Transcript The cognate interaction

The Cognate interaction
Genomic arrays
A new era for modeling the immune response
Benoit Morel
Today’s experimental data:
A NEW ERA
More information
than we can
digest, yet.
(blurred…)
Clearly a
revolution in the
making, for the
experimentalists,
the modelers,
AND (more
importantly) their
relations…
Importance of Large Numbers
and variability
•
•
•
•
•
Immune system involves ~1012 cells
Each cell is a complex object (~109 molecules)
Functional repertoire > 108
Cells act in populations;
Cells of the same population are significantly
different.
• There are many factors and co-factors: many
kinds of cytokines, chemokines, receptors, CD’s.
• Microarrays  many genes are activated together
Importance of the Information
flow
• Innate response:
– Toll Receptors, PAMPs (=Pathogen Associated Motif Patterns),
– Danger signal (LPS?, Viruses??)
• Cognate interaction (D-cells communicate a lot
of information during the cognate interaction)
• CD4 cells information processors
• Immunological memory: the ultimate legacy of
the response
The cognate interaction:
-Couples the innate to the
adaptive response
-It is a protracted event, using the
“immunological synapse” which
leads to the differentiation of Tcells .
-TCR have their share of
promiscuity.
-TCR engagement has a very low
activation energy.
- Still the cognate interaction has
a very high sensitivity and
selectivity.
-A very information intensive
biological process
The cognate interaction
generates a complicated
set of events inside the
cells:
Signaling cascades.
The signaling cascades
translate a pattern of
activation at the cell
membrane into the
triggering of some genetic
activity inside the nucleus
More information
processing is taking
place…than we seem able
to “model”
Signaling cascades
• “Evolutionary stables” (animal  human
models).
• Parallel processing of information ?
– Maps the footprint of a stimulus at the membrane into a
pattern of genetic activity
– The information is conveyed and processed through
physical interactions between molecules
– the same stimulus can have different effects on
different cells.
• What can be known about the dynamics of the
cascades and the Interactions between
cascades?
Input Layer
Shared
kinases
Cascades
NF-AT
Cascades
NF-kB
Neural Net architecture?
Parsimony?
Cascades do not seem to involve
so many factors considering the
variety of footprints of excitation
they convey to the genes
Where is the
difference?
Information
processing in
cascades?
Filtering?
amplification?
Integration?
analysis of signal?
Biological form of
Computation through
direct interactions of
molecules and
complex formation?
Are there biological
gates??
Modeling MAPK cascades
(Huang-Ferrell: PNAS 93 (1996), pp. 10078-10083)
GoldbeterKoshland 81
Why
MAPKKK??
Boris N. Kholodenko :Eur. J. Biochem. 267, 1583±1588 (2000)
Negative feedback and ultra-sensitivity can bring about oscillations in the
mitogen-activated protein kinase (MAPK) cascades
One fundamental mechanism:
Michaelis-Menten
a
A + E
{E.A}
d
k
E +B
dB
ka E A

dt k  d  aA
“Switch” or “ultra-sensitivity”
Why
MAPKKK??
h
“Hill equation”:
a
h
a k
Effects of cascades quite variable
and complicated
- Dynamical properties sensitive to parameters
(relative concentrations of enzymes) that are difficult
to measure and one can assume quite variable
- May lead to the activation of many genes
Nuclear factors
like NF-kB or
NFAT are involved
in the activation of
many different
genes.
Gene transcription
is a complicated
process whose
regulation
involves a lot of
factors
4 possible levels of control
Transcription: quite a regulated and complex process
…which involves quite a lot of factors…
“DNA-protein
interactions are among
the tightest and most
specific molecular
interactions known in
biology”
“DNA sequences act as
nucleation sites for the
assembly of protein
complexes”
The genes are the central compiler
of the cells
• The product of the signaling cascades is
conveyed to a system even more complex
and regulated: the chromatine.
• Several percent of the genes regulate the
chromatine.
• A large chunk of the energy consumed by
the cell is for that regulation.
Structure of chromatine decides which genes
can be activated.
Chromatine made of Nucleosomes
Chromatine remodeling
• Chromatine remodeling leads to the expression
of different genes.
• This process involves dedicated nuclear
proteins.
• It tends to be slower than mere transcription.
• It takes place during differentiation
• It leads to different patterns of gene activations
• It is known to take place during thymic
maturation of the cells.
• A safe assumption: It takes place during the
cognate interaction
Cell, Vol. 114, 277–280, August 8, 2003, Copyright
Minireview Nuclear Receptors: A Rendezvous
for Chromatin Remodeling Factors
2003 by Cell Press
A new perspective on the cognate
interaction and T-cell differentiation?
• Now that genomic arrays exist, it is possible to
monitor at the genetic level what happens during
the cognate interaction
• … and after
• We can try to learn to analyze T cell specificity
on the basis of the new genes that are activated
or not accessible anymore as a result of
chromatine remodeling.
• D-cells also interesting to analyze and the effect
of their activation and the information they
convey to the T cells
Conjecture
• T-Cells and D-cells adaptive agents with
two levels of adaptiveness:
– Chromatin remodeling signals a change of
nature of activation for T-cells
– Otherwise, T-cells act as “repetitive”
processors of the information
• What factors influence D-cells?
The immune system
a Multi-intelligent-agent system?
• Interfaces with (i.e. could learn from and
benefit to) the study of
– Distributed intelligence systems, and/or
– Distributed control with learning, i.e.
– Systems with intelligent agent accessing,
filtering, evaluating, integrating information.
• Architecture of the distributed processing
of information
• Mobile agents (codes)?
And compare with random graphs