Bio

Dr. Cooper received his B.S. in Biology in 1977 from Lebanon Valley College, and his Ph.D. in Plant Biology from Washington University in 1982 where he studied the structure and biosynthesis of hydroxyproline-rich cell wall proteins in plants. He continued his research on plant extracellular matrix molecules as a Postdoctoral Fellow both at Washington University and at the ARCO Plant Cell Research Institute. From 1986 to 1988 he was a Research Associate in the Department of Biological Sciences at Stanford University where he developed his interest in plant-microbe symbiosis. Dr. Cooper joined the UCSB faculty in 1988 and has been a recipient of the UC Regents' Junior Faculty Fellowship and a Presidential Young Investigator Award from the National Science Foundation. He served as Associate Director and Director of the Interdepartmental Biomolecular Science and Engineering Program from 1996-2000 and as Associate Dean of Mathematical, Life and Physical Sciences from 2000-2006.

Research

My lab studies plant cell wall proteins thought to play important roles in plant development and plant-microbe symbiosis. The repetitive sequences of these plant gene products consist of tandemly repeated peptides, a sequence architecture shared with structural proteins that form numerous important biomaterials (e.g., insect and spider silks, animal collagens and keratins, bivalve mussel holdfasts, insect flight muscles, and plant cell wall matrices). Recently, we developed the requisite data-mining and data-visualization tools to exploit the rapidly-expanding genomic and metagenomic sequence databases for the discovery of new naturally evolved biostructural TR proteins.

A long-term goal of my lab is to elucidate the role of hydroxyproline-rich structural proteins in plant cell walls. We currently focus on five repetitive Proline-Rich Proteins in Medicago truncatula, a model legume for studies on host-microbe symbiosis (Figure 1). Genes encoding MtPRP1 and MtPRP2 are expressed at high levels in root tissues where the PRP depostion is restricted to distinctive cell wall subdomains in the root cortex and vascular tissues (Figure 2), a pattern that coincides with the known localization of cell wall pectins. Symbiotic root nodules result from specific interactions of Medicago roots with Sinorhizobium meliloti, and three additional PRP genes (MtPRP4, MtENOD11, and MtENOD12) are expressed early in nodule development. Antibodies were raised against the two distinct TR peptide motifs, both found in MtENOD12. Affinity-purified antibodies against both TRs recognize a single ENOD PRP shown to engulf rhizobial cells in the nodule invasion zone (Figure 3). To better assess the biochemical and cellular function of each of the five different PRP gene products, we generated hairy root lines engineered with constitutive or inducible hairpin-RNAi gene constructs, and are in the process of analyzing the biochemical, developmental, and symbiotic phenotypes of these "knock-down" mutants.

TR Proteins represent a large and diverse class of gene products known to form important bio-structural materials throughout the living world. To date, two distinct strategies have been utilized for investigating novel biomaterials: characterization of natural biomaterials, and directed evolution of small functional peptides (e.g., using phage display). To both complement these "traditional" approaches, my lab is pioneering a "genomics" strategy for biostructural protein discovery. New repeat-recognition software, called XSTREAM, uses seed-extension coupled with post-processing algorithms to efficiently identify fundamental TR motifs in large sequence datasets (approximately 10% of the ~12M available protein sequences have some TR content). Key features of XSTREAM allow merging of discontinuous TR domains, modeling of TR architecture, and detection of complex hierarchical TR patterns. To navigate MySQL databases populated with the output from XSTREAM at the multi-genome scale, an integrated graphical user interface, the TR Browser, was developed. The TR Browser features a suite of machine-learning tools, including both artificial neural networks and self-organizing maps, designed for the visualization and a priori clustering of TRs according to physico-chemical properties. These bioinformatics tools readily model the TR architectures of well-characterized structural proteins, and identify structurally distinct but related novel TRs from diverse genomes that presumably evolved properties "tuned" for diverse physical conditions and distinct biological functions. Current experimental work is focused on synthesis and characterization of two novel classes of TRPs discovered in the metagenome of marine picoplankton: naturally evolved AB di-block and ABA/ABC tri-block copolymer proteins predicted to self-assemble into protein nanostructures (Figure 4), and diverse TRPs predicted to bind specific metal ions. We hope to demonstrate that these novel approaches will provide a valuable discovery platform for uncovering 'green' biomaterials with novel properties stemming from the precise nanoscale engineering evolved on Earth over the past 3.5 B years.