RAW264.7 Cell Ligand Screen Summary Progress Report and Perspectives AfCS 5/24/04

RAW264.7 Cell Ligand Screen

Summary Progress Report and Perspectives

AfCS 5/24/04

RAW Cell Ligand Screens

System complexity / richness / interestHow many inputs are there? How many primary signal outputs are there?How many outputs/inputs show up only in the two-ligand screen?How many interactions (complexity)?How many are macrophage specific?

RAW Cell Ligand Screens

System complexity / richness / interestHow many inputs are there?How many primary signal outputs are there (weak inference)?How many show up only in the two-ligand screen?How many interactions (complexity)?How many are macrophage specific?

Pathway topology and structure – double ligand spinoffWhat are the interactions?What are the likely nodes?What are the likely mediators of interaction? Where do we put the meters?

RAW Cell Ligand Screens

System complexity / richness / interestHow many inputs are there?How many primary signal outputs are there (weak inference)?How many show up only in the two-ligand screen?How many interactions (complexity)?How many are macrophage specific?

Pathway topology and structure – double ligand spinoffWhat are the interactions?What are the likely nodes?What are the likely mediators of interaction? Where do we put the meters?

MechanismInference of causality from order of events and identity of proteins

RAW Cell Ligand Screens

Progress Report Summary

Ligand list chosen (literature, Affy, Macrophage Committee)

Assays adapted, cytokine assay added, lipid assays operational

Cyclic AMP, Ca2+, cytokines: single AND double almost done

Phosphoproteins: interpretable informative now, done in 2004

Lipids and transcripts: in progress for select ligands and pairs

Analytical approaches: in place and largely automated

RAW264.7 CellsSystem complexity / richness / interest

How many inputs are there?~ 60 compounds tested of possible ~90~25 positives in single ligand screen

Do “negatives” alter responses in the double ligand screen~10 ligands alter activity in assays where they alone

have no effectProbability of effect for these ligands lowerNo assays yet for these mechanisms

Perhaps 40 active regulatory ligandsProposal: screen all the negatives as doubles with positives

in highest throughput, most global assays

Conclusion: We have a big toolboxMuch of it is NOT macrophage specific

How many primary signal outputs are there ?

It’s an OUTPUT screen too !!

Are patterns of outputs discrete? Probably not.

They are clusterable ! ~10 identifiable groups cAMP, Ca2+, cytokines, phosphoproteins, transcripts

Clusters imply shared mechanisms -- MadhuSeparation of clusters traceable to specific outputs

RAW264.7 CellsSystem complexity / richness / interest

R R R R

E E E E E E E

B Cell Merged Unified Experiment SpaceMadhu Natarajan

Move the bar left or right according to statistical significance of groupings.Then look at the data to see what distinguishes the groups.

-20

20

M. Natarajan

How many primary signal outputs are there ?

Are patterns of outputs discrete? Probably not.

They are clusterable ! ~10 identifiable groups cAMP, Ca2+, cytokines, phosphoproteins, transcripts

Clusters imply shared mechanisms -- MadhuSeparation of clusters traceable to specific outputs

Lipids and phosphoproteins: infer enzymes from metabolism

RAW264.7 CellsSystem complexity / richness / interest

R R R R

E E E E E E E

RAW264.7 CellsThe Double Ligand Screen for System Complexity

AKA Interactive Output ScreenA B C

Y

A B C

X

A B C

X

Additive

Non-additive - Cross-talk

Three-way

How many interactions ?

Phosphoproteins: 39 from a 15x15 matrix 17%Cyclic AMP and Ca2+ : 35 from 181 19%Cytokines: ~50 so far, pending follow-up

Lipids, transcripts yet to comeTranscript interactions apparently abundant

Can we identify, classify and understand them?

RAW264.7 CellsThe Double Ligand Screen for System Complexity

RAW cells:Ligand pair interactions

2MA848C5A CGMF > AdditiveI04 < AdditiveI06 Additive or Not calledI10 Not testedI1B A/C Result with cAMP or CaIFAIFBIFGISO A ALPA C A/CLPSM1AMC1MCFP2C CP3CPAF APGE A A C A A A A AS1P A C ATGF AUDP C A C C C A/A CUTP C C A C C A C C

2MA 848 C5AGMF I04 I06 I10 I1B IFA IFB IFG ISO LPA LPS M1AMC1MCFP2C P3C PAF PGE S1P TGF UDPUTP

- P.C.S. / Cell Lab

Ca++ & cAMP combined

Stimulating ligand pairs

(either assay)

Stimulating vs. Non-

stim pairs

No stim-ulation

(either assay)Totals

Pairs 28 136 136 300

Non-additive 22 12 NA 34

Additive / Not called 6 124 NA 130

Not tested 0 0 136 136

% Non- additive 79 % 9 % 11 %

% Non-additive of

tested21 %

RAW 264.7 Cells: Density of Interactions- P.C.S. / Cell Lab

So: Test the others (as pools, perhaps) Novel inputs observable in phosphoprotein, cytokine assays

How many interactions ?

Phosphoproteins: 39 from a 15x15 matrix 17%Cyclic AMP and Ca2+ : 34 from 164 21%

Cytokines, lipids, transcripts yet to come

Can we identify, classify and understand them?

Classification by OUTPUT is more meaningful thanclassification by LIGANDS

RAW264.7 CellsThe Double Ligand Screen for System Complexity

Mechanistic Information from the Ligand Screen

Pathway Interactions --

Identify: Non-additivity in N-dimensional parameter spaceRama, Madhu

Classify: Direct analysis of interactions

Paul PCA of difference vectors -- classification by output interaction

Yet to comeCan they be clustered to give new mechanisms?

Understand: These experiments will point to the nodes in the RAW cell signaling network

Regulation, downstream amplifiers, inhibitors

Mechanistic Information from the Ligand Screen

Ca cAMPPGE

ISO

UDP

PAF

C5A

I04

IFG

TGF

848

P2C S1P2MA

LPA

UTP

Paul Sternweis

Pathway Interactions --

Identify: Non-additivity in N-dimensional parameter spaceRama, Madhu

Classify: Direct analysis of interactions

Paul PCA of difference vectors -- classification by output interaction

Yet to comeCan they be clustered to give new mechanisms?

Understand: Clusters of outputs expand / reinforce identification of pathways Use RNAi, inhibitors, to identify the shared components Non-additivity = interactions = linkages among pathways

Use RNAi, inhibitors, to identify the likely nodes These nodes are where the biosensors should go

Mechanistic Information from the Ligand Screen

Time Domains of the Ligand Screen Assays

Ca2+

Cyclic AMP

Lipids

Phosphoproteins

mRNAs

Cytokines

Time (s) 1 10 100 1000 10,000

Mechanistic Information from the Ligand Screen

-20

0

20

40

60

80

100

120

140

0 100 200 300 400

Time (sec)

Ch

an

ge

in

ca

lciu

m (

nM

)

2MA

C5a

LPA

PAF

S1P

UDP

UTP

RAW: Stimulation of Ca2+--Cell Lab

Time Domains of the Ligand Screen Assays

Ca2+

Cyclic AMP

Lipids

Phosphoproteins

mRNAs

Cytokines

Time (s) 1 10 100 1000 10,000

Mechanistic Information from the Ligand Screen

Both responses and interactions can be ordered in time.Post hoc ergo propter hoc??

Mechanistic Information from the RAW Cell Ligand Screen

Classes of responses that the RAW cell can generate

Responses that group -- common mechanisms

Responses that are ordered in time -- hints at causation

Modulation of responses -- intersection of pathways0 + 1 = 7: Directionality of modulation

Modulations coupled with primary responses -- hints at mechanismInhibitors, amplifiers, regulators

The ligand screens provide the benchmarks for mechanistic experimtents and modeling

the RAW signaling network

RAW264.7 Cell Ligand Screen

Summary Progress Report and Perspectives

AfCS 5/24/04