The green proteome: challenges in plant proteomics.

An organism is an expression of its underlying molecular composition that reacts and responds to a variety of stimuli. Central to this response are proteins, which undertake a multitude of functional and structural roles throughout an organism. The ability to readily identify and analyze protein populations (proteomics) represents a recent technological advance in the field of biological sciences. Although the term proteomics was coined in the mid 1990’s (Wilkins, 2009), the technique was significantly hampered by a lack of cohesive genomics data and advanced instrumentation. The field of proteomics has expanded rapidly in recent years due to the completion of genomes, access and improvements to mass spectrometers and the development of new techniques all of which have increased its role in biological research (Han et al., 2008). In general the area of plant proteomics suffers from the similar challenges that face other research fields. While the area was energized with the release of the model dicot genome sequence of Arabidopsis (Arabidopsis Genome Initiative, 2000) and several years later with the monocot genome of rice (Goff et al., 2002), the development of plant specific procedures for proteomic analyses have been necessary. These have essentially been associated with improvements in sample extraction procedures do deal with recalcitrant tissues and the effects of plant secondary metabolites on both extraction and analysis (Heazlewood and Millar, 2006). A number of successful strategies have been developed to overcome these issues including mass spectrometry compatible extraction procedures designed for plant tissues (Isaacson et al., 2006; Sheoran et al., 2009). In general, the plant proteomics community face many of the same limitations that the proteomics community as a whole faces and will benefit significantly with improvements in the field. A significant challenge in proteomics when studying plants or any complex biological system is an inability to measure the entire proteome (Ahn et al., 2007). While there have been major advances in instrumentation and sample delivery, the number of proteins that can be reproducibly identified from a single sample analysis is limited to hundreds. Since protein samples derived from whole tissue are likely to contain many thousands of proteins, there are considerable technological advances that will need to be achieved before complete proteomic profiling can occur in plants. Although limiting, a number of approaches have been used to partially overcome these restrictions. This includes sample fractionation and the enrichment of protein subpopulations or compartments prior to sample analysis by mass spectrometry (Eubel et al., 2008; Huang et al., 2009; Hynek et al., 2009; Ferro et al., 2010). When these studies are combined, such approaches begin to create a protein location map of the plant cell and have gone some way to provide overviews of the subcellular proteome (Heazlewood et al., 2007). Advances in instrumentation, sample delivery, and reproducible fractionation will all be essential for limitations in detection and dynamic range to be completely overcome. A fundamental challenge for proteomics is the ability to deliver large-scale protein quantification and to permit comparative proteomics studies (Schulze and Usadel, 2010). This would enable the examination of global protein changes during processes such as plant development or stress responses and provide a powerful biological application to the technology. Currently, limitations in comparative proteomics are constrained by both an inability to measure the entire protein complement and by technical limitations in quantitation procedures. Initial comparative studies were conducted using 2D-PAGE arrays to compare samples of interest and have now developed to incorporate fluorescent dyes for multiplexing and improved sensitivity (Marouga et al., 2005). Although the approach still suffers from the inherent limitations of 2D-PAGE (Taylor et al., 2011). Techniques involving quantitation by mass spectrometry have been widely embraced as sample analysis has moved away from gel arraying techniques. Early methods involved sample multiplexing with isobaric peptide labels (Zieske, 2006) but have been somewhat superseded by a plethora of label-free techniques (Schulze and Usadel, 2010). Unfortunately there is often an increased need for experimental design and replication to ensure statistical significance when it comes to data analysis and the technique still suffers from sample sensitivity in complex mixtures and dynamic range issues. The utilization of unlabeled targeted approaches (selected reaction monitoring, SRM) greatly improves sample sensitivity by mass spectrometry as well as reducing variation (Lange et al., 2008). While these advantages make the SRM analysis technique very powerful it is still limited by the number of peptides and subsequently proteins that can be monitored during sample analysis (Picotti et al., 2009). Finally, stable isotope labeling with amino acids (SILAC) has been widely employed in non-plant systems to enable reliable protein quantification (Mann, 2006). Since this technique relies on the exogenous addition of labeled amino acids the technique has been difficult to implement in autotrophic plants due to low incorporation rates (Gruhler et al., 2005). While comparative proteomics has been successfully and extensively employed to characterize plants, significant breakthroughs are still required for this technology to enable the complete quantification of an organism’s proteome. Generally plant proteomic studies have focused on the analysis of multiple organs and cell types. For most plant organs this has been a relatively uncomplicated task and has resulted in an extensive collection of studies analyzing and comparing samples derived from different plant organs (Sheoran et al., 2007; Baerenfaller et al., 2008; Castellana et al., 2008). Consequently, few studies if any have attempted in-depth characterizations of single cell lines. Such an intricate approach will be vital to more completely understand the nuanced role of proteins in plant processes from distinct cell types and even single cells. While genomic and transcriptomics approaches