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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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Differences in growth characteristics of a metabolically cyclingculture compared to cells synchronously undergoing the cell divisioncycle.We predict periodic bursts of growth during the oxidative phase of themetabolic cycle as described by [12]. Conversely, weobserve essentially no variation in growth in cultures synchronouslyundergoing the cell division cycle, which has been shown to primarilyoccupy the reductive phase of the metabolic cycle [32]. (A) In cellsundergoing metabolic cycling, growth rates are predicted to peak duringthe oxidative phase of the cycle, where [12] also observesstrong upregulation of translational and ribosomal genes. (B) Thepredicted growth rate for the [13]alpha-factor synchronized cell cycle is essentially constant, after aninitial release from the synchronization block. (C) Predicted rates forthe [8] alpha-factor synchronized cell cyclealso show an initial resumption of growth after alpha-factor blockfollowed by relatively constant growth rate. Taken together, theseobservations support the claim that growth rate regulation is notspecific to any one cell cycle phase. This also agrees with the factthat rapidly growing (and thus fermenting) S.cerevisiae does not partition metabolism into discrete stages,a phenomenon only occurring when reductive metabolism is hindered bynutrient limitation or other stresses.
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pcbi-1000257-g007: Differences in growth characteristics of a metabolically cyclingculture compared to cells synchronously undergoing the cell divisioncycle.We predict periodic bursts of growth during the oxidative phase of themetabolic cycle as described by [12]. Conversely, weobserve essentially no variation in growth in cultures synchronouslyundergoing the cell division cycle, which has been shown to primarilyoccupy the reductive phase of the metabolic cycle [32]. (A) In cellsundergoing metabolic cycling, growth rates are predicted to peak duringthe oxidative phase of the cycle, where [12] also observesstrong upregulation of translational and ribosomal genes. (B) Thepredicted growth rate for the [13]alpha-factor synchronized cell cycle is essentially constant, after aninitial release from the synchronization block. (C) Predicted rates forthe [8] alpha-factor synchronized cell cyclealso show an initial resumption of growth after alpha-factor blockfollowed by relatively constant growth rate. Taken together, theseobservations support the claim that growth rate regulation is notspecific to any one cell cycle phase. This also agrees with the factthat rapidly growing (and thus fermenting) S.cerevisiae does not partition metabolism into discrete stages,a phenomenon only occurring when reductive metabolism is hindered bynutrient limitation or other stresses.

Mentions: Growth rate prediction applied to the yeast metabolic cycle data revealed astriking periodicity (Figure7A). The cyclical pattern of growth rate variation occurs completely inconcert with the metabolic cycle as defined by Tu et al. Specifically, theculture's growth rate is predicted to be at minima during the reductivephase of the metabolic cycle, when oxygen consumption is at a minimum, and reachmaxima during the peak of the oxidative phases when oxygen consumption ismaximal. In contrast, growth rate prediction for the cell cycle (Figure 7B and 7C) showvirtually no variation in predicted growth rate during the different stages ofcell division.


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)

Differences in growth characteristics of a metabolically cyclingculture compared to cells synchronously undergoing the cell divisioncycle.We predict periodic bursts of growth during the oxidative phase of themetabolic cycle as described by [12]. Conversely, weobserve essentially no variation in growth in cultures synchronouslyundergoing the cell division cycle, which has been shown to primarilyoccupy the reductive phase of the metabolic cycle [32]. (A) In cellsundergoing metabolic cycling, growth rates are predicted to peak duringthe oxidative phase of the cycle, where [12] also observesstrong upregulation of translational and ribosomal genes. (B) Thepredicted growth rate for the [13]alpha-factor synchronized cell cycle is essentially constant, after aninitial release from the synchronization block. (C) Predicted rates forthe [8] alpha-factor synchronized cell cyclealso show an initial resumption of growth after alpha-factor blockfollowed by relatively constant growth rate. Taken together, theseobservations support the claim that growth rate regulation is notspecific to any one cell cycle phase. This also agrees with the factthat rapidly growing (and thus fermenting) S.cerevisiae does not partition metabolism into discrete stages,a phenomenon only occurring when reductive metabolism is hindered bynutrient limitation or other stresses.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2599889&req=5

pcbi-1000257-g007: Differences in growth characteristics of a metabolically cyclingculture compared to cells synchronously undergoing the cell divisioncycle.We predict periodic bursts of growth during the oxidative phase of themetabolic cycle as described by [12]. Conversely, weobserve essentially no variation in growth in cultures synchronouslyundergoing the cell division cycle, which has been shown to primarilyoccupy the reductive phase of the metabolic cycle [32]. (A) In cellsundergoing metabolic cycling, growth rates are predicted to peak duringthe oxidative phase of the cycle, where [12] also observesstrong upregulation of translational and ribosomal genes. (B) Thepredicted growth rate for the [13]alpha-factor synchronized cell cycle is essentially constant, after aninitial release from the synchronization block. (C) Predicted rates forthe [8] alpha-factor synchronized cell cyclealso show an initial resumption of growth after alpha-factor blockfollowed by relatively constant growth rate. Taken together, theseobservations support the claim that growth rate regulation is notspecific to any one cell cycle phase. This also agrees with the factthat rapidly growing (and thus fermenting) S.cerevisiae does not partition metabolism into discrete stages,a phenomenon only occurring when reductive metabolism is hindered bynutrient limitation or other stresses.
Mentions: Growth rate prediction applied to the yeast metabolic cycle data revealed astriking periodicity (Figure7A). The cyclical pattern of growth rate variation occurs completely inconcert with the metabolic cycle as defined by Tu et al. Specifically, theculture's growth rate is predicted to be at minima during the reductivephase of the metabolic cycle, when oxygen consumption is at a minimum, and reachmaxima during the peak of the oxidative phases when oxygen consumption ismaximal. In contrast, growth rate prediction for the cell cycle (Figure 7B and 7C) showvirtually no variation in predicted growth rate during the different stages ofcell division.

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