Adam Arkin Faculty Scientist Assistant Professor of Bioengineering & Chemistry
University of California, Berkeley
College of Chemistry, Bioengineering Department
Research Emphasis The Arkin Lab works on detailed modeling of genetic and biochemical
networks with emphasis on developmental systems. The laboratory creates
custom genetic circuitry in Saccaromyces cerivisiae and multichannel,
protein and small molecule biosensors. The Arkin Lab is interested in
the detailed physical analysis of the network of biochemical and genetic
reactions that govern cellular development. The goal is to divine the
engineering principles of the control systems that determine cell behavior
and differentiation in response to internal and external signals. Because
of their simplicity (relative to eukaryotic cells), and because many bacterial
genome sequencing projects have recently completed, we study mostly bacterial
and viral circuitry. Particular biological systems currently under study
in my lab include, l-phage/Escherichia coli interactions, the role of
stochastic phase-variation of type-1 pili in uropathic E. coli virulence,
and analysis of the sporulation initiation and germination pathways in
Bacillus subtilis. As the basis for such analyses we examine the detailed
mechanisms of the underlying chemical reactions. For example, a rigorous
physical analysis of the mechanisms of prokaryotic gene expression revealed
that the temporal pattern of protein production from a single gene is
an erratic and bursty stochastic process. Analysis of networks of such
genes responsible for developmental switches demonstrated that while some
architectures generate deterministic outcomes despite this noise, others
exploit the noise to produce population diversity to, for example, evade
attack by the immune system. In addition to theoretical analyses, the
laboratory has started experimental measurements on such systems and has
begun design and implementation (in yeast and E. coli) of our own custom
genetic circuitry. Thus, the laboratory applies theoretical and computational
analyses from dynamical systems, stochastic processes, chemical kinetics
and statistical mechanics and methods from molecular biology to determine
the principles of cellular signal processing and to aid in design of custom
cellular circuitry that may, for example, act as sensitive biosensors.
