Causes and consequences of phenotypic variability: a preliminary study of life & death of individual E. coli

1. Causes and consequences of phenotypic variability: a preliminary study of life & death of individual E. coli

2. The paradigm of genetics Phenotype = Genotype  Environment … but is there any phenotypic variability when genotype and environment remain constant ?

3. 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)

4. Classical sources of phenotypic variability • Environmental differences Geographical Temporal • Differences in the life cycle stages e.g new-born vs reproducing • Genetic differences caused by mutation recombination (Horizontal Transfer)

5. Is there other sources of variability of individual life history 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)

6. Noise in gene expression is affected by genotype and environment Life with small number of big molecules Elowitz Science 2002 2 different fluorescent proteins controlled by identical promoters

7. Genes involved Error rates 10-9 DNA Mutations mutS, mutT RNA 10-5 aberrant RNA mutT gidA, mnmE aberrant proteins Proteins 10-4 Functions Functional degeneracy Functional fidelity ? Cells cell death Maintenance ?

8. Strategies to maintain DNA integrity Eliminate source of lesions Physical protection Template maintenance Pool sanitization Polymerase fidelity Quality control

9. Strategies to maintain DNA integrity R • Eliminate source of lesions • Physical protection • Template maintenance • Pool sanitization • Polymerase fidelity • Quality control

10. 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 pool Taddei Science (1997)

12. MutT hydrolyses dG°TP & rG°TP Taddei Science 1997

13. RNA polymerase incorporate 8-oxoG Genomic DNA template Poly dAdT template Taddei Science 1997

14. Errors during transcription lead to protein oxidation Dukan PNAS 2000

15. Error in translation increase misfolding & protein oxidation Dukan PNAS 2000

16. Translation error as a limiting step for protein oxidation Dukan PNAS 2000

17. 8-oxo-G concentration increase in the brain during neuro-degeneration Nunomura J Neuroscience 1999

18. Cause & consequences of 8-oxo-G in RNA

19. 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

20. 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)

21. 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

22. Monod, ‘preinduction effect’ 1956 uninduced culture high inducer Fully induced growth in low inducer level Fully induced

23. b -galactosidase assays on ‘single-cell’ cultures Novick & Weiner, 1957; maintenance uninduced high inducer induced growth in maintenance inducer level dilute single cells into maintenance inducer level growth in maintenance inducer level

24. b -galactosidase assays on ‘single-cell’ cultures Novick & Weiner, 1957; ‘all or none’ uninduced cultures high inducer intermediate inducer mixed induced growth in maintenance inducer level dilute single cells into maintenance inducer level growth in maintenance inducer level

25. b -galactosidase assays on ‘single-cell’ cultures Novick & Weiner, 1957; ‘all or none’ uninduced cultures high inducer intermediate inducer mixed induced growth in maintenance inducer level dilute single cells into maintenance inducer level growth in maintenance inducer level

26. Ozbudak et al., Nature427, 737 (2004)

27. Ozbudak et al., Nature427, 737 (2004)

28. Ozbudak et al., Nature427, 737 (2004)

29. Monitoring phenotypic variability in cell lineages Development of molecular tools, microfluidic, databases, image analysis, statistical tools, tweezers, microscopes

30. Time-lapse of a bacterial lineage

31. Manually corrected mask Automatically generated mask

32. Data available after image analysis • >100 movies (E. Stewart) • > 100000 divisions (R. Madden) • Morphometry : • Length • Positions • Exhaustive genealogies > 10 generations

33. Individual sizes grow exponentially within a lineage

34. Distributions of individual phenotypes Biomasse (µm) Growth rate (µm/min) Time to division (min)

36. For phenotype to depend only genotype and environment One must take into account DNA extended environment (intracellular environment is dynamic, ~ heritable & local)

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