W599 Proteomics Analysis Revealed Co-regulatory Network for Biomass Degradation in Cattle Rumen

Date: Tuesday, January 17, 2012
Time: 11:40 AM
Room: Pacific Salon 3
Shangxian Xie , Department of Plant Pathology and Microbiology, Texas A&M University, college station, TX
Weibing Shi , Department of Plant Pathology and Microbiology, Texas A&M University, college station, TX
Peng Gao , Department of Plant Pathology and Microbiology, Texas A&M University, college station, TX
Su Sun , Department of Plant Pathology and Microbiology, Texas A&M University, college station, TX
Junyan Tao , Department of Plant Pathology and Microbiology, Texas A&M University, college station, TX
Yixiang Zhang , Department of Plant Pathology and Microbiology, Texas A&M University, college station, TX
William E. Pinchak , Texas Agrilife Vernon Center, Vernon, TX
Susie Y. Dai , Department of Veterinary Pathobiology, Texas A&M University, college station, TX
Joshua S. Yuan , Department of Plant Pathology and Microbiology, Texas A&M University, college station, TX
We have recently carried out comprehensive proteomics analysis of cattle rumen microbiota to study the molecular mechanisms of biomass deconstruction and utilization. The study includes four treatments of high fiber to low fiber in the treatments in a 72 day feeding trial. Metagenome sequencing was first carried out to derive the gene models for proteomics data search. Enzyme assays revealed that the cellulytic enzyme activities are higher in the high fiber biomass treated time point. MudPIT-based shot-gun proteomics was carried out to characterize both the soluble and fiber portion of the rumen material. The proteome profiling highlighted that microbial diversity and enzyme profile change dramatically in response to the feeding content. Furthermore, cluster analysis and protein co-regulatory network modeling of protein abundance revealed that several groups of enzymes are coordinatively regulated in response to the high fiber biomass feeding. Each group of these coordinative enzymes includes multiple glycoside hydrolase (GH) families and functional category, indicating the synergistics toward biomass deconstruction. More importantly, the protein profiling correlates with the metagenome analysis in a way that some co-regulating enzymes were found in the same operon in metagneome sequences. The results highlighted both the regulation mechanisms and the reliability of proteomics data. Based on the network modeling, we have cloned and characterized multiple enzymes toward reverse design of a biorefinery process for efficient biomass utilization. Overall, the systems biology analysis revealed the potential mechanisms for efficient biomass degradation in cattle rumen, which can be used for both animal nutrition and biotechnology applications.