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Circadian Profiling of the Arabidopsis Proteome Using 2D-DIGE.

Choudhary MK, Nomura Y, Shi H, Nakagami H, Somers DE - Front Plant Sci (2016)

Bottom Line: Clock-generated biological rhythms provide an adaptive advantage to an organism, resulting in increased fitness and survival.The phasing of maximum expression for the cyclic proteins was similar for both datasets, with a nearly even distribution of peak phases across the time series.Taken together, this study provides new insights into the importance of post-transcriptional circadian control of plant physiology and metabolism.

View Article: PubMed Central - PubMed

Affiliation: Division of Integrative Biosciences and Biotechnology, Pohang University of Science and Technology Pohang, South Korea.

ABSTRACT
Clock-generated biological rhythms provide an adaptive advantage to an organism, resulting in increased fitness and survival. To better elucidate the plant response to the circadian system, we surveyed protein oscillations in Arabidopsis seedlings under constant light. Using large-scale two-dimensional difference in gel electrophoresis (2D-DIGE) the abundance of more than 1000 proteins spots was reproducibly resolved quantified and profiled across a circadian time series. A comparison between phenol-extracted samples and RuBisCO-depleted extracts identified 71 and 40 rhythmically-expressed proteins, respectively, and between 30 and 40% of these derive from non-rhythmic transcripts. These included proteins influencing transcriptional regulation, translation, metabolism, photosynthesis, protein chaperones, and stress-mediated responses. The phasing of maximum expression for the cyclic proteins was similar for both datasets, with a nearly even distribution of peak phases across the time series. STRING clustering analysis identified two interaction networks with a notable number of oscillating proteins: plastid-based and cytosolic chaperones and 10 proteins involved in photosynthesis. The oscillation of the ABA receptor, PYR1/RCAR11, with peak expression near dusk adds to a growing body of evidence that intimately ties ABA signaling to the circadian system. Taken together, this study provides new insights into the importance of post-transcriptional circadian control of plant physiology and metabolism.

No MeSH data available.


Related in: MedlinePlus

Protein distribution by circadian phase and mRNA rhythmicity. Number of rhythmic proteins (Phenol extracted) are shown as the number above the two bars for each phase of peak occurrence (A) and relative to whether the respective mRNA is also rhythmic (B). Peak phasing of rhythmic proteins are further shown according to whether the respective mRNA is rhythmic (dark bar) or whether the respective mRNA is arrhythmic (gray bar). (C,D) Results for same categories obtained from RuBisCO-depleted protein extracts. Discrepancies between the total number of proteins and the sum of the two bars for each phase is due to mRNA data missing from DIURNAL.
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Figure 2: Protein distribution by circadian phase and mRNA rhythmicity. Number of rhythmic proteins (Phenol extracted) are shown as the number above the two bars for each phase of peak occurrence (A) and relative to whether the respective mRNA is also rhythmic (B). Peak phasing of rhythmic proteins are further shown according to whether the respective mRNA is rhythmic (dark bar) or whether the respective mRNA is arrhythmic (gray bar). (C,D) Results for same categories obtained from RuBisCO-depleted protein extracts. Discrepancies between the total number of proteins and the sum of the two bars for each phase is due to mRNA data missing from DIURNAL.

Mentions: The co-expression profile of the oscillating peptides was represented by a heat map (Figure S3) using the MEV software (The Institute of Genomic Research, TIGR; Saeed et al., 2003). The phase distributions of the cyclic proteins were similar for both datasets, with a similar number of peak phases across the time series (Figures 2A,C). These results differ from a recent circadian phosphoproteome analysis where peak phosphopeptide abundance occurred just after subjective dawn and subjective dusk (Choudhary et al., 2015). mRNA phasing patterns in Arabidopsis were more evenly distributed across day and night, though there was still a slight bias toward near dusk and near dawn (Harmer et al., 2000). Rhythmic proteins from both extraction methods mostly correlated with rhythmic transcripts (56 and 69%; phenol-extracted and RuBisCO-depleted, respectively; Figures 2B,D). Thus, between ca. 30 and 40% of rhythmic proteins derive from non-rhythmic transcripts, and these were not associated with a particular circadian phase (Figures 2B,D). These results are similar to an Arabidopsis phosphoproteomic study which reported that more than half of the cycling phosphopeptides came from genes with arrhythmic transcripts (Choudhary et al., 2015). Similar findings were reported from mouse liver studies, where 20–50% of the rhythmic proteins did not exhibit corresponding rhythmic transcripts (Reddy et al., 2006; Mauvoisin et al., 2014b; Robles et al., 2014). Taken together, these results emphasize the importance of circadian control over post-transcriptional and post-translational processes that lead to the net result of rhythmic patterns of protein abundance.


Circadian Profiling of the Arabidopsis Proteome Using 2D-DIGE.

Choudhary MK, Nomura Y, Shi H, Nakagami H, Somers DE - Front Plant Sci (2016)

Protein distribution by circadian phase and mRNA rhythmicity. Number of rhythmic proteins (Phenol extracted) are shown as the number above the two bars for each phase of peak occurrence (A) and relative to whether the respective mRNA is also rhythmic (B). Peak phasing of rhythmic proteins are further shown according to whether the respective mRNA is rhythmic (dark bar) or whether the respective mRNA is arrhythmic (gray bar). (C,D) Results for same categories obtained from RuBisCO-depleted protein extracts. Discrepancies between the total number of proteins and the sum of the two bars for each phase is due to mRNA data missing from DIURNAL.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4940426&req=5

Figure 2: Protein distribution by circadian phase and mRNA rhythmicity. Number of rhythmic proteins (Phenol extracted) are shown as the number above the two bars for each phase of peak occurrence (A) and relative to whether the respective mRNA is also rhythmic (B). Peak phasing of rhythmic proteins are further shown according to whether the respective mRNA is rhythmic (dark bar) or whether the respective mRNA is arrhythmic (gray bar). (C,D) Results for same categories obtained from RuBisCO-depleted protein extracts. Discrepancies between the total number of proteins and the sum of the two bars for each phase is due to mRNA data missing from DIURNAL.
Mentions: The co-expression profile of the oscillating peptides was represented by a heat map (Figure S3) using the MEV software (The Institute of Genomic Research, TIGR; Saeed et al., 2003). The phase distributions of the cyclic proteins were similar for both datasets, with a similar number of peak phases across the time series (Figures 2A,C). These results differ from a recent circadian phosphoproteome analysis where peak phosphopeptide abundance occurred just after subjective dawn and subjective dusk (Choudhary et al., 2015). mRNA phasing patterns in Arabidopsis were more evenly distributed across day and night, though there was still a slight bias toward near dusk and near dawn (Harmer et al., 2000). Rhythmic proteins from both extraction methods mostly correlated with rhythmic transcripts (56 and 69%; phenol-extracted and RuBisCO-depleted, respectively; Figures 2B,D). Thus, between ca. 30 and 40% of rhythmic proteins derive from non-rhythmic transcripts, and these were not associated with a particular circadian phase (Figures 2B,D). These results are similar to an Arabidopsis phosphoproteomic study which reported that more than half of the cycling phosphopeptides came from genes with arrhythmic transcripts (Choudhary et al., 2015). Similar findings were reported from mouse liver studies, where 20–50% of the rhythmic proteins did not exhibit corresponding rhythmic transcripts (Reddy et al., 2006; Mauvoisin et al., 2014b; Robles et al., 2014). Taken together, these results emphasize the importance of circadian control over post-transcriptional and post-translational processes that lead to the net result of rhythmic patterns of protein abundance.

Bottom Line: Clock-generated biological rhythms provide an adaptive advantage to an organism, resulting in increased fitness and survival.The phasing of maximum expression for the cyclic proteins was similar for both datasets, with a nearly even distribution of peak phases across the time series.Taken together, this study provides new insights into the importance of post-transcriptional circadian control of plant physiology and metabolism.

View Article: PubMed Central - PubMed

Affiliation: Division of Integrative Biosciences and Biotechnology, Pohang University of Science and Technology Pohang, South Korea.

ABSTRACT
Clock-generated biological rhythms provide an adaptive advantage to an organism, resulting in increased fitness and survival. To better elucidate the plant response to the circadian system, we surveyed protein oscillations in Arabidopsis seedlings under constant light. Using large-scale two-dimensional difference in gel electrophoresis (2D-DIGE) the abundance of more than 1000 proteins spots was reproducibly resolved quantified and profiled across a circadian time series. A comparison between phenol-extracted samples and RuBisCO-depleted extracts identified 71 and 40 rhythmically-expressed proteins, respectively, and between 30 and 40% of these derive from non-rhythmic transcripts. These included proteins influencing transcriptional regulation, translation, metabolism, photosynthesis, protein chaperones, and stress-mediated responses. The phasing of maximum expression for the cyclic proteins was similar for both datasets, with a nearly even distribution of peak phases across the time series. STRING clustering analysis identified two interaction networks with a notable number of oscillating proteins: plastid-based and cytosolic chaperones and 10 proteins involved in photosynthesis. The oscillation of the ABA receptor, PYR1/RCAR11, with peak expression near dusk adds to a growing body of evidence that intimately ties ABA signaling to the circadian system. Taken together, this study provides new insights into the importance of post-transcriptional circadian control of plant physiology and metabolism.

No MeSH data available.


Related in: MedlinePlus