Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses

Abstract

BackgroundMultidimensional protein identification technology (MudPIT)-based shot-gun proteomics has been proven to be an effective platform for functional proteomics. In particular, the various sample preparation methods and bioinformatics tools can be integrated to improve the proteomics platform for applications like target organelle proteomics. We have recently integrated a rapid sample preparation method and bioinformatics classification system for comparative analysis of plant responses to two plant hormones, zeatin and brassinosteroid (BR). These hormones belong to two distinct classes of plant growth regulators, yet both can promote cell elongation and growth. An understanding of the differences and the cross-talk between the two types of hormone responses will allow us to better understand the molecular mechanisms and to identify new candidate genes for plant engineering.ResultsAs compared to traditional organelle proteomics, the organelle-enrichment method both simplifies the sample preparation and increases the number of proteins identified in the targeted organelle as well as the entire sample. Both zeatin and BR induce dramatic changes in signaling and metabolism. Their shared-regulated protein components indicate that both hormones may down-regulate some key components in auxin responses. However, they have shown distinct induction and suppression of metabolic pathways in mitochondria and chloroplast. For zeatin, the metabolic pathways in sucrose and starch biosynthesis and utilization were significantly changed, yet the lipid biosynthesis remained unchanged. For BR, lipid biosynthesis and β-oxidation were both down-regulated, yet the changes in sucrose and starch metabolism were minor.ConclusionsWe present a rapid sample preparation method and bioinformatics classification for effective proteomics analysis of plant hormone responses. The study highlighted the largely differing response to zeatin and brassinosteroid by the metabolic pathways in chloroplast and mitochondria.

Enhancement of Environmental Hazard Degradation in the Presence of Lignin: a Proteomics Study

“…The isolated total protein from the mycelium of I . lacteus CD2 was analyzed by MudPIT-based shot-gun proteomics system as described in previous publications 19 , 37 . In summary, the extracted protein was digested by Mass Spectometry Grade Trypsin (Promega.…”

Application of an Improved Proteomics Method for Abundant Protein Cleanup: Molecular and Genomic Mechanisms Study in Plant Defense

“…Approximately 100 g protein was digested by Mass Spectrometry Grade Trypsin Gold (Promega, Madison, WI) with 1:40 w/w at 37°C for 24 h. The digested peptides were desalted using a Sep-Pak C18 plus column (Waters Corporation, Milford, MA) and then loaded onto a biphasic (strong cation exchange/reversed phase) capillary column using a high pressure tank. The two-dimensional liquid chromatography separation and tandem mass spectrometry were carried out as previously described (24).…”

“…These strategies included target proteomics, fractionation, antibody-based protein removal, improved algorithm for protein identification, and others. Recently, we developed an organelle-enriched method to enhance the identification and differential expression analysis of mitochondrial proteins (24). The method involved both organelle enrichment for sample preparation and bioinformatics classification.…”

Plant hormone signalling through the eye of the mass spectrometer

“…More than 750 proteins with altered abundances upon auxin treatment were identified in wild‐type plants, whereas less than 150 auxin‐controlled proteins could be detected in the auxin receptor mutant tir1–1 . Another label‐free proteomics study investigated the crosstalk of brassinosteroids and cytokinin in Arabidopsis organelles . Here, samples of plants treated with the respective hormones were enriched for mitochondria and chloroplasts via centrifugation, and the organelle proteomes were evaluated via MudPIT‐based proteomics.…”