An automated platform for analysis of phosphoproteomic datasets: application to kidney collecting duct phosphoproteins - PubMed (original) (raw)

An automated platform for analysis of phosphoproteomic datasets: application to kidney collecting duct phosphoproteins

Jason D Hoffert et al. J Proteome Res. 2007 Sep.

Abstract

Large-scale phosphoproteomic analysis employing liquid chromatography-tandem mass spectrometry (LC-MS/MS) often requires a significant amount of manual manipulation of phosphopeptide datasets in the post-acquisition phase. To assist in this process, we have created software, PhosphoPIC (PhosphoPeptide Identification and Compilation), which can perform a variety of useful functions including automated selection and compilation of phosphopeptide identifications from multiple MS levels, estimation of dataset false discovery rate, and application of appropriate cross-correlation (XCorr) filters. In addition, the output files generated by this program are compatible with downstream phosphorylation site assignment using the Ascore algorithm, as well as phosphopeptide quantification via QUOIL. In this report, we utilized this software to analyze phosphoproteins from short-term vasopressin-treated rat kidney inner medullary collecting duct (IMCD). A total of 925 phosphopeptides representing 173 unique proteins were identified from membrane-enriched fractions of IMCD with a false discovery rate of 1.5%. Of these proteins, 106 were found only in the membrane-enriched fraction of IMCD cells and not in whole IMCD cell lysates. These identifications included a number of well-studied ion and solute transporters including ClC-1, LAT4, MCT2, NBC3, and NHE1, all of which contained novel phosphorylation sites. Using a label-free quantification approach, we identified phosphoproteins that changed in abundance with vasopressin exposure including aquaporin-2 (AQP2), Hnrpa3, IP3 receptor 3, and pur-beta.

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Figures

Figure 1

Figure 1

Experimental approach. (A) IMCD cells were enriched from rat kidney inner medullas by enzymatic digestion followed by low-speed centrifugation. Cells were lysed by sonication in sucrose buffer. Differential centrifugation produced a 200 000 g pellet which was digested with trypsin, followed by IMAC to enrich for phosphopeptides. Phosphopeptides were then analyzed by LC–MS/MS. (B) Postacquisition analysis. The 3 modules that comprise PhosphoPIC are indicated in red font. FDR = false discovery rate; XCorr = cross-correlation filter. (C) Detailed workflow for the “Phosphopeptide Selection/Filtering” module of PhosphoPIC. (D) Detailed workflow for the “MSn Compilation” module of PhosphoPIC.

Figure 2

Figure 2

Estimation of false discovery rates. Both MS (A, B) and MS (C, D) phosphopeptide datasets were filtered using target false discovery rates (FDR) from 1 to 10%. The number of peptides identified from the forward database (blue) as well as from the reversed database (green) increases as the FDR increases owing to the application of less stringent XCorr filters. A target FDR of 2% (*), which corresponded to an actual FDR of 1.32% for MS and 1.61% for MS, was used for subsequent phosphopeptide identification and site assignment. Adjusted FDR is calculated after removal of hits from the reversed database.

Figure 3

Figure 3

Functional classification of identified IMCD phosphoproteins. Heat maps were constructed from the three major Gene Ontology (GO) categories: cellular component (cyan), biological process (yellow), and molecular function (magenta). The percentage of phosphoproteins associated with each individual GO term has been log2 transformed and then converted into a 16-bit grayscale intensity value (min = 0, max = 255). A direct comparison of whole cell lysate (total) with the membrane-enriched fraction (200k) indicates an increased number of phosphoproteins in the 200k fraction that have GO terms associated with membrane localization/membrane transport functions.

Figure 4

Figure 4

Label-free quantification using QUOIL software. Phosphopeptides from IMCD samples incubated in the absence or presence of 10 nM dDAVP for 10 min were selected using PhosphoPIC software and then quantified using a label-free approach based on normalized peak area ratios obtained from reconstructed ion chromatograms. Shown are the extracted ion chromatograms for a triply phosphorylated AQP2 peptide (RQpS-VELHpSPQpSLPR). The dashed red lines indicate the beginning and the end of the peaks that were quantified. The relative abundance of this AQP2 phosphopeptide was increased an average of 20.7-fold in samples that were incubated with dDAVP (n = 3).

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