Supplementary Materials - Nature Research · Ignacio A. Zuleta1,2, Andrés Aranda-Díaz1,2, Hao Li1-3, Hana El-Samad1-3 1 Department of Biochemistry and Biophysics, University of

Dynamic Characterization of Growth and Gene Expression Using High-throughput Automated Flow cytometry

Ignacio A. Zuleta1,2, Andrés Aranda-Díaz1,2, Hao Li1-3, Hana El-Samad1-3

Supplementary Materials 1Department of Biochemistry and Biophysics, University of California, San Francisco, CA.

2The California Institute for Quantitative Biosciences, San Francisco, CA.

3Correspondence to:

Hana El-Samad [email protected] Hao Li [email protected]

Nature Methods: doi:10.1038/nmeth.2879

Supplementary Figures

Supplementary Figure 1 Serial liquid transfer scheme and reproducibility for step input stimulus-response experiments. (a) Different media are used to dilute a culture of fixed volume (VC) at different stages in the experiment. Before the start of the experiment (t<t0), outgrowth growth media (i) with no stimulus is used for dilution by adding and removing a fixed volume of sample (Vs). (ii) Growth media containing a d1-times concentrated dose of stimulus is used to bring its concentration to nominal value at the start of the experiment (t = t0). At later times (t>t0), Growth media with nominal stimulus concentration (iii) is used for dilution during the response stage of the experiment. The cell culture is constantly diluted and sampled (iv), d2 being the effective dilution taking place at every timepoint. Finally, every sample is also diluted before injection into the flow cytometer (v) d3-fold by adding the sample to a pre-dispensed (VB) amount of buffer. (b) Fluorescence of p4XUPRE-GFP reporter for the first timepoint in our timecourse for all 96-wells (left) and average cell division rate (right) during the outgrowth phase measured using 5 timepoints. (c) Day-to-day variability of measurement of fluorescence of our p4XUPRE-GFP reporter (left) and relative cell number (right) during treatment of cells with 5μg/mL of tunicamycin. (d) Distribution of fluorescence of two adjoining samples, where the well containing cells with no treatment (brown) is measured after measuring a well with cells treated with 5μg/mL of tunicamycin (red), showing that no high fluorescent cells are carried over between wells.

0X d1X 1X

stimulusmedia

replacementmedia

outgrowthmedia

culture plate sample plate

VS

VS

VC VB

d1 = (VS+VC)/VS

(concentration ofstimulus spike)

(dilution rate forevery timepoint)

(dilution rate forsampling)

d2 = VC/(VS+VC) d3 = VS/(VS+VB)

i ii ivv

iii

t<t0t0 t>t0time

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well #13, timepoint 20well #12, timepoint 20


Supplementary Figure 2 Side-scatter is linearly dependent on cell-volume. (a) Sample forward (FSC) and side scatter (SSC) distributions for Saccharomyces cerevisiae cells measured using flow cytometry. (b) Microscopy-based average volume for sub-populations sorted based on forward scatter values (blue) across a population (green, histogram).

Supplementary Figure 3 Structure of measured growth phenotypes in liquid media. (a) Representative automated colony forming units (CFU) measurements from plating a 50 μL sample from our automated flow cytometry setup. (b) Computed effective growth curves using cell viability assay. (c) Computed growth curves using our automated flow cytometry setup.

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4Colony counting assay Flow cytometer

Automated colonycounting


Supplementary Figure 4 Protein synthesis rate of constitutive gene TDH3. Expression rate of mKate2 driven by the promoter of gene TDH3 for different doses of tunicamycin (biological repeat of Fig. 2f) with a starting OD of 0.12. Figure 2f data was collected for an initial OD of 0.26.

Supplementary Figure 5 Differential co-culture experiment to measure protein degradation. (a) Cell division rate (top) and volume growth rate (bottom) for two competing strains in the same culture with (left) and without (right) a degradable GFP allele. These strains are identical in terms of their growth, highlighting the reproducibility of our measurements. (b) Degradation rate dependence on abundance of the substrate for different levels of stress (each trace is a temporal trajectory) in the presence (right) and absence (left) of pathway activation via estradiol (E2).

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mK2pTDH3

*= Ub-Tyr-

0 μg/mL Tm

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Supplementary Figure 6 Cell number and volume growth rates in two-dimensional dose response. Average cell division rate (top), cell volume growth rate (center) and total growth rate (bottom) for combinations of tunicamycin (Tm) and estradiol (E2).

Supplementary Figure 7 Population dynamics for different levels of stress. Distribution of raw fluorescence for reporters (a) p4XUPRE-GFP and (b) pTDH3-mKate2 as a function of time, for each dose of tunicamycin. Distribution of (c) forward-scatter and (d) side-scatter as a function of time, for each dose of tunicamycin. Fluorescence of reporters (e) p4XUPRE-GFP and (f) pTDH3-mKate2 corrected by dividing by side-scatter as a function of time.

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Supplementary Figure 8 Population dynamics for different levels of UPR overexpression. Distribution of raw fluorescence for reporters (a) p4XUPRE-GFP and (b) pTDH3-mKate2 as a function of time for each dose of estradiol. Distribution of forward-scatter (c) and side-scatter (d) as a function of time for each dose of estradiol. Fluorescence of reporters (e) p4XUPRE-GFP and (f) pTDH3-mKate2 corrected by dividing by side-scatter as a function of time.

Supplementary Figure 9 Single-cell fluorescence distributions centered at the same mean (in different experimental conditions) can have different structures. Normalized fluorescence of p4XUPRE-GFP distribution for conditions with similar means at a given timepoint (4.7 hours) in a 2D dose-response. The mean for these conditions is indicated with a dot in the x-axis.

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Supplementary Figure 10 CV2 versus mean for stable and unstable GFP for different levels of stress and UPR overexpression. Squared coefficient of variation of p4XUPRE fluorescence as a function of mean for the stable GFP (blue) and unstable GFP (red) for different doses of (a) tunicamycin (Tm) and (b) estradiol (E2). (c) Whole (orange) and subset (purple) of the cell population used to compute CV2 and mean.

Supplementary Figure 11 Single-cell fluorescence distributions centered at the same mean (at different points in time) can have different structures. Normalized fluorescence distribution for timepoints with similar means at a given condition (0.3125 μg/mL tunicamycin), taken at 5 hours (blue) and 10 hours (red).

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Supplementary Figure 12 Global noise landscape is dominated by two distinct regimes. Joint distribution of CV2 and mean of fluorescence of p4XUPRE-GFP for all data in the experiment.

Supplementary Figure 13 Noise structure as a function of scatter parameters. Distribution of CV2 of p4XUPRE-GFP as a function of side- and forward-scatter for all doses of tunicamycin and estradiol at 6.6 hours after the start of the experiment.

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Supplementary Figure 14 Noise structure as a function of mean fluorescence. CV2 as a function of mean fluorescence of p4XUPRE-GFP for all doses of tunicamycin and estradiol at 6.6 hours after the start of the experiment.

Supplementary Figure 15 Fluorescence timecourse of stress reporters. Fluorescence of reporters of (a) UPR stress (Hac1 and Ire1 activity), (b) general stress (Msn2/4 activity), (c) heat-shock (Hsf1 activity) and (d) high-osmolarity (Hog1 activity) for no treatment (left), UPR activation with estradiol (center) and ER stress (right).

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Supplementary Note Derivation of the Fluorescent Protein Turnover Equation

Our derivation is based on the basic assumption that the observed abundance of GFP at any given point in time is the balance of all its sources and sinks. In our framework, these include the rate at which protein production processes (folding, synthesis, transcription, etc.) produce detectable reporter, and the rates at which the reporter decreases through cell growth/division or degradation. Although the relationship between steady-state exponential growth and gene expression in terms of regulation1–5 and the tradeoffs6–8 associated with the cost of gene expression have been discussed, this major effect of growth dynamics in reporter levels has only been explored in the context of LacZ promoter fusions9.

We have derived two expressions, one for the rate of protein synthesis per cell and one for the rate of protein synthesis per unit volume, which can incorporate volume information as well.

For our first expression, we start with an expression for the total rate of change of fluorescence in the culture:

dd

Where αtotal(t) and βtotal(t) are the total instantaneous protein synthesis and degradation rates respectively. Since Ftotal = ∑Fcell (where Fcell is the fluorescence measurement in single cells), then

dd

dd

If Fvolume is the fluorescence per unit volume and Vcell is the volume of a cell, then Fcell = Fvolume×Vcell

and consequently:

dd

dd

dd

⟨ ⟩

where ⟨ ⟩ indicates average, and N is the total number of cells. This equation can be re-written as

dd

dd

⟨ ⟩dd⟨ ⟩

Since

⟨ ⟩ ⟨ ⟩ ⟨ ⟩ cov ,

and under the assumption that the main contribution to the volume change is through the cell cycle and that reporter protein concentration is not cell cycle dependent, the covariance can be ignored, that is

cov , 0

then


dd

dd

⟨ ⟩ ⟨ ⟩dd

⟨ ⟩ ⟨ ⟩

We then divide both sides by N

dd

1 dlogd

⟨ ⟩ ⟨ ⟩dd

⟨ ⟩ ⟨ ⟩

Differentiating the second term on the right hand side gives:

dd

1 dlogd

⟨ ⟩ ⟨ ⟩d⟨ ⟩

d⟨ ⟩ ⟨ ⟩

dd⟨ ⟩

Dividing both sides by ⟨Vcell⟩ gives:

dd

1⟨ ⟩

dlogd

⟨ ⟩d⟨ ⟩

d⟨ ⟩

dlogd

Substituting (1) into (7) yields:

,dlogd

⟨ ⟩d⟨ ⟩

d⟨ ⟩

dlogd

8

Where

⟨ ⟩

and

β F, tβ F, tN⟨V ⟩

.

Solving (8) for d⟨Fvolume⟩/dt yields the protein turnover or gene expression equation:

d⟨ ⟩

d, ⟨ ⟩ 9

Where Fvolume is the mean fluorescence per unit volume, αvolume and βvolume are the protein synthesis and degradation rates per unit volume, γ(t) = dlogN/dt and θ(t) = dlog⟨Vcell⟩/dt. Similarly, an expression relating the total cell fluorescence with the synthesis and degradation rates per cell can be derived and is used in most of our calculations:

d⟨ ⟩

d, ⟨ ⟩

where

and

,,

This simple model computes an estimate of the rate of appearance of detectable florescent protein. This rate


is an aggregate of all processes from transcription to fluorophore maturation. This could be used as a surrogate for protein production rate if the folding rate of the fluorophore is constant across our experiments.

Degradation flux expression

We derived an expression for the difference in degradation flux by subtracting two protein turnover expressions (9):

d⟨ , ⟩

d , , , θ γ ⟨ , ⟩

d⟨ , ⟩

d, , ,

⟨ , ⟩

After subtracting (11) from (12) we get:

d⟨ , ⟩

dd⟨ , ⟩

d, , , ,

⟨ , ⟩ ⟨ , ⟩ 13

Which, after rearrangement, yields an expression for the instantaneous relative degradation flux per unit volume:

∆ ∆d⟨ ⟩

d Δ⟨ ⟩

Where

∆ , , , , ,

∆⟨ ⟩ ⟨ , ⟩ ⟨ , ⟩

and

Δ⟨ ⟩ ⟨ , ⟩ ⟨ , ⟩.

Similarly, an expression for the instantaneous degradation per cell can be derived if the same derivation is carried over subtracting two protein turnover expressions (10):

∆ ∆d⟨ ⟩

d Δ⟨ ⟩ 15


1. Brauer, M. J. et al. Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast. Mol. Biol. Cell 19, 352–67 (2008).

2. Zurita-Martinez, S. A. & Cardenas, M. E. Tor and cyclic AMP-protein kinase A: two parallel pathways regulating expression of genes required for cell growth. Eukaryot. Cell 4, 63–71 (2005).

3. Jorgensen, P. et al. A dynamic transcriptional network communicates growth potential to ribosome synthesis and critical cell size. Genes Dev. 18, 2491–505 (2004).

4. Lu, C., Brauer, M. J. & Botstein, D. Slow growth induces heat-shock resistance in normal and respiratory-deficient yeast. Mol. Biol. Cell 20, 891–903 (2009).

5. Regenberg, B. et al. Growth-rate regulated genes have profound impact on interpretation of transcriptome profiling in Saccharomyces cerevisiae. Genome Biol. 7, R107 (2006).

6. Scott, M., Gunderson, C. W., Mateescu, E. M., Zhang, Z. & Hwa, T. Interdependence of cell growth and gene expression: origins and consequences. Science 330, 1099–102 (2010).

7. Lang, G. I., Murray, A. W. & Botstein, D. The cost of gene expression underlies a fitness trade-off in yeast. Proc. Natl. Acad. Sci. U. S. A. 106, 5755–60 (2009).

8. Klumpp, S., Zhang, Z. & Hwa, T. Growth rate-dependent global effects on gene expression in bacteria. Cell 139, 1366–75 (2009).

9. Warner, J. B. & Lolkema, J. S. LacZ-promoter fusions: the effect of growth. Microbiology 148, 1241–3 (2002).


Supplementary Tables

Supplementary Table 1: Strains used in this study

Name Background Description YPD Growth Rate (h-1)

HES-2.27 w303a pNH604 pGAL1-HAC1i::TRP1; pRS306 pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]::URA3; pNH605 p[4XUPRE]CYC1->Ub-Tyr-GFP::LEU2

0.80±0.04

HES-9.51 w303a pNH604 pGAL1- HAC1i::TRP1; pRS306 pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]::URA3; pNH605 p[4XUPRE]CYC1->GFP::LEU2; pTDH3->mKate2-HIS3::CAN1

0.79±0.04

HES-2.13 w303a pNH604 pGAL1-HAC1i::TRP1; pRS306 pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]::URA3; pNH605 pSSA1->GFP::LEU2

N/A

HES-2.14 w303a pNH604 pGAL1-HAC1i::TRP1; pRS306 pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]::URA3; pNH605 pHSP12->GFP::LEU2

N/A

HES-2.15 w303a pNH604 pGAL1-HAC1i::TRP1; pRS306 pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]::URA3; pNH605 pHSP82->GFP::LEU2

N/A

HES-2.16 w303a pNH604 pGAL1-HAC1i::TRP1; pRS306 pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]::URA3; pNH605 pHOR2->GFP::LEU2

N/A

HES-2.17 w303a pNH604 pGAL1-HAC1i::TRP1; pRS306 pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]::URA3; pNH605 pGPD1->GFP::LEU2

N/A

HES-2.18 w303a pNH604 pGAL1-HAC1i::TRP1; pRS306 pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]::URA3; pNH605 pERO1->GFP::LEU2

N/A

HES-2.26 w303a pNH604 pGAL1-HAC1i::TRP1; pRS306 pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]::URA3; pHAC1->5'HAC1-GFP-3'HAC1 (Splicing Reporter)::LEU2

N/A


Supplementary Table 2: Plasmids used in this study

Name Backbone (Marker) Description

pPW2085 pNH604 (TRP1) pGAL1-HAC1i

pPW2078 pRS306 (URA3) pADH1(tet)->GAL4[DBD]-ER[LBD]-MSN2[AD]

pPW2081 pNH605 (LEU2) p[4XUPRE]CYC1->Ub-Tyr-GFP

pAAD53 pNH605 (LEU2) p[4XUPRE]CYC1->GFP

pAAD39 pAAD33 (HIS3) pTDH3->mKate2-HIS3CA

pAAD7 pNH605 (LEU2) pSSA1->GFP

pAAD8 pNH605 (LEU2) pHSP12->GFP

pAAD9 pNH605 (LEU2) pHSP82->GFP

pAAD10 pNH605 (LEU2) pHOR2->GFP

pAAD11 pNH605 (LEU2) pGPD1->GFP

pAAD12 pNH605 (LEU2) pERO1->GFP

pPW2339 pRS305 (LEU2) pHAC1->5'HAC1-GFP-3'HAC1 (Splicing Reporter)

Supplementary Table 3: Oligonucleotides used in this study

Name Description Sequence oAAD17 [KpnI-

PspOMI]4XUPRE Fwd GGAAGGTACCAAGGAAGGGCCCTGCCACCTGACGTCTAAGA

oAAD18 [NotI]4XUPRE Rev GGAAGCGGCCGCCGGATCTGGTCGAGCTT

oAAD149 [PspOMI]pCYC1 Fwd GGAAGGGCCCCATATGGCATGCATGTGCTC

oAAD150 [XhoI]pCYC1 Rev GGAACTCGAGTGTGTGTATTTGTGTTTGTGTGT oAAD290 [Can1]pAAD33 Fwd ATCTAAGGATAAAAACGAAGGGAGGTTCTTAGGTTGGG

GGACCAATCAAGCAATTCAGAA oAAD291 [Can1]pAAD33 Rev TGAAATGTGAAGGCAGCGTTAATCAAAGAGGAAAC

GACATGGAGGCCCAGAATAC


Documents

Supplementary Materials - Nature Research · Ignacio A. Zuleta1,2, Andrés Aranda-Díaz1,2, Hao Li1-3, Hana El-Samad1-3 1 Department of Biochemistry and Biophysics, University of