causes and consequences of phenotypic variability: a preliminary study of life & death of...
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Causes and consequences of phenotypic variability: a preliminary study of life & death of individual E. coli
The paradigm of genetics
Phenotype = Genotype Environment
… but is there any phenotypic variability when genotype and environment remain constant ?
In theory phenotypic variability could favour
Bet-hedging strategies in face of an uncertain future (Do not put all your genomes in one phenotypic basket, Balaban Science 2004)
Rapid epigenetic changes
(e.g. inherited through autocatalytic feedback loop)
Division of labour (including altruistic behavior)
(as the cells with identical genome maximize their inclusive fitness)
Classical sources of phenotypic variability
Environmental differencesGeographical
Temporal
Differences in the life cycle stages e.g new-born vs reproducing
Genetic differences caused by mutation recombination (Horizontal Transfer)
Is there other sources of variability of individual lifehistory when genotype and environment are constant ?
Measurement errors (minimized by repeated measures)
Epigenetic (non genetic heritability ?)
Aging (in a symetrically dividing organism?)
Stochastic sources quantitative (small numbers of big molecules) qualitative (error rates > 0)
Noise in gene expression is affected by genotype and environment
2 different fluorescent proteins controlled by identical promoters
Elowitz Science 2002
Life with small number of big molecules
DNA
RNA
Proteins
Mutations
aberrant RNA
aberrant proteins
10-9
10-4
10-5
Error rates
Functions
Cells
Functional degeneracy
cell death
Genes involved
mutS, mutT
mutT
gidA, mnmE
Maintenance ?
Functional fidelity ?
Strategies to maintain DNA integrity
Eliminate source of lesions
Physical protection
Template maintenance
Pool sanitization
Polymerase fidelity
Quality control
Strategies to maintain DNA integrity
• Eliminate source of lesions
• Physical protection
• Template maintenance
• Pool sanitization
• Polymerase fidelity
• Quality control
R
Preventing RNA infidelity• Transcription coupled repair (preferential repair of transcribed DNA strand)
• RNA polymerase fidelity (Blank Biochemistry 1986)
• alkB repair of alkylated mRNA, Aas Nature (2003)
• Release of ribosome facing truncated/damaged mRNA (tmRNA encoded by ssrA) Keller Science (1996)
• MutT sanitizes the ribonucleotide poolTaddei Science (1997)
DNA
mRNA
tRNA
relativeβ - galactivity
- T A G -- A T C -
- U A G -
S T O P
10-5
- G A G -- C T C -
- G A G -
- C U C -
1
. . .
Glu
- T A G -- A T C -
- C U C -. . .
Glu
- G A G -°
rGTP° rGTPOHRNA
polymerase
MutT
MutT controls transcription fidelityScience (1997) 278 128-130
lacZ-lacZ+Genotype
lacZ-
10-3
mutT+ mutT-
°
RNA polymerase incorporate 8-oxoG
GTP
8-oxo-GTP
UTP
8-oxo-GTP
GTP
Matrice ADN Matrice dA-dTGenomic DNA template
Poly dAdT template
Taddei Science 1997
8-oxo-G-ARN binding protein
Degradation?
G°
Translation
Erroneous Protein
8-oxo-G-RNA G°
TP
Oxydative Stress
RNA polymerase
8-oxo-G-ARN
direct oxidation of RNA
MutT
GTP Oxidation
G°
G°MP + PPiG°
RNA
RNA
Cause & consequences of 8-oxo-G in RNA
Consequences of RNA infidelity
• from a mutant gene may come transient function, leakiness
• from a wild-type gene may come a transient function loss
1 erroneous mRNA --> 40 erroneous protein
Non uniform distribution of erroneous proteins
Can transient transcription errors lead to phenotypic change that have long lasting consequences
> Transient mutators: wild-type bacteria that exhibit a mutator phenotype due to transcription/translation errors
Ninio suggests that a 1% subpopulation of cells is
transiently deficient for a protein involved in DNA fidelity
>How to capture and quantify transient events (via heritable consequences, epigenetic switch)
lac operon
• set of coordinately expressed genes under the negative control of lac repressor
• classical induction system: the active inducer is a product of one of the controlled enzymes
• lac repressor is a rare protein (~10-20)• transient depletion of repressor will lead to a
transient derepression of operon and to a burst of lacZYA gene expression
growth in low inducer level
high inducer
uninduced culture
Fully induced
Monod, ‘preinduction effect’ 1956
Fully induced
dilute single cells into maintenance inducer level
growth in maintenance inducer level
high inducer
β-galactosidase assays on ‘single-cell’ cultures
growth in maintenance inducer level
uninduced
induced
Novick & Weiner, 1957; maintenance
dilute single cells into maintenance inducer level
growth in maintenance inducer level
high inducer intermediate inducer
β-galactosidase assays on ‘single-cell’ cultures
growth in maintenance inducer level
uninduced cultures
induced mixed
Novick & Weiner, 1957; ‘all or none’
dilute single cells into maintenance inducer level
growth in maintenance inducer level
high inducer intermediate inducer
β-galactosidase assays on ‘single-cell’ cultures
growth in maintenance inducer level
uninduced cultures
induced mixed
Novick & Weiner, 1957; ‘all or none’
Monitoring phenotypic variability in cell lineages
Development of molecular tools, microfluidic, databases, image analysis, statistical tools, tweezers, microscopes
Time-lapse of a bacterial lineage
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Data available after image analysis
• >100 movies (E. Stewart)• > 100000 divisions
(R. Madden)• Morphometry :
– Length– Positions
• Exhaustive genealogies > 10 generations
For phenotype to depend only genotype and environment
One must take into account DNA extended environment
(intracellular environment is dynamic, ~ heritable & local)
Why change ?Population geneticsGodelle Gouyon Brown Maynard-Smith
Change where ?Microbial ecology Fons
Who changes ?Molecular epidemiologyBinguen Denamur Picard Brisabois Berche
A network approach of bacterial variability
GiraudLechatBambou
B. ToupanceO. TenaillonJ-B André
Duriez
Change what?Bio-informaticsRocha
Who has changed ?Molecular PhylogenyLecointre Darlu
How to change ? Molecular biology Matic Radman Vulic Dionisio BjedovBregeon Leroy Hayakawa Sekiguchi Dukan
Change when ?transcriptome analysis Knudsen Cerf
Phenotypic variabilityLife History Stewart Madden Lindner Paul Gabriel Fontaine Depaepe Bredèche Mosser
Why change ?Population geneticsGodelle Gouyon Brown Maynard-Smith
Change where ?Microbial ecology Fons
Who changes ?Molecular epidemiologyBinguen Denamur Picard Brisabois Berche
A network approach of bacterial variability
GiraudLechatBambou
B. ToupanceO. TenaillonJ-B André
Duriez
Change what?Bio-informaticsRocha
Who has changed ?Molecular PhylogenyLecointre Darlu
How to change ? Molecular biology Matic Radman Vulic Dionisio BjedovBregeon Leroy Hayakawa Sekiguchi Dukan
Change when ?transcriptome analysis Knudsen Cerf
Phenotypic variabilityLife History Stewart Madden Lindner Paul Gabriel Fontaine Depaepe Bredèche Mosser
www.necker.fr/tamara/
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