Single-cell protein dynamics reproduce universal fluctuations in cell populations

Brenner, Naama; Braun, Erez; Yoney, Anna; Susman, Lee; Rotella, James; Salman, Hanna

doi:10.1140/epje/i2015-15102-8

Cited by 51 publications

(96 citation statements)

References 36 publications

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“…In addition to the work presented here Brenner et al (13,14) have shown other ordered processes (growth and division) can generate universal statistical distributions for protein copy numbers in populations (13) and individual microorganisms (14). The ordered recursive nature of growth and division has shared mathematical roots and structure with the ordered mechanical arrest process presented.…”

Section: Discussionsupporting

confidence: 52%

Mechanical bounds to transcriptional noise

Sevier

Kessler

Levine

2016

Proc. Natl. Acad. Sci. U.S.A.

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Over the past several decades it has been increasingly recognized that stochastic processes play a central role in transcription. Although many stochastic effects have been explained, the source of transcriptional bursting (one of the most well-known sources of stochasticity) has continued to evade understanding. Recent results have pointed to mechanical feedback as the source of transcriptional bursting, but a reconciliation of this perspective with preexisting views of transcriptional regulation is lacking. In this article, we present a simple phenomenological model that is able to incorporate the traditional view of gene expression within a framework with mechanical limits to transcription. By introducing a simple competition between mechanical arrest and relaxation copy number probability distributions collapse onto a shared universal curve under shifting and rescaling and a lower limit of intrinsic noise for any mean expression level is found.transcription | supercoiling | topoisomerase | bursting noise T he ability to watch biological phenomena play out at the single-molecule level has revealed a rich and nuanced view of the central dogma of biology. From the single-molecule vantage it has become clear that random forces and events play a key role in transcription (1), although how important expression noise is for crucial biological functions is a matter of debate. The identification of transcriptional bursting, in which genes undergo periods of paused activity even in fully induced environments in both prokaryotes and eukaryotes (2, 3), has been one of the most notable examples of this new perspective. Bursting has also figured prominently in the discussion concerning universal properties of transcriptional noise (4). In particular, a number of recent experimental results have found a link between the rate and randomness of mRNA production whereby highly expressed genes have increased noise associated with production (4). This result transcends specific organisms or genes and may be explained if expression inevitably exhibits bursting. Other work, however, has argued that under some conditions there are nonuniversal gene-specific relationships between the rate and randomness of mRNA production (5); these results are more consistent with the pure model of transcription regulated by the binding of specific regulatory proteins to the promoter regions, in which high expression is not necessarily associated with high noise.What is needed is a framework that is able to accommodate the traditional "promoter architecture" view of transcription while at the same time capturing recently observed universal aspects of bursting. To accomplish this, we start from the "twin-supercoiling domain" (6) model of transcription wherein the helical nature of DNA combined with topological obstructions leads to the accumulation of mechanical strain in DNA during transcription. This strain can result in arrested gene expression. Specific biological machinery (topoisomerases) must relieve the strain created by transcription throug...

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Section: Discussionsupporting

confidence: 52%

Mechanical bounds to transcriptional noise

Sevier

Kessler

Levine

2016

Proc. Natl. Acad. Sci. U.S.A.

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“…• Protein number increases as e kit during the i th generation, where the exponential growth rate k i fluctuates with i [8].…”

Section: Model Without Feedbackmentioning

confidence: 99%

“…2a. The data points were collected from six individual trajectories normalized to unit average (data from [8]). In agreement with Eq.…”

Section: Comparison With Datamentioning

confidence: 99%

“…A recent study following the protein content in individual E. coli bacteria over roughly 70 generations has revealed that, under the same scaling criteria, the shape of the distribution of protein copy number sampled over time in an individual converges to the one observed in large populations [8]. While analogous temporal data are currently unavailable for yeast, this is an important property that reflects the ergodicity of the relative fluctuations in protein expression in bacteria.…”

Section: Introductionmentioning

confidence: 98%

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Universal protein distributions in a model of cell growth and division

Brenner¹,

Newman²,

Osmanović³

et al. 2015

Phys. Rev. E

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Protein distributions measured under a broad set of conditions in bacteria and yeast were shown to exhibit a common skewed shape, with variances depending quadratically on means. For bacteria these properties were reproduced by temporal measurements of protein content, showing accumulation and division across generations. Here we present a stochastic growth-and-division model with feedback which captures these observed properties. The limiting copy number distribution is calculated exactly, and a single parameter is found to determine the distribution shape and the variance-to-mean relation. Estimating this parameter from bacterial temporal data reproduces the measured distribution shape with high accuracy, and leads to predictions for future experiments.

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“…These include bacteria [7][8][9][10], budding yeast [10][11][12][13][14] and mammalian cells [10,15]. Moreover, the mRNA and protein numbers are on average proportional to the cell volume throughout the cell cycle [16][17][18][19][20]. Therefore, the homeostasis of mRNA concentration and protein concentration is maintained in an exponentially growing cell volume.…”

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confidence: 99%

Homeostasis of protein and mRNA concentrations in growing cells

Lin

Amir

2018

Preprint

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Many experiments show that the concentrations of protein and mRNA fluctuate but on average are constant in growing cells, independent of the genome copy number. However, models of stochastic gene expression often assume constant gene expression rates that are proportional to the gene copy numbers, which are therefore incompatible with experiments. Here, we construct a minimal gene expression model to fill this gap. We show that (1) because the ribosomes translate all proteins, the concentrations of proteins are regulated in an exponentially growing cell volume; (2) the competition between genes for the RNA polymerases makes the gene expression rate independent of the genome number; (3) the fluctuations in ribosome level and cell density can generate a global extrinsic noise in protein concentrations; (4) correlations between mRNA and protein levels can be quantified.Despite the noisy nature of gene expression [1][2][3][4][5][6], various aspects of single cell dynamics, such as volume growth, are effectively deterministic. Recent single-cell measurements show that the growth of cell volumes is often exponential. These include bacteria [7][8][9][10], budding yeast [10][11][12][13][14] and mammalian cells [10,15]. Moreover, the mRNA and protein numbers are on average proportional to the cell volume throughout the cell cycle [16][17][18][19][20]. Therefore, the homeostasis of mRNA concentration and protein concentration is maintained in an exponentially growing cell volume. The exponential growths of mRNA and protein number indicate dynamical transcription and translation rates proportional to the cell volume, and also independent of the genome copy number. However, current gene expression models often assume a fixed cell volume with constant transcription and translation rates [1,5,[21][22][23], which are proportional to the gene copy number. Therefore, fixed cell volume models fail to reveal how cells keep constant mRNA and protein concentrations as the cell volume grows and the genome is replicated.The homeostasis of protein and mRNA concentrations imply that there must be a regulatory mechanism in place to prevent the accumulation of noise over time and to maintain a bounded distribution of concentrations. The goal of this work is to identify such a mechanism by developing a genome-wide coarse-grained model taking into account explicitly cell volume growth. We will consider an idealized cell in which genes are constitutively expressed for simplicity. The ubiquity of homeostasis suggests that the global machineries of gene expression, RNA polymerases (RNAPs) and ribosomes, should play a central role within the model. Indeed, as we will show later, the exponential growth of cell volume, protein and mRNA number originates from the auto-catalytic nature of ribosomes, the limiting factor in the translational process [24][25][26]. The bounded distributions of concentrations are a result of the fact that ribosomes make all proteins. The independence of the mRNA concentration of the genome copy number is a natural resul...

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Single-cell protein dynamics reproduce universal fluctuations in cell populations

Cited by 51 publications

References 36 publications

Mechanical bounds to transcriptional noise

Mechanical bounds to transcriptional noise

Universal protein distributions in a model of cell growth and division

Homeostasis of protein and mRNA concentrations in growing cells

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