Abstract
BackgroundCitrus is one of the most important and widely grown commodity fruit crops. In this study a label-free LC-MS/MS based shot-gun proteomics approach was taken to explore three main stages of citrus fruit development. These approaches were used to identify and evaluate changes occurring in juice sac cells in various metabolic pathways affecting citrus fruit development and quality.ResultsProtein changes in citrus juice sac cells were identified and quantified using label-free shotgun methodologies. Two alternative methods, differential mass-spectrometry (dMS) and spectral counting (SC) were used to analyze protein changes occurring during earlier and late stages of fruit development. Both methods were compared in order to develop a proteomics workflow that could be used in a non-model plant lacking a sequenced genome. In order to resolve the bioinformatics limitations of EST databases from species that lack a full sequenced genome, we established iCitrus. iCitrus is a comprehensive sequence database created by merging three major sources of sequences (HarvEST:citrus, NCBI/citrus/unigenes, NCBI/citrus/proteins) and improving the annotation of existing unigenes. iCitrus provided a useful bioinformatics tool for the high-throughput identification of citrus proteins. We have identified approximately 1500 citrus proteins expressed in fruit juice sac cells and quantified the changes of their expression during fruit development. Our results showed that both dMS and SC provided significant information on protein changes, with dMS providing a higher accuracy.ConclusionOur data supports the notion of the complementary use of dMS and SC for label-free comparative proteomics, broadening the identification spectrum and strengthening the identification of trends in protein expression changes during the particular processes being compared.
Highlights
Citrus is one of the most important and widely grown commodity fruit crops
Label-free proteomics allows for the quantification of peptides using spectral characteristics such as retention time, m/z ratio and peak intensity by comparing the direct mass spectrometric signal intensity for any given peptide or by counting the number of acquired tandem mass spectra matching to a specific peptide as an indicator for their abundance in a given sample [25,26]. differential mass-spectrometry (dMS) is based on comparisons of chromatographic peaks of peptide precursor ion measurements belonging to a specific protein extracted from an LCMS/MS run [27,28,29,30,31,32]
With the advantage of comprehensive sequence dataset in hand, there were many challenges to be addressed before using the databases for proteomic research
Summary
In this study a labelfree LC-MS/MS based shot-gun proteomics approach was taken to explore three main stages of citrus fruit development. DMS is based on comparisons of chromatographic peaks of peptide precursor ion measurements belonging to a specific protein extracted from an LCMS/MS run [27,28,29,30,31,32]. Peak intensity for every individual spectrum is determined and the comparison of spectra between multiple LC-MS runs provides quantitative measurement of thousands of peptides From this massive data a selected list of differential peptides can be produced for subsequent fragmentation by LC-MS/MS for sequence determination and protein identification. SC counting is based on counting and comparing the number of spectra identifying specific peptides of a given protein to assess relative protein abundance, found to be in good correlation with protein abundance [15,30]
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