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. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation.

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. In this study, we used two proteomics approaches, namely label-free shotgun proteomics based on SDS-PAGE gel separation and gas phase fractionation, to investigate the heavy metal stress responses of Sydney rock oysters. Protein samples were prepared from haemolymph of oysters exposed to 100 μg/L of PbCl(2), CuCl(2), or ZnCl(2) for 4 days in closed aquaria. Peptides were identified using a Bivalvia protein sequence database, due to the unavailability of a complete oyster genome sequence. Statistical analysis revealed 56 potential biomarker proteins, as well as several protein biosynthetic pathways to be greatly impacted by metal stress. These have the potential to be incorporated into bioassays for prevention and monitoring of heavy metal pollution in Australian oyster beds. The study confirms that proteomic analysis of biomonitoring species is a promising approach for assessing the effects of environmental pollution, and our experiments have provided insights into the molecular mechanisms underlying oyster stress responses.

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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. Data from these experiments can be used for spectral counting, where simultaneous quantitation of several thousand proteins can be obtained.

This review describes our recent work on environmental stress in Sydney rock oysters, focusing on the identification of molecular biomarkers for ecotoxicological analysis. We begin by describing the environmental pressures facing coastal estuaries in Australia, with particular reference to Sydney Harbour. After providing that context, we summarise our transcriptional and proteomic analyses of Sydney rock oysters responding to chemical contamination and other forms of environmental stress. This work has shown that the intracellular processes of oysters are highly responsive to environmental threats. Our data agree with the broader literature, which suggests that there is a highly conserved intracellular stress response in oysters involving a limited number of biological processes. We conclude that many effective molecular markers for environmental biomonitoring are likely to lie within these biological pathways.