Single Cell Variability

The contribution of noise to biological systems

Outline

Background Why single cells? Noise in biological systems Cool studies Conclusions

Background – Microscale Life Sciences Center

Funded by NIH CEGS To develop technologies for single cell

research Lab-on-a-chip modality Collaborative approach

Why Single Cells?

Variable of interest Bulk data represents

averages Averages may not

represent behavior of subpopulations

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Singular Resonse50% response

Range of Response0

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Potential Resonse Profiles for a Population

Why Single Cells? – One Example

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Why Single Cells? – One Example

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Why Single Cells? – One Example

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Variability in populations – What we know so far

Population response is governed by: Variability at the single cell level Subpopulations Noise inherent to any complex system

Noise in biological systems

“Chemical analysis are affected by two types of noise: chemical noise and instrumental noise”*

What is chemical noise? What is instrument noise? In general: Noise = σ/mean

*Principals of Instrumental Analysis. 1998. Skoog, Holler, and Nieman.

Noise in biological systems

“Chemical analysis are affected by two types of noise: chemical noise and instrumental noise”*

What is chemical noise? Fluctuations in Temp, concentration,

vibrations, light, gradients, etc What is instrument noise?

Composite of noise from individual components of a system*Principals of Instrumental Analysis. 1998. Skoog, Holler, and Nieman.

Noise in biological systems

Noise in a nutshell Chemical noise = intrinsic (inherent) variability Instrument noise = extrinsic (global) variability

Will show examples from literature and my research

Noise in biological systems

Intrinsic noise: Inherent Order of events Entropy Binding of substrate to enzyme

Noise in biological systems

Extrinsic noise: Concentrations of system components

Regulatory proteins, polymerase Chemical flux through components

Enzyme activities Substrate to product conversion

Global effects of all components

Extrinsic Noise – cell growth

Global variability that is a composite of intrinsic noise from each component of a system.

First observed by Kelly and Rahn in 1932* Measured 2-3 fold variation in the division times

of single E. coli cells No correlation between division time of mother

cell and division time of either of the two daughter cells

*Kelly & Rahn, J. Bacteriol., 1932

Extrinsic Noise – cell growth

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*Kelly & Rahn, J. Bacteriol., 1932

Cells imbedded in soft agar

Extrinsic Noise – cell growth

Reservoir Lung (50ft tubing)

EnvironmentalChamber

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Extrinsic Noise

LSM Data

Strovas et al. In preparation.

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Strovas et al. In preparation.

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Extrinsic Noise

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Strovas et al. In preparation.

3.12 +/- 0.55 hrs (N = 115) 3.73 +/- 0.63 hrs (N = 195)

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Succinate Methanol

•Over 2 fold range in division rates•Extrinsic noise differs based on carbon source

Extrinsic Noise

Intrinsic Noise - Transcription

The noise inherent to a system component What are components of a biological system? Focus on noise in transcription

How does one measure transcription rates?

Intrinsic Noise - Transcription

Px GFPuvPx GFPuvPx GFPuv

Promoter Activities via Transcriptional Fusions

light

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Intrinsic Noise - Transcription

http://meds.queensu.ca/~mbio318/EXTRA_MATERIAL.html

Intrinsic Noise - Transcription

http://meds.queensu.ca/~mbio318/EXTRA_MATERIAL.html

Intrinsic Noise

Elowitz et al, 2002 Elegant experiment to show intrinsic noise Made two transcriptional fusions in E. coli:

Plac-YFP Plac-CFP

Observed YFP and CFP fluorescence w/ and w/out IPTG present

Intrinsic Noise

Elowitz et al, Science, 297, 1183-1186, 2002

Intrinsic NoiseFluorescence vs. Growth rate

Strovas et al. In preparation.

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R2 = 0.0257 R2 = 0.0049

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Succinate -> Methanol Carbon Shift

Succinate: 1993.15 +/- 468.14 RFU/mm^2 (N = ~1000)Methanol: 3075.30 +/- 243.35 RFU/mm^2 (N = ~1000)

Strovas et al. In preparation.

Intrinsic Noise

Noise in biological systems - Summary

Variability in biological systems at the population and single cell level is governed by intrinsic and extrinsic noise. Extrinsic noise dominates variability as a whole Intrinsic noise dominates the variability observed

from individual components of a system Intrinsic noise can be independent of extrinsic

noise

Now what?

Since noise in biological systems can govern biological variability, can’t we cure cancer and move on?

No! Like all complex systems we must characterize them!

What we know is just the tip of the iceberg!

Nifty stuff – Balaban et al.

Bacterial persistence as a phenotypic switch Balaban et al. 2004. Science. 305: 1622-1625

Demonstrated the ability of single cells from an E. coli clonal population to survive treatment with antibiotics.

Nifty stuff – Balaban et al.

Nifty stuff – Balaban et al.

Nifty stuff – Balaban et al.

Persister cells were susceptible to subsequent antibiotic treatment

Heterogeneity (variance) within the population attributed to presence of persisters

Why can persisters survive and how is it useful? What type of noise governs this response?

Nifty stuff – Raser and Shea

Control of stochasticity in eukaryotic gene expression Raser and Shea. 2004. Science. 304: 1811-1814

Used similar methods to Elowitz et al. only using yeast.

Suggests that noise is an evolvable trait that can help balance fidelity and diversity

Nifty stuff – Raser and Shea

Time course during phosphate starvation

Showed extrinsic noise dominates total noise in yeast

Intrinsic noise only contributed 2-20% Transcription in eukaryotes has been

described as pulsative Results in variable mRNA levels from cell to cell Causes phenotypic diversity in clonal yeast

populations

Nifty stuff – Raser and Shea

Conclusions

Population averages skew the underlying contributions of subpopulations

Subpopulations are the result of variable cellular response within a clonal population

Cellular variability arises from intrinsic noise, but governed by extrinsic noise

Cellular variability allows for adaptation to environmental perturbations