Comparaison des intentions entrepreneuriales des étudiants : France –Pays arabes

A partir d'une grille de lecture dérivée du modèle psychosocial du comportement planifié d'Ajzen, nous étudions les déterminons des intentions entrepreneuriales affichées par les étudiants en France et dans trois pays arabes, Algérie, Liban et Tunisie. Nous observons que les niveaux mesurés de ces intentions sont très différents d'un pays à l'autre et nous essayons d'expliquer ces divergences à partir des éléments qui, selon le modèle retenu, sont à la base de ces intentions : attitude envers la création d'entreprises, normes sociales et contrôle comportemental perçu. Pour ce faire, nous proposons, en utilisant des techniques d'analyse des données, quatre facteurs (perception de la gestion du temps dans la vision de l'entrepreneuriat ; projection dans le future professionnel ; goût du risque dans la vie professionnel ; capacité perçue) qui structurent les intentions entrepreneuriales des étudiants, ainsi qu'une typologie qui montre des comportements quant aux intentions entrepreneuriales bien caractérisées et distinctes, entre d'une part, la France, et d'autre part, les autres pays.intentions entrepreneuriales ; étudiants ; France ; Pays arabes

Modified bases enable high-efficiency oligonucleotide-mediated allelic replacement via mismatch repair evasion

Genome engineering using single-stranded oligonucleotides is an efficient method for generating small chromosomal and episomal modifications in a variety of host organisms. The efficiency of this allelic replacement strategy is highly dependent on avoidance of the endogenous mismatch repair (MMR) machinery. However, global MMR inactivation generally results in significant accumulation of undesired background mutations. Here, we present a novel strategy using oligos containing chemically modified bases (2′-Fluoro-Uridine, 5-Methyl-deoxyCytidine, 2,6-Diaminopurine or Iso-deoxyGuanosine) in place of the standard T, C, A or G to avoid mismatch detection and repair, which we tested in Escherichia coli. This strategy increases transient allelic-replacement efficiencies by up to 20-fold, while maintaining a 100-fold lower background mutation level. We further show that the mismatched bases between the full length oligo and the chromosome are often not incorporated at the target site, probably due to nuclease activity at the 5′ and 3′ termini of the oligo. These results further elucidate the mechanism of oligo-mediated allelic replacement (OMAR) and enable improved methodologies for efficient, large-scale engineering of genomes.Synthetic Biology Engineering Research CenterNational Science Foundation (U.S.) (Grant #SA5283-11210)United States. Dept. of Energy (Genomes to Life Center) (Grant #DE-FG02-03ER6344)Wyss Institute for Biologically Inspired Engineerin

Roles of DNA polymerase I in leading and lagging-strand replication defined by a high-resolution mutation footprint of ColE1 plasmid replication

DNA polymerase I (pol I) processes RNA primers during lagging-strand synthesis and fills small gaps during DNA repair reactions. However, it is unclear how pol I and pol III work together during replication and repair or how extensive pol I processing of Okazaki fragments is in vivo. Here, we address these questions by analyzing pol I mutations generated through error-prone replication of ColE1 plasmids. The data were obtained by direct sequencing, allowing an accurate determination of the mutation spectrum and distribution. Pol I’s mutational footprint suggests: (i) during leading-strand replication pol I is gradually replaced by pol III over at least 1.3 kb; (ii) pol I processing of Okazaki fragments is limited to ∼20 nt and (iii) the size of Okazaki fragments is short (∼250 nt). While based on ColE1 plasmid replication, our findings are likely relevant to other pol I replicative processes such as chromosomal replication and DNA repair, which differ from ColE1 replication mostly at the recruitment steps. This mutation footprinting approach should help establish the role of other prokaryotic or eukaryotic polymerases in vivo, and provides a tool to investigate how sequence topology, DNA damage, or interactions with protein partners may affect the function of individual DNA polymerases

Avoiding Dangerous Missense: Thermophiles Display Especially Low Mutation Rates

Rates of spontaneous mutation have been estimated under optimal growth conditions for a variety of DNA-based microbes, including viruses, bacteria, and eukaryotes. When expressed as genomic mutation rates, most of the values were in the vicinity of 0.003–0.004 with a range of less than two-fold. Because the genome sizes varied by roughly 104-fold, the mutation rates per average base pair varied inversely by a similar factor. Even though the commonality of the observed genomic rates remains unexplained, it implies that mutation rates in unstressed microbes reach values that can be finely tuned by evolution. An insight originating in the 1920s and maturing in the 1960s proposed that the genomic mutation rate would reflect a balance between the deleterious effect of the average mutation and the cost of further reducing the mutation rate. If this view is correct, then increasing the deleterious impact of the average mutation should be countered by reducing the genomic mutation rate. It is a common observation that many neutral or nearly neutral mutations become strongly deleterious at higher temperatures, in which case they are called temperature-sensitive mutations. Recently, the kinds and rates of spontaneous mutations were described for two microbial thermophiles, a bacterium and an archaeon. Using an updated method to extrapolate from mutation-reporter genes to whole genomes reveals that the rate of base substitutions is substantially lower in these two thermophiles than in mesophiles. This result provides the first experimental support for the concept of an evolved balance between the total genomic impact of mutations and the cost of further reducing the basal mutation rate

Variable Mutation Rates as an Adaptive Strategy in Replicator Populations

For evolving populations of replicators, there is much evidence that the effect of mutations on fitness depends on the degree of adaptation to the selective pressures at play. In optimized populations, most mutations have deleterious effects, such that low mutation rates are favoured. In contrast to this, in populations thriving in changing environments a larger fraction of mutations have beneficial effects, providing the diversity necessary to adapt to new conditions. What is more, non-adapted populations occasionally benefit from an increase in the mutation rate. Therefore, there is no optimal universal value of the mutation rate and species attempt to adjust it to their momentary adaptive needs. In this work we have used stationary populations of RNA molecules evolving in silico to investigate the relationship between the degree of adaptation of an optimized population and the value of the mutation rate promoting maximal adaptation in a short time to a new selective pressure. Our results show that this value can significantly differ from the optimal value at mutation-selection equilibrium, being strongly influenced by the structure of the population when the adaptive process begins. In the short-term, highly optimized populations containing little variability respond better to environmental changes upon an increase of the mutation rate, whereas populations with a lower degree of optimization but higher variability benefit from reducing the mutation rate to adapt rapidly. These findings show a good agreement with the behaviour exhibited by actual organisms that replicate their genomes under broadly different mutation rates

Mutator Suppression and Escape from Replication Error–Induced Extinction in Yeast

Cells rely on a network of conserved pathways to govern DNA replication fidelity. Loss of polymerase proofreading or mismatch repair elevates spontaneous mutation and facilitates cellular adaptation. However, double mutants are inviable, suggesting that extreme mutation rates exceed an error threshold. Here we combine alleles that affect DNA polymerase δ (Pol δ) proofreading and mismatch repair to define the maximal error rate in haploid yeast and to characterize genetic suppressors of mutator phenotypes. We show that populations tolerate mutation rates 1,000-fold above wild-type levels but collapse when the rate exceeds 10−3 inactivating mutations per gene per cell division. Variants that escape this error-induced extinction (eex) rapidly emerge from mutator clones. One-third of the escape mutants result from second-site changes in Pol δ that suppress the proofreading-deficient phenotype, while two-thirds are extragenic. The structural locations of the Pol δ changes suggest multiple antimutator mechanisms. Our studies reveal the transient nature of eukaryotic mutators and show that mutator phenotypes are readily suppressed by genetic adaptation. This has implications for the role of mutator phenotypes in cancer

Natural Selection Fails to Optimize Mutation Rates for Long-Term Adaptation on Rugged Fitness Landscapes

The rate of mutation is central to evolution. Mutations are required for adaptation, yet most mutations with phenotypic effects are deleterious. As a consequence, the mutation rate that maximizes adaptation will be some intermediate value. Here, we used digital organisms to investigate the ability of natural selection to adjust and optimize mutation rates. We assessed the optimal mutation rate by empirically determining what mutation rate produced the highest rate of adaptation. Then, we allowed mutation rates to evolve, and we evaluated the proximity to the optimum. Although we chose conditions favorable for mutation rate optimization, the evolved rates were invariably far below the optimum across a wide range of experimental parameter settings. We hypothesized that the reason that mutation rates evolved to be suboptimal was the ruggedness of fitness landscapes. To test this hypothesis, we created a simplified landscape without any fitness valleys and found that, in such conditions, populations evolved near-optimal mutation rates. In contrast, when fitness valleys were added to this simple landscape, the ability of evolving populations to find the optimal mutation rate was lost. We conclude that rugged fitness landscapes can prevent the evolution of mutation rates that are optimal for long-term adaptation. This finding has important implications for applied evolutionary research in both biological and computational realms

Aag DNA Glycosylase Promotes Alkylation-Induced Tissue Damage Mediated by Parp1

Alkylating agents comprise a major class of front-line cancer chemotherapeutic compounds, and while these agents effectively kill tumor cells, they also damage healthy tissues. Although base excision repair (BER) is essential in repairing DNA alkylation damage, under certain conditions, initiation of BER can be detrimental. Here we illustrate that the alkyladenine DNA glycosylase (AAG) mediates alkylation-induced tissue damage and whole-animal lethality following exposure to alkylating agents. Aag-dependent tissue damage, as observed in cerebellar granule cells, splenocytes, thymocytes, bone marrow cells, pancreatic β-cells, and retinal photoreceptor cells, was detected in wild-type mice, exacerbated in Aag transgenic mice, and completely suppressed in Aag−/− mice. Additional genetic experiments dissected the effects of modulating both BER and Parp1 on alkylation sensitivity in mice and determined that Aag acts upstream of Parp1 in alkylation-induced tissue damage; in fact, cytotoxicity in WT and Aag transgenic mice was abrogated in the absence of Parp1. These results provide in vivo evidence that Aag-initiated BER may play a critical role in determining the side-effects of alkylating agent chemotherapies and that Parp1 plays a crucial role in Aag-mediated tissue damage.National Institutes of Health (U.S.) (NIH grant R01-CA075576)National Institutes of Health (U.S.) (NIH grant R01-CA055042)National Institutes of Health (U.S.) (NIH grant R01-CA149261)National Institutes of Health (U.S.) (NIH grant P30-ES00002)National Institutes of Health (U.S.) (NIH grant P30-ES02109)National Center for Research Resources (U.S.) (grant number M01RR-01066)National Center for Research Resources (U.S.) (grant number UL1 RR025758, Harvard Clinical and Translational Science Center

Adaptive Evolution of the Lactose Utilization Network in Experimentally Evolved Populations of Escherichia coli

Adaptation to novel environments is often associated with changes in gene regulation. Nevertheless, few studies have been able both to identify the genetic basis of changes in regulation and to demonstrate why these changes are beneficial. To this end, we have focused on understanding both how and why the lactose utilization network has evolved in replicate populations of Escherichia coli. We found that lac operon regulation became strikingly variable, including changes in the mode of environmental response (bimodal, graded, and constitutive), sensitivity to inducer concentration, and maximum expression level. In addition, some classes of regulatory change were enriched in specific selective environments. Sequencing of evolved clones, combined with reconstruction of individual mutations in the ancestral background, identified mutations within the lac operon that recapitulate many of the evolved regulatory changes. These mutations conferred fitness benefits in environments containing lactose, indicating that the regulatory changes are adaptive. The same mutations conferred different fitness effects when present in an evolved clone, indicating that interactions between the lac operon and other evolved mutations also contribute to fitness. Similarly, changes in lac regulation not explained by lac operon mutations also point to important interactions with other evolved mutations. Together these results underline how dynamic regulatory interactions can be, in this case evolving through mutations both within and external to the canonical lactose utilization network