WS3: Systems Biology for Microbial Genomes
Understanding microbes through multifaceted functional genomics
As the world-wide efforts continue to make available a large amount of omics data, system biology has been gradually shaped as a field to study
the interactions among components of biological systems, to address the causes and effects in biological networks through simultaneously
measuring multiple components and rigorous data integration with mathematical models, and to integrate computational modeling, hypotheses
formulation, experimental validation, and computational model refining.
We have invited scientists from leading research centers/laboratories to present their work in system biology, particularly for microbial
genomes, which cover different aspects (reconstruction, modeling, analysis and simulation) of biological network studies using both experimental
and computational techniques.
The workshop will also provide a platform for researchers from different disciplines to exchange visions, insights, ideas, and discoveries
about the challenges and opportunities in the field of system biology, to share and appreciate research efforts that have been devoted to
the field, to provide and seek advice/suggestion/solutions to some problems in the field, and to establish face-to-face collaboration.
Invited Speakers :
• Nitin S. Baliga
Institute for System Biology
Title: "A Predictive Model of Adaptive Responses to Environment"
All organisms routinely sense and process complex changes in their environment through a web of intricate information processing networks
to adapt their behavior. Any attempt to predict these responses or re-engineer new ones would require a sophisticated and quantitative
understanding of this entire process. Using a systems approach we have constructed a predictive model of the complete gene regulatory
program in Halobacterium salinarum NRC-1, an archaeal microbe that thrives in a saturated salt environment that is lethal to most life forms.
The architecture of this model reflects how diverse physiological processes are inter-coordinated during environmental responses and as such
can now be used as a framework for characterizing and reengineering environmental response sub-circuits. This study promotes the idea that
a systems approach can help to quickly unlock the potential of the already vast and increasing numbers of organisms with fully sequenced genomes.
• Frank Bergmann
Keck Graduate Institute / University of Washington
Title: The Systems Biology Workbench: A modular framework for Systems Biology
A large number of software packages are available to assist researchers in systems biology. In this talk, I describe the current state
of the Systems Biology Workbench (SBW), a modular framework that connects modeling and analysis applications, enabling them to reuse
each other’s capabilities. I describe how users and developers will perceive SBW and then focus on currently available SBW modules.
There is a wide variety of SBW enabled applications available, such as modeling, bifurcation analysis, frequency analysis, deterministic
and stochastic simulation, and 3D visualization.
The developer of a new software application can use these tools as a foundation instead of recreating existing functionality, which
allows them to focus on novel tasks. An existing application written in any supported programming language (C/C++, Java, .NET, Python,
Delphi/Kylix, Matlab and FORTRAN) can be modified to interact with SBW with minimal programming overhead. This enables other applications
to use its functionality.
The software, tutorial manual, and test models are freely available from the Computational and Systems Biology group at University of
Washington. Source code is available from Source Forge. The software is open source and licensed under BSD.
• Jason Chan
University of California - San Diego
Title: "Integrating genetic and physical relationships – our current understanding of the genetic model"
The rising influx of sequenced genomes and the need to understand how their functional components relate presents an interesting and unique
logistic challenge. Increasing availability of data from large scale screens introduced both interesting systematic insights as well as
increased levels of artifacts due to noise. Previously, we have applied homology across species to both filter protein-protein interactions
as well as infer previously unreported protein-protein interactions. Work has also been done to reconcile our understanding of genetics with
high throughput protein interaction data to form conceptualized "pathways." Here, we provide evidence for an interesting motif found between
protein-protein interactions and synthetic lethal interactions within Saccharomyces cerevisiae. Unsurprisingly, interactions involving
essential genes tend to be genetically antagonistic. I will describe our current efforts to predict physical protein interactions as well
as our current efforts to understand how this "synthetic lethal" motif plays a role in our concept of 'pathways' within an organism, and
its potential use for analysis across species.
• Eric Mjolsness
University of California - Irvine
Title: "A random steady state model for the activity of pyruvate dehydrogenase"
Pyruvate dehydrogenase is a key metabolic enzyme which occurs in a complex containing many copies of three enzymes E1, E2, and E3.
These enzymes act in a reaction sequence. We hypothesized that an important function of their multiplicity in the complex is to mix E1,
E2, and E3 in approximately the right proportions so as to maximize net flux through the sequence, despite the inevitable local imbalances
in their number. To quantify this hypotheses we constructed a “random steady state” (RSS) model combining equilibrium statistical mechanics
(at a slow time scale) with steady-state kinetics (at a faster time scale). This order inverts that of the more common "quasi-equilibrium"
class of molecular complex activity models, in which equilibration happens on a fast time scale. We show results from the RSS model and
compare to data on pyruvate dehydrogenase in E. coli.
• Bernhard O. Palsson
University of California - San Diego
Title: "Reconstruction of the genome-scale transcriptional regulatory network in E. coli"
High-density tiling arrays have been used to perform location analysis for three classes of DNA protein in E. coli and for high
resolutions expression profiling. The protein examined are: 1) the RNA polymerase and sigma factors, 2) 12 broad acting transcription
factors, and 3) 7 DNA bending protein. This data will be discussed and its representation in an R matrix form discussed. The
computation of the functional state of the TRN are illustrated.
• Bruce E. Shapiro
Caltech and Cal State University
Title: "Designing Simulations for Portability and Reuse: The Systems Biology Markup Language"
The Systems Biology Markup Language (SBML) is a tool-neutral, computer-readable, text file (XML) format for representing models of biochemical
reaction networks. It is especially applicable to descriptions of cell signaling pathways, metabolic networks, genomic regulatory networks,
and other modeling problems in systems biology. SBML is based on XML (the eXtensible Markup Language), a standard medium for representing
and transporting data that is widely supported on the Internet as well as in computational biology and bioinformatics. The central goal of
SBML is model portability. By encoding models in SBML, they can be freely interchanged between users, regardless of which software tool,
hardware platform, or operating system each uses. The benefits of this interoperability are enormous: models can be shared, standardized,
and made survivable through databases. These benefits are enhanced through publication on the BioModels database, a peer-reviewed, curated
database that utilizes SBML as one of its core file formats; the Systems Biology Ontology (SBO), a set of controlled vocabularies and ontologies
for the kinds of problems faced by computational modelers in systems biology; and a number of open source tools provided by the sbml.org website
that facilitate incorporation of SBML into users' individual modeling software.
• Lingchong You
Duke University
Title: "Sensing and communication in natural and engineered bacteria"
Quorum sensing is a mechanism by which many bacteria sense and respond to changes in their density via production and detection of small,
diffusible chemical signals. Since its initial discovery, quorum sensing has been found to be involved in regulating diverse cellular
functions, including bioluminescence, antibiotic resistance, and biofilm formation. From an engineering perspective, quorum sensing provides
an elegant strategy for bacteria to coordinate their behavior in a population. Here I will discuss our computational and experimental efforts
to analyze dynamic properties of quorum sensing and its application for engineering gene circuits. Specifically, I will discuss how and to
what extent quorum sensing may reduce noise in gene expression, how quorum sensing provides a means for a bacterium to "measure" the dimension
of its microenvironment, and how, when coupled regulated cell killing, quorum sensing enables programming of roust population dynamics.
Organizers:
Jason Chan, University of California - San Diego
Hongwei Wu, University of Georgia
John Wooley, University of California - San Diego