Protein pathway and complex clustering of correlated mRNA and protein expression analyses in
            <i>Saccharomyces</i>
            <i>cerevisiae</i>

Washburn, Michael P.; Koller, Antonius; Oshiro, Guy; Ulaszek, Ryan; Plouffe, David; Deciu, Cosmin; Winzeler, Elizabeth A.; Yates, John R.

doi:10.1073/pnas.0634629100

Cited by 333 publications

(247 citation statements)

References 44 publications

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“…However, it was recently shown that protein expression is transcriptionally controlled for some entire protein pathways such as purine and pyrimidine nucleotide biosynthetic pathways and pathways for amino acids such as methionine (49). This corresponds with our findings for the purine and pyrimidine metabolism where the four proteins found to have changed expression in this part of the metabolism also were identified as changed on the transcriptional level.…”

Section: Discussionsupporting

confidence: 91%

Transcriptional, Proteomic, and Metabolic Responses to Lithium in Galactose-grown Yeast Cells

Bro

Regenberg

Lagniel³

et al. 2003

Journal of Biological Chemistry

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Lithium is highly toxic to yeast when grown in galactose medium mainly because phosphoglucomutase, a key enzyme of galactose metabolism, is inhibited. We studied the global protein and gene expression profiles of Saccharomyces cerevisiae grown in galactose in different time intervals after addition of lithium. These results were related to physiological studies where both secreted and intracellular metabolites were determined. Microarray analysis showed that 664 open reading frames were down-regulated and 725 up-regulated in response to addition of lithium. Genes involved in transcription, translation, and nucleotide metabolism were down-regulated at the transcriptional level, whereas genes responsive to different stresses as well as genes from energy reserve metabolism and monosaccharide metabolism were up-regulated. Compared with the proteomic data, 26% of the down-regulated and 48% of the up-regulated proteins were also identified as being changed on the mRNA level. Functional clusters obtained from proteome data were coincident with transcriptional clusters. Physiological studies showed that acetate, glycerol, and glycogen accumulate in response to lithium, as reflected in expression data, whereas a change from respiro-fermentative to respiratory growth could not be predicted from the expression analyses.

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Section: Discussionsupporting

confidence: 91%

Transcriptional, Proteomic, and Metabolic Responses to Lithium in Galactose-grown Yeast Cells

Bro

Regenberg

Lagniel³

et al. 2003

Journal of Biological Chemistry

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“…Among the 74 proteins enriched in GC described in the previous section, 15 are represented on the microarray, and nine transcripts were identified as enriched in GC (supplemental Table 2). These results confirm the general observation that mRNA levels are not always consistent with protein levels because of post-transcriptional, translational, or post-translational regulations (32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44). They also highlight the importance of proteomics analysis.…”

Section: Comparative Analysis Of Transcriptome Data and Proteome Data-supporting

confidence: 76%

Functional Differentiation of Brassica napus Guard Cells and Mesophyll Cells Revealed by Comparative Proteomics

Zhu

Dai

McClung

et al. 2009

Molecular & Cellular Proteomics

111

115

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Guard cells (GC)1 are highly specialized cells that form tiny pores called stomata on the leaf surface. When environmental conditions change, guard cells can rapidly change shape so that the pores open or close to control leaf gas exchange and water transpiration. Mesophyll cells (MC) are mainly parenchyma cells between the upper and lower epidermis specialized for photosynthesis. Previous studies that focused on guard cell metabolism and response to environmental signals have revealed important features of functional differentiation of GC (1, 2). Compared with MC, GC contain few chloroplasts with very limited structures and thus possess very low photosynthetic capability. The Calvin cycle in GC only assimilates 2-4% of CO 2 fixed in MC (3). In contrast, GC contain abundant mitochondria and display a high respiratory rate, suggesting that oxidative phosphorylation is an important source of ATP to fuel the guard cell machinery (4). Using microarrays covering just one-third of the Arabidopsis genome, Leonhardt et al. (5) observed a differential abscisic acid (ABA) modulation of many guard cell ABA signaling components as well as key enzymes involved in carbon metabolism in GC and MC. This only available large scale genomics study identified 1309 guard cell expressed genes of which 64 transcripts mainly involved in transcription, signaling, and cytoskeleton were preferentially expressed in GC compared with MC. However, functional grouping of the genes revealed only a 1.9% higher representation of photosynthesis genes in MC than in GC. The percentages of genes in all other categories such as protein turnover, defense, signaling, channels and transporters, and metabolism are similar between the two distinct cell types (5). These proteins are known to play specific roles in guard cell functions (6). This highlights the necessity of studying guard cell functions at the protein level.To date, there have been very few analyses of single celltype proteomes in plants. Proteome analyses of trichomes from Arabidopsis (7) and tobacco (8) and root hairs from soybean (9) exist but have identified fewer than 100 proteins per proteome. The proteomes of pollen from different species have been relatively well studied, but the pollen grains are not single cells because they contain two/three-cell gametophytes (10). A critical factor for large scale proteomics analFrom the ‡Department

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“…By focusing our microarray data analysis on proteins significantly enriched at the TC surface, we focused our analysis on the putative primary source of disease in PE, the trophoblast and effectively only included microarray probes validated at the level of protein expression. Numerous genes are regulated by post-transcriptional and post-translational mechanisms and as such the array signal for the mRNA may not directly correlate with protein expression levels (17,51,52).…”

Section: Discussionmentioning

confidence: 99%

Translational Analysis of Mouse and Human Placental Protein and mRNA Reveals Distinct Molecular Pathologies in Human Preeclampsia

Cox

Sharma

Evangelou

et al. 2011

Molecular & Cellular Proteomics

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Preeclampsia (PE) adversely impacts ϳ5% of pregnancies. Despite extensive research, no consistent biomarkers or cures have emerged, suggesting that different molecular mechanisms may cause clinically similar disease. To address this, we undertook a proteomics study with three main goals: (1) to identify a panel of cell surface markers that distinguish the trophoblast and endothelial cells of the placenta in the mouse; (2) to translate this marker set to human via the Human Protein Atlas database; and (3) to utilize the validated human trophoblast markers to identify subgroups of human preeclampsia. To achieve these goals, plasma membrane proteins at the blood tissue interfaces were extracted from placentas using intravascular silica-bead perfusion, and then identified using shotgun proteomics. We identified 1181 plasma membrane proteins, of which 171 were enriched at the maternal blood-trophoblast interface and 192 at the fetal endothelial interface with a 70% conservation of expression in humans. Three distinct molecular subgroups of human preeclampsia were identified in existing human microarray data by using expression patterns of trophoblast-enriched proteins. Analysis of all misexpressed genes revealed divergent dysfunctions including angiogenesis (subgroup 1), MAPK signaling (subgroup 2), and hormone biosynthesis and metabolism (subgroup 3). Subgroup 2 lacked expected changes in known preeclampsia markers (sFLT1, sENG) and uniquely overexpressed GNA12. In an independent set of 40 banked placental specimens, GNA12 was overexpressed during preeclampsia when co-incident with chronic hypertension. In the current study we used a novel translational analysis to integrate mouse and human trophoblast protein expression with human microarray data. This strategy identified distinct molecular pathologies in human preeclampsia. We conclude that clinically similar

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Protein pathway and complex clustering of correlated mRNA and protein expression analyses in Saccharomyces cerevisiae

Cited by 333 publications

References 44 publications

Transcriptional, Proteomic, and Metabolic Responses to Lithium in Galactose-grown Yeast Cells

Transcriptional, Proteomic, and Metabolic Responses to Lithium in Galactose-grown Yeast Cells

Functional Differentiation of Brassica napus Guard Cells and Mesophyll Cells Revealed by Comparative Proteomics

Translational Analysis of Mouse and Human Placental Protein and mRNA Reveals Distinct Molecular Pathologies in Human Preeclampsia

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