single cell variability the contribution of noise to biological systems
TRANSCRIPT
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Single Cell Variability
The contribution of noise to biological systems
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Outline
Background Why single cells? Noise in biological systems Cool studies Conclusions
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Background – Microscale Life Sciences Center
Funded by NIH CEGS To develop technologies for single cell
research Lab-on-a-chip modality Collaborative approach
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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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Intensity of Response
Potential Resonse Profiles for a Population
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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
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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.
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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.
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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
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Noise in biological systems
Intrinsic noise: Inherent Order of events Entropy Binding of substrate to enzyme
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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
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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
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Extrinsic Noise – cell growth
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*Kelly & Rahn, J. Bacteriol., 1932
Cells imbedded in soft agar
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Extrinsic Noise – cell growth
Reservoir Lung (50ft tubing)
EnvironmentalChamber
Waste
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Light Source
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Objective
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Extrinsic Noise
LSM Data
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Strovas et al. In preparation.
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Single Cell Growth over Time
Extrinsic Noise
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Single Cell Growth over Time
Strovas et al. In preparation.
0.55mm/hr 0.73 mm/hr
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
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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?
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Intrinsic Noise - Transcription
Px GFPuvPx GFPuvPx GFPuv
Promoter Activities via Transcriptional Fusions
light
Plac
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Intrinsic Noise - Transcription
http://meds.queensu.ca/~mbio318/EXTRA_MATERIAL.html
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Intrinsic Noise - Transcription
http://meds.queensu.ca/~mbio318/EXTRA_MATERIAL.html
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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
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Intrinsic Noise
Elowitz et al, Science, 297, 1183-1186, 2002
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Intrinsic NoiseFluorescence vs. Growth rate
Strovas et al. In preparation.
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Succinate Methanol
R2 = 0.0257 R2 = 0.0049
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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
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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
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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!
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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.
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Nifty stuff – Balaban et al.
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Nifty stuff – Balaban et al.
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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?
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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
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Nifty stuff – Raser and Shea
Time course during phosphate starvation
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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
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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