378 Outline for B M B 400 at PSU
378 Outline for B M B 400 at PSU
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Date Created: 02/06/15
BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase B M B 400 Part Four Gene Regulation Section II Chapter 17 TRAN SCRIPTIONAL REGULATION EXERTED BY EFFECTS ON RNA POLYMERASE Dr Tracy Nixon made major contributions to this chapter A The multiple steps in initiation and elongation by RNA polymerase are targets for regulation 1 RNA Polymerase has to bind to promoters form an open complex initiate transcription escape from the promoter elongate and terminate transcription See Fig 421 2 Summarizing a lot of work we know that 0 strong promoters have high KB high kf low kr and high rates of promoter clearance weak promoters have low KB low kf high kr and low rates of promoter clearance moderate promoters have one or more quotweakquot spots 3 To learn these facts we need 0 genetic data to identify which macromolecules DNA and proteins interact in a specific regulation event and to determine which base pairs and amino acid residues are needed for that regulation event biochemical data to describe the binding events and chemical reactions that are affected by the specific regulation event Ideally we would determine all forward and reverse rate constants or equilibrium constants which are a function of the ratio of rate constants if rates are inaccessible Although in reality we cannot get either rates or equilibrium constants for many of the steps some of the steps are amenable to investigation and have proved to be quite informative about the mechanisms of regulation m mp u z cm 17 mmcnptmnal gunman by men an RNA palymuase RPnE nczmczEczEc alnngninn verminavjnn anemlavms anutverminams mama ng LZJ REGULATION or RNAFOLYMERASE my ki RF RPd RPcZ K k h gtgt k clnsa l man quotpen unnka plummet fnrmavjnn fnrmavjnn clmrance 13 m ltlgEnzt2Linn 1n A r fnld mum Cnnunl neg mumquot pus actime pus sigma xpnA a cum hummzym 33 um1 szB39cr an um plummet mngpiunmmelvjng xan m mangmmpnmv W cm W cm ungzunn fanny mle NuxA g verminavjnnfacmxs nusD 9 Pa clused pmmm camplzx Pa apen pmmnmxcamplzx m z mmal maxmung camplzx use mmalelmga ngcamplzx Ex langa nncmnplex m unman Hangman camplzx BMB4OO Part Four A ll Chpt l7 Transcriptional regulation by effects on RNA polymerase B Methods exist for measuring rate constants and equilibrium constants and newer more accurate methods are now being used 1 Classical methods of equilibrium studies and data analysis 0 use low concentrations of enzymes and make assumptions that simplify complex reactions so that they can be treated by definite integrals of chemical ux equations 0 manipulate an equation into a form that can be plotted as a linear function and derive parameter estimates by slope and intercept values 2 Driven by the success of recombinant DNA and protein purification technology and by the increased computational power in desktop computers the classical methods are being replaced by 0 using of large amounts of enzymes to directly include them in kinetic studies In this approach the enzymes are used in substrate level quantities o numerical integrations of chemical ux equations Kinetic Simulation 0 more rigorous methods based on NonLinear Least Squares NLLS regression and o analyzing data from multiple experiments of different design simultaneously global NLLS analysis 3 These changes increase the steps in a reaction that can be examined experimentally replace the limited set of simple mechanisms that can be analyzed with essentially any mechanism increase knowledge of error permitting conclusions to be drawn with more confidence Box 1 The equations used in this chapter come from several different sources that use different names for the same thing The following lists some of these synonyms Synonymous and related terms KB Kb Keq equilibrium constant for binding KS KB for binding of protein to aspecific DNA sequence KNS KB for binding of protein tononspecific DNA P P2 molar concentration of protein R4 molar concentration of repressor D molar concentration of free DNA DS concentration of free specific DNA DNS concentration of free nonspecific DNA DP molar concentration of DNAprotein complex R4Ds concentration of repressoroperator BMB4OO Part Four 7 II Chpt l7 Transcriptional regulation by effects on RNA polymerase C Experimental approaches to macromolecular binding reactions Several methods are available for measuring the amount of protein that binds specifically to a DNA molecule We have already encountered these as methods for localizing proteinibinding sites on DNA and all are amenable to quantitation Major methods include nitrocellulose lter binding electrophoretic mobility shift assays and DNase protection assays Which Experimental Technique is Best The kind of observations that can be made about the system differ for different experimental approaches These differences lead to specific problems with each technique Each technique depends on combining the analysis of more than one experiment to obtain enough information to resolve intrinsic binding free energy from cooperativity energy Fig 422 Protein binding assayed by DNase I footprinting P x L ULWY ramming Protein Commutation 1 4 w in g 9 55 i g a 2 f mill rmc y r 4 i 17 L I m mxml Iruumnry I Site 1 I Sim Need to use many orders of magnitude of P 9117le IN 1 liipvrlrmur P or Y Data courtesy of Dr Tracy Nixon The most robust technique is DNase I footprinting If you are studying the binding of multiple interacting proteins then it is possible that these proteins are showing cooperativity in their binding to DNA When analyzing such cooperativity by DNase I footprinting the resolution is limited to cooperativities gt05 kcalmole and is subject to some critical assumptions Gelishifts also called electrophoretic mobility shift assays or EMSAs are useful when there is no cooperativity or when cooperativity is large relative to site heterogeneity Filter binding studies require knowledge about filter retention efficiencies for the different proteiniDNA complexes which can only be empirically determined And always keep in mind that anking sequences do affect binding affinities and even point mutations can have distant effects In any of these assays we are devising a physical means for measuring a quantity that is related to fractional occupancy BMB400 Part Four 7 II Chpt 17 Transcriptional regulation by effects on RNA polymerase D Measurement of equilibrium constants in macromolecular binding reactions 1 Classical methods with their linear transformation are not as accurate as the NonLinear Least Squares NLLS regression analysis but they can serve to show the general approach a The binding constants can be determined by titrating labeled DNA binding sites with increasing amounts of the repressor and measuring amount of protein bound DNA and the amount of free DNA Typical techniques are electrophoretic mobility shift assays or nitrocellulose filter binding Note that for a simple equilibrium ofa single protein binding to a single site on the DNA the equilibrium constant for binding KB is approximated by the inVerse of the protein concentration at which the concentration of DNA bound to protein equals the concentration of free DNA Fig 423 Fig 423 Measure KB by EMSA 0 P DP 2 DP DP DP El KB DHP D EItu When 33 1then 1 K B P If it were possible to reliably determine both the concentration of DNA bound to protein ie DP and the concentration of free DNA D then one could plot the ratio of bound DNA to free DNA at each concentration of repressor If the results were linear then the slope of the line would giVe the equilibrium binding constant KB See Fig 424 BMB400 Part Four 7 ll Chpt 17 Transcriptional regulation by effects on RNA polymerase Fig 424 Measure KB from DPD D p 2 DP If you could measure DP and D at each P you could DP measure KB KB D P g D DP 10 When 1then D I 1 KB W 1 P KB slope KB However the error associated with determining Very low concentrations of free or bound DNA is substantial and a more reliable measurement is that of the ratio of bound DNA to total DNA ie DPDm as illustrated in Fig 425 The equation describing this binding curve has a form equivalent to the Michelierenten equation for steadyestate enyzme kinetics Note that the concentration of protein at which half the DNA is bound to protein is the inVerse of KB You can show this for yourself by substituting 05 for DPDm in the equation At this point P lKB Fig 425 Measure KB from DPDtot It is more reliable to measure the fraction of labeled DNA in complex with protein ie DPDtot Substitution of DD01 DP into equation for KB gives DP Kalpl Dltot l KBipl 10 DP Dltot 10 P 50nM BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase 2 Problems with the classical approach In this classical approach experiments were designed such that 0 one or more concentrations could be assumed to be unchanging and o observations were manipulated mathematically transformed to a linear equation so that one could plot the transformed data decide where to draw a straight line and use the slope and intercepts to estimate the parameters in question Scatchard plots Lineweaver Burke plots etc Two problems are associated with the older technique 0 Deciding where to draw the straight line is an arbitrary decision for each person doing the analysis and using a linear regression to find the quotbest fitquot line is not justified as two of the assumptions about your data that are needed to justify such a regression are not true 0 There is no accurate estimate of the error in the estimate of the parameter value 3 These limitations have been overcome in the last 5 or so years aided by the advent of recombinant DNA techniques that allow the production of large amounts of the proteins being analyzed and the availability of powerful microcomputers that can carry out the large number of computations required for nonlinear least squares regression analysis NLLS a We can model binding reactions by tabulating the different states that exist in a system associating each state with a fractional probability based on the Boltzmann partition function and the Gibbs free energy for that state AG5 and determine the probability of any observed measurement by the ratio of o the sum of fractional probabilities that give the observation and o the sum of the fractional probabilities of all possible states Where j is the number of ligands bound the fractional probability of a particular state is given by this equation for f3 e AGS RT XP2j ffm 5 As an example consider a one site system such as an operator that binds one protein There are two states the 0 state with no protein bound to the operator and the 1 state with one protein bound Thus one can write the equation for f0 and for f BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase If we expand the fractional probabilities for each of these fractional occupancy equations we derive equations relating fractional occupancy to a function of Gibbs free energies for binding AG protein concentration P2 and complex stoichiometry j For a single site system we have the following equations 39L Y2 AG RT 6 gtltle AG RT r le gtltPZ Since Gibbs free energy is also related to the equilibrium constant for reactions AG RT ln Keq these free energies can be re cast as equilibrium constants as follows Kb gtlt P2 Y1KbgtltP2 A more complete presentation of this method including a treatment of multiple binding sites can be obtained at the BMB Courses web site httpwwwbmbpsueducoursesdefaulthtm by clicking on BMB400 quotNixon Lectures quot b Analyzing the data After collecting the binding data we are in a position to analyze the observed data to find out what values for AG or Kb make the function best predict the observations Statisticians have developed Maximum Likelihood Theory to allow using the data to find for each parameter the value that is most likely to be correct For biochemical data the approach that is most appropriate most of the time is global nonlinear least squares NLLS regression Fortunately desktop computers are now powerful enough to do these calculations in a few minutes for one experiment or even for many experiments combined in a global analysis This method has several advantages It gives you BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase o the same parameter estimates no matter what program or method you or someone else uses provided that the program is written correctly and used correctly 0 much more rigorous estimates of error This last point is worth emphasizing is it not true that 100 minus 50 is much less attractive as a fee for your time than is 100 minus 001 The same can be true for estimates of binding free energies or equilibrium constants 0 Moreover when several experiments are required to estimate a parameter the error in each experiment should be included in the estimate of the parameter Without a global analysis that determines a conglomerate error it is not possible to carefully carry forward the error of one experiment to the analysis of data from additional ones c This analysis produces a plot of the variance of fit or error over a wide range of possible values for the parameter being measured such as the AG for binding The AG value with the smallest error is the most accurate value EMBAUEI PanFuure u chpt 17 anscnpnmal regulaan bye ems unRNA pulymemse Anexample D hs aralysls 15 shuumanxg 42 6 The raw u a39a Shawn thth A 2 2 eftpan l pmdmed the bmmng ewves shewh mnghtpahel nflhat gure These data were thehsuheeteene mnehnearleastrsquares analysis The ems emuahee amt Breach pusslble velue ems are planed thth 42 6 Fur example hue thetthe lewestmahee emth 15 aheuteg 5 hidmule Fig 6 Variance aniIvs Free Energy Parameters new quot e quotm t 7 icaapevmw v nuns 1 u m 42 Au re s a 72 u 2 Gum39s nee Enemy dGl AG Gibbs free energny bmdmg In the mstsme Ufa tweme syshem AG Gibbs free energny bmdmg In the securd sue mamDst system The mama nfmfurthe AG fur the cuupemuwty hetweeh pmtems buund at the am sues IS alsn planed These u a39a were kmily pmvlded byDr neeyNtxm BMB400 Part Four 7 11 Chpt 17 Tmnscriptional reguiauon by effects on RNA polymerme As indicaed above once aValue for AG is available one can calculate Keq from AG VRT 1n Keq Hg427 Example of calculating KB from plot of variance of fit vs AG AG 95 kcal mol gives the minimum variance or error AG eRTlnKeq In KB AGFiT 95 kcalmol 161017 059 kcalmol KB 98x106M1 R 198X 10393 kcal deg391 mol391 7 298 K RE 059 kcalmol Some key references for N39LLS Senear and Bolen 1992 Meihods Enzymol 210463 Koblan el al 1992 Meihods Enzymol 210405 Senear el al 1991 J Biol Chem 26613661 BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase E Insights into the mechanism of lac regulation by measuring binding constants 1 Having gone through both classical and non linear least squares analysis for measuring binding constants let s look at an example of how one uses these measurements to better understand the mechanism of gene regulation We know that transcription of the lac operon is increased in the presence of the inducer but how does this occur One could list a number of possibilities each with different predictions about how the inducer may affect the binding constant of repressor for operator KB a Does the inducer change the conformation of the lac repressor so that it now activates transcription This could occur with no effect on KB b Does inducer cause the repressor to dissociate from the operator DNA and remain free in solution This predicts a decrease in KB for specific DNA but no binding to nonspecific DNA c Does inducer cause the repressor to dissociate from the operator and redistribute to nonspecific sites on the DNA This predicts a decrease in KB for specific DNA but proposes that most of the repressor is bound to non operator sites Measurement of the equilibrium constants for lac repressor binding to operator and to nonspecific DNA in the absence and presence of the inducer shows that possibility 0 above is correct This section of the chapter explores this result in detail 2 In the absence of inducer the repressor or R4 will bind to speci c sites in this case the operator with high af nity and to nonspecific sites other DNA sequences with lower affinity Fig 428 This is stated quantitatively in the following values for the equilibrium association constant Either equilibrium constant can be abbreviated Keq or KB We will use the term Ks to refer to KB at specific sites and KNS for the KB at nonspecific sites KS 2x1013 M l KNS 2x106M 1 A detailed presentation of some representative data and how to use them to determine these binding constants for the lac repressor is in Appendix A at the end of this chapter This Appendix goes through the classic approach to measuring binding constants 3 The binding constant of lac repressor to its operator changes in the presence of inducer Fig 428 Binding of the inducer to the repressor lowers the affinity of the repressor for the operator 1000 fold but does not affect the affinity of repressor for nonspecific sites For R4 with inducer KS 2 x1010M1 ltst 2 x106M1 BMB400 Part Four 7 II Chpt 17 Transcriptional regulation by effects on RNA polymerase Fig 428 Inducer lowers the KB for repressor binding to operator acrepressor acrepressor I I I Operator nonspecific Site t 2 g 8 gt KB Ks 2x1013 ivi1 KB KNS 2x106 M1 In the presence of inducer acrepressor nonspecific site 88 I2 T g 3 gt KB KS 2X1010 M391 KB KNS 2x106 M391 4 The difference in affinity for specific Versus nonspecific sites can be described by the specificity parameter which is the ratio between the equilibrium constant for specific binding and the equilibrium constant for nonspecific binding Specificity IS 5 107 in absence ofirlducer NS 10A inprerence of inducer KNS Note the in the presence of the inducer the specificity with which the lac repressor binds to DNA is decreased lOOOefold Even though the repressor still has a higher affinity for specific DNA in the presence of the inducer there are so many norspeci c sites in the genome that the repressor stays bound to these nonspecific sites rather than finding the operator Hence in the presence of the inducer the operator is largely unoccupied by repressor and the operon is actively transcribed The regulation of the lac operon Via redistribution of the repressor to nonspecific sites in the genome is coVered in more detail in the next two sections They show the effect of haVing a large number of nonspecific low affinity sites competing with a single high affinity site for a small number of repressor molecules BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase 5 Distribution of repressor between operator and nonspeci c sites Although repressor has a much higher affinity for the operator than for nonspecific sites there are so many more nonspecific sites 46 X 106 since essentially every nucleotide in the E coli genome is the beginning of a nonspecific binding site than specific sites one operator per genome that virtually all of the repressor is bound to DNA even if only nonspecific sites are present a We use the binding constants above and couple them with a calculation that the concentration of repressor 10 molecules per cell is 17 X 10 8 M and the concentration of nonspecific sites 46 X 106 per cell is 764 X 10 3 M These values for R4 and DNS are essentially constant With this information we can compute that the ratio of free repressor to that bound to nonspecific sites is less that 1 X 10 4 it is about 66 X 105 as shown in the box below Thus only about 1 in 15000 repressor molecules is not bound to DNA b This analysis shows that the lac repressor is partitioned between nonspecific sites and the operator When it is not bound to the operator it is bound elsewhere to any of about 46 million sites in the genome Almost none of the repressor is unbound to DNA in the cell c Box 2 below goes through these calculations in more detail Box 2 Effectively all repressor protein is bound to DNA 10 molecules 10 make602 X 1023 molec mole 1 R 17 X10 8M I 4t0tul cell 1071511 Dm 46 X 105sites 46 X 1053ites 602 X 1023m0lecules m0le 764X104M cell 103915L K NS 2 105M1 RAIDNs X R4 1 1 RADNS KNSDNS 2 x105M 1764x10 3M 65X10 5 BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase 6 Regulation of the lac operon via redistribution of the repressor to nonspecific sites in the genome a The high specificity of repressor for the operator means that in the absence of inducer the operator is bound by the repressor virtually all the time This is true despite the huge excess of nonspecific binding sites b The specificity parameter described above KsKm allows one to evaluate the simultaneous equilibria repressor for operator and repressor for nonspecific sites on the DNA We want to calculate the ratio of repressor bound operators to free operators Values for KS KNS and DNS are already known and the concentration of repressor not bound to DNA is negligible Box 3 Speci city parameter is related to ratio of bound to free operator sites RAD Ks R4 Dr R4DS DNS Spec1f1c1ty Km R4 DNS Dy X R4DNS RAIDNs ratio of BoundFree operator sites Now we need a value for R4DNS This is obtained by realizing that under conditions that saturate specific sites the concentration of repressor bound to nonspecific sites is closely approximated by repressortotal operator or R4total D5total in the equations in Box 4 Box 4 RADNS R4taml R4DSl R4free R4fm is negligible see above Under conditions that saturate specific sites RADS E Dslmut Thus R4DN S R4oal 39 Dstotal 17gtlt10 9M lsite 1 make602 X 1023 molec mole 1 S W cell 1015 L DNS 7 x10 3M BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase c After making these simplifying assumptions we now have a value for every variable and constant in the equation except the ratio of boundfree operator sites Thus we can compute the desired ratio Box 5 Equation relating speci city to the ratio of bound to free operator and a set of constants s ecificit 5 R D D P y X KNS D5 ltlitul D5 1mm T T T already want to constants measured detennine d Now that we have the equation in Box 5 we can calculate the ratio of free operator to operator bound by repressor can be calculated in the absence and presence of inducer 51 In the absence of inducer K Specificity S 107 NS DS KNSX DNS LX 764x10393M R4DSKS R4Wl DSWI107 17x10399M 17gtlt10 9M D J T igtlt499gtlt10S 0049950050 R4DS 10 quot e the ratio of free operators to operators bound by repressor is 005 R4 is bound to the operator 5 of the time Thus the operon is not expressed 32 In the presence of 1nducer K Specificity S 104 NS g i4x499x10550 0r T Luoz R4DS 10 D3 Eie in the presence of inducer only about 2 of the operators are bound by repressor or R4 is Ebound to the operator 2 of the time Thus the operon is expressed m BMB400 Part Four 7 II Chpt 1397 Transcriptional regulation by effects on RNA polymerase In summary these calculations show that in the absence of inducer 95 of the operators are occupied a is bound by R4 95 of the time In the presence of inducer the repressor rerdistributes to nonspecific sites on the DNA leavin onl 2 of the operators bound by R47 Thus the operon is exprased in most of the cells An additional example of the use of the measured binding constants and the specificity parameter is in Appendix B at the end of this chapter This example explores the effects of operator mutants F Mechanism of reprasion and induction for the lac operon 1 Effect of lac repressor on the ability of RNA pol merase to bind to the promoter The analysis in the previous section showed how the inducer affects the partitioning of the repressor between specific and nonspecific sites Now let39s examine the effect that repressor bound to the operator has on the function of the polymerase at the promoter Figure 419 Repressor increases affinity of polymerase for promoter RNA polymerase 63 Q or U 1 o 339 4 aIhLgtilt k 35 10 1 11 KBKS19x1o7 M1 Promoter Operator Re ressor a 13 y k V V 2 KB KS 25x1o9 M1 BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase a Binding of repressor to the operator actuallv increases the aff mitv of the RNA polymerase for the promoter Consider the following equilibrium RNA polymerase promoter Z RNA polymerase promoter closed complex In the absence of repressor on the operator the affinity of RNA polymerase for the lac promoter is KB 2 19 x107 M 1 In the presence of repressor on the operator the affinity is KB 2 25 x109 M 1 b Repressor bound to the operator increases the affinity of RNA polymerase for the lac promoter about 100 fold so the closed complex is formed much more readily The repressor essentially holds the RNA polymerase in storage at the promoter but transcription is not initiated c Upon binding of the inducer to the repressor the repressor dissociates and the RNA polymerase promoter complex can shift to the open complex and initiate transcription thus switching on the operon d Thus the effect of repressor bound to the operator is not on Kb for the polymerase promoter interaction but rather is on kf for the conversion from closed to open complex G Kinetic measurements of the abortive initiation reaction allow one to calculate kf 1 Abortive Transcription Assay The initial transcribing complex ITC that exists after open complex formation frequently fails to transform into the initial elongating complex IEC The RNA product is released and the system initiates again The rate at which the aborted transcripts accumulates can provide a measure of promoter strength and experiments have been devised to use such an assay to estimate KB for polymerase binding to the promoter region and kf for isomerization from closed to open complex form Polymerase promoter DNA and nucleotides are mixed such that a radiolabeled phosphate will be introduced into transcripts that are made and aborted The amount of radioactivity in the short transcripts is then counted as a function of time BMB400 Part Four 7 II Chpt l7 Transcriptional regulation by effects on RNA polymerase Fig 4210 Abortive initiation assay Let R RNA polymerase P promoter closed and Po promoter open K k ATPUTP RP 5 RP 12 Rpo kr Apupu Abortivetranscripts time There is a lag between mixing reagents and optimal rate of abortive transcript production The length of this lag is inversely proportional to the RNAP A plot oflagetime Vs lRNAP giVes a straight line plot with slope equal to lKB x kf and yeintercept of lkf Fig 4211 Measure kf and KB from lag time vs 1R Lag time in abortive initiation assay is inversely proportional to R Lagtime 1 x 1 1 KB kr R kt Lag time Y intercept 1 kt mama m mp u z cm 17 mmcnptmnal gunman by men an RNA palymuase a Acmmnnfnumuphnnhymz CAP pmunnfE call 1 Athvn nn m txme by 0 CAP pm am can mushus mull guluil xeguhtmy pimps We mu m an m pm m m mum mums mm pmmmus a slug pmmn can uently mm mm mm m a 1m 2 msum cantam suf ces Depemmgan m mm cm can arm K5 ax mm WA pulymzmer pmmm mmacunm m mme um mmch taxman mm mm mm mm mum mmnsy ase macs mum zvd m mmlmy zmyymu mm m Mm mm xszuhe mm was mm quotHm 1mm 1mm mmmm he Mammy z smumlnfRNAplymuag a Rana mmh ThIze thank a submmfRNA pulymuase mm sepala e damn m 3mm mrmmal damn mm 1 assume in dummaonn and assembly afpalymzlase am m cathaxy mm damam uCTD s medzd mthdmg m mm and fursmnmnmcaonn wnh many hm mm all manponn mm Mast RNA palymuase may 1 asmcxamd mm mm ax mm gems ms 1 accmnpllshzdhy a special sequnce lps eam a h pmmnmxelzmzms u e m 45am4unms gammy up 21mm 7575 7MM1TA1139H V m whlchhmds n dmls ammunases accnpancyhypalymzme nyqurmm mm a 7 Vi mm c DNA g 4 735 rl mm DNA 7 3 7 UP 735 710 n Much a h cammunlca un between amvatms and z m RNA pulymzmse s mama between m cm at at am thzse mm mama Rumour r u Chpt 17 T nscnpnunal legulanun bye ec39s unRNA pulymexase see Ebnghtand Emby 1995 Cun Opmmnm Gen Mm 5 1977203 Fig 4213 150 260 270 180 290 300 310 Ill an IIICTD I I CAP AraC Plv gr FN39R CysB P4d 39 MdR ompR OxyR mama m mp u z cm 17 mmcnptmnal gunman by men an RNA palymuase a Snmmgg ampDlsnnmans human 2 a Class Iamcap a Class n Pmmnms Fm nvxews 22 Ma Maw 23 5537559 am on 0pm Genn m 5 1mm Chslpxmnmusmve cm hmmng mescemmm 52 as my Nuts pmnmzxs xmcememmuamvemps m iidz ermmamaflhz pmmm mum mmmmxmmnpms a lJ 39 1mm DNA 7 9 Acmmr as an 510 a DNA 12an Fig oz u m mmmc CAPpmmms mewwmm Emmgmaclassl pmmm s shwn m pm c am hmmng m a class u pmmm s shwn m pm a o cmmmummmmmgmm ARI mm mm M class xpmmnm ARI mm Wmmammmmcw ms mamzm 255 at cm at a This mmaconn muses Ks fuxpalymuase hmmng m m pmmm M class n pmmm cm mm m mcrn mumgw mm avemamz by manaan K5 m npsnzam suhnnn ARLaCTD mmzconn m mm 19 2195 m A class pummel m auwmmmsnnnm msme nsmuzs 1527155 manaan k vnmmznn un mm chased m apen Campinas BMB400 Part Four 7 II Chpt 17 Transcriptional regulation by effects on RNA polymerase Fig 4215 Activation Regions on CAP Pllrplen s i FN39lemolng V gt g sstromnters Rail ARI Class 11 promoters At both class I and class II promoters CAP AR1 interacts with the CTD of on It is clear that for class I promoters residues 258265 of the or subunit are the target ofAR1 of CAP it is not clear ifthese are the same residues needed for interaction at class II promoters At class I promoters this interaction provides quottruequot direct activation the interaction is between the downstream subunit of CAP and appears to only be used to increase KB for the binding of RNA polymerase to the promoter region perhaps substituting for the lack of an UP sequence At class II promoters AR1 in the upstream subunit contacts the alpha subunit but it does not appear to cause direct stimulation of transcription Instead it overcomes inhibition of polymerase that is hypothesized to arise from CAP displacing the alpha subunit from its preferred position near 745 This is evidenced by the following observations 0 otCTD binds to 740 to 755 region at class II promoters in the absence of CAP but binds to the 758 to 774 region in its presence 0 AR1 mutants in CAP decrease KB for RNA polymerase at class II promoters but have no affect on kf 0 Removal of the or CDT eliminates the need for CAP AR1 in class II promoters and has no negative affect 0 In contrast removal of the or CDT prevents activation by CAP at class I promoters In addition to overcoming a decrease in KB by AR1 at class II promoters CAP also exerts a quotdirectquot activation This occurs between CAP residues 19 21 96 and 101 AR2 in the downstream subunit of CAP and residues 162165 of the or subunit NTD This interaction increases the kf and has no affect on KB Region 162165 is between regions 30755 65775 and 1757185 195210 which are essential for contact with the 5 and 539 subunits of polymerase respectively AR2 is not needed for CAP to work at class I promoters BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase Appendix A for Chapter 17 Part Four section 11 Measurement of equilibrium constants for binding of lac repressor to speci c and nonspecific sites in DNA R4 Repressor D S 2 Specific DNA site gt operator D NS Nonspecific DNA site gt all other sites in genome R4 DS 2 R4DS R4 DNS 2 R4DNS R4 39 Dr R4 DNS39 Tum KNSWRAIDM i253 K4R41 RADS 4 R AINS4 D5 2 2 0 01 02 3 pM 0 3 M 4 R4 R4 slope KS 4 2 x 1013M1 Km 4 2x 105M1 1x10 13M 1x10 M The lac repressor will bind to its specific site the operator with very high affinity Keq 2 KS 2 2 X 1013 M4 where Ks is the equilibrium association constant for binding to a specific site and it will bind to other DNA sequences or nonspeci c sites with a lower affinity BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase Keq KNS 2 X 106 M l where KHS is the equilibrium association constant for binding to a nonspecific site Measurements in the laboratom Since it can be difficult to measure the amount of bound or free probe at very low concentrations it is more reliable to measure the fraction of probe bound as a function of R4 The fraction of probe bound is R4Ds R4Ds R4Ds Ds Dsltotal 39 By substituting Ds Dst0tal R4Ds into the equation for Ks you can derive the following relationship between the fraction of probe bound by repressor and the concentration of the repressor R4Ds Kis4 Dsltotal 1 Since the R4 is usually much greater than the Dstota1 in these assays the R4lfree gtgt R4Ds and R4 is W611 aPPTOXimated by R4ltotal This equation has the form of the classic Michaelis Menten equation for steady state enzyme kinetics and it is also useful in analysis of many binding assays R4D Once m is plotted against R4 one can do curve fitting to derive a value for Ks One can also get a value for Ks by measuring the R4 at which half the probe 1 is bound At this point R4 This can be seen simply by substituting R4Ds m 05 into the equation above The algebra is exactly the same as is done for the determination of Km by the Michaelis Menten analysis BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase Appendix B Use of binding constants and the equations relating the speci city parameter to the ratio of bound to free operator sites to study the effects of operator mutants The same equations used in section E of this chapter also can be used to examine the effects of operator mutants The following analysis shows that a mutation that decreases the affinity of the operator 20 fold for the repressor will result in about half the operators being free of repressor or the operon being expressed about half the time KS 2 x 1013M1 for wild type 2gtlt1013M1 12 1 KS T 1gtlt10 M for the mutant K 1 1012M1 Specificity X M 05x106 5gtlt10S Km 2x10 M D D i l K i l 5 gtlt499gtlt10S 1241 Ks XR4Ds5x10 D5 0998 s 10 RADsl This says that the operator is essentially equally distributed between the bound and free form Ds1Ds1R4Ds DslDsl Ds1Ds1 Ds1 mew EL 1 050 Dsimal 2 50 of the operators are not occupied by repressor thus only about half of the operons will be expressed in a population of bacteria or any particular operon will be expressed about half the time BMB400 161 162 163 164 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase Questions for Chapter 17 Transcriptional regulation by effects on RNA polymerase The ratio RDS Ds is the concentration of a hypothetical repressor R bound to its specific site on DNA divided by the concentration of unbound DNA ie it is the ratio of bound DNA to free DNA When the measured RDsDs is plotted versus the concentration of free repressor R the slope of the plot showed that the ratio RDS Ds increased linearly by 60 for every increase of 1x1011 M in R What is the binding constant Ks for association of the repressor with its specific site The binding of the protein TBP to a labeled short duplex oligonucleotide containing a TATA box the probe was investigated quantitatively The following table gives the fraction of total probe bound column 2 and the ratio of bound to free probe column 3 as a function of TBP These data are provided courtesy of Rob Coleman and Frank Pugh TBP bound probe bound probe HM total probe free probe 010 0040 0042 020 016 019 030 033 05 040 044 078 050 052 11 070 062 16 10 071 245 20 083 488 30 087 669 50 093 14 10 097 323 20 099 99 Plot the data for the two different measures of bound probe Note that since the denominator for column 2 is a constant the ratio of bound to total probe will level off whereas the amount of free probe can continue to decrease with increasing TBP and thereby getting a continuing increase in the ration of bound to free probe What is the equilibrium constant for TBP binding to the TATA box What is the fate of the lac repressor after it binds the inducer How does the lac repressor prevent transcription of the lac operon BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase For the next two questions let39s imagine that you mixed increasing amounts of the DNA binding protein called APl with a constant amount of a labeled duplex oligonucleotide containing the binding site TGACTCA After measuring the fraction of DNA bound by API ie the fractional occupancy as a function of APl the data were analyzed by nonlinear least squares regression analysis at a wide range of possible values for AG The error associated with the fit of each of those values to experimental data is shown below the higher the variance of fit the larger the error 004 003 002 Variance of Fit 001 AG in kcalmole 165 What is the most accurate value of AG for binding of API to this duplex oligonucleotide 166 What is the most accurate measure of the equilibrium constant Ks for binding of API to this duplex oligonucleotide BMB400 Part Four II Chpt 17 Transcriptional regulation by effects on RNA polymerase For the next two problems consider a hypothetical eubacterial operon in which the operator overlaps the 10 region of the promoter Measurement of the lag time before production of abortive transcripts in an abortive initiation assay as a function of the inverse of the RNA polymerase concentration 1RNAP gave the results shown below The filled circles are the results of the assay in the absence of repressor and the open circles are the results in the presence of repressor bound to the operator 50 4 0 re pressor 30 no repressor 20 lag time in sec 10 0 I I I I I I I I I I I I I I I I 0 10gtlt108 20gtlt108 80x108 40gtlt108 1RNAP in M391 167 What is the value of the forward rate constant kf for closed to open complex formation under the two different conditions 168 What is the value of the equilibrium constant KB for binding of the RNA polymerase to the promoter under the 2 conditions
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