2003 Inferring Connection Maps from AfCS Experimental Data and Legacy Data.
RAW264.7 Cell Ligand Screen Summary Progress Report and Perspectives AfCS 5/24/04.
Transcript of 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
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0
20
40
60
80
100
120
140
0 100 200 300 400
Time (sec)
Ch
an
ge
in
ca
lciu
m (
nM
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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