Proteome distribution between nucleoplasm and nucleolus and its relation to ribosome biogenesis in <i>Arabidopsis thaliana</i>

<p>Ribosome biogenesis is an essential process initiated in the nucleolus. In eukaryotes, multiple ribosome biogenesis factors (RBFs) can be found in the nucleolus, the nucleus and in the cytoplasm. They act in processing, folding and modification of the pre-ribosomal (r)RNAs, incorporation of ribosomal proteins (RPs), export of pre-ribosomal particles to the cytoplasm, and quality control mechanisms. Ribosome biogenesis is best established for <i>Saccharomyces cerevisiae</i>. Plant ortholog assignment to yeast RBFs revealed the absence of about 30% of the yeast RBFs in plants. In turn, few plant specific proteins have been identified by biochemical experiments to act in plant ribosome biogenesis. Nevertheless, a complete inventory of plant RBFs has not been established yet. We analyzed the proteome of the nucleus and nucleolus of <i>Arabidopsis thaliana</i> and the post-translational modifications of these proteins. We identified 1602 proteins in the nucleolar and 2544 proteins in the nuclear fraction with an overlap of 1429 proteins. For a randomly selected set of proteins identified by the proteomic approach we confirmed the localization inferred from the proteomics data by the localization of GFP fusion proteins. We assigned the identified proteins to various complexes and functions and found about 519 plant proteins that have a potential to act as a RBFs, but which have not been experimentally characterized yet. Last, we compared the distribution of RBFs and RPs in the various fractions with the distribution established for yeast.</p

Population density-dependent expression of <i>pilAB</i> of <i>Azoarcus</i> sp.

<p>(A) Population density-dependent induction of <i>pilAB</i> gene expression in <i>Azoarcus</i> sp. BH72 wild type background and BHΔ<i>pilS</i> mutant background. Cultures were grown in liquid aerobic culture (VM-Ethanol), and samples were taken at certain time points to measure β-glucuronidase activity (<i>pilAB</i>::<i>uidA</i>-fusion, left axis). The optical densities at these time points are shown in the inlay. The results are representative of three independent experiments. Error bars indicate standard deviations. Increase of the expression levels at exponential in comparison to stationary growth phase (last time point) was significant for wild type (BH72::pJBLP14, black triangles, <i>P</i><0.001), and highly significant for <i>pilS</i> mutant cells (BHD<i>pilS</i>::pJBLP14, black squares, <i>P</i><0.0001, unpaired t-test). (B) PilA protein abundance in <i>Azoarcus</i> sp. BH72 wild type and mutant background. Stationary phase cultures (OD 2.5) of <i>Azoarcus</i> wild type (wt) and Δ<i>pilS</i> mutant cells were compared. Western blot of whole-cell protein extracts with antiserum against PilA. Equal amounts of protein were loaded (8 µg).</p

Expression of a transcriptional <i>azo2876::gfp</i> fusion in pure culture or during interaction with rice roots.

<p>Phase contrast (A–C) and corresponding fluorescence micrographs (E–G), of strain <i>Azoarcus</i> sp. BH<i>azo2876</i> expressing a transcriptional <i>2876::gfp</i> fusion in pure culture, or in infected rice roots (fluorescence micrographs D, H). Cells grown in VM-ethanol medium at exponential (A, E) or stationary growth phase (C, G), or in conditioned supernatant for 4 h (B, F); all fluorescence images taken with the same setting of the video camera. (D, H) Roots of rice seedlings 13 d after inoculation; bacterial GFP fluorescence at emergence points of lateral roots (D, with close-up in right corner, and in epidermal root cell (H). Bars correspond to 7 µm (A–C, E–G), 10 µm (D) and 20 µM (H).</p

Expression of transcriptional gene fusions in conditioned supernatant.

<p>(A–F) Gene expression determined by ß-glucuronidase activities from respective transcriptional reporter gene fusions with <i>uidA</i>, in VM-ethanol medium. (A) Induction of <i>pilAB</i> gene expression in BHΔ<i>pilS</i>::pJBLP14 by supernatants of <i>Azoarcus</i> sp. BH72, <i>Azoarcus communis</i>, <i>Chromobacterium violaceum</i>, <i>Pseudomonas stutzeri</i> and <i>Azospirillum brasilense</i> obtained by supernatant bioassays after four hours of incubation. (B, C, D, E) Induction of <i>azo1544</i> (B), <i>azo1684</i> (C), <i>azo2876</i> (D) and <i>azo3874</i> (E) gene expression in the respective strains by supernatants of <i>Azoarcus</i> sp. BH72, <i>Azoarcus communis</i> and <i>Azospirillum brasilense</i> obtained by supernatant bioassays after four hours of incubation. (F) Fold changes of induction for all tested genes (<i>pilAB</i>, <i>azo1544</i>, <i>azo1684</i>, <i>azo2876</i> and <i>azo3874</i>) in comparison to each other. For all experiments, fresh medium was used instead of supernatant as negative control, and the values were set to one for calculation of fold changes. Standard deviation was calculated from at least three independent experiments. Stars indicate significance (at least <i>P<0.05</i>) as determined by unpaired t-test analyses.</p

A–E: Meso scale networks Ba/F3-p210 cells.

<p>(<b>A</b>) High degree of co-regulation across the protein set for IM, DASA and NILO, which can effectively represented by the mean component of factor analysis. (<b>B</b>) Significant deviations for a small set of proteins for DANU suggesting the use of the more stable factor analysis instead of PCA for reduction of dimension. (<b>C</b>) Analysis quantitatively the amount of induction of protein expression, which is associated with the activation of the dominant mechanisms, quantified by the mean component of factor analysis. Whereas a good and almost similar behaviour for IM, DASA and NILO is observed, DANU activates the proteins in two clearly separated modes (indicated by the upper and lower line of red stars). This finding is supported by quantitatively testing the distribution of the residuals of protein expressions with respect to the linear regression model given by the mean component of factor analysis. (<b>D</b>) Apparently only DANU induces residuals with significant non-gaussian noise indicating the existence of two separate mechanisms of protein induction. (<b>E</b>) Structure of meso scale pathways for induced protein expression. Black block represents induction of the protein expression by the main pathway, whereas the red block is indicating an inhibition via the main pathway.</p

A–D: Western blot analyses revealed posttranslational modification of eIF5A and up regulation of TGM2 after treatment with IM.

<p>(<b>A</b>) Enlarged regions from a coomassie stained 2D-PAGE from Ba/F3-p210 cells after treatment with IM or DMSO as a control. The arrows indicate two spots for eIF5A, one at pI of 5.2 and the other one at a pI of 6.1. The latter appeared after IM treatment. (<b>B</b>) 2D-WB validated the appearance of a second spot for eIF5A at a pI of 6.2 after IM treatment. (<b>C</b>) Enlarged regions from a coomassie stained 2D-PAGE from Ba/F3-p210 cells after treatment with IM or DMSO as a control. One spot for TGM2 (arrow) demonstrated an increased expression after IM treatment. (<b>D</b>) The increased expression of TGM2 after treatment with rising concentrations of IM could be validated in human Bcr-Abl K562 cells.</p

Schematic representation of meso network architecture and experimental design.

<p>(<b>A</b>) Exemplifies an abstract meso-scale network representing (abstract) pathways of drug action of drugs A and B on induction of proteins (red, yellow and orange bullets). Drug A uses two pathways (blue and black), whereas the blue pathway induces expression shifts only on a subset of the proteins (red, yellow), whereas the black pathway induces expression shifts in all proteins. Drug B acts only via one pathway which joins the black pathway of Drug A in an abstract node (represented by the green bullet). The mutation inhibits both pathways between the green and blue bullet resulting in an interference with drug induced expression shift for all proteins. The blue pathway from Drug A to the proteins, however, is not affected by the mutation. Hence the mutation may have a strong impact on the efficacy of drug B, whereas the profile of action of drug A is only altered by the mutation. (B) Imatinib sensitive and resistant cells were treated with four tyrosine kinase inhibitor and mesoscale network were reengineered based on specific proteome expression patterns.</p

A–C: Venn diagrams for representation of drug specific protein expression.

<p>Venn diagrams illustrated the drug specific effects in different cell lines: (<b>A</b>) Ba/F3-p210, (<b>B</b>) Ba/F3-M351T and (<b>C</b>) Ba/F3-T351I cells. The numbers inside the circles represent the number of regulated proteins.</p

A–D: Meso scale networks Ba/F3-M351T.

<p>(<b>A</b>) Shows the protein expressions for wt and T351 cell type for all drugs. (<b>B</b>) Shows the sensitivity of protein expression with respect to the dominant activation mechanism, quantified by the mean component of factor analysis. (<b>C</b>) Shows, that surprisingly the overall level of protein expression induced by NILO increases, although the sensitivity decreases. (<b>D</b>) Shows the modifications which are induced by the analysis of the M351I mutation to the meso scale pathway network depicted in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053668#pone-0053668-g005" target="_blank">Figure 5E</a>. Black block represents induction of the protein expression by the main pathway, whereas the red block is indicating an inhibition via the main pathway. Green block represents the unique effect of NILO on the overall protein expression level.</p

A–D: Meso scale network models for apoptosis induction.

<p>(<b>A</b>) Distribution of the Pearson coefficient between individual protein expression and the mean component of factor analysis which represents the dominant co-regulation mechanism. (<b>B</b>) Shows that the proteins can be decomposed into two groups differing with respect to the impact of DANU. Most proteins show no different co-regulation behaviour if DANU is omitted from the data set, whereas three proteins show a significantly higher degree of co-regulation (increased r value) when DANU is omitted indicating a second mode of action of DANU. (<b>C</b>) Shows that with exception of two treatments the mean protein expression, represented by the value of the mean component of the factor analysis (y-axis) is correlated to the observed induction of apoptosis (x-axis) indicating a similar efficacy in apoptosis induction for most drugs. The exceptions indicate that protein expression is induced which does not contribute to apoptosis induction. (<b>D</b>) Depicts the meso scale set of pathways, which fits two the observations.</p