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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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Predicted growth rates for S. bayanus and S.                                pombe expression datasets.By examining genes orthologous to our ∼70 S.                            cerevisiae growth-specific calibration genes, we successfully                            applied our model to predict growth rates in S. bayanus                            (∼50 orthologous growth-specific genes, ∼20 M years                            diverged) and S. pombe (∼75 growth-specific                            genes due to one-to-many mappings, ∼1B years diverged). (A)                            Predicted growth rates for S. bayanus undergoing the                            diauxic shift from fermentative to respiratory growth (Table                            S3). As observed for the S. cerevisiae diauxic                            shift in [4], growth pauses as glucose is exhausted                            and resumes as the yeast begins consuming ethanol. (B) Predicted growth                            rates for S. bayanus exposed to a 25–37 C heat shock (Table                            S3). In contrast to Figure 4B, in which S. cerevisiae is                            observed to recover from a 37 C heat shock, the less-thermotolerant S.                            bayanus [28] is predicted to halt growth at high                            temperatures. (C) Predicted growth rates for S. pombe wild-type and                            rad3Δ time courses, grown normally and exposed to hydroxyurea                            (HU, an inhibitor of DNA synthesis and thus growth) [29]. Despite the wide evolutionary divergence                            between S. pombe and our S. cerevisiae                            training data, predicted growth rates are in substantial agreement with                            expected biology. Each time course begins with low growth in a                            synchronized culture. When the synchronization block is released, cells                            begin growing, wild-type more efficiently than the rad3Δ mutant.                            Exposure to HU decreases growth over time, and this effect is                            exacerbated by RAD3 deletion. While the S. cerevisiae                            RAD3 ortholog MEC1 is essential, knockouts of the MEC1 pathway members                            SOD1 and LYS7 have been previously observed to induce HU sensitivity                                [30].
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pcbi-1000257-g006: Predicted growth rates for S. bayanus and S. pombe expression datasets.By examining genes orthologous to our ∼70 S. cerevisiae growth-specific calibration genes, we successfully applied our model to predict growth rates in S. bayanus (∼50 orthologous growth-specific genes, ∼20 M years diverged) and S. pombe (∼75 growth-specific genes due to one-to-many mappings, ∼1B years diverged). (A) Predicted growth rates for S. bayanus undergoing the diauxic shift from fermentative to respiratory growth (Table S3). As observed for the S. cerevisiae diauxic shift in [4], growth pauses as glucose is exhausted and resumes as the yeast begins consuming ethanol. (B) Predicted growth rates for S. bayanus exposed to a 25–37 C heat shock (Table S3). In contrast to Figure 4B, in which S. cerevisiae is observed to recover from a 37 C heat shock, the less-thermotolerant S. bayanus [28] is predicted to halt growth at high temperatures. (C) Predicted growth rates for S. pombe wild-type and rad3Δ time courses, grown normally and exposed to hydroxyurea (HU, an inhibitor of DNA synthesis and thus growth) [29]. Despite the wide evolutionary divergence between S. pombe and our S. cerevisiae training data, predicted growth rates are in substantial agreement with expected biology. Each time course begins with low growth in a synchronized culture. When the synchronization block is released, cells begin growing, wild-type more efficiently than the rad3Δ mutant. Exposure to HU decreases growth over time, and this effect is exacerbated by RAD3 deletion. While the S. cerevisiae RAD3 ortholog MEC1 is essential, knockouts of the MEC1 pathway members SOD1 and LYS7 have been previously observed to induce HU sensitivity [30].

Mentions: While our growth rate model is based on a transcriptional growth signature in S. cerevisiae, the model can be applied to any organism with sufficiently orthologous transcriptional activity. This is likely to be the case within the sensu stricto yeasts, separated by ∼25 million years of evolution [27]. By finding the ∼50 S. bayanus genes orthologous to our ∼70 S. cerevisiae growth-specific calibration genes [19], we can apply our model directly to S. bayanus expression data (Table S4). Figure 6 demonstrates such a result for two S. bayanus time courses assaying the diauxic shift and a response to heat shock. These results have comparable profile to those from S. cerevisiae and are similarly biologically compelling. For example, the diauxic shift in S. bayanus results in a very similar growth pattern to the known response in S. cerevisiae, with a near-cessation of growth during the shift and subsequent rebound. Conversely, S. bayanus is less resistant to high temperatures than S. cerevisiae  [28], and our growth rate inferences show a corresponding failure in its ability to grow following severe heat shock.


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)

Predicted growth rates for S. bayanus and S.                                pombe expression datasets.By examining genes orthologous to our ∼70 S.                            cerevisiae growth-specific calibration genes, we successfully                            applied our model to predict growth rates in S. bayanus                            (∼50 orthologous growth-specific genes, ∼20 M years                            diverged) and S. pombe (∼75 growth-specific                            genes due to one-to-many mappings, ∼1B years diverged). (A)                            Predicted growth rates for S. bayanus undergoing the                            diauxic shift from fermentative to respiratory growth (Table                            S3). As observed for the S. cerevisiae diauxic                            shift in [4], growth pauses as glucose is exhausted                            and resumes as the yeast begins consuming ethanol. (B) Predicted growth                            rates for S. bayanus exposed to a 25–37 C heat shock (Table                            S3). In contrast to Figure 4B, in which S. cerevisiae is                            observed to recover from a 37 C heat shock, the less-thermotolerant S.                            bayanus [28] is predicted to halt growth at high                            temperatures. (C) Predicted growth rates for S. pombe wild-type and                            rad3Δ time courses, grown normally and exposed to hydroxyurea                            (HU, an inhibitor of DNA synthesis and thus growth) [29]. Despite the wide evolutionary divergence                            between S. pombe and our S. cerevisiae                            training data, predicted growth rates are in substantial agreement with                            expected biology. Each time course begins with low growth in a                            synchronized culture. When the synchronization block is released, cells                            begin growing, wild-type more efficiently than the rad3Δ mutant.                            Exposure to HU decreases growth over time, and this effect is                            exacerbated by RAD3 deletion. While the S. cerevisiae                            RAD3 ortholog MEC1 is essential, knockouts of the MEC1 pathway members                            SOD1 and LYS7 have been previously observed to induce HU sensitivity                                [30].
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2599889&req=5

pcbi-1000257-g006: Predicted growth rates for S. bayanus and S. pombe expression datasets.By examining genes orthologous to our ∼70 S. cerevisiae growth-specific calibration genes, we successfully applied our model to predict growth rates in S. bayanus (∼50 orthologous growth-specific genes, ∼20 M years diverged) and S. pombe (∼75 growth-specific genes due to one-to-many mappings, ∼1B years diverged). (A) Predicted growth rates for S. bayanus undergoing the diauxic shift from fermentative to respiratory growth (Table S3). As observed for the S. cerevisiae diauxic shift in [4], growth pauses as glucose is exhausted and resumes as the yeast begins consuming ethanol. (B) Predicted growth rates for S. bayanus exposed to a 25–37 C heat shock (Table S3). In contrast to Figure 4B, in which S. cerevisiae is observed to recover from a 37 C heat shock, the less-thermotolerant S. bayanus [28] is predicted to halt growth at high temperatures. (C) Predicted growth rates for S. pombe wild-type and rad3Δ time courses, grown normally and exposed to hydroxyurea (HU, an inhibitor of DNA synthesis and thus growth) [29]. Despite the wide evolutionary divergence between S. pombe and our S. cerevisiae training data, predicted growth rates are in substantial agreement with expected biology. Each time course begins with low growth in a synchronized culture. When the synchronization block is released, cells begin growing, wild-type more efficiently than the rad3Δ mutant. Exposure to HU decreases growth over time, and this effect is exacerbated by RAD3 deletion. While the S. cerevisiae RAD3 ortholog MEC1 is essential, knockouts of the MEC1 pathway members SOD1 and LYS7 have been previously observed to induce HU sensitivity [30].
Mentions: While our growth rate model is based on a transcriptional growth signature in S. cerevisiae, the model can be applied to any organism with sufficiently orthologous transcriptional activity. This is likely to be the case within the sensu stricto yeasts, separated by ∼25 million years of evolution [27]. By finding the ∼50 S. bayanus genes orthologous to our ∼70 S. cerevisiae growth-specific calibration genes [19], we can apply our model directly to S. bayanus expression data (Table S4). Figure 6 demonstrates such a result for two S. bayanus time courses assaying the diauxic shift and a response to heat shock. These results have comparable profile to those from S. cerevisiae and are similarly biologically compelling. For example, the diauxic shift in S. bayanus results in a very similar growth pattern to the known response in S. cerevisiae, with a near-cessation of growth during the shift and subsequent rebound. Conversely, S. bayanus is less resistant to high temperatures than S. cerevisiae  [28], and our growth rate inferences show a corresponding failure in its ability to grow following severe heat shock.

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