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The yin and yang of yeast transcription: elements of a global feedback system between metabolism and chromatin.

Machné R, Murray DB - PLoS ONE (2012)

Bottom Line: We show that the ATP:ADP ratio oscillates, compatible with alternating metabolic activity of the two superclusters and differential feedback on their transcription via activating (RSC) and repressive (Isw2) types of promoter structure remodeling.We propose a novel feedback mechanism, where the energetic state of the cell, reflected in the ATP:ADP ratio, gates the transcription of large, but functionally coherent groups of genes via differential effects of ATP-dependent nucleosome remodeling machineries.Besides providing a mechanistic hypothesis for the delayed negative feedback that results in the oscillatory phenotype, this mechanism may underpin the continuous adaptation of growth to environmental conditions.

View Article: PubMed Central - PubMed

Affiliation: Institute for Theoretical Chemistry, University of Vienna, Vienna, Austria. raim@tbi.univie.ac.at

ABSTRACT
When grown in continuous culture, budding yeast cells tend to synchronize their respiratory activity to form a stable oscillation that percolates throughout cellular physiology and involves the majority of the protein-coding transcriptome. Oscillations in batch culture and at single cell level support the idea that these dynamics constitute a general growth principle. The precise molecular mechanisms and biological functions of the oscillation remain elusive. Fourier analysis of transcriptome time series datasets from two different oscillation periods (0.7 h and 5 h) reveals seven distinct co-expression clusters common to both systems (34% of all yeast ORF), which consolidate into two superclusters when correlated with a compilation of 1,327 unrelated transcriptome datasets. These superclusters encode for cell growth and anabolism during the phase of high, and mitochondrial growth, catabolism and stress response during the phase of low oxygen uptake. The promoters of each cluster are characterized by different nucleotide contents, promoter nucleosome configurations, and dependence on ATP-dependent nucleosome remodeling complexes. We show that the ATP:ADP ratio oscillates, compatible with alternating metabolic activity of the two superclusters and differential feedback on their transcription via activating (RSC) and repressive (Isw2) types of promoter structure remodeling. We propose a novel feedback mechanism, where the energetic state of the cell, reflected in the ATP:ADP ratio, gates the transcription of large, but functionally coherent groups of genes via differential effects of ATP-dependent nucleosome remodeling machineries. Besides providing a mechanistic hypothesis for the delayed negative feedback that results in the oscillatory phenotype, this mechanism may underpin the continuous adaptation of growth to environmental conditions.

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Overlap of the consensus clusters with other gene clusterings.Clusters were tested for enrichment in other gene categorizations by cumulative hypergeometric distribution tests. The text in the fields gives the number of genes in the respective overlap (top line) and the p-values (bottom line). The p-values are further indicated by gray-scale (see legend to the right of each panel). The bottom row gives the total number of genes in each tested category. Figures S4 & S5 give results for all 14 clusters and Dataset S7 provides the original gene classifications. “NA” indicates that no classification was available for these genes in the respective dataset. 2A: genes whose expression positively (“up”) or negatively (“down”) correlates with, or does not respond (“unresp.”) to growth rates in nutrient-limited conditions, data from [31]. 2B: genes which are upregulated (“up”) or downregulated (“down”) in response to a variety of stress conditions, data from [29]via supplementary material of [31]. 2C: dependence on transcription initiation complexes “TFIID”, “SAGA” or “both”, from [34]. 2D: genes with fuzzy nucleosome positioning (“fuzzy”), nucleosome-depleted promoters (“depleted”), a large and pronounced NDR (“large NDR”) or a small but pronounced NDR (“small NDR”), from [36]. 2E: genes with no Isw2(K215R) binding but remodeling at promoter NDR (“RMD”), with Isw2(K215R) binding but no remodeling (“Isw2”), with Isw2(K215R) binding and remodeling (“RMD+Isw2”) or neither binding nor remodeling (“none”), data from [40]. 2F: as Figure 2E but for the NDR at 3′ ends of genes.
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pone-0037906-g002: Overlap of the consensus clusters with other gene clusterings.Clusters were tested for enrichment in other gene categorizations by cumulative hypergeometric distribution tests. The text in the fields gives the number of genes in the respective overlap (top line) and the p-values (bottom line). The p-values are further indicated by gray-scale (see legend to the right of each panel). The bottom row gives the total number of genes in each tested category. Figures S4 & S5 give results for all 14 clusters and Dataset S7 provides the original gene classifications. “NA” indicates that no classification was available for these genes in the respective dataset. 2A: genes whose expression positively (“up”) or negatively (“down”) correlates with, or does not respond (“unresp.”) to growth rates in nutrient-limited conditions, data from [31]. 2B: genes which are upregulated (“up”) or downregulated (“down”) in response to a variety of stress conditions, data from [29]via supplementary material of [31]. 2C: dependence on transcription initiation complexes “TFIID”, “SAGA” or “both”, from [34]. 2D: genes with fuzzy nucleosome positioning (“fuzzy”), nucleosome-depleted promoters (“depleted”), a large and pronounced NDR (“large NDR”) or a small but pronounced NDR (“small NDR”), from [36]. 2E: genes with no Isw2(K215R) binding but remodeling at promoter NDR (“RMD”), with Isw2(K215R) binding but no remodeling (“Isw2”), with Isw2(K215R) binding and remodeling (“RMD+Isw2”) or neither binding nor remodeling (“none”), data from [40]. 2F: as Figure 2E but for the NDR at 3′ ends of genes.

Mentions: The functional profiles of the clusters, especially of the two antiphase clusters A and D, are reminiscent of the environmental stress response (ESR) to various cellular stress conditions [29], [30], [32]. This relation had been previously noted [20], [31] and is reflected in sequence motif and binding site enrichments in the promoters of cluster genes (Table S5, Figure S3 and Datasets S5 & S6), e.g., the RRPE and PAC motifs in cluster A, and STRE motif and Msn2/Msn4 binding sites in cluster D [32]. We find highly significant overlaps of clusters A & AB with gene groups [29], [31] downregulated in response to stress and positively correlating with growth rate and of clusters D & B.D with those upregulated upon stress and negatively correlating with growth rate (Figures 2A, 2B & S7C). A statistical analysis of the cluster distributions of transcript levels in a previously published collection of 1,327 individiual transcriptome microarray hybridizations [60] confirms a general anti-correlation in expression between clusters A, AB & B, and clusters D & B.D (Figure 3A). Cluster C expression is more diverse but overall correlates positively with cluster D, i.e. Spearman’s correlation of the normalized rank sums in Figure 3A is (). The regulatory antagonism, i.e., when one gene group is downregulated the other is upregulated, is most apparent between clusters A and D (, ) and is further reflected in strong biases in various measures of expression kinetics, such as transcriptional frequency, protein level and noise (Figure S7).


The yin and yang of yeast transcription: elements of a global feedback system between metabolism and chromatin.

Machné R, Murray DB - PLoS ONE (2012)

Overlap of the consensus clusters with other gene clusterings.Clusters were tested for enrichment in other gene categorizations by cumulative hypergeometric distribution tests. The text in the fields gives the number of genes in the respective overlap (top line) and the p-values (bottom line). The p-values are further indicated by gray-scale (see legend to the right of each panel). The bottom row gives the total number of genes in each tested category. Figures S4 & S5 give results for all 14 clusters and Dataset S7 provides the original gene classifications. “NA” indicates that no classification was available for these genes in the respective dataset. 2A: genes whose expression positively (“up”) or negatively (“down”) correlates with, or does not respond (“unresp.”) to growth rates in nutrient-limited conditions, data from [31]. 2B: genes which are upregulated (“up”) or downregulated (“down”) in response to a variety of stress conditions, data from [29]via supplementary material of [31]. 2C: dependence on transcription initiation complexes “TFIID”, “SAGA” or “both”, from [34]. 2D: genes with fuzzy nucleosome positioning (“fuzzy”), nucleosome-depleted promoters (“depleted”), a large and pronounced NDR (“large NDR”) or a small but pronounced NDR (“small NDR”), from [36]. 2E: genes with no Isw2(K215R) binding but remodeling at promoter NDR (“RMD”), with Isw2(K215R) binding but no remodeling (“Isw2”), with Isw2(K215R) binding and remodeling (“RMD+Isw2”) or neither binding nor remodeling (“none”), data from [40]. 2F: as Figure 2E but for the NDR at 3′ ends of genes.
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getmorefigures.php?uid=PMC3369881&req=5

pone-0037906-g002: Overlap of the consensus clusters with other gene clusterings.Clusters were tested for enrichment in other gene categorizations by cumulative hypergeometric distribution tests. The text in the fields gives the number of genes in the respective overlap (top line) and the p-values (bottom line). The p-values are further indicated by gray-scale (see legend to the right of each panel). The bottom row gives the total number of genes in each tested category. Figures S4 & S5 give results for all 14 clusters and Dataset S7 provides the original gene classifications. “NA” indicates that no classification was available for these genes in the respective dataset. 2A: genes whose expression positively (“up”) or negatively (“down”) correlates with, or does not respond (“unresp.”) to growth rates in nutrient-limited conditions, data from [31]. 2B: genes which are upregulated (“up”) or downregulated (“down”) in response to a variety of stress conditions, data from [29]via supplementary material of [31]. 2C: dependence on transcription initiation complexes “TFIID”, “SAGA” or “both”, from [34]. 2D: genes with fuzzy nucleosome positioning (“fuzzy”), nucleosome-depleted promoters (“depleted”), a large and pronounced NDR (“large NDR”) or a small but pronounced NDR (“small NDR”), from [36]. 2E: genes with no Isw2(K215R) binding but remodeling at promoter NDR (“RMD”), with Isw2(K215R) binding but no remodeling (“Isw2”), with Isw2(K215R) binding and remodeling (“RMD+Isw2”) or neither binding nor remodeling (“none”), data from [40]. 2F: as Figure 2E but for the NDR at 3′ ends of genes.
Mentions: The functional profiles of the clusters, especially of the two antiphase clusters A and D, are reminiscent of the environmental stress response (ESR) to various cellular stress conditions [29], [30], [32]. This relation had been previously noted [20], [31] and is reflected in sequence motif and binding site enrichments in the promoters of cluster genes (Table S5, Figure S3 and Datasets S5 & S6), e.g., the RRPE and PAC motifs in cluster A, and STRE motif and Msn2/Msn4 binding sites in cluster D [32]. We find highly significant overlaps of clusters A & AB with gene groups [29], [31] downregulated in response to stress and positively correlating with growth rate and of clusters D & B.D with those upregulated upon stress and negatively correlating with growth rate (Figures 2A, 2B & S7C). A statistical analysis of the cluster distributions of transcript levels in a previously published collection of 1,327 individiual transcriptome microarray hybridizations [60] confirms a general anti-correlation in expression between clusters A, AB & B, and clusters D & B.D (Figure 3A). Cluster C expression is more diverse but overall correlates positively with cluster D, i.e. Spearman’s correlation of the normalized rank sums in Figure 3A is (). The regulatory antagonism, i.e., when one gene group is downregulated the other is upregulated, is most apparent between clusters A and D (, ) and is further reflected in strong biases in various measures of expression kinetics, such as transcriptional frequency, protein level and noise (Figure S7).

Bottom Line: We show that the ATP:ADP ratio oscillates, compatible with alternating metabolic activity of the two superclusters and differential feedback on their transcription via activating (RSC) and repressive (Isw2) types of promoter structure remodeling.We propose a novel feedback mechanism, where the energetic state of the cell, reflected in the ATP:ADP ratio, gates the transcription of large, but functionally coherent groups of genes via differential effects of ATP-dependent nucleosome remodeling machineries.Besides providing a mechanistic hypothesis for the delayed negative feedback that results in the oscillatory phenotype, this mechanism may underpin the continuous adaptation of growth to environmental conditions.

View Article: PubMed Central - PubMed

Affiliation: Institute for Theoretical Chemistry, University of Vienna, Vienna, Austria. raim@tbi.univie.ac.at

ABSTRACT
When grown in continuous culture, budding yeast cells tend to synchronize their respiratory activity to form a stable oscillation that percolates throughout cellular physiology and involves the majority of the protein-coding transcriptome. Oscillations in batch culture and at single cell level support the idea that these dynamics constitute a general growth principle. The precise molecular mechanisms and biological functions of the oscillation remain elusive. Fourier analysis of transcriptome time series datasets from two different oscillation periods (0.7 h and 5 h) reveals seven distinct co-expression clusters common to both systems (34% of all yeast ORF), which consolidate into two superclusters when correlated with a compilation of 1,327 unrelated transcriptome datasets. These superclusters encode for cell growth and anabolism during the phase of high, and mitochondrial growth, catabolism and stress response during the phase of low oxygen uptake. The promoters of each cluster are characterized by different nucleotide contents, promoter nucleosome configurations, and dependence on ATP-dependent nucleosome remodeling complexes. We show that the ATP:ADP ratio oscillates, compatible with alternating metabolic activity of the two superclusters and differential feedback on their transcription via activating (RSC) and repressive (Isw2) types of promoter structure remodeling. We propose a novel feedback mechanism, where the energetic state of the cell, reflected in the ATP:ADP ratio, gates the transcription of large, but functionally coherent groups of genes via differential effects of ATP-dependent nucleosome remodeling machineries. Besides providing a mechanistic hypothesis for the delayed negative feedback that results in the oscillatory phenotype, this mechanism may underpin the continuous adaptation of growth to environmental conditions.

Show MeSH
Related in: MedlinePlus