SUBAcon: a consensus algorithm for unifying the subcellular localization data of the <i>Arabidopsis</i> proteome

Hooper, Cornelia M.; Tanz, Sandra K.; Castleden, Ian; Vacher, Michaël; Small, Ian; Millar, A. Harvey

doi:10.1093/bioinformatics/btu550

Cited by 160 publications

(165 citation statements)

References 58 publications

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“…Notably, of the 92 differentially expressed transcripts encoding PPR proteins in tric1tric2 seedlings, 51 are predicted to be mitochondrial and 19 are predicted to be plastidial. Similarly, of the 54 differentially expressed transcripts encoding PPR proteins in the rosettes, 34 are predicted to be mitochondrial while 15 are predicted to be plastidial, using the consensus algorithm for protein localization SUBAcon (Hooper et al, 2014). Of the mitochondriaencoded genes, 49 genes were observed to have significantly higher (P , 0.05) transcript abundance in tric1tric2 plants compared with Col-0 ( Fig.…”

Section: Transcriptome Changes In Tric1tric2 Plants Reveal Direct Andmentioning

confidence: 99%

Plant-Specific Preprotein and Amino Acid Transporter Proteins Are Required for tRNA Import into Mitochondria

et al. 2016

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Section: Transcriptome Changes In Tric1tric2 Plants Reveal Direct Andmentioning

confidence: 99%

Plant-Specific Preprotein and Amino Acid Transporter Proteins Are Required for tRNA Import into Mitochondria

et al. 2016

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“…The 20 fastest degrading proteins comprised a set of eight plastid proteins, six cytosolic proteins, and six proteins localized elsewhere in the cell (Table 1). To look for evidence of differences in the rate of autophagy of cellular structures or the role of intraorganellar proteases in changing the degradation rate inside specific organelles, we arranged the data set into the final subcellular location of proteins using the location Bayesian classifier, SUBAcon (Tanz et al, 2013;Hooper et al, 2014). This showed a lower median degradation rate of mitochondrial, plastidial, and nuclear proteomes and a higher median degradation rate for the proteomes of endoplasmic reticulum (ER) and the Golgi apparatus.…”

Section: Protein Degradation Rate Of Specific Proteins In Arabidopsismentioning

confidence: 99%

Protein Degradation Rate in Arabidopsis thaliana Leaf Growth and Development

et al. 2017

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We applied 15 N labeling approaches to leaves of the Arabidopsis thaliana rosette to characterize their protein degradation rate and understand its determinants. The progressive labeling of new peptides with 15 N and measuring the decrease in the abundance of >60,000 existing peptides over time allowed us to define the degradation rate of 1228 proteins in vivo. We show that Arabidopsis protein half-lives vary from several hours to several months based on the exponential constant of the decay rate for each protein. This rate was calculated from the relative isotope abundance of each peptide and the fold change in protein abundance during growth. Protein complex membership and specific protein domains were found to be strong predictors of degradation rate, while N-end amino acid, hydrophobicity, or aggregation propensity of proteins were not. We discovered rapidly degrading subunits in a variety of protein complexes in plastids and identified the set of plant proteins whose degradation rate changed in different leaves of the rosette and correlated with leaf growth rate. From this information, we have calculated the protein turnover energy costs in different leaves and their key determinants within the proteome.

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“…A process termed instantiation (Latendresse et al, 2012) was employed, using an implementation of the relevant algorithm in YASMEnv, to ensure that only mass-balanced reactions were included in the model. Each reaction was associated with a subcellular compartment based on the records in the Arabidopsis Core Model, AraCyc, and MetaCyc, and these associations were confirmed by searches against the TargetP and SUBAcon databases (Emanuelsson et al, 2000;Hooper et al, 2014). Sequences of transcripts represented in recently acquired transcriptome data sets for peppermint GTs (Ahkami et al, 2015) were compared, based on global identity (Myers and Miller, 1988;Tian and Skolnick, 2003), with those associated with reactions in the Arabidopsis Core Model, AraCyc, and MetaCyc.…”

Section: Reconstruction Of Metabolism In Peppermint Gtsmentioning

confidence: 99%

Bioenergetics of Monoterpenoid Essential Oil Biosynthesis in Nonphotosynthetic Glandular Trichomes

et al. 2017

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ORCID IDs: 0000-0001-8261-9015 (S.R.J.); 0000-0001-7934-7987 (N.S.); 0000-0001-6565-9584 (B.M.L.).The commercially important essential oils of peppermint (Mentha 3 piperita) and its relatives in the mint family (Lamiaceae) are accumulated in specialized anatomical structures called glandular trichomes (GTs). A genome-scale stoichiometric model of secretory phase metabolism in peppermint GTs was constructed based on current biochemical and physiological knowledge. Fluxes through the network were predicted based on metabolomic and transcriptomic data. Using simulated reaction deletions, this model predicted that two processes, the regeneration of ATP and ferredoxin (in its reduced form), exert substantial control over flux toward monoterpenes. Follow-up biochemical assays with isolated GTs indicated that oxidative phosphorylation and ethanolic fermentation were active and that cooperation to provide ATP depended on the concentration of the carbon source. We also report that GTs with high flux toward monoterpenes express, at very high levels, genes coding for a unique pair of ferredoxin and ferredoxin-NADP + reductase isoforms. This study provides, to our knowledge, the first evidence of how bioenergetic processes determine flux through monoterpene biosynthesis in GTs.

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SUBAcon: a consensus algorithm for unifying the subcellular localization data of the Arabidopsis proteome

Cited by 160 publications

References 58 publications

Plant-Specific Preprotein and Amino Acid Transporter Proteins Are Required for tRNA Import into Mitochondria

Plant-Specific Preprotein and Amino Acid Transporter Proteins Are Required for tRNA Import into Mitochondria

Protein Degradation Rate in Arabidopsis thaliana Leaf Growth and Development

Bioenergetics of Monoterpenoid Essential Oil Biosynthesis in Nonphotosynthetic Glandular Trichomes

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