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Coupling among growth rate response, metabolic cycle, and cell division cycle in yeast.

Slavov N, Botstein D - Mol. Biol. Cell (2011)

Bottom Line: All genes with universal GRR, which comprise 25% of the genome, are expressed periodically in the yeast metabolic cycle (YMC).This idea is supported by oxygen consumption data from metabolically synchronized cultures with doubling times ranging from 5 to 14 h.We found that the high oxygen consumption phase of the YMC can coincide exactly with the S phase of the cell division cycle, suggesting that oxidative metabolism and DNA replication are not incompatible.

View Article: PubMed Central - PubMed

Affiliation: Massachusetts Institute of Technology, Cambridge, MA 02139, USA. nslavov@alum.mit.edu

ABSTRACT
We studied the steady-state responses to changes in growth rate of yeast when ethanol is the sole source of carbon and energy. Analysis of these data, together with data from studies where glucose was the carbon source, allowed us to distinguish a "universal" growth rate response (GRR) common to all media studied from a GRR specific to the carbon source. Genes with positive universal GRR include ribosomal, translation, and mitochondrial genes, and those with negative GRR include autophagy, vacuolar, and stress response genes. The carbon source-specific GRR genes control mitochondrial function, peroxisomes, and synthesis of vitamins and cofactors, suggesting this response may reflect the intensity of oxidative metabolism. All genes with universal GRR, which comprise 25% of the genome, are expressed periodically in the yeast metabolic cycle (YMC). We propose that the universal GRR may be accounted for by changes in the relative durations of the YMC phases. This idea is supported by oxygen consumption data from metabolically synchronized cultures with doubling times ranging from 5 to 14 h. We found that the high oxygen consumption phase of the YMC can coincide exactly with the S phase of the cell division cycle, suggesting that oxidative metabolism and DNA replication are not incompatible.

Show MeSH
Singular value decomposition (SVD) of the gene expression data. Top, first singular pair; middle, second singular pair; and bottom, third singular pair. The fraction of variance explained by each singular pair is indicated by the numbers in red to the right of the corresponding panels.
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Figure 3: Singular value decomposition (SVD) of the gene expression data. Top, first singular pair; middle, second singular pair; and bottom, third singular pair. The fraction of variance explained by each singular pair is indicated by the numbers in red to the right of the corresponding panels.

Mentions: To explore the data further, we computed the singular value decomposition (SVD; Golub and Kahan, 1965; Alter et al., 2000) of the gene expression data for all conditions (carbon sources and limitations). Such decomposition allows one to summarize and visualize the changes in gene expression in terms of a set of orthogonal vectors, sometimes referred to as “eigengenes.” Eigengenes can be thought of as representative expression profiles that, together, represent all the variations in a set of experiments. The extent to which each vector represents the expression profiles of many genes is quantified by the magnitude of the corresponding singular value relative to all singular values. As shown in Figure 3, the results closely resemble those found by Brauer et al. (2008). The most prominent singular vector, which accounts for 48% of the variance (that is 48% of the change in gene expression), is strongly correlated 11


Coupling among growth rate response, metabolic cycle, and cell division cycle in yeast.

Slavov N, Botstein D - Mol. Biol. Cell (2011)

Singular value decomposition (SVD) of the gene expression data. Top, first singular pair; middle, second singular pair; and bottom, third singular pair. The fraction of variance explained by each singular pair is indicated by the numbers in red to the right of the corresponding panels.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3113766&req=5

Figure 3: Singular value decomposition (SVD) of the gene expression data. Top, first singular pair; middle, second singular pair; and bottom, third singular pair. The fraction of variance explained by each singular pair is indicated by the numbers in red to the right of the corresponding panels.
Mentions: To explore the data further, we computed the singular value decomposition (SVD; Golub and Kahan, 1965; Alter et al., 2000) of the gene expression data for all conditions (carbon sources and limitations). Such decomposition allows one to summarize and visualize the changes in gene expression in terms of a set of orthogonal vectors, sometimes referred to as “eigengenes.” Eigengenes can be thought of as representative expression profiles that, together, represent all the variations in a set of experiments. The extent to which each vector represents the expression profiles of many genes is quantified by the magnitude of the corresponding singular value relative to all singular values. As shown in Figure 3, the results closely resemble those found by Brauer et al. (2008). The most prominent singular vector, which accounts for 48% of the variance (that is 48% of the change in gene expression), is strongly correlated 11

Bottom Line: All genes with universal GRR, which comprise 25% of the genome, are expressed periodically in the yeast metabolic cycle (YMC).This idea is supported by oxygen consumption data from metabolically synchronized cultures with doubling times ranging from 5 to 14 h.We found that the high oxygen consumption phase of the YMC can coincide exactly with the S phase of the cell division cycle, suggesting that oxidative metabolism and DNA replication are not incompatible.

View Article: PubMed Central - PubMed

Affiliation: Massachusetts Institute of Technology, Cambridge, MA 02139, USA. nslavov@alum.mit.edu

ABSTRACT
We studied the steady-state responses to changes in growth rate of yeast when ethanol is the sole source of carbon and energy. Analysis of these data, together with data from studies where glucose was the carbon source, allowed us to distinguish a "universal" growth rate response (GRR) common to all media studied from a GRR specific to the carbon source. Genes with positive universal GRR include ribosomal, translation, and mitochondrial genes, and those with negative GRR include autophagy, vacuolar, and stress response genes. The carbon source-specific GRR genes control mitochondrial function, peroxisomes, and synthesis of vitamins and cofactors, suggesting this response may reflect the intensity of oxidative metabolism. All genes with universal GRR, which comprise 25% of the genome, are expressed periodically in the yeast metabolic cycle (YMC). We propose that the universal GRR may be accounted for by changes in the relative durations of the YMC phases. This idea is supported by oxygen consumption data from metabolically synchronized cultures with doubling times ranging from 5 to 14 h. We found that the high oxygen consumption phase of the YMC can coincide exactly with the S phase of the cell division cycle, suggesting that oxidative metabolism and DNA replication are not incompatible.

Show MeSH