Large-scale Arabidopsis phosphoproteome profiling reveals novel chloroplast kinase substrates and phosphorylation networks

Abstract

We have characterized the phosphoproteome of Arabidopsis (Arabidopsis thaliana) seedlings using high-accuracy mass spectrometry and report the identification of 1,429 phosphoproteins and 3,029 unique phosphopeptides. Among these, 174 proteins were chloroplast phosphoproteins. Motif-X (motif extractor) analysis of the phosphorylation sites in chloroplast proteins identified four significantly enriched kinase motifs, which include casein kinase II (CKII) and proline-directed kinase motifs, as well as two new motifs at the carboxyl terminus of ribosomal proteins. Using the phosphorylation motifs as a footprint for the activity of a specific kinase class, we connected the phosphoproteins with their putative kinases and constructed a chloroplast CKII phosphorylation network. The network topology suggests that CKII is a central regulator of different chloroplast functions. To provide insights into the dynamic regulation of protein phosphorylation, we analyzed the phosphoproteome at the end of day and end of night. The results revealed only minor changes in chloroplast kinase activities and phosphorylation site utilization. A notable exception was ATP synthase beta-subunit, which is found phosphorylated at CKII phosphorylation sites preferentially in the dark. We propose that ATP synthase is regulated in cooperation with 14-3-3 proteins by CKII-mediated phosphorylation of ATP synthase beta-subunit in the dark.

Figure 1.

Acquisition and characteristics of the phosphoprotein data set. A, Workflow for the acquisition of phosphopeptides from different Arabidopsis plant samples. ED, End of day; EN, end of night, IMAC, immobilized metal affinity chromatography. B, Overrepresented GO categories in the complete phosphoproteome data set compared with the Arabidopsis TAIR8 protein database as determined by the elim method implemented in the topGO algorithm (Alexa et al., 2006). Shown are overrepresented categories with P values below 10⁻⁵ from the GO category Cellular component. The pie graph shows relative amounts of Ser, Thr, and Tyr phosphorylation in phosphopeptides for which the exact site of phosphorylation was determined.

Figure 2.

Identification of phosphoproteins at the end of day and end of night. Reproducibility score for end-of-day (ED)/end-of-night (EN) phosphorylations. Each end-of-day phosphorylation event was scored as +1, and each end-of-night phosphorylation event was scored as −1. All individual scores for three biological replicates were added to result in the final score plotted on the y axis. Only ATPB received the highest possible end-of-night score of −3, since it was found phosphorylated exclusively at the end of night in all biological replicates.

Figure 3.

Quantification of ATPB phosphorylation at the end of day and end of night. A, Strategy for the quantification of the ATPB phosphopeptide and the ATPB protein. End-of-day (ED) and end-of-night (EN) samples are subjected to affinity chromatography on IMAC or TiO₂ as described in “Materials and Methods.” B, Phosphopeptides are eluted from the affinity column and identified by mass spectrometry. The relative quantification of phosphopeptides in the different samples is based on their extracted ion chromatograms (XIC), and the ATPB phosphopeptide is presented in comparison with two reference peptides (532.215 amu, AT1G68060-MAP70 and 724.837 amu, AT4G15930-dynein light chain). Quantification was also based on SuperHirn (Mueller et al., 2007), which supported the consistently higher abundance of the ATPB phosphopeptide in all end-of-night samples (Supplemental Table S4). C, The unphosphorylated peptides are collected in the flow-through fraction and used for the quantification of proteins by their unphosphorylated peptides via normalized spectral counting (nSpC) in three biological samples.

Figure 4.

Sequence alignment of phosphorylation sites and extraction of significantly enriched phosphorylation motifs. A, Amino acid sequence around the phosphorylated amino acid based on alignment of all phosphorylation sites established in the entire chloroplast data set. B, Motif-X-extracted motifs from the entire phosphopeptide data set. The TAIR8 protein database was used as the background database to normalize the score against a random distribution of amino acids. Note that only those phosphorylated amino acids that were confidently identified as the exact site of phosphorylation were used for the analysis (see “Materials and Methods” for a description). Motifs 1 and 2, Unknown phosphorylation motifs (n = 3 + 3); motif 3, Pro-directed kinase motif (n = 21); motif 4, CKII motif (n = 10).

Figure 5.

A phosphorylation network for chloroplast CKII. The network was assembled using NetPhosK motif analysis (Blom et al., 2004). The width of the arrows indicates the extent of additional evidence for CKII phosphorylation. Thick arrows are used in cases where phosphorylation has been biochemically characterized in vitro and inhibitor studies support CKII activity. Thin arrows indicate kinase/substrate relationships that are exclusively inferred from motif prediction. The motif score calculated by NetPhosK was assigned to the arrows. In all cases, the CKII motif received the highest score among all eukaryotic kinases that are considered by the NetPhosK algorithm (Blom et al., 2004).