The lac repressor-operator system: Swimming in Data - PowerPoint PPT Presentation

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The lac repressor-operator system: Swimming in Data

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  1. The lac repressor-operator system:Swimming in Data • Collaborators: • Mitch Lewis, Bob Daber, Leslie Milk, Matt Sochor, Chuck Bell, Steve Stayrook • Thermodynamics of Allostery • Kinetics of Allostery: Induced Fit or Landscape Shift? • Large Scale Analysis of base sequence specificity/affinity

  2. Repressor has two conformations R: Active form, binds DNA tightly, Inducer weakly R*: Induced form, binds DNA weakly, Inducer tightly

  3. Repressor binds O1 operator site >1000 more tightly than non-specific DNA

  4. Symmetrized O1 operator G4 T5 G6 Q18 R22 Y17 Position L87654321.12345678R Base TTGTGAGC.GCTCACAA Residue RQY YQR / | \ aa number 22 18 17

  5. How does the lac genetic switch work? Mechanism of allostery Thermodynamics Kinetics The origin of base sequence specific recognition of DNA by proteins Prototype for gene therapy Design of Tools for DNA manipulation Cronin, et al lac operator-repressor system is functional in the mouse Genes & Dev. 2001. 15: 1506-1517

  6. in-vivo system for evolution and functional characterization of lac repressor (Lewis Lab) Expression/Assay System Two plasmid system: one contains a Lac repressor gene other contains the GFPmut3.1 gene controlled by the Lac promoter and a given operator. FACS used to screen and separate phenotypes by GFP fluorescence. Directed evolution: Randomize plasmid sequence corresponding to given aa positions in repressor Screen for given phenotype Engineered heterodimer: Permits assymmetric DNA recognition domains to target non-symmetric Operator Sequences Knockout one inducer site: Probe allosteric mechanism

  7. E. Coli with GFPmut3.1 reporter and repressor plasmid Fluorescence quantified by plate reader Fractional GFP expression relative to that with no repressor plasmid Induced by IPTG

  8. MWC model for Allostery KRR*: Repressor conformational equilibrium (Induced/active) KIR*, KIR: Inducer binding affinities for induced, active repressor KR*O, KRO: Operator DNA binding affinities for induced, active repressor

  9. MWC model for Allostery O/(O+RO)-> Transcription (mRNA) -> Translation (GFP level) Fractional GFP expression with no inducer Fractional GFP expression at saturation (n=1 inducer site) (n=2 inducer sites)

  10. Repressor Conformation Equilibrium [R*]/[R] = 2 Inducer Binding Affinity Ratio KIR*/KIR = 15 In Vivo Repressor Concentration [R]KRO = 150 Inducer-Repressor Binding Affinity KD,IR* = 4uM All constants are obtained in vivo, without doing a single binding measurement!

  11. KRR*=2 in ‘wrong’ direction. DG 0 This explains why Xtal structures of lac with and without IPTG bound are so similar But why is Repressor conformational equilibrium so weak? DG to drive conformational change available from inducer binding is about 1.6 kcal/mole, or about 3.2kcal/mole total, a fairly modest amount

  12. Cell achieves effective repression in spite of weak equilibrium by setting [R] at 150-fold excess Lac Switch has evolved to combine effective switchability given modest driving force from inducer binding, balancing the conflicting requirements of repression and induction

  13. Comparison of Allostery in lac and Hb Lac Hb # of ligands 2 4 Binding Ratio 15-20 30 Conf. Equilibrium 2 1/1000 Hill # 1.2 >3 Comparison of equilibrium constants with previous in vitro studies

  14. ‘Classic’ view of ligand induced conformational change of a protein Ligand L binds, induces conformational change A->B (induced fit) B is of higher free energy than A L binds to B tighter than to A, so now LB has lower free energy than A or LA B A L DG

  15. ‘New’ view of ligand induced conformational change of a protein Protein exists in an ensemble of conformations A, B, C….. Higher energy forms less populated. L binds to and ‘selects’ one of the higher energy conformers, lowering its free energy so it becomes the dominant form This is the population selection model, aka the protein landscape model, the protein ensemble model B L A DG

  16. …applied to the Lac-Operon system RO R+O I I RIO RI+O Low inducer, R binds O tightly

  17. …applied to the Lac-Operon system R+O RO I I RI+O RIO High inducer, R dissociates from O

  18. Population selection route? R+O RO RI+O RIO Induced fit route? …applied to the Lac-Operon system This can only be determined by kinetics, not equilibria. Lac is one of the few systems where there is enough kinetic data to definitively discriminate

  19. …applied to the Lac-Operon system 2x109 /M/s RO R+O I I 0.08 /s 5x104 /M/s 0.2 /s 5 /s 5x104 /M/s 40 /s RIO RI+O 2x109 /M/s Association rates depend on concentration In cell, [R] = 1nM [I] varies

  20. …applied to the Lac-Operon system Time constants for various steps at I = 1uM 0.5 s RO R+O I I 12 s 20 s 5 s 0.2 s 20 s 25 ms RIO RI+O 0.5 s

  21. …applied to the Lac-Operon system Time constants for various steps at I = 10uM 0.5 s RO R+O I I 12 s 2 s 5 s 0.2 s 2 s 25 ms RIO RI+O 0.5 s

  22. …applied to the Lac-Operon system Time constants for various steps at I = 100uM 0.5 s RO R+O I I 12 s 0.2 s 5 s 0.2 s 0.2 s 25 ms RIO RI+O 0.5 s

  23. PS route R+O RO RIO RI+O Flux at 1uM IPTG (below induction midpoint) RO→R+O RO+I→RIO RIO→RI+O

  24. R+O RO RIO RI+O IF route Flux at 10uM IPTG near midpoint RO+I→RIO RIO→RI+O RO→R+O

  25. R+O RO RIO RI+O IF route

  26. Repressor is leaky-This is functionally important, since in vivo inducer is metabolic product of enzymes repressed by lac • Leakiness is directly related to repressor-operator affinity, KRO Changes in leakiness, as measured by GFP levels, due to mutation/base changes → R-O affinity changes

  27. Screening for functional Repressor-Operator Sequence Pairs Functional Rules for Lac Repressor-Operator Associations and Implications for Protein-DNA Interactions Milk, Daber and Lewis,Protein Science (2010) Vol 19. A library of Lac mutants, fully randomized at positions 17, 18 and 22 screened against 64 symmetric Lac operator variants. Functional repressors sequenced, purified and assayed with the corresponding operators. Lower GFP expression = Tighter binding. Increase in GFP by IPTG = Inducibility. GFP levels in absence of inducer (leakness) used to calculate change in Repressor-Operator affinity relative to wild type (YQR-GTG). Changes in affinity occur due to localized sequence changes in 3 aa’s or 3 bp’s within the framework of the rest of the lac-operator

  28. Base sequences recognized by a given aa triplet sequence AA    Bases                            AA    Bases                AAN   TGA   TTA                        HNR   GTG                AAR   GAG   GGA   GTA                  HQN   TTT                ACR   GAA   GCA                        HQR   GTG                AGN   TGA   TTA                        HSN   TGG   TTT             AGR   GAA   GGA   GGG   GTA   GTG      HSR   GAG   GAT   GGG   GTG       AIR   GGT                              HTA   CTT                AKN   TAC                              HTK   CTT                AKR   GAC                              HTN   TTG   TTT             AMR   GAT   GGT   GTG                  HTR   GTA   GTG             ANR   GTG                              HVR   GTA                APR   GAA                              HYR   GTG                AQR   GAT   GGG   GTG                  IAA   CTA                ASA   CGA   CGT                        IAF   CTA                ASL   TAG                              IAG   CTA                ASN   TGA   TGG   TGT                  IAN   TGA   TTA             ASR   GCA   GGG   GGT                  IAR   GAA   GTA             ASS   CGA                              IAY   CTA   TTA             ... CAN   TTA                              IGR   GAA   GGA   GTG   TAA       CMR   GGT   GTG                        IKR   GAC                CQR   GTG                              IMR   GAG                CSR   GGG   GGT                        INR   GTG                CTR   GAA   GGA   GGT                  IQR   GTG                DAR   GTA                              ISL   CGA                EAR   GTA                              ISR   GAA   GCA             EMR   GTG                              ITR   GAA   GCA   GTG          ESR   GGG                              IWK   CTA                FAR   GAA                              KAN   TGG                FKR   GAC                              KAR   GAG   GGG             FMR   GTG                              KGR   GTG                GAN   TTA                              KMR   GGG   GTG             GAR   GAA   GCA   GGA   GTA            KNR   GGG                GCR   GAA                              ...    ...         GGR   GTG                              YQR   GTG  (Wild Type)      GKR   GAC                              YTR   GTG             196 Different AA sequences 26 Different Base sequence

  29. AA sequences recognized by a given Base triplet sequence AGG CGA CGG CGT CTA CTT GAA GAC GAG GAT GCA GGA GGC GGG GGT GTA GTG TAA TAC TAG TGA TGG TGT TTA TTG TTT KSL ASA KSA ASA IAA HTA ACR AKR AAR AMR ACR AAR GSR AGR AIR AAR AGR IGR AKN ASL AAN ASN ASN AAN HTN HMN     ASS KSC KSA IAF HTK AGR FKR HAR AQR ASR AGR     AQR AMR AGR AMR PAN PKN HGN AGN HGN KSN AGN     HQN     ATA KSL PSA IAG     APR GKR HCR HSR GAR ATR     ASR ASR ATR ANR PSN     KSL ASN HSN PSN CAN     HSN     ISL KSM TSA IAY     AVR IKR HGR PAR GSR AVR     CSR ATR DAR AQR         PAN ATN KAN TSN GAN     HTN     PSA KSY     ICK     CTR MKR HSR PMR GTR CTR     ESR AVR EAR CMR         PSN IAN KSA     HAN           PTA KTA     ICN     FAR NKR IMR SMR ISR GAR     GSR CMR GAR CQR         RSL LGN KSC     IAN           SSA KTD     ICY     GAR PKR KAR TMR ITR GSR     HGR CSR GTR EMR             PAN KSF     IAY           STA KTM     IWK     GCR SKR PAR     PCR GTR     HSR CTR HTR FMR             PSN KSG     IGN               KTN     TAA     GTR TKR PQR     PGR IGR     KAR GSR HVR GGR             PTN KSH     SAH                       TAY     HAR     RAR     PSR NTR     KMR GTR IAR GMR             TGH KSL     SAN                               IAR     RSR     SAR PVR     KNR KQR LAR GNR             TGN KSM     SAY                               IGR     SSR     SCR SGR     KSR KSR MAR GQR             KSS         SGN                               ISR             SSR STR     KTR KTR PAR GTR             KSY         STN                               ITR             STR TTR     NSR PIR PTR HAR             KTN         TAH                               LAR             TAR         NTR PVR QAR HCR             PSN         TAN                               MAR             TTR         PSR SMR SAR HGR             RSL         TAY                               MTR                         PTR SSR SCR HNR             RSN         TGN                               PCR                         QSR STR SGR HQR             SSN         VAN                               PVR                         RAR TMR STR HSR                         YAN                               QAR                         RGR TSR TAR HTR                                                  SAR                         RQR TTR TCR HYR                                                  SCR                         RSR VMR TGR IGR                                                  SGR                         RTR VTR TTR INR                                                  TAR                         SGR     VAR IQR                                                  TSR                         SSR     VYR ITR                                                  TTR                         STR         KGR                                                  VAR                         TGR         KMR                                                                              TSR         KQR                                                                              TTR         LMR                                                                              VSR         ...                          >300 aa-base pair combinations now screened. Now we have a Thermodynamic Model for Induction, all 300+ affinities can be extracted from the leakiness…

  30. AGG CGA CGG CGT CTA CTT GAA GAC GAG GAT GCA GGA GGC GGG GGT GTA GTG TAA TAC TAG TGA TGG TGT TTA TTG TTTAGG CGA CGG CGT CTA CTT GAA GAC GAG GAT GCA GGA GGC GGG GGT GTA GTG TAA TAC TAG TGA TGG TGT TTA TTG TTT Relative Affinity

  31. Origin of sequence specific Protein-DNA Recognition I. Given: 196 variants of Lac differing in aa sequence in the recognition helix, each of which bind specifically to different subsets of 26 DNA base pair sequences, for a total of 331 aa-bp complexes with known affinity. Extract as much sequence level information about specificity as possible to infer sequence recognition ‘rules’. Can take a ‘bioinformatics’ approach

  32. Analysis of aa-bp sequence pair recognition by clustering AA’s Bases Bipartite Graph partitioning

  33. Origin of sequence specific Protein-DNA Recognition II Given: 331 (and counting) amino-acid, base sequence variants and their relative affinities Identify the structural basis for sequence specific protein-DNA recognition using a conformational analysis approach, i.e. by searching through protein and base sequence/conformation space to generate Lac-DNA structural models that explain, and ultimately predict, which amino-acid sequences recognize which base sequences. What structural features determine high affinity, and/or sequence specificity? Can we predict, and so design, repressor sequences that will bind given lac-operator sequences, and more generally, bind any base sequence of the same length? EVOLVE: Searches in both protein and DNA sequence space, with full amino-acid, base rotamer exploration, torsional minimization. Simultaneously generations conformers for bound, unbound states, evaluates energy difference.

  34. If I’m lucky, my EVOLVE movie will work!

  35. Analysis of 75 or 331 amino acid base pair variants so far EVOLVE energy difference vs. Measured Affinity difference. Correlation coefficient = 0.66 Not bad: without full rotamer exploration (depth first), no solvent, and no binding entropy yet