Quantitative proteomics analysis of high and low polyphenol expressing recombinant inbred lines (RILs) of peanut (Arachis hypogaea L.).

To facilitate selective breeding of polyphenol-rich peanuts, we looked for mass spectrometry-based proteomic evidence, investigating a subset of recombinant inbred lines (RILs) developed by the Australian peanut breeding program. To do this, we used label-free shotgun proteomics for protein and peptide quantitation, statistically analyzed normalized spectral abundance factors using R-package, as well as assayed important antioxidants. Results revealed statistically significant protein expression changes in 82 proteins classified between high or low polyphenols expressing RILs.

A label-free shotgun proteomics analysis of macadamia nut.

In this study, we present a systematic proteomic overview of macadamia nut using a label-free shotgun proteomic approach. We identified 947 proteins in 723 clusters and gene ontology analysis revealed proteins across 46 functional categories including carbohydrate metabolism (10%), protein metabolic processes (5%), amino acid metabolism (4%), transport (4%), stress response (3%), lipid metabolism (3%), protein folding (3%) and defense response (1.4%).

Analysis of rice proteins using SDS-PAGE shotgun proteomics.

In this chapter we describe the workflow used in our laboratory to analyze rice leaf samples using label-free shotgun proteomics based on SDS-PAGE fractionation of proteins. Rice proteomics has benefitted substantially from successful execution of shotgun proteomics techniques. We describe steps on how to proceed starting from rice protein extraction, SDS-PAGE, in-gel protein digestion with trypsin, nanoLC-MS/MS, and database searching using the GPM.

Quantitative proteomics of heavy metal stress responses in Sydney rock oysters.

Currently, there are few predictive biomarkers in key biomonitoring species, such as oysters, that can detect heavy metal pollution in coastal waterways. Several attributes make oysters superior to other organisms for positive biomonitoring of heavy metal pollution. In particular, they are filter feeders with a high capacity for bioaccumulation.

Less label, more free: approaches in label-free quantitative mass spectrometry.

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation.