Single Cell Variability
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Transcript of Single Cell Variability
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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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
Waste
Air tank
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Light Source
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Extrinsic Noise
LSM Data
Strovas et al. In preparation.
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Single Cell Growth over Time
Extrinsic Noise
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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
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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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Growth Rate (mm/hr)
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Growth Rate (mm/hr)
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Succinate Methanol
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