13.7

12.8

10.7

9.1

7.8

4.9

3.5

3.4

2.9

2.5

2.1

2.0

0.1

0.8

0.4

2.1

1.1

0.6

1.4

0.8

0.5

2.0

0.8

0.7

0.9

0.4

0.2

0.5

0.7

3.2

0.5

0.7

3.0

34.2

2.7

2.6

1.2

1.5

0.5

1.9

1.8

0.5

2.2

0.9

1.5

0.8

1.8

0.8

0.5

0.7

2.9

0.2

0.5

3.2

III. Expression of salivary gland genes in the embryo coincides with patterns of PCD

3/15 genes examined have embryonic expression patterns that at least partially coincide with patterns of PCD

CG3132 Cp1

akap200 akap200

IV. Loss-of-function mutant analyses.

e.g. akap200 mutants indicate a possible defect in PCD:

• salivary glands• embryos• retinas

wild-type (41 hr APF) akap200EP2254 (41 hr APF)

Differentially expressed genes reveal molecular features associated with autophagic cell death

• Autophagic cell death involves the induction of genes required for protein synthesis

e.g. 6 different translation initiation factors

• Novel transcription factors share transcription profiles with known salivary gland transcription factors

e.g. maf-S, CG3350

• Components of multiple signal transduction pathways are involvede.g. TNF- like pathway, akap200, Doa

Differentially expressed genes and molecular features of autophagic cell death, continued.

• some apg-like genes are upregulated transcriptionallye.g. genes involved in two ubiquitin-like pathways

CG6194 (apg4;novel cysteine protease)CG5429 (apg6/beclin-1)

• Other autophagy-associated genes are likely involvede.g. lysosomal enzymes, rab-7

• Autophagic and apoptotic cell death appear to utilize at least some common pathways or pathway components

Acknowledgements

Genome Sciences CentreVictor Ling

Marco Marra

Functional GenomicsSuganthi Chittaranjan

Doug FreemanCarrie AndersonShaun Coughlin

SequencingGenome Sciences Centre

Sequencing Team

BioinformaticsSteven JonesErin Garland

Richard VarholScott Zuyderduyn

SAGE team

University of MarylandBiotech InstituteEric Baehrecke