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The volumes and transcript counts of single cells reveal concentration homeostasis and capture biological noise.

Kempe H, Schwabe A, Crémazy F, Verschure PJ, Bruggeman FJ - Mol. Biol. Cell (2014)

Bottom Line: Cell-to-cell variability is best captured in terms of concentration rather than molecule counts, because reaction rates depend on concentrations.We compared three cell clones that differ only in the genomic integration site of an identical constitutively expressed reporter gene.This study highlights the importance of the quantitative measurement of transcript concentrations in studies of cell-to-cell variability in biology.

View Article: PubMed Central - PubMed

Affiliation: Synthetic Systems Biology and Nuclear Organization Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 XH Amsterdam, The Netherlands.

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Statistics of single-cell mRNA concentrations. (A) The previously obtained mRNA number (Figure 1) and volume data (Figure 2) were used to determine the concentration of mRNA in single cells (c), in their nuclei (cN), and in their cytoplasm (cc). (B) Statistics of the different mRNA concentrations for the three different clones (color coded). Notation: μ = mean; σ = SD; cv = coefficient of variation; Δσ = the fraction of samples between μ – σ and μ + σ; ρ = correlation between mc and mN; and *p < 0.001 (H0: ρ = 0). The 95% confidence intervals of the statistics are given in Supplemental Figure S15. (C) For a specific cell volume (V), the mean mRNA concentration (〈c/V〉) is calculated. This conditional mean is constant with respect to volume. The gray histogram in the background shows the number of cells considered per volume bin (bin size = 100 μm3). Higher counts indicate higher reliability of the corresponding determination of A least-squares linear fit is shown for all three clones, indicating mRNA concentration homeostasis. The conditional variances of the data set are shown in Supplemental Figure S10. (D–F) Scatter plots of (cN) and (cc) for the three different clones. Marginal histograms show the distribution of (cc) (top) and (cN) (right). The given concentration (number per cubic micrometer) can be converted to picomoles (pM) by multiplying with a conversion factor of 1660. The sample size is given by n. The bin size for the marginal histograms is 0.001 #/μm3.
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Figure 3: Statistics of single-cell mRNA concentrations. (A) The previously obtained mRNA number (Figure 1) and volume data (Figure 2) were used to determine the concentration of mRNA in single cells (c), in their nuclei (cN), and in their cytoplasm (cc). (B) Statistics of the different mRNA concentrations for the three different clones (color coded). Notation: μ = mean; σ = SD; cv = coefficient of variation; Δσ = the fraction of samples between μ – σ and μ + σ; ρ = correlation between mc and mN; and *p < 0.001 (H0: ρ = 0). The 95% confidence intervals of the statistics are given in Supplemental Figure S15. (C) For a specific cell volume (V), the mean mRNA concentration (〈c/V〉) is calculated. This conditional mean is constant with respect to volume. The gray histogram in the background shows the number of cells considered per volume bin (bin size = 100 μm3). Higher counts indicate higher reliability of the corresponding determination of A least-squares linear fit is shown for all three clones, indicating mRNA concentration homeostasis. The conditional variances of the data set are shown in Supplemental Figure S10. (D–F) Scatter plots of (cN) and (cc) for the three different clones. Marginal histograms show the distribution of (cc) (top) and (cN) (right). The given concentration (number per cubic micrometer) can be converted to picomoles (pM) by multiplying with a conversion factor of 1660. The sample size is given by n. The bin size for the marginal histograms is 0.001 #/μm3.

Mentions: Next we combined the mRNA number and volume data of each cell to determine the statistics of cellular, cytoplasmic, and nuclear mRNA concentrations (Figure 3A). Figure 3B shows that the mean mRNA concentration differs among the three clones, indicating the dependence of expression levels on the gene location (Supplemental Information 2). Scaling of the mean and SD are independent. We observe higher mRNA concentrations in the cytoplasm than in the nucleus. Similar conclusions can be drawn from the mRNA numbers.


The volumes and transcript counts of single cells reveal concentration homeostasis and capture biological noise.

Kempe H, Schwabe A, Crémazy F, Verschure PJ, Bruggeman FJ - Mol. Biol. Cell (2014)

Statistics of single-cell mRNA concentrations. (A) The previously obtained mRNA number (Figure 1) and volume data (Figure 2) were used to determine the concentration of mRNA in single cells (c), in their nuclei (cN), and in their cytoplasm (cc). (B) Statistics of the different mRNA concentrations for the three different clones (color coded). Notation: μ = mean; σ = SD; cv = coefficient of variation; Δσ = the fraction of samples between μ – σ and μ + σ; ρ = correlation between mc and mN; and *p < 0.001 (H0: ρ = 0). The 95% confidence intervals of the statistics are given in Supplemental Figure S15. (C) For a specific cell volume (V), the mean mRNA concentration (〈c/V〉) is calculated. This conditional mean is constant with respect to volume. The gray histogram in the background shows the number of cells considered per volume bin (bin size = 100 μm3). Higher counts indicate higher reliability of the corresponding determination of A least-squares linear fit is shown for all three clones, indicating mRNA concentration homeostasis. The conditional variances of the data set are shown in Supplemental Figure S10. (D–F) Scatter plots of (cN) and (cc) for the three different clones. Marginal histograms show the distribution of (cc) (top) and (cN) (right). The given concentration (number per cubic micrometer) can be converted to picomoles (pM) by multiplying with a conversion factor of 1660. The sample size is given by n. The bin size for the marginal histograms is 0.001 #/μm3.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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Figure 3: Statistics of single-cell mRNA concentrations. (A) The previously obtained mRNA number (Figure 1) and volume data (Figure 2) were used to determine the concentration of mRNA in single cells (c), in their nuclei (cN), and in their cytoplasm (cc). (B) Statistics of the different mRNA concentrations for the three different clones (color coded). Notation: μ = mean; σ = SD; cv = coefficient of variation; Δσ = the fraction of samples between μ – σ and μ + σ; ρ = correlation between mc and mN; and *p < 0.001 (H0: ρ = 0). The 95% confidence intervals of the statistics are given in Supplemental Figure S15. (C) For a specific cell volume (V), the mean mRNA concentration (〈c/V〉) is calculated. This conditional mean is constant with respect to volume. The gray histogram in the background shows the number of cells considered per volume bin (bin size = 100 μm3). Higher counts indicate higher reliability of the corresponding determination of A least-squares linear fit is shown for all three clones, indicating mRNA concentration homeostasis. The conditional variances of the data set are shown in Supplemental Figure S10. (D–F) Scatter plots of (cN) and (cc) for the three different clones. Marginal histograms show the distribution of (cc) (top) and (cN) (right). The given concentration (number per cubic micrometer) can be converted to picomoles (pM) by multiplying with a conversion factor of 1660. The sample size is given by n. The bin size for the marginal histograms is 0.001 #/μm3.
Mentions: Next we combined the mRNA number and volume data of each cell to determine the statistics of cellular, cytoplasmic, and nuclear mRNA concentrations (Figure 3A). Figure 3B shows that the mean mRNA concentration differs among the three clones, indicating the dependence of expression levels on the gene location (Supplemental Information 2). Scaling of the mean and SD are independent. We observe higher mRNA concentrations in the cytoplasm than in the nucleus. Similar conclusions can be drawn from the mRNA numbers.

Bottom Line: Cell-to-cell variability is best captured in terms of concentration rather than molecule counts, because reaction rates depend on concentrations.We compared three cell clones that differ only in the genomic integration site of an identical constitutively expressed reporter gene.This study highlights the importance of the quantitative measurement of transcript concentrations in studies of cell-to-cell variability in biology.

View Article: PubMed Central - PubMed

Affiliation: Synthetic Systems Biology and Nuclear Organization Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 XH Amsterdam, The Netherlands.

Show MeSH