Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
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 differences Geographical 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 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) Life with small number of big molecules Elowitz Science 2002 2 different fluorescent proteins controlled by identical promoters Noise in gene expression is affected by genotype and environment Genes involved Error rates DNA 10-9 RNA 10-5 aberrant RNA Proteins 10-4 aberrant proteins Functions Cells Mutations mutS, mutT mutT gidA, mnmE Functional degeneracy Functional fidelity ? cell death Maintenance ? Strategies to maintain DNA integrity Eliminate source of lesions Physical protection Template maintenance Pool sanitization Polymerase fidelity Quality control Strategies to maintain DNA integrity R • • • • • • Eliminate source of lesions Physical protection Template maintenance Pool sanitization Polymerase fidelity Quality control 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) MutT controls transcription fidelity Science (1997) 278 128-130 Genotype DNA lacZ+ lacZmutT + -GAG-CTC- -TAG-AT C- lacZmutT -TAG-ATCRNA polymerase mRNA - GAG- ... -UAG- - G°A G - -CUC- STOP -CUC- ... tRNA Glu relative - gal activity 1 Glu 10-5 ° rGTP 10-3 MutT OH° rGTP MutT hydrolyses dG°TP & rG°TP Taddei Science 1997 RNA polymerase incorporate 8-oxoG Genomic DNA template Taddei Science 1997 Poly dAdT template Errors during transcription lead to protein oxidation Dukan PNAS 2000 Error in translation increase misfolding & protein oxidation Dukan PNAS 2000 Translation error as a limiting step for protein oxidation Dukan PNAS 2000 8-oxo-G concentration increase in the brain during neuro-degeneration Nunomura J Neuroscience 1999 Cause & consequences of 8-oxo-G in RNA Oxydative Stress GTP Oxidation direct oxidation of RNA MutT G° M P + PPi G° TP 8-oxo-G-ARN G° RNA RNA RNA polymerase 8-oxo-G-ARN binding protein 8-oxo-G-RNA G° G° Translation Erroneous Protein Degradation? 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 Monod, ‘preinduction effect’ 1956 uninduced culture high inducer Fully induced growth in low inducer level Fully induced 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 -galactosidase assays on ‘single-cell’ cultures Novick & Weiner, 1957; ‘all or none’ uninduced cultures high inducer induced intermediate inducer mixed growth in maintenance inducer level dilute single cells into maintenance inducer level growth in maintenance inducer level -galactosidase assays on ‘single-cell’ cultures Novick & Weiner, 1957; ‘all or none’ uninduced cultures high inducer induced intermediate inducer mixed growth in maintenance inducer level dilute single cells into maintenance inducer level growth in maintenance inducer level -galactosidase assays on ‘single-cell’ cultures Ozbudak et al., Nature 427, 737 (2004) Ozbudak et al., Nature 427, 737 (2004) Ozbudak et al., Nature 427, 737 (2004) Monitoring phenotypic variability in cell lineages Development of molecular tools, microfluidic, databases, image analysis, statistical tools, tweezers, microscopes Time-lapse of a bacterial lineage QuickTime™ et un décompresseur Animation sont requis pour visualiser cette image. Manually corrected mask Automatically generated mask Data available after image analysis • >100 movies (E. Stewart) • > 100000 divisions (R. Madden) • Morphometry : – Length – Positions • Exhaustive genealogies > 10 generations Individual sizes grow exponentially within a lineage Distributions of individual phenotypes Biomasse (µm) Growth rate (µm/min) Time to division (min) QuickTime™ et un décompresseur Sorenson Video 3 sont requis pour visualiser cette image. For phenotype to depend only genotype and environment One must take into account DNA extended environment (intracellular environment is dynamic, ~ heritable & local) A network approach of bacterial variability Why change ? Population genetics Who changes ? Molecular epidemiology Godelle Gouyon Brown Maynard-Smith Binguen Denamur Picard Brisabois Berche B. Toupance O. Tenaillon J-B André Change what? Bio-informatics Rocha Change where ? Microbial ecology Fons Duriez How to change ? Molecular biology Matic Radman Vulic Dionisio Bjedov Bregeon Leroy Hayakawa Sekiguchi Dukan Who has changed ? Molecular Phylogeny Lecointre Darlu Giraud Lechat Bambou Change when ? transcriptome analysis Knudsen Cerf Phenotypic variability Life History Stewart Madden Lindner Paul Gabriel Fontaine Depaepe Bredèche Mosser A network approach of bacterial variability Why change ? Population genetics Who changes ? Molecular epidemiology Godelle Gouyon Brown Maynard-Smith Binguen Denamur Picard Brisabois Berche B. Toupance O. Tenaillon J-B André Change what? Bio-informatics Rocha Change where ? Microbial ecology Fons Duriez How to change ? Molecular biology Matic Radman Vulic Dionisio Bjedov Bregeon Leroy Hayakawa Sekiguchi Dukan Who has changed ? Molecular Phylogeny Lecointre Darlu Giraud Lechat Bambou Change when ? transcriptome analysis Knudsen Cerf Phenotypic variability Life History Stewart Madden Lindner Paul Gabriel Fontaine Depaepe Bredèche Mosser Quick Time™ et un décompresseur Photo - JPEG sont requis pour visualiser cette image. www.necker.fr/tamara/ Join Fun & Science in Paris QuickTime™ et u n dé com press eur Pho to - JPEG so nt re quis pou r visua lise r cette ima ge. QuickTime™ et un décompresseur Photo - JPEG sont requis pour visualiser cette image.