Differentially Accumulated Proteins in Coffea arabica Seeds during Perisperm Tissue Development and Their Relationship to Coffee Grain Size

Coffee is one of the most important crops for developing countries. Coffee classification for trading is related to several factors, including grain size. Larger grains have higher market value then smaller ones. Coffee grain size is determined by the development of the perisperm, a transient tissue with a higly active metabolism, which is replaced by the endosperm during seed development. In this study, a proteomics approach was used to identify differentially accumulated proteins during perisperm development in two genotypes with regular (IPR59) and large grain sizes (IPR59-Graudo) in three developmental stages. Twenty-four spots were identified by MALDI-TOF/TOF-MS, corresponding to 15 proteins. We grouped them into categories as follows: storage (11S), methionine metabolism, cell division and elongation, metabolic processes (mainly redox), and energy. Our data enabled us to show that perisperm metabolism in IPR59 occurs at a higher rate than in IPR59-Graudo, which is supported by the accumulation of energy and detoxification-related proteins. We hypothesized that grain and fruit size divergences between the two coffee genotypes may be due to the comparatively earlier triggering of seed development processes in IPR59. We also demonstrated for the first time that the 11S protein is accumulated in the coffee perisperm

Renal Proteome in Mice with Different Susceptibilities to Fluorosis

<div><p>A/J and 129P3/J mouse strains have different susceptibilities to dental fluorosis due to their genetic backgrounds. They also differ with respect to several features of fluoride (F) metabolism and metabolic handling of water. This study was done to determine whether differences in F metabolism could be explained by diversities in the profile of protein expression in kidneys. Weanling, male A/J mice (susceptible to dental fluorosis, n = 18) and 129P3/J mice (resistant, n = 18) were housed in pairs and assigned to three groups given low-F food and drinking water containing 0, 10 or 50 ppm [F] for 7 weeks. Renal proteome profiles were examined using 2D-PAGE and LC-MS/MS. Quantitative intensity analysis detected between A/J and 129P3/J strains 122, 126 and 134 spots differentially expressed in the groups receiving 0, 10 and 50 ppmF, respectively. From these, 25, 30 and 32, respectively, were successfully identified. Most of the proteins were related to metabolic and cellular processes, followed by response to stimuli, development and regulation of cellular processes. In F-treated groups, PDZK-1, a protein involved in the regulation of renal tubular reabsorption capacity was down-modulated in the kidney of 129P3/J mice. A/J and 129P3/J mice exhibited 11 and 3 exclusive proteins, respectively, regardless of F exposure. In conclusion, proteomic analysis was able to identify proteins potentially involved in metabolic handling of F and water that are differentially expressed or even not expressed in the strains evaluated. This can contribute to understanding the molecular mechanisms underlying genetic susceptibility to dental fluorosis, by indicating key-proteins that should be better addressed in future studies.</p> </div

Label-Free Quantitative Proteomic Analysis of <i>Puccinia psidii</i> Uredospores Reveals Differences of Fungal Populations Infecting Eucalyptus and Guava

<div><p><i>Puccinia psidii</i> sensu lato (s.l.) is the causal agent of eucalyptus and guava rust, but it also attacks a wide range of plant species from the myrtle family, resulting in a significant genetic and physiological variability among populations accessed from different hosts. The uredospores are crucial to <i>P</i>. <i>psidii</i> dissemination in the field. Although they are important for the fungal pathogenesis, their molecular characterization has been poorly studied. In this work, we report the first in-depth proteomic analysis of <i>P</i>. <i>psidii</i> s.l. uredospores from two contrasting populations: guava fruits (PpGuava) and eucalyptus leaves (PpEucalyptus). NanoUPLC-MS^E was used to generate peptide spectra that were matched to the UniProt <i>Puccinia</i> genera sequences (UniProt database) resulting in the first proteomic analysis of the phytopathogenic fungus <i>P</i>. <i>psidii</i>. Three hundred and fourty proteins were detected and quantified using Label free proteomics. A significant number of unique proteins were found for each sample, others were significantly more or less abundant, according to the fungal populations. In PpGuava population, many proteins correlated with fungal virulence, such as malate dehydrogenase, proteossomes subunits, enolases and others were increased. On the other hand, PpEucalyptus proteins involved in biogenesis, protein folding and translocation were increased, supporting the physiological variability of the fungal populations according to their protein reservoirs and specific host interaction strategies.</p></div

Venn diagram showing distribution of total kidney proteins identified with differences in expression from the 2D-PAGE and LC-MS/MS-based proteome.

<p>The numbers indicate the total protein identified from each comparison (control, 10 and 50 ppmF A/J and 129P3/J) and the number of proteins commonly identified between them.</p

Expression of unique kidney proteins between A/J and 129P3/J mice.

a<p>Experimental molecular weight (kDa)/p<i>I</i> of protein spot in the gel (Mean of min. and max.) based on the coordinates of landmark proteins. <i>^b</i>Theoretical molecular weight (kDa)/p<i>I</i> of theoretical protein. <i>^c</i>Number of peptides identified and score. <i>^d</i>Identification is based on protein ID from IPI (international protein index) protein database (<a href="http://www.uniprot.org/" target="_blank">http://www.uniprot.org/</a>). <i>^e</i>Category of protein based on its primary biological function according to Rison (2000) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053261#pone.0053261-Rison1" target="_blank">[18]</a>.</p

Expression of differentially significant kidney proteins between control A/J <i>vs</i> control 129P3/J mice.

a<p>Experimental molecular weight (kDa)/p<i>I</i> of protein spot in the gel (Mean of min. and max.) based on the coordinates of landmark proteins. <i>^b</i>Theoretical molecular weight (kDa)/p<i>I</i> of theoretical protein. <i>^c</i>Number of peptides identified and score. <i>^d</i>Differences in expression in relation to 129P3/J mice (↓ down-modulation; ↑ up-modulation); Individual <i>P</i> value after ANOVA. <i>^e</i>Identification is based on protein ID from IPI (international protein index) protein database (<a href="http://www.uniprot.org/" target="_blank">http://www.uniprot.org/</a>). <i>^f</i>Category of protein based on its primary biological function according to Rison (2000) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053261#pone.0053261-Rison1" target="_blank">[18]</a>.</p

Expression of differentially significant kidney proteins between 10 ppmF A/J <i>vs</i> 10 ppmF 129P3/J mice.

a<p>Experimental molecular weight (kDa)/p<i>I</i> of protein spot in the gel (Mean of min. and max.) based on the coordinates of landmark proteins. <i>^b</i>Theoretical molecular weight (kDa)/p<i>I</i> of theoretical protein. <i>^c</i>Number of peptides identified and score. <i>^d</i>Differences in expression in relation to 129P3/J mice (↓ down-modulation; ↑ up-modulation); individual <i>P</i> value after ANOVA. <i>^e</i>Identification is based on protein ID from IPI (international protein index) protein database (<a href="http://www.uniprot.org/" target="_blank">http://www.uniprot.org/</a>). <i>^f</i>Category of protein based on its primary biological function according to Rison (2000) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053261#pone.0053261-Rison1" target="_blank">[18]</a>.</p

Proteins identified from <i>P</i>. <i>psidii</i> uredospore populations.

<p>The proteins exclusively found in PpGuava (right) and PpEucalyptus (left) and common to both populations (center). Of the common proteins, 25 and 120 whose abundance were increased in PpEucalyptus and PpGuava, respectively.</p

Gene ontology of biological process terms in the proteomic analysis.

<p>Bar graph represents the ratio of % composition of term in the proteomic data.</p

Morphological and viability analysis of <i>Puccinia psidii</i> uredospores.

<p><i>P</i>. <i>psidii</i> uredospores from <i>E</i>. <i>grandis</i><b>(A)</b> and <i>P</i>. <i>guajava</i><b>(B)</b> exhibit similar morphology and germination viability, respectively <b>(C and D)</b>.The arrows indicate the fungal germ tube in both uredospore populations, 24 hours after inoculation in water-agar medium. Light microscopy images of PpEucalyptus and PpGuava uredospores are shown at 100 X (A and B) and 200 X (C and D) magnification. Scale bar: 20 μm in A and B, 50 μm in C and D.</p