Single Cell Variability

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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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Why Single Cells? One Example
?
?
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Why Single Cells? One Example
Gaussian
Bimodal
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Why Single Cells? One Example
Gaussian

Bimodal
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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 s/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
Cells imbedded in soft agar
Kelly Rahn, J. Bacteriol., 1932
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Extrinsic Noise cell growth
Light Source
Air tank
vent
hv
Pump
Environmental Chamber
Reservoir
Lung (50ft tubing)
Objective
Waste
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Extrinsic Noise
LSM Data
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Extrinsic Noise
Single Cell Growth over Time
Strovas et al. In preparation.
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Extrinsic Noise
Single Cell Growth over Time
0.73 mm/hr
0.55mm/hr
Strovas et al. In preparation.
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Extrinsic Noise
Methanol
Succinate
3.73 /- 0.63 hrs (N 195)
3.12 /- 0.55 hrs (N 115)

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

Strovas et al. In preparation.
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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
Promoter Activities via Transcriptional Fusions
light
Plac
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Intrinsic Noise - Transcription
http//meds.queensu.ca/mbio318/EXTRA_MATERIAL.htm
l
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Intrinsic Noise - Transcription
http//meds.queensu.ca/mbio318/EXTRA_MATERIAL.htm
l
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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 Noise
Fluorescence vs. Growth rate
Methanol
Succinate
R2 0.0257
R2 0.0049
Strovas et al. In preparation.
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Intrinsic Noise
Succinate - Methanol Carbon Shift
Succinate 1993.15 /- 468.14 RFU/mm2 (N
1000) Methanol 3075.30 /- 243.35 RFU/mm2 (N
1000)
Strovas et al. In preparation.
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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, cant 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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Nifty stuff Raser and Shea

• 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

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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