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Douglas Brutlag
Professor, Departments of Biochemistry & Medicine
Stanford University School of Medicine

Keynote Address: Discovering Function in Proteins and Proteomes

Our group develops databases of protein sequence motifs that are useful for predicting the function of individual proteins and entire proteomes. Unlike sequence similarity, protein motifs examine only the functionally important amino acids. This property of sequence motifs gives increased specificity of motifs and permits analysis entire genomes with no false predictions and few missing predictions.

Functional protein sequence motifs represent conserved catalytic sites, substrate & cofactor binding sites, DNA binding sites, and protein-protein interaction sites. As such, these motifs are all potential drug targets, siRNA targets and site directed mutagenesis targets. We have also mapped all of our sequence motifs onto the protein structure database to obtain three-dimensional representations of these sites and drug targets.

In this talk I will discuss the efforts of my group to develop a database of conserved regions in protein families (eBLOCKs) using the PSI-BLAST program. Then I will discuss converting these conserved regions into both consensus patterns (eMOTIFs) and position specific scoring matrices (eMATRICES). We have also developed a 3-dimensional representation of these motifs (3MOTIFs and 3MATRICES) in which one can visualize the location of the motif in a known protein structure and associations with potential ligands. I will mention a database of motifs specific for signal transduction proteins (eSIGNAL), and finally I will discuss a database that maps these motifs on all the sequenced proteomes (ePROTEOME).

All of these databases and resources are available on the Web:

References:

  • Bennett, S. P., Lu, L., & Brutlag, D. L. (2003). 3MATRIX and 3MOTIF: a protein structure visualization system for conserved sequence motifs. Nucleic Acids Res, 31(13), 3328-3332.
  • Bennett, S. P., Nevill-Manning, C. G., & Brutlag, D. L. (2003). 3MOTIF: visualizing conserved protein sequence motifs in the protein structure database. Bioinformatics, 19(4), 541-542.
  • Huang, J. Y., & Brutlag, D. L. (2001). The EMOTIF database. Nucleic Acids Res, 29(1), 202-204.
  • Nevill-Manning, C. G., Wu, T. D., & Brutlag, D. L. (1998). Highly specific protein sequence motifs for genome analysis. Proc Natl Acad Sci U S A, 95(11), 5865-5871.
  • Su, Q., Saxonov, S., Lu, L. and Brutlag, D. L. (2005). eBLOCKS: enumerating conserved protein blocks to achieve maximal sensitivity and specificity. Nucleic Acids Res, 33, D178-D182.
  • Wu, T. D., Nevill-Manning, C. G., & Brutlag, D. L. (2000). Fast probabilistic analysis of sequence function using scoring matrices. Bioinformatics, 16(3), 233-244.

Andrew Farmer
Principal Software Engineer, NCGR

Workshop: Comparative Genomics

Comparative genomics, broadly speaking, attempts to characterize the similarities and differences observed in the genomic information for multiple species (or individuals). Comparative analyses can take place on a number of different levels of resolution, from genetic maps to whole-genome sequence comparisons, and the resulting information can be used in a wide variety of applications, including gene prediction, genome assembly, phylogenetics, functional annotation, and candidate gene discovery. In this workshop, we will look at a few of the analyses that are being used for characterizing the similarities and differences between two or more genomes, as well as some of the visualizations and downstream analyses that try to make sense of the data produced by such studies.

Sheng Gu
Technical Staff Member, Los Alamos National Laboratory

Talk: When Bioinformatics meets Proteomics

In the post-genomic arena, mass spectrometry has become the method-of-choice for proteomic researches. However, the complexity of mass spectrometry data and large-scale data size encumbered high-through put proteomics. Bioinformatics advancement in the past 10 years synergy with technology innovations in biological mass spectrometry provides the solution for high-throughput proteomics. The presentation will give an overview of bioinformatics tools for proteomics and how these tools help in mining the cellular proteome.

Carla Kuiken
Staff Scientist, Los Alamos National Laboratory

Carla Kuiken obtained a PhD in Medicine at the University of Amsterdam, and started work as a Posdoc at the Los Alamos HIV database group in . She started a new database for hepatitis C sequences and immunological epitopes in 2001, and divides her time between database and website development and scientific research on HIV and HCV.

Talk: The Los Alamos viral databases: research tools and their applications.

The Theoretical Biology and Biophysics group in Los Alamos maintains three virus databases: HIV, hepatitis C and influenza. All three databases are publicly accessible and offer tools to search the databases and analyze the results. The presentation will give an overview of the research possibilities using these databases, and present a few recent using these sites.

Peter Lammers
Professor, Department of Chemistry and Biochemistry
New Mexico State University

For the last several years, Dr. Lammers' laboratory has been identifying biochemical pathways that support the widespread symbiosis between arbuscular mycorrhizal fungi and the vast majority of land plants. This has been a collaborative effort between Dr. Lammers' laboratory, Yair Shachar-Hill (Michigan State University) and Phillip Pfeffer (USDA-Eastern Regional Research Center). Dr. Lammers is currently collaborating with the Department of Energy's Joint Genome Institute (JGI) on genome sequence analysis of an arbuscular mycorrhizal genome project (Glomus intraradices) and an ectomycorrhizal genome project (Laccaria bicolor), both of which form beneficial symbioses with the model perennial tree, Populus tricocarpa, whose genome sequence has recently been released by JGI.

Talk: Genomics of an obligately symbiotic, ancient asexual fungus

Glomus intraradices is an arbuscular mycorrhizal (AM) fungus that promiscuously colonizes the majority of plants. The AM fungi are thought to have co-evolved with plants as they colonized the continents some 400 million years ago. AM fungi play critical roles in phosphorus, nitrogen and water transport to the host plant and provide protection to the host from pathogens via mechanisms that remain largely unknown. AM fungi are obligate biotrophs that are unable to grow except in symbiosis, where morphological and biochemical differentiation produce the only fungal structures capable of taking up carbon in the form of hexoses provided by the host plant. In this talk, I will describe early information on the organization of the 16 Mbp genome of G. intraradices. The multinucleate, asexual nature of the fungus dictates profoundly different ways of maintaining genetic diversity within a species. Indeed the fungus appears to act more like a collective of syncytial nuclei than as individuals within a population. Nevertheless, early results shows that despite it's asexual lifestyle, G. intraradices still has at least some of the genes encoding key events in meiotic recombination.

Thomas Leitner
Staff Member, Los Alamos National Laboratory

Dr. Leitner is currently a staff member of LANL group T-10 where he is co-PI of the HIV database. Before that, he was an Assistant Professor and head of the HIV & Retrovirus Section at the Swedish Institute for Infectious Disease Control, Karolinska Institute, Sweden as well as the Head of the Genomics Core facility at the same institute. He has published over 70 scientific publications (including original papers, books, book chapters and review articles) on molecular evolution and related subjects. His main research interest has been in HIV evolution and molecular epidemiology, including development of both molecular biology laboratory methods and computational methods for analyzing genetic sequences. He has also been involved in research on other virus systems as well as bacterial genetic evolution and canine mtDNA evolution.

Tony Martino
Department Manager, Advanced Measurement and Imaging Biosciences Group - Sandia National Laboratories

Dr. Martino received his Ph.D. in Chemical Engineering from the University of Washington in 1991. He was a staff scientist at Sandia National Laboratories from 1991 to 2004 most recently in the Biosystems Research Sciences Department before becoming department manager of the Advanced Measurement and Imaging Biosciences group. His research interests include cytokine IL-2 signaling pathways in the proliferation and differentiation of T-cells in immune response and high-throughput studies of protein complexes and interactions in cyanobacteria.

Talk: Hopes and Challenges in High-Throughput Proteomics.

Charlie Strauss
Staff Member, Los Alamos National Laboratory, cems@lanl.gov

Charlie Strauss is a staff member in the Bioscience Division of Los Alamos National Laboratory. In bioscience he is best known as a co-developer of the Rosetta ab intio protein structure prediction algoritm and the Mammoth structural alignment algorithm. He also developed instrumentaion for ultra-fast Transient Circular Dichroism of Biomolecules to monitor protein folding. Currently he is focused on structure based annotaion. In the physical chemistry community, he is known both for experimental and theoretical work on synchronous molecular reactions in which more than a one chemical bond is broken within a single molecule, and well as for his discovery of excess photon detachment in atomic ions. His inventions include synthetic array heterodyne detection, a broadly tunable vacuum ultra-violet laser and a rapid solid state method for laser wavelength. Past work includes information theoretical chemistry, and Maximum Entropy image enhancement and deblurring, medical imaging through tissue using light, Differential Absorption Lidar for remote detection of trace chemicals, advanced carbon dioxide laser development and ultra-sensitive infrared detection.

Talk: Structure based annotation using Rosetta.

Most genomes are annoated on the basis of sequence simmilarity to other genes of putative known function. Typically less than 60% of any novel genome can be annotated in such a fashion, leaving a large number of unannotated hypothetical proteins as well as many with poor or misleading annotation. Moreover, the fraction that is annotatable by sequence simmilarity by definition must relate to closely related functions shared between organisms. Yet a common goal in sequencing a new organism is to discover the functions and proteins that have diverged the most from common sequences and thus are too remote for recognition by sequence homology. We are developing automated structure based annotation. We predict the structures of unknown proteins and then associate the compare these strucures with known structures. If the strucutures match well a remote structural homolog has been found and if they match none a unique protein may have been found. I will discuss the Rosetta structure prediction algorithm and its applications.

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