# Getting Ready for Large-Scale Proteomics in Crop Plants
## 4 Discussion  
The workflow presented in this study was designed to support a large number of samples from which we intend to build a crop proteome atlas covering the 100 most important crop plants for human nutrition. None of the elements in the workflow are new as such. However, the way they were put together is novel and has a few interesting features. For instance, the workflow contains three steps in which small molecule components are extracted by organic solvent. First during TCA/acetone precipitation, second during phenol extraction and third during ethanol precipitation onto SP3 beads. This generates protein preparations that are essentially free of non-proteinous material, which greatly contributes to the robustness of the workflow. This comes at the price of losing about 50% of the total protein content of a sample. Considering that most crop plant samples are abundantly available and the fact that the workflow only requires a total amount of 200 ug of protein, the loss of material is a lesser concern. In addition, most steps are performed in 96-well format, enabling a high degree of parallelization and automation. This not only increases sample throughput but, more importantly, improves reproducibility. The end-to-end technical variation of the workflow is very low as quantitative precision is better than 10% CV for half of all proteins and better than 20% for 90% of all proteins. These figures of merit were partly achieved by operating the chromatography part of the LC-MS/MS system at microliter flow rates rather than the more typical nanoliter flow rates. This renders the chromatography more robust and reduces overhead times [25; 26; 39]. The bottleneck of the workflow is the time needed for LC-MS/MS analysis (6 h per proteome). Still, in the current configuration, up to 28 crop proteome samples may be collected within one week, albeit 24 is more realistic considering that instrumentation also requires maintenance. Nearly 10,000 proteins were identified from tomato fruit in this study, rendering it the largest tomato proteome published to date. These proteins span nearly six orders of magnitude of dynamic range. In other words, it is possible to detect proteins that are present with only 10 copies per cell in the presence of other proteins with >10 million copies per cell. In this regard, the workflow should cover the proteome of the fruit rather comprehensively. Still, the tomato fruit data only cover 30% of the total proteome as estimated from the prediction of coding regions from the tomato genome. This is substantially lower than what our laboratory achieved when mapping the proteomes of Arabidopsis (66% coverage), mouse (76% coverage) and human (68% coverage) [23; 40; 41]. However, these studies analyzed many tissues, each of which also only covered about 10,000 proteins. Hence, it is reasonable to expect that a more substantial increase in the coverage of the tomato proteome will come from analyzing other tissues where other proteins are more abundant. Figure 6: Assessment of workflow bias. (**a**) Distribution of the molecular weights of all proteins in ITAG 4.0 vs. proteins identified in this study; (**b**) same as panel (**a**) but for peptide hydrophobicity (expressed as GRAVY index). (**c**) Fraction of proteins with or without predicted transmembrane domains (TMF) in ITAG 4.0 or identified in this study. (**d**) Percentage of proteins with different numbers of predicted transmembrane domains in ITAG 4.0 or identified in this study. In addition, the strong bias we observed against the detection of low-molecular-weight proteins raises the question if ITAG 4.0 contains rather too many small proteins, as these are notoriously difficult to call correctly by all major gene prediction programs [42]. This study did not include the analysis of post-translational modifications, as this is not the current focus of the crop proteome atlas project. However, the presented workflow can be easily adapted to include the enrichment of phosphorylated peptides.