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Molecular |
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Present
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Structure of DNA
Solutions: |
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DNA structural
organization both in bacterial and in
eukaryotic cells remains a mystery. While some structural features can
be
inferred indirectly, there are simply no good experimental techniques
which
allow to measure chromatin structure at the spatial scales between 10
nm and ~
1mm. More
surprisingly, the structure of bare DNA
solutions is not known. There is no good method to measure the
structure factor
even for solutions of pure DNA in vitro. Static light scattering (SLS)
approach
does not give reliable data for DNA because of unavoidable presence of
dust in
solutions. Yet polymer structure of DNA solutions
should be rather
unusual. DNA is a semi-flexible polymer with a very large persistence
length/monomer size ratio. Excluded volume interactions in such coils
are weak,
yet present. Such conditions were termed “marginal” to
differentiate them from
both “theta” solvents where excluded volume interactions
are negligible and
“good” solvents, where they are strong. The properties of
marginal solutions
are predicted to be rather peculiar and not necessarily intermediate
between
those of theta and good solutions [Schaefer et al, Macromol. 13, 1280 (1980)]. E.g. the correlation
length x in semi-dilute marginal polymer
solutions should
scale like |
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Environmental Stress Response in Yeast Cells: |
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Complex biological and human engineered systems share many of the same design principles since both types of systems are optimized for robust operation and, at the same time, for great evolvability. One such shared design rule is the bow-tie architecture: a set of different inputs to the system converges onto a core machinery hub from which a number of different outputs diverge. In the course of system evolution, the core machinery module is highly conserved allowing for the robust operation of the system, while different input and output modules are modified or added as new challenges arise. Within this
project we use system
engineering approach to analyze the environmental stress response (ESR)
system of
yeast. Indeed, ESR reacts to a number of different inputs -
stresses
such as DNA damage, heat, oxidative, osmotic, heavy metal, and salt
stress,
etc, by utilizing appropriate transducer proteins. We
identified core machinery: the
circuitry involved in the expression of RPN4, the
transcriptional
regulator of the proteasome genes, as a main computational unit of the
ESR, that
integrates different stresses and leads to outputs,
down-regulation of
protein synthesis genes and an up-regulation of genes involved in
protein
degradation. In this model, the Rpn4 hub in the biochemical network
acts as a
switch that changes the cell state into an ESR active state. Indeed,
the Rpn4
expression hub possesses the features of a true switch: a combination
of a
negative feedback regulatory loop (Rpn4
autocatalyzes its transcription) and positive feedback (via
upregulation of
proteasomes that degrade Rpn4). These are the standard mechanisms of
robust
control: negative feedback loops tend to keep the expression level of a
protein
constant minimizing outside interference; whereas positive feedback
elements
serve as switches in the system behavior by amplifying the effects of
changes
in system inputs. |
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Quantitative Study of Phenotype Variation in Isogenic E. Coli: |
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A population of genetically identical bacterial cells exhibit a range of phenotypes due to the stochastic nature of gene expression and of segregation of proteins during cell division. The adaptive fitness of intrapopulation variation has been the topic of many recent studies. In this project we examine the variation in plasmid copy number in the cell population as a measure of cell individuality. There is a cost/benefit trade-off for a cell to harbour a plasmid that depends on the environmental conditions, e.g., the concentration of antibiotics. We hypothesize that the plasmid copy distribution in a cell population adapts itself to changes in environment. Moreover, we assume that the presence of cells with different plasmid copy numbers helps the population to survive sudden changes in the environmental conditions, as there are will always be some cells in the distribution most adapted to the prevailing conditions. Here we propose highly sensitive
time-resolved imaging technology to directly measure plasmid copy
number
distribution in individual cells in the bacterial population and to
study how
these distributions adapt to changes in the environment. The methods
for visualization
of individual living cells are based on highly sensitive fluorescence
microscopy, fluorescence correlation spectroscopy, and the cell sorting
using
microfluidic devices. Cells harbouring four types of plasmids that
differ in
their average copy number and in their partitioning properties will be
examined. |
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Past
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Internal dynamics
of biological polymers:
in collaboration with Dr. Anne Bernheim-Groswasser, Chem. Eng. BGU |
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How the
stochastic thermal motion (diffusion)
reveals itself in the dynamics of polymer segments which are bound by
connectivity along the chain, by polymer stiffness, by topological
constrains, by hydrodynamic and other interactions? The question does
not have simple solutions either in theory, nor in computer
simulations, and neither in experiments. We have developed an original
experimental approach to measure the dynamics of biological polymers,
such as DNA at the level of single monomer with high temporal and
spatial resolution. Furthermore,
one does not have to rely on classical
thermal fluctuations to drive the dynamics of the system. We introduce
now molecular motors – little nanomachines
– which actively push polymers around at the nanoscale |
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in collaboration
with Prof. Leonid Mirny, MIT |
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in collaboration
with Prof. Itzhak Fishov, Life Sciences, BGU |
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