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Predicting cellular growth from gene expression signatures.

Airoldi EM, Huttenhower C, Gresham D, Lu C, Caudy AA, Dunham MJ, Broach JR, Botstein D, Troyanskaya OG - PLoS Comput. Biol. (2009)

Bottom Line: The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution.We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes.More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods.

View Article: PubMed Central - PubMed

Affiliation: Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.

ABSTRACT
Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

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Perturbations and potential transcriptional regulators of the growth                            rate response.(A) Predicted growth rates for gal1Δ cells shifted to glucose, to                            galactose, and to galactose with a constitutively active RAS2G19V                            allele. On glucose, rapid growth is induced within ∼40 m; growth                            on galactose falls to low levels within ∼40 m, as it cannot be                            metabolized by this mutant. However, when glucose sensing is emulated by                            artificial activation of the Ras/PKA pathway, the transcriptional                            regulatory network attempts to induce rapid growth within                            ∼60–80 m despite the unavailability of appropriate                            nutrients. This disconnect between actual and perceived cellular state                            leads to cell death within 4–6 hours and suggests that                            nutrient sensing (as opposed to metabolic activity or internal cellular                            state) is responsible for a large portion of the transcriptional growth                            rate response. (B) Regulatory binding sites enriched in growth up- and                            down-regulated genes. We clustered the yeast genome by degree of growth                            rate response, yielding ten clusters with average responses ranging from                            −12.0 (strongly downregulated with increasing growth rate) to                            8.6 (strongly upregulated). The FIRE program [34] predicted                            10 regulatory motifs in the upstream flanks and 3′ UTRs of the                            most up- and down-regulated clusters. These included the known                            stress-responsive MSN2/4 binding sites in downregulated genes, the                            ribosomal regulators RAP1 and PUF4 in upregulated genes, and INO4 sites                            in upregulated genes (possibly corresponding to its role in the stress                            response and fatty acid biosynthesis [35]. We also                            identified five additional putative growth regulatory sites for which                            the binding factor is not yet known.
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pcbi-1000257-g008: Perturbations and potential transcriptional regulators of the growth rate response.(A) Predicted growth rates for gal1Δ cells shifted to glucose, to galactose, and to galactose with a constitutively active RAS2G19V allele. On glucose, rapid growth is induced within ∼40 m; growth on galactose falls to low levels within ∼40 m, as it cannot be metabolized by this mutant. However, when glucose sensing is emulated by artificial activation of the Ras/PKA pathway, the transcriptional regulatory network attempts to induce rapid growth within ∼60–80 m despite the unavailability of appropriate nutrients. This disconnect between actual and perceived cellular state leads to cell death within 4–6 hours and suggests that nutrient sensing (as opposed to metabolic activity or internal cellular state) is responsible for a large portion of the transcriptional growth rate response. (B) Regulatory binding sites enriched in growth up- and down-regulated genes. We clustered the yeast genome by degree of growth rate response, yielding ten clusters with average responses ranging from −12.0 (strongly downregulated with increasing growth rate) to 8.6 (strongly upregulated). The FIRE program [34] predicted 10 regulatory motifs in the upstream flanks and 3′ UTRs of the most up- and down-regulated clusters. These included the known stress-responsive MSN2/4 binding sites in downregulated genes, the ribosomal regulators RAP1 and PUF4 in upregulated genes, and INO4 sites in upregulated genes (possibly corresponding to its role in the stress response and fatty acid biosynthesis [35]. We also identified five additional putative growth regulatory sites for which the binding factor is not yet known.

Mentions: We used a gal1Δ strain carrying the activated allele RAS2G19V under control of the galactose inducible GAL10 promoter. Addition of galactose activates the Ras/PKA pathway, but since galactose cannot be metabolized by this strain, the metabolic state of the cell remains unaltered [9]. When grown on glycerol our model predicts a relative growth rate of ∼0.2 for this strain (Figure 8A), which changes to ∼0.6 within twenty minutes following glucose addition, consistent with the change in doubling time from 5.8 hr to 2.6 hr. When we performed the same experiment on glycerol media and induced the RAS2G19V by means of galactose addition, we detected a transcriptional response within sixty minutes. The predicted growth rate of the RAS2G19V mutant strain was comparable to the addition of glucose despite the fact that galactose addition does not yield an increase in growth, as measured by optical density, since the cells are unable to metabolize galactose. In fact, while the model's summarization of gene expression state indicates that the culture is attempting to increase growth, induction of the RAS2G19V allele results in an immediate decrease in growth rate and complete cessation of growth within four hours [33]. These results are consistent with the cell setting its growth-specific transcription program on the basis of its perception of nutrients present in the environment, rather than on the direct availability of energy or metabolites produced from such nutrients. The mechanism by which the cell integrates this external state in order to set the appropriate growth rate expression state must be mediated, at least in part, through the Ras/cAMP/PKA pathway.


Predicting cellular growth from gene expression signatures.

Airoldi EM, Huttenhower C, Gresham D, Lu C, Caudy AA, Dunham MJ, Broach JR, Botstein D, Troyanskaya OG - PLoS Comput. Biol. (2009)

Perturbations and potential transcriptional regulators of the growth                            rate response.(A) Predicted growth rates for gal1Δ cells shifted to glucose, to                            galactose, and to galactose with a constitutively active RAS2G19V                            allele. On glucose, rapid growth is induced within ∼40 m; growth                            on galactose falls to low levels within ∼40 m, as it cannot be                            metabolized by this mutant. However, when glucose sensing is emulated by                            artificial activation of the Ras/PKA pathway, the transcriptional                            regulatory network attempts to induce rapid growth within                            ∼60–80 m despite the unavailability of appropriate                            nutrients. This disconnect between actual and perceived cellular state                            leads to cell death within 4–6 hours and suggests that                            nutrient sensing (as opposed to metabolic activity or internal cellular                            state) is responsible for a large portion of the transcriptional growth                            rate response. (B) Regulatory binding sites enriched in growth up- and                            down-regulated genes. We clustered the yeast genome by degree of growth                            rate response, yielding ten clusters with average responses ranging from                            −12.0 (strongly downregulated with increasing growth rate) to                            8.6 (strongly upregulated). The FIRE program [34] predicted                            10 regulatory motifs in the upstream flanks and 3′ UTRs of the                            most up- and down-regulated clusters. These included the known                            stress-responsive MSN2/4 binding sites in downregulated genes, the                            ribosomal regulators RAP1 and PUF4 in upregulated genes, and INO4 sites                            in upregulated genes (possibly corresponding to its role in the stress                            response and fatty acid biosynthesis [35]. We also                            identified five additional putative growth regulatory sites for which                            the binding factor is not yet known.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2599889&req=5

pcbi-1000257-g008: Perturbations and potential transcriptional regulators of the growth rate response.(A) Predicted growth rates for gal1Δ cells shifted to glucose, to galactose, and to galactose with a constitutively active RAS2G19V allele. On glucose, rapid growth is induced within ∼40 m; growth on galactose falls to low levels within ∼40 m, as it cannot be metabolized by this mutant. However, when glucose sensing is emulated by artificial activation of the Ras/PKA pathway, the transcriptional regulatory network attempts to induce rapid growth within ∼60–80 m despite the unavailability of appropriate nutrients. This disconnect between actual and perceived cellular state leads to cell death within 4–6 hours and suggests that nutrient sensing (as opposed to metabolic activity or internal cellular state) is responsible for a large portion of the transcriptional growth rate response. (B) Regulatory binding sites enriched in growth up- and down-regulated genes. We clustered the yeast genome by degree of growth rate response, yielding ten clusters with average responses ranging from −12.0 (strongly downregulated with increasing growth rate) to 8.6 (strongly upregulated). The FIRE program [34] predicted 10 regulatory motifs in the upstream flanks and 3′ UTRs of the most up- and down-regulated clusters. These included the known stress-responsive MSN2/4 binding sites in downregulated genes, the ribosomal regulators RAP1 and PUF4 in upregulated genes, and INO4 sites in upregulated genes (possibly corresponding to its role in the stress response and fatty acid biosynthesis [35]. We also identified five additional putative growth regulatory sites for which the binding factor is not yet known.
Mentions: We used a gal1Δ strain carrying the activated allele RAS2G19V under control of the galactose inducible GAL10 promoter. Addition of galactose activates the Ras/PKA pathway, but since galactose cannot be metabolized by this strain, the metabolic state of the cell remains unaltered [9]. When grown on glycerol our model predicts a relative growth rate of ∼0.2 for this strain (Figure 8A), which changes to ∼0.6 within twenty minutes following glucose addition, consistent with the change in doubling time from 5.8 hr to 2.6 hr. When we performed the same experiment on glycerol media and induced the RAS2G19V by means of galactose addition, we detected a transcriptional response within sixty minutes. The predicted growth rate of the RAS2G19V mutant strain was comparable to the addition of glucose despite the fact that galactose addition does not yield an increase in growth, as measured by optical density, since the cells are unable to metabolize galactose. In fact, while the model's summarization of gene expression state indicates that the culture is attempting to increase growth, induction of the RAS2G19V allele results in an immediate decrease in growth rate and complete cessation of growth within four hours [33]. These results are consistent with the cell setting its growth-specific transcription program on the basis of its perception of nutrients present in the environment, rather than on the direct availability of energy or metabolites produced from such nutrients. The mechanism by which the cell integrates this external state in order to set the appropriate growth rate expression state must be mediated, at least in part, through the Ras/cAMP/PKA pathway.

Bottom Line: The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution.We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes.More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods.

View Article: PubMed Central - PubMed

Affiliation: Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.

ABSTRACT
Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

Show MeSH
Related in: MedlinePlus