Boris I. Shraiman

                                                   Statistical Physics,
                                                  PhD Physics,  Harvard 1983
 
Permanent Member of the Kavli Institute for Theoretical Physics
Professor, Department of Physics, UCSB
 

Address:
room 2317
KITP, Kohn Hall, 
University of California,
Santa Barbara, CA 93106

E-Mail: shraiman@kitp.ucsb.edu
Tel.           805-893-2835
FAX         805-893-2431

Publication List
 

Research Interests:

Quantitative Systems Biology and Bioinformatics;
Statistical Mechanics of Non-Equilibrium Systems.    
 

Current Research:

I. Patterning and growth in development.

Understanding how a multicellular organism developes is one of the fundamental problems in science. Despite widely held belief that "theory" has no place in biology, this field is clearly in need of new ideas and concepts which can be generated  by oldfashioned process of developing models which explain observations and make falsifiable predictions. In fact, theoretical ideas such as Wolpert's idea of morphogen gradient have had massive impact in the development field. Our current work is focused on the problem of coordination of patterning and growth in the process of organogenesis in Drosophila.  In collaboration with  S. Cohen's lab (EMBL),  Lars Hufnagel (KITP), Herve Roualt (ENS) and I are examining the dynamics of morphogen gradient formation in the wing imaginal disc - larval precursor of the adult wing. In the wing imaginal disc patterning induced by morphogen gradient is concurrent with cell growth and proliferation (the number of cells increases by a factor of > 1000). How is patterning coordinated with growth? How is the growth controlled? How does the developing limb know when to stop growing? 

Mechanical feedback as a mechanism of growth control.
  A recent paper (Shraiman BI, Proc Natl Acad Sci U S A. 2005 Mar 1;102(9):3318-23) considers the mechanism responsible for the observed uniformity of growth in wing imaginal discs which persists in the presence of gradients in growth inducing morphogens and in spite of the stochastic nature of cell division. The phenomenon of  “cell competition” which manifests itself in apoptosis of slower growing cells in the vicinity of faster growing tissue, suggests that uniform growth is not a default state but a result of active regulation. How can a patch of tissue compare its growth rate with that of its surroundings? A possible way is furnished by mechanical interactions. To demonstrate this we formulate a mathematical model of non-uniform growth in a layer of tissue and examine its mechanical implications. We show that a clone growing faster or slower than the surrounding tissue is subject to mechanical stress and propose that dependence of the rate of cell division on local stress could provide an “integral feedback” mechanism stabilizing uniform growth. The proposed mechanism of growth control is not specific to imaginal disc growth and could be of general relevance. Several experimental tests of the proposed mechanism are suggested.

Mechanical interaction can in principle provide a mechanism for propagating information about disc size (and shape) throughout the disc. Together with morphogen gradients, tissue mechanics is capable of reliably terminating growth in the disc, as shown in Hufnagel L, Teleman AA, Rouault H, Cohen SM, Shraiman BI.,” On the mechanism of wing size determination in fly development,” Proc Natl Acad Sci U S A.104(10):3835-40,(2007)

Other developmental modeling projects
include modeling of the Planar Cell Polarity phenomenon in
fly wings (see picture) in collaboration with Yoram Burak
(former KITP postdoc)  and modeling of the ommatidial xtal formation in eye imaginal discs during Drosophila larval stage (with David Lubensky, U. Michigan) and Nick Baker (Einstein School of Medicine.)



Eye imaginal disc development:  J. Kumar, Nature Review of Genetics 2, 846 (2001)        



II. Regulatory Networks in Biology.

I am interested in understanding the general principles governing the organization and evolution of intracellular bio-molecular networks which are involved in signal transduction and in control of gene expression.  Two broad projects are being pursued:

1) Adaptive regulation in cell signaling. The question is to understand and quantitatively describe the function and evolution of enzymatic signaling pathways underlying signal transduction. What are the engineering characteristics and design principle of these systems? What parameters are available to the cell in "fining tuning" or adaptively optimizing the performance of the signaling cascade in response to current environment? What can we learn about network evolution from comparing different signaling pathways and different incarnations of the same pathway (e.g. G-protein coupled receptor and cyclic nucleotide pathways in different sensory systems)?      
                          
The first steps in this program are described in the (2000) paper "Engineering aspects of phototransduction..." in collaboration with Peter Detwiler (U.Washington), Sharad Ramanathan (Bell Labs) and Anirvan Sengupta (Rutgers) which dealt with vertebrate photo-transduction.  Current work in collaboration with Alain Pumir (INLN, Nice) and Rama Ranganathan (SW Med School)  models fly (Drosophila) photo-transduction. Fly photo-transduction is quite different from the vertebrate case as it involves a non-linear "digital" rather then linear "analog" response.

A set of single photon responses of Drosophila - so called Quantum Bumps - is shown in the Figure
along with a simplified diagram of the phototransduction cascade.





2) Transcription control networks  employ DNA-binding proteins (aka transcription factors) which regulate the recruitment of RNA polymerase and therefore control the transcription and expression of genes. We are interested in quantitative modeling of transcription control networks and in understanding the "design principles" undelying their architecture. We are also interested in the development of bio-informatic algorithms which could allow reconstruction of transcription factor mediated regulation from genomic and high-throughput expression data. Some general questions: what aspects of biological networks, as observed in nature, are responsible for their "robustness" -- i.e. relative insensitivity to mutation -- and "evolvability"  -- i.e. ability to acquire new function? Some specific questions: how can one reliably identify transcription factor binding sites in regulatory stretches of DNA? can one predict the interactions and functional modality of different transcription factor binding sites? 

Recent work:
a) examined constraints on the transcription network imposed by minimization of its sensitivity to mutation
"Specificity and Robustness in Transcription Control Networks"   in collaboration with Anirvan Sengupta (Rutgers) and Marko Djordjevic (Columbia)
b) developed a novel algorithm for identification of transcription factor binding sites and applied to to the analysis of the highly pleiotropic transcription factors in E. coli: "Biophysical Approach to Transcription Factor Binding Site Identification" (in collaboration with Anirvan Sengupta (Rutgers) and Marko Djordjevic (Columbia)
c) analyzed the function of the PEP Phosphotransferase System ( PTS) and the effect of transcriptional regulation on it. The PTS underlies uptake of many sugars and implements a general nutrient sensory system. This work classified the possible switching phenotypes arising from the interactions of different sugar uptake modules:   “Switching in the E.coli Carbohydrate Metabolic Network” (in collaboration with Mukund Thattai (MIT))


III.  Search behavior: Exploration, Exploitation and Information

Olfactory source location at high Reynolds number and Infotaxis
Olfactory search involves "climbing" the concentration gradient of the odorant. At least naively. At least at low Reynolds number, e.g. the conditions appropriate to bacterial chemotaxis. At high Reynold number, local gradient of concentration is far too intermittent to point in the right direction. What is then an optimal, or at least reasonable search strategy? A paper with Eugene Balkovsky, "Olfactory search at high Reynolds number", PNAS (2002),  provided a simple strategy for olfactory search in the presence of a steady (mean) wind velocity. More recent work in collaboration with Massimo Vergassola (Pastuer Inst, Paris) attempted to generalize this approach and to provide a unified description of search strategies, revisiting and rethinking our understanding of bacterial chemotaxis along the way.
This effort has lead us to a rather general search strategy which is based on maximizing the rate of information gain which we called "Infotaxis" described in "Infotaxis: a strategy for searching without gradients", Nature (2007), by M. Vergassola and BIS. Remarkably this approach appears to be a particular (limiting case) of dealing with the well known "exploration and exploitation" problem of reinforcement learning and infotaxis strategy is various modified forms is applicable in a broad range of applications.

IV. Statistical Hydrodynamics.

Statistical Geometry of Turbulence
This effort (currently in the background) centers on the construction of a phenomenological model describing the dynamics of large fluctuations in the inertial scaling range of a fully turbulent flow. The goal is to understand the statistics of large fluctuations on small scales (which does not follow Kolmogorov's 1941 scaling theory) and to understand how it depends on the strain and vorticity structure of the larger scales. Recent paper "Lagrangian Tetrad Dynamics..." argues that a simplest non-trivial model must follow (for a short time only) the evolution of not one or two but at least 4 Lagrangian points - enough to define a "shape" tensor which integrates over the history of the strain along the trajectory. Energy transfer is found to be associated with formation of "pancakes" or "ribbons"  by strain configurartions with two stretching and one compressing eigenvalues (tr s^3 ) <0 product. Many other geometrical aspects are discussed (see recent
talk at http://online.itp.ucsb.edu/online/hydrot_c00/shraiman/).  The kinematics of Lagrangian shapes was examined in another recent paper, "Geometry of Lagrangian Dispersion..."  The emphasis on the Lagrangian dynamics and multipoint correlators derives in part from the earlier work on the Passive Scalar Problem (for review see "Scalar Turbulence", for technical detail see
"Anomalous Scaling fo a Passive Scalar near Batchelor Limit" and "Lagrangian Path Integrals ..."


  Bio- group members:
 students:  Ben Callahan, Kevin Chou
 postdocs: Richard Neher, Pierre Neveu, Alberto Puliafito
visitors/collaborators:  Michael Brenner (Harvard), Michael Elowitz (Caltech), Deborah Fygenson (UCSB), Lars Hufnagel (EMBL, Heidelberg), Alain Pumir (U Nice),  Aurelio Teleman (Heidelberg), Mukund Thattai (NCBS, Bangalore), Massimo Vergassola (Inst Pasteur)
 


Teaching:
Spring 2005     (Physics 257, Special topics in biophysics):  Modeling in Systems Biology
Winter 2006     Physics 219, Statistical Mechanics
Winter 2007     Physics 219, Statistical Mechanics
Spring 2008     Physics 223C, Physics of Biophysics
Spring 2009     Physics 259 (Special topics) Statistical Mechanics of Genetics and Genomics.
                                                    


                     

Other activities: Interdisciplinary Biology community building

Past programs:
Aspen workshop on "Cell Signaling and Development" (2001)
KITP program on "Bio-molecular Networks"  (2003)
Jerusalem Winter School of Theoretical Physics:  "Networks and Evolution" (2004).
KITP mini-workshop on "Networks of growth, death and aging" (2005)
KITP mini-workshop "Interdisciplinarity and Discipline in Education" (2006)
KITP mini-workshop "Physics and Biology of Morphogenesis" (2008)