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What matters for lac repressor search in vivo--sliding, hopping, intersegment transfer, crowding on DNA or recognition?

Mahmutovic A, Berg OG, Elf J - Nucleic Acids Res. (2015)

Bottom Line: Including a mechanism of inter-segment transfer between distant DNA segments does not bring down the 1D diffusion to the expected fraction of the in vitro value.This suggests a mechanism where transcription factors can slide less hindered in vivo than what is given by a simple viscosity scaling argument or that a modification of the model is needed.For example, the estimated diffusion rate constant would be consistent with the expectation if parts of the chromosome, away from the operator site, were inaccessible for searching.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, 75124 Uppsala, Sweden.

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The level curves correspond to chi-square values less than 3 measuring the goodness of fit of simulations to experiment for one of the two operator sites at distances 25, 45, 65, 115 and 203 bp. The values are calculated for combinations of D1 and α values given the vacancy v, the probability of specific binding pbind as indicated and the fraction of non-specific binding FB equal to 90% (Table 1). The cyan region in this figure shows where the absolute search time is in the interval 236 s (three proteins)–416 s (five proteins).
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Figure 2: The level curves correspond to chi-square values less than 3 measuring the goodness of fit of simulations to experiment for one of the two operator sites at distances 25, 45, 65, 115 and 203 bp. The values are calculated for combinations of D1 and α values given the vacancy v, the probability of specific binding pbind as indicated and the fraction of non-specific binding FB equal to 90% (Table 1). The cyan region in this figure shows where the absolute search time is in the interval 236 s (three proteins)–416 s (five proteins).

Mentions: Our approach to estimate the in vivo parameters governing the target search is to acquire the time it takes for LacI to find its specific binding site using a combination of Monte Carlo simulations and analytical calculations as a function of three unknown variable input parameters D1, α and pbind. The calculated search time is then used to compare with two sets of single molecule in vivo data which are the search times to one operator site and the ratio of search times for one and two operator sites at various distances. The parameter regions where there is agreement between the calculated search times and the measured search times are illustrated in Figure 2. Here the semi-transparent cyan region corresponds to parameters where the overall search time to one site is acceptable and the level curves correspond to chi-square values for the agreement for the two-operator data set. The calculated search times should conform to both sets of in vivo data, which means that the acceptable parameter space is the region where the cyan region overlaps with the contour map. The constraint to small chi-squared values is because they quantify the difference between the estimated search times and the experimental search times for the data involving two operator sites as exemplified in Figure 3. This approach is expanded upon and clarified in the sections that follow.


What matters for lac repressor search in vivo--sliding, hopping, intersegment transfer, crowding on DNA or recognition?

Mahmutovic A, Berg OG, Elf J - Nucleic Acids Res. (2015)

The level curves correspond to chi-square values less than 3 measuring the goodness of fit of simulations to experiment for one of the two operator sites at distances 25, 45, 65, 115 and 203 bp. The values are calculated for combinations of D1 and α values given the vacancy v, the probability of specific binding pbind as indicated and the fraction of non-specific binding FB equal to 90% (Table 1). The cyan region in this figure shows where the absolute search time is in the interval 236 s (three proteins)–416 s (five proteins).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4402528&req=5

Figure 2: The level curves correspond to chi-square values less than 3 measuring the goodness of fit of simulations to experiment for one of the two operator sites at distances 25, 45, 65, 115 and 203 bp. The values are calculated for combinations of D1 and α values given the vacancy v, the probability of specific binding pbind as indicated and the fraction of non-specific binding FB equal to 90% (Table 1). The cyan region in this figure shows where the absolute search time is in the interval 236 s (three proteins)–416 s (five proteins).
Mentions: Our approach to estimate the in vivo parameters governing the target search is to acquire the time it takes for LacI to find its specific binding site using a combination of Monte Carlo simulations and analytical calculations as a function of three unknown variable input parameters D1, α and pbind. The calculated search time is then used to compare with two sets of single molecule in vivo data which are the search times to one operator site and the ratio of search times for one and two operator sites at various distances. The parameter regions where there is agreement between the calculated search times and the measured search times are illustrated in Figure 2. Here the semi-transparent cyan region corresponds to parameters where the overall search time to one site is acceptable and the level curves correspond to chi-square values for the agreement for the two-operator data set. The calculated search times should conform to both sets of in vivo data, which means that the acceptable parameter space is the region where the cyan region overlaps with the contour map. The constraint to small chi-squared values is because they quantify the difference between the estimated search times and the experimental search times for the data involving two operator sites as exemplified in Figure 3. This approach is expanded upon and clarified in the sections that follow.

Bottom Line: Including a mechanism of inter-segment transfer between distant DNA segments does not bring down the 1D diffusion to the expected fraction of the in vitro value.This suggests a mechanism where transcription factors can slide less hindered in vivo than what is given by a simple viscosity scaling argument or that a modification of the model is needed.For example, the estimated diffusion rate constant would be consistent with the expectation if parts of the chromosome, away from the operator site, were inaccessible for searching.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, 75124 Uppsala, Sweden.

Show MeSH