Fall 2007 BCB 691 - Faculty Seminar

Overview & 10' Presentations by BCB Faculty (see BCB Rotation Projects)
Aug 24	Hui-Hsien Chou, GDCB&ComS Sue Lamont, AnS Basil Nikolau, BBMB Chris Tuggle, AnS	Potential Rotation Projects
Aug 31	Volker Brendel, GDCB Oliver Eulenstein, ComS Les Miller, ComS	Potential Rotation Projects
Sept 7	Drena Dobbs, GDCB Vasant Honavar, ComS Eve Wurtele, GDCB	Potential Rotation Projects
40' Presentations by BCB Faculty
Sept 14	Krishna Rajan, MSE	Learning from systems biology: an omics approach to materials design
Sept 21	Yves Sucaet Matt Moscou John Van Hemert Fadi Towfic	Bioinformatics Laboratory is a forum for the exchange of experience, knowledge, and resources that can be brought to bear on research endeavors at ISU. Descriptions of research projects assisted by the BCB lab will be presented including: microarray consulting, baboonbase, and TAL effector genes.
Sept 28	Volker Brendel, GDCB	Annotating the maize (and other plant) genomes
Oct 5	No Class - Trip to Midwest Conference
Oct 12	Ed Yu, Physics & BBMB	Structural basis of bacterial multi-drug transporters
Oct. 19	Lyric Bartholomay, Ent	Computational Biology and vector-borne disease: from the field to the bench
Oct. 26	Guang Song, ComS	Probing functional mechanisms by structure-based modeling and simulations
Nov. 2	Robert Jernigan, BBMB	Control of Protein Motions by Structure
Nov. 9	Amy Andreotti, BBMB	"T cell signaling: insights from protein NMR spectroscopy"
Nov. 16	Karin Dorman , Statistics	Spatial Fluctuation of Recombination Rates in the HIV Genome: A Computational Model Identifies Hotspots
Nov 23	No Class - Thanksgiving Break
Nov. 30	Shashi Gadia, ComS	Harnessing the potential of XML
Dec 7
Dec 14	Finals Week

1) to introduce new BCB students to examples of research rotation/exploration opportunities available in BCB research groups
2) to provide all BCB students with an overview of active research areas in Bioinformatics and Computational Biology at ISU

Requirements: Attendance and participation. Each student is allowed one "excused absence" (missed due to conference attendance, illness, family obligation, etc.) and one "unexcused absence" (rather eat lunch, whatever...). Students who exceed these limits and wish to pass the course will be expected to perform makeup work (see class schedule for Dec. 2 and 9).

Questions: contact Chris Tuggle , instructor, email: cktuggle@iastate.edu
2255 Kildee, 4-4252

Krishna Rajan
Department of Materials Science & Engineering and
Bioinformatics and Computational Biology Program

The goal of modern systems biology is to understand physiology and disease from the level of molecular pathways, regulatory networks, cells, tissues, organs and ultimately the whole organism . As currently employed, the term 'systems biology' encompasses many different approaches and models for probing and understanding biological complexity, and studies of many organisms from bacteria to man. A similar paradigm exists for materials science where one ultimately wants to link macroscopic properties to atomistic scale features. The challenge in materials science is identifying pathways of how chemistry, crystal structure, microstructure, processing variables and component design and manufacturing “communicate” with each other to ultimately define performance. This forms the materials science equivalent of the biological regulatory network. In this talk we provide some examples of how materials informatics and bioinformatics are linked.

Please join us for the BCB Faculty Seminar, this Friday, Sept. 21st at 2:10 in 102 Science Hall I to learn about the BCB Lab and the projects they have done for life science researchers at Iowa State University.

The following BCB Graduate Students will present some of these projects to highlight the role bioinformatics can play in helping researchers understand and analyze biological information.

Yves Sucaet (Eve Wurtele's lab) - introduction
Matt Moscou (Roger Wise' lab) - microarray consultancy
Fadi Towfic (Vasant Honavar's lab) - TAL effector genes
John Van Hemert (Julie Dickerson's lab) - baboonbase

Come and learn how bioinformatics approaches have been applied to life science research projects by this group of graduate students. Perhaps you will learn how bioinformatics might be applied to one of your research projects...they are open to receiving more projects.

Recently, the BCB lab worked on the mosquito data collected by Prof. Emeritus, Wayne Rowley, Entomology, and others, including Lyric Bartholomay who now heads up the project in Entomology. Misha Rajaram (Karin Dorman's lab) was instrumental in setting up a database to organize the data. It can be viewed here:
http://lab.bcb.iastate.edu/sandbox/mishar/ .

To partially quote from their mission statement, the BCB Lab provides graduate students with a forum to share experience, knowledge, and resources and apply that synergy to the development, organization, and solution for real-world research problems. To view more information about the BCB lab, visit their website located here:
http://lab.bcb.iastate.edu/ .

We hope you will join us this Friday, Sept. 21 at 2:10 p.m. in 102 Science Hall I for this presentation.

Title: Annotating the maize (and other plant) genomes

Abstract: DNA sequencing technology continues to advance, with new technologies suggesting the possibilities of whole genome sequencing of even complex genomes at a fraction of previous costs. But sequencing is only part of the task - genome informatics seeks to annotate the protein coding genes and other features in the genome at commensurable speeds. I shall discuss my group's efforts on this topic, involving both computational and community annotation technology.

No class - trip to Northwestern University for Midwest Symposium on Bioinformatics

Abstract: Multidrug efflux pumps interfere significantly with cancer chemotherapy and the treatment of bacterial infections, by recognizing a number of structurally unrelated toxic compounds and actively extruding them from cells. We have determined the x-ray structures of the Escherichia coli AcrB transmembrane efflux pump in the presence of four structurally different agents. These are the first structures of any transporter that have been solved in complex with a variety of ligands by x-ray crystallography. The crystal structures illustrate that three ligand molecules bind simultaneously to the extremely large central cavity of 5000 cubic Angstroms, primarily by hydrophobic, aromatic stacking and van der Waals interactions. Each ligand uses a slightly different subset of AcrB residues for binding. The subsequent study of the efflux pump by crystallizing a mutant AcrB with five structurally diverse ligands indicates that AcrB consists of two distinct binding sites. These five ligands not only bind to various positions of the central cavity, but also to residues lining the deep external depression formed by the C-terminal periplasmic domain. The structures also suggest that AcrB assembles as a trimer of three identical channels for the extrusion of drugs.

Title: Computational Biology and vector-borne disease: from the field to the
bench

Abstract: The Medical Entomology laboratory at Iowa State University researches arthropod vectors (ticks and mosquitoes in this case) of public health
significance - from a holistic perspective. We operate surveillance programs in which we trap mosquitoes and drag for ticks in the field, identify and count specimens, and assay for infectious agents. At the bench, we ask how ticks and mosquitoes respond to infection, emphasizing immune response activation. Of particular interest are mosquito and tick blood cells that are first-line defenders in the arthropod immune response. Computational biology spans all of our efforts. For surveillance purposes, collaboration with the BCB lab has facilitated presentation of ~40 years of mosquito surveillance data in an interactive website powered by a relational database. At the molecular level, we are interrogating genome sequence and using microarray analysis to target genes of interest for future research.

Probing functional mechanisms by structure-based modeling and simulations

Protein dynamics can provide important insights to the understanding of protein functions. In this talk, we will describe some available approaches for studying protein dynamics and show how they can be applied to understand the mechanisms of some protein functions. These approaches include molecular dynamics simulations, ensemble-based methods, and mechanistic models. We will explain one type of mechanistic models, the elastic network models in details, and show how they can be used to explain protein dynamics observed in crystals, dynamics observed in solution, and conformational changes seen in many proteins upon ligand binding. As a case study, the dynamics and flexibility of HIV (human immunodeficiency virus) protease is investigated. An understanding of such dynamics and flexibility may play a key role on the
future design of protein inhibitor drugs.

Abstract: Computing the functional motions from protein structures is an important challenge in computational biology. Simple coarse-grained elastic network models have proven to be particularly useful for this, and more so than atomic molecular dynamics. The behaviors of protein machines can understood with these models, and the important large domain motions can be readily obtained. The mechanics of the protein synthesis machine, the ribosome, will be discussed.

Karin Dorman
Statistics and Genetics, Development and Cell Biology

Title: Spatial Fluctuation of Recombination Rates in the HIV Genome: A Computational Model Identifies Hotspots

Abstract: Coinfection of a single cell with two or more HIV strains may produce recombinant viruses upon template switching by the replication machinery. Selection effects and sequence features predictive of high local rates of recombination in HIV-1 can be uncovered by surveys of recombination in natural sequences. We undertook a comprehensive survey of inter-subtype recombination in public database HIV-1 isolates using a hierarchical, spatially smoothed Bayesian multiple change point model for recombination. The model accounts for the uncertainty associated with inferring past recombination, while allowing simultaneous inference of inter-subtype recombination breakpoints and spatial variation in the recombination rate along the HIV-1 genome. We have revealed that the \textit{in vivo} pattern of recombination breakpoints along the HIV-1 genome is highly non-uniform. The overwhelmingly dominant hotspot for recombination was in the reverse transcriptase gene, part of the \textit{pol} open reading frame. Other hot regions include p24 in the \textit{gag} and essentially all of the \textit{env} open reading frame.