Download Complexity and the Immune System

Complexity and the Immune
System
Why look at the immune system?
-Intermediate level
-One of the major information processing
systems in the body (with neural system)
-Competing theories that can be tested - we’ll
see how well the network theory holds up in
this case
Main Issues
• Protection: find and destroy invaders
• Self Recognition: don’t destroy cells from
your own body
• Memory of past pathogens
Immune System Basics
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Antigens and antigen determinants
Multiple epitopes per cell of any type
Antibodies (4 chains; “variable region”)
B cells and clones
T cells (recognize peptide fragments from
MHC)
Niels Kaj Jerne
Danish Immunologist
• Shared the Nobel prize in 1984 for his work
• Theory of antibody formation (from genetic
variation rather than a response to
pathogens) - 1955
• The body learns to distinguish between self
and nonself in the thymus - 1971
• Concept of the immune system as complex,
self-regulating network - 1974
Self Defense in a Network
System
• Key factors:
– Quick and full response from those antibodies
that can bind to the right antigen determinants
– Response that dies down (ie doesn’t explode)
– Memory of past pathogens so that response is
quicker next time
Networks that do this
• Coupled PDEs involving the concentration
of antibodies and antigens
• Multi-dimensional space that maps shape
characteristics that allow binding (eg
hydrophilicity/polarity, physical shape, etc)
• Cellular automata where each point r
(vector) is coupled to the points around its
mirror image, -r
Results
-This behavior was seen for a region near the
boundary between stable and chaotic
behavior of the automata
-Preserved over a range of dimensions
(biologically need at least 5 dimensions to
cover “shape space”) and lattice sizes
But do we really need the
network?
• Genetic variation can lead to B and T cells
that cover the entire range of pathogens, and
each antibody hits on average one antigen
• B cells differentiate into memory cells,
which are able to quickly split into lots of
effector cells and more memory cells
• After an attack, have more memory cells,
and they’re more coordinated
What about self-recognition?
-Self recognition is “learned” - each organism
has different self-antigens and can
recognize them
-If “other” antigens are introduced at a
particular stage in development, the
organism will incorporate them as “self”
(mice)
Can networks do this?
• Yes! Well, small networks can. Particularly,
networks with an odd number of nodes connected
in loops can.
• Some networks blow up under a small but
constant antigen concentration
• But some don’t - and those are the ones that seem
to correspond most closely to biological reality
But… the non-network solution
• T cells are “weeded out” in the thymus if
they attack the self antigens
• B and T cells somehow trigger a selfdestruction signal if they respond too
strongly or too weakly to self antigens as
they develop
But, immune networks have other
applications!
• Data analysis
• Other computers
• Models for body-wide immune events (as
models of system-wide behavior, can
explain some medical results)
References
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Bernandes, A. T. et al. Immune network at the edge of chaos. Journal of Theoretical Biology. ISI Web of Knowledge.
1997.
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Calenbuhr, V. et al. Natural tolerance in a simple immune network. Journal of Theoretical Biology. ISI Web of
Knowledge. 2001.
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Sun, J. et al. Glassy dynamics in the adaptive immune response prevents autoimmune disease. Physical Review
Letters. ISI Web of Knowledge. 2005.
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Sadava, David, et al. Life: The Science of Biology. 2006. Chapter 18: The Immune System.
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Muc-Wierzgon, M, et al. On the holistic approach in cancer biology: Tumer necrosis factor, colon cancer cells, chaos
theory and complexity. Journal of Biological Regulators and Homeostatic Agents. ISI Web of Knowledge. 2004.
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"Jerne, Niels K.." Encyclopædia Britannica. 2008. Encyclopædia Britannica Online. 3
May 2008 <http://www.britannica.com/eb/article-9043549>.
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