Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization

Chou, Kuo‐Chen; Shen, Hong-Bin

doi:10.1371/journal.pone.0011335

Cited by 853 publications

(561 citation statements)

References 69 publications

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“…Literature sources were again used to localize the individual reactions in draft network to appropriate subcellular compartments. If the subcellular localizations of certain reactions are not available in published articles, then the Plant-mPLoc (Chou and Shen, 2010) localization prediction software was used to predict putative cellular compartment. After each reaction in the draft network was assigned to a certain subcellular compartment, the intracellular metabolite transport reactions were then added based on the evidence found in the literature and TransportDB database (Ren et al, 2004).…”

Section: Metabolic Network Reconstructionmentioning

confidence: 99%

Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis

et al. 2015

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Light quality is an important signaling component upon which plants orchestrate various morphological processes, including seed germination and seedling photomorphogenesis. However, it is still unclear how plants, especially food crops, sense various light qualities and modulate their cellular growth and other developmental processes. Therefore, in this work, we initially profiled the transcripts of a model crop, rice (Oryza sativa), under four different light treatments (blue, green, red, and white) as well as in the dark. Concurrently, we reconstructed a fully compartmentalized genome-scale metabolic model of rice cells, iOS2164, containing 2,164 unique genes, 2,283 reactions, and 1,999 metabolites. We then combined the model with transcriptome profiles to elucidate the light-specific transcriptional signatures of rice metabolism. Clearly, light signals mediated rice gene expressions, differentially regulating numerous metabolic pathways: photosynthesis and secondary metabolism were upregulated in blue light, whereas reserve carbohydrates degradation was pronounced in the dark. The topological analysis of gene expression data with the rice genome-scale metabolic model further uncovered that phytohormones, such as abscisate, ethylene, gibberellin, and jasmonate, are the key biomarkers of light-mediated regulation, and subsequent analysis of the associated genes' promoter regions identified several light-specific transcription factors. Finally, the transcriptional control of rice metabolism by red and blue light signals was assessed by integrating the transcriptome and metabolome data with constraint-based modeling. The biological insights gained from this integrative systems biology approach offer several potential applications, such as improving the agronomic traits of food crops and designing light-specific synthetic gene circuits in microbial and mammalian systems.Light is the primary energy source as well as a key signaling element for plant growth and development. Although both light quantity (fluence) and quality (wavelength) are important for plant life, the latter is a crucial environmental indicator for plants to modulate their growth and morphological processes, such as seed germination, stem elongation, phototropism, circadian rhythms, and flowering induction (Neff et al., 2000). Since the discovery of red light (R)-stimulated seed germination in lettuce (Lactuca sativa;Borthwick et al., 1952), several studies have been focused on investigating the effect of individual light quality on plant growth and development. Earlier works used the classical genetic and molecular approaches, such as the use of light signaling-deficient mutants, measurement of enzyme activities, and enzyme/metabolite levels of certain pathway(s). However, it is required to comprehensively interrogate plant metabolism, because the transitions of light quality are likely to affect the plant physiology by modulating several metabolic effectors

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Section: Metabolic Network Reconstructionmentioning

confidence: 99%

Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis

et al. 2015

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“…edu.cn/bioinf/plant-multi/; Chou and Shen, 2010), OsPP18 was predicted to be located in chloroplast, cytoplasm, and nucleus. To examine the location of OsPP18 in vivo, yellow fluorescent protein (YFP)-tagged OsPP18 and cyan fluorescent protein (CFP)-tagged GHD7 (a welldefined nuclear protein in rice; Xue et al, 2008) or YFPtagged OsPP18 and CFP were cotransformed into rice protoplasts.…”

Section: The Expression Profile and Subcellular Localization Of Ospp18mentioning

confidence: 99%

A STRESS-RESPONSIVE NAC1-Regulated Protein Phosphatase Gene RiceProtein Phosphatase18Modulates Drought and Oxidative Stress Tolerance through Abscisic Acid-Independent Reactive Oxygen Species Scavenging in Rice

et al. 2014

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Plants respond to abiotic stresses through a complexity of signaling pathways, and the dephosphorylation mediated by protein phosphatase (PP) is an important event in this process. We identified a rice (Oryza sativa) PP2C gene, OsPP18, as a STRESS-RESPONSIVE NAC1 (SNAC1)-regulated downstream gene. The ospp18 mutant was more sensitive than wild-type plants to drought stress at both the seedling and panicle development stages. Rice plants with OsPP18 suppressed through artificial microRNA were also hypersensitive to drought stress. Microarray analysis of the mutant revealed that genes encoding reactive oxygen species (ROS) scavenging enzymes were down-regulated in the ospp18 mutant, and the mutant exhibited reduced activities of ROS scavenging enzymes and increased sensitivity to oxidative stresses. Overexpression of OsPP18 in rice led to enhanced osmotic and oxidative stress tolerance. The expression of OsPP18 was induced by drought stress but not induced by abscisic acid (ABA). Although OsPP18 is a typical PP2C with enzymatic activity, it did not interact with SNF1-RELATED PROTEIN KINASE2 protein kinases, which function in ABA signaling. Meanwhile, the expression of ABA-responsive genes was not affected in the ospp18 mutant, and the ABA sensitivities of the ospp18 mutant and OsPP18-overexpressing plants were also not altered. Together, these findings suggest that OsPP18 is a unique PP2C gene that is regulated by SNAC1 and confers drought and oxidative stress tolerance by regulating ROS homeostasis through ABA-independent pathways.

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“…Besides the improvements mentioned above, the developments from Plant-PLoc [43] in the Cell-PLoc package [50] to Plant-mPLoc [59], from Gpos-PLoc [60] to Gpos-mPLoc [57], and from Gneg-PLoc [61] to Gneg-mPLoc [58], have made it possible to deal with the multiple-location problem for plant proteins, Grampositive bacterial proteins, and Gram-negative bacterial proteins, respectively, as well.…”

Section: Cell-plocmentioning

confidence: 99%

REVIEW : Recent advances in developing web-servers for predicting protein attributes

Chou¹,

Shen²

2009

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Recent advance in large-scale genome sequencing has generated a huge volume of protein sequences. In order to timely utilize the information hidden in these newly discovered sequences, it is highly desired to develop computational methods for efficiently identifying their various attributes because the information thus obtained will be very useful for both basic research and drug development. Particularly, it would be even more useful and welcome if a user-friendly web-server could be provided for each of these methods. In this minireview, a systematic introduction is presented to highlight the development of these web-servers by our group during the last three years.

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Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization

Cited by 853 publications

References 69 publications

Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis

Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis

A STRESS-RESPONSIVE NAC1-Regulated Protein Phosphatase Gene RiceProtein Phosphatase18Modulates Drought and Oxidative Stress Tolerance through Abscisic Acid-Independent Reactive Oxygen Species Scavenging in Rice

REVIEW : Recent advances in developing web-servers for predicting protein attributes

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