Occupancies in the DNA-Binding Pathways of Intrinsically Disordered

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Occupancies in the DNA-Binding Pathways of Intrinsically Disordered Helix-Loop-Helix Zipper Proteins Renee Vancraenenbroeck, and Hagen Hofmann J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.8b07351 • Publication Date (Web): 05 Sep 2018 Downloaded from http://pubs.acs.org on September 6, 2018

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The Journal of Physical Chemistry

Occupancies in the DNA-binding Pathways Disordered Helix-loop-helix Zipper Proteins

of

Intrinsically

Renee Vancraenenbroeck and Hagen Hofmann* Department of Structural Biology, Weizmann Institute of Science, Herzl St. 234, 76100 Rehovot, Israel Corresponding authors: [email protected] and [email protected]

Abstract. Quantifying the stability of intermediates along parallel molecular pathways is often hampered by the limited experimental resolution of ensemble methods. In biology however, such intermediates may represent important regulatory targets, thus calling for strategies to map their abundance directly. Here, we use single-molecule Foerster resonance energy transfer (FRET) to quantify the occupancies of intermediates along two parallel DNA-binding pathways of the basic helix-loop-helix leucine-zipper (bHLH-LZ) domains of the transcription factors cMyc and Max. We find that both proteins are intrinsically disordered with submicrosecond end-to-end distance dynamics. In mixtures of the proteins with their promoter DNA, our experiments identify the disordered conformers, the folded MycMax dimer, and ternary Myc-Max-DNA complexes. However, signatures of the intermediate along the alternative pathway, i.e., one domain bound to DNA, remained undetectable. This implies that disordered Max-DNA and Myc-DNA complexes are by at least 6 kBT higher in free energy than folded dimers of Myc and Max. The disordered monomer-DNA complex is therefore unlikely to be of importance for the regulation of transcriptional processes.

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Introduction The discovery of intrinsically disordered proteins (IDPs)1-3 changed our view on how proteins interact. The coupling between binding and folding, a cornerstone of IDP interactions, lead to a renaissance of induced fit (IF)4-5 and conformational selection (CS)6 models that date back to the seminal work of Koshland, Monod, Wyman and Changeaux. Translated to folding-coupled binding reactions of IDPs1, 7-10, the two models suggest folding to take place either before (CS) or after (IF) ligand binding. This difference is by no means subtle. For example, the IF model implies that in the absence of ligand, the ligand-bound conformation of a protein is not accessible while it is in the CS model. CS and IF define the two branches of a thermodynamic cycle and as such they are likely to be extreme pictures of the real scenario. Differentiating between IF and CS is of great mechanistic interest and requires knowledge about the order of events in time11. From a biological perspective however, the equilibrium occupancies of states along parallel pathways are of equal importance since they determine whether these intermediates could serve as regulatory targets, e.g., via posttranslational modifications. This is of particular importance for transcription processes that require a fine-tuned balance between transcriptional activators and repressors. Many intrinsically disordered transcription factors form 2:1 complexes with DNA, among them proteins of the basic helix-loop-helix leucine zipper (bHLHLZ) type12-13. Prominent representatives of this class of transcription factors are the intrinsically disordered proteins Max and Myc, the latter being a universal amplifier of gene expression14 whose deregulation is associated with more than half of human cancers15-16. In analogy with IF and CS, the binding of bHLH-LZ domains follows two possible routes13, 17-20: (i) the monomer pathway in which one protein binds DNA in a disordered state and folding then occurs on DNA after binding of the second protein, and (ii) the dimer pathway in which two proteins form a dimer first which then binds DNA (Fig. 1). In a series of elegant experiments, it has been shown that the monomer pathway is kinetically preferred for many dimeric domains13, 17-19, 21 including the Max-homodimer. The natural intermediate along this pathway is a disordered monomer that interacts with DNA via electrostatic interactions20, 22. The low specificity of this interaction has been suggested to allow dimeric transcription factors to locate their target site quickly without becoming kinetically entrapped at nonspecific sites23. Here, we aim at identifying the relative free energies of the intermediates along the monomer and dimer pathway of Myc and Max using single-molecule Foerster resonance energy transfer (smFRET) experiments. Even though factors such as crowding or post-translational modifications may affect these values in the actual intracellular environment, in vitro experiments provide important information about


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thermodynamic preferences that could indicate whether the intermediates along both pathways are biologically steerable. Methods The sequence of Myc (amino acids 353-434 from UniProt ID P01106-1) and Max (amino acids 22-102 from UniProt ID P61244-1) were provided by GenScript and are detailed in Table 1. After cleaving the N-terminal His6-tag followed by purification with C18 reversed-phase chromatography, the proteins were labeled with the FRETdonor AlexaFluor 488 (C5-maleimide) and the FRET-acceptor AlexaFluor 594 (C5maleimide) via thiol-maleimide chemistry. Reversed-phase chromatography (C18) was used to remove free label and to enrich the fraction of doubly labeled proteins. The correct mass of the proteins was confirmed via ESI-MS. An E-box containing hairpin with a 26-base stem 24 and a T4-loop (Table 2) was used as DNA-promoter sequence. Before use, the oligonucleotide was annealed by heating to 95 °C for 5 min followed by cooling on ice. Annealing was verified by 10 % polyacrylamide gel electrophoresis. The oligonucleotide was obtained from Sigma-Aldrich with HPLC-grade quality. Single-molecule fluorescence measurements were performed with a MicroTime 200 confocal microscope (PicoQuant) equipped with an Olympus IX73 inverted microscope with a 60x/1.2 water objective (Olympus). Linearly polarized light from a 485 nm diode laser (LDH-D-C-485, PicoQuant) was used to excite the FRET-dyes either in pulsed (40 MHz) or in continuous excitation mode. Fluorescent light passed through a dichroic mirror (ZT 470-491/594 rpc, Chroma), a long-pass filter (BLP01-488R, Semrock) and a 100 µm pinhole. Afterwards, the photons were either distributed onto two detectors (SPAD, Excelitas) using a dichroic mirror (T585 LPXR, Chroma) or they were first separated according to their polarization and then monitored with four detectors. Before reaching detection, the donor and acceptor emission was additionally filtered (FF03-525/50 (Semrock) and FF02-650/100 (Semrock). The arrival time of every detected photon was recorded with a HydraHarp 400M time-correlated single photon counting (TCSPC) module (PicoQuant). Pulsed interleaved excitation (PIE) was used to identify molecules without an active acceptor dye25-26. All measurements were performed at 23°C in 20 mM Tris-HCl pH 8.0, 5 mM MgCl2, 200 mM KCl containing 0.001% Tween 20 (Pierce) and 100 mM βmercaptoethanol. In addition, the surface of the quartz coverslips was coated with poly-L-lysine to prevent charge-driven surface adhesion of the positively charged proteins. Fluorescence bursts from individual molecules were identified by inter-photon times of < 100 µs and a threshold >75 photons per burst. The photon numbers were corrected for background, cross-talk, acceptor direct excitation at the excitation ACS Paragon Plus Environment


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wavelength of the donor, and the relative brightness of the dyes27. Histograms of transfer efficiencies were fitted with combinations of lognormal and Gaussian distributions28. For binding experiments with unlabeled protein, the width and position of the FRET-peaks were fixed to minimize the number of free fitting parameters, and the area under the histogram curve for each subpopulation was determined using numerical integration. For a disordered protein, the mean transfer efficiency obtained from a fit of the FRET histogram is linked to the donor-acceptor distance distribution P ( r ) via

E =

L

L

0

0

∫ E ( r ) P ( r ) dr ∫ P (r ) dr .

(R

Here, E ( r ) = R06

6 0

(1)

+ r 6 ) is the Foerster equation with R0 = 5.4 nm being the

Foerster distance at which the transfer efficiency is 50%. To extract an average distance of the disordered ensembles, equation 1 has to be solved numerically using an appropriate one-parameter model for P ( r ) . We followed recent approaches29 and used the self-avoiding polymer chain model (SAW)30 as an estimate for P ( r )

P ( r ) = 4π a (ν ) x 2+g exp −b (ν ) xδ 

(2)

with ν = ln RDA ln n being the length scaling exponent of the chain. Here, n is the number of bonds in the chain (nMyc = 96, nMax = 95) including the length of the dye linkers that were estimated to be equivalent to 9 peptide bonds31. The coefficients a (ν ) and b (ν ) are the solutions of the coupled system

1 = 4π a (ν ) b (ν )

−

3+g

δ

5+g  3+ g  −1  5+ g  −1 − Γ δ and 1 = 4π a (ν ) b (ν ) δ Γ  δ  δ   δ 

where Γ ( z ) is Eulers Gamma function. In addition, x = r bK with bK = 0.55 nm as Kuhn length29,

32

and the relations g = 1 6ν and δ = 1 (1 − ν ) . Since RDA and ν are

directly coupled, the only free parameter is the average donor-acceptor distance RDA. Equation 1 was solved numerically using Mathematica 10.3 to determine the unknown donor-acceptor distance RDA from the measured mean transfer efficiency E . We used nanosecond fluorescence correlation spectroscopy (nsFCS) to determine the donor-acceptor reconfiguration times of MYC and MAX33-36. The nsFCS data were obtained in a sub-population specific manner, thus excluding the contribution from molecules with an inactive acceptor. The auto- and crosscorrelation functions were globally fitted using


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g ( t ) = n−1 1− cab exp ( − ( t − t0 ) τ ab )1+ cc exp ( − ( t − t0 ) τ c ) 1+ cT exp ( − ( t − t0 ) τ T )  

(3)

The three terms in brackets describe photon antibunching (ab), conformational dynamics (c), and triplet blinking of the dyes (T). In addition, n is the effective number of molecules in the confocal volume and cab , cc , and cT are amplitudes. The correlation times τ ab , τ c , and the time origin t0 are global fitting parameters. Here, the global correlation time τ c describes the correlated decay in the donor and acceptor autocorrelation functions and the anti-correlated decay in the donor-acceptor cross-correlation function. Hence, τ c is directly related to the donor-acceptor distance dynamics and equation 6 can be used to extract the diffusion coefficient for the relative motion of donor and acceptor dyes. We performed two binding experiments to identify the interactions between Myc (C), labeled Max (X*), and DNA (D). The asterisk indicates the fluorescently labeled species. Let φi be the concentration of species i where Myc, Max, and DNA are indicated by the subscripts c, x, and d, respectively. To describe the experimental binding isotherms, we numerically solved the system:

φcφ x* = K12φ x*c φcφ d = K13φcd φ x*cφd = K 24φ x*cd φcdφ x* = K 34φ x*cd

(4)

with the corresponding mass balances

φc,0 = φc + φ x*c + φcd + φ x*cd φ x*,0 = φ x* + φ x*c + φ x*cd φd,0 = φ d + φcd + φ x*cd .

(5)

The subscript 0 indicates the total concentration of the pure components. Due to the low picomolar concentration of labeled Max (X*) and since we did not observe binding after the addition of 1 µM E-box to picomolar concentrations of labeled Max, we neglected the interaction between labeled Max with DNA in the model. We solved the system numerically and used global fitting of all available fractions from our two binding experiments using Mathematica 10.3. Finally, the sequence homology between Myc and Max was computed by clustering the amino acids into groups. The following groups were considered similar amino acids: hydrophobic residues (A, F, I, L, M, V, W), charged residues (D, E, H, K, R), polar, non-charged residues (N, Q, S, T, Y), and special amino acids (P, C, G). ACS Paragon Plus Environment


Values were calculated using the program Sim in the Sequence Manipulation Suite provided by bioinformatics.org.

Results We use smFRET in combination with nsFCS on freely diffusing molecules to distinguish between four possible states of the Myc-Max-DNA system: (i) the disordered monomers of Myc and Max, (ii) the folded heterodimer Myc-Max, (iii) the disordered domains bound to DNA, and (iv) the folded heterodimer in complex with DNA (Fig. 1). The Max- and Myc-sequences (Table) were each labeled site-specifically with AlexaFluor488 as a FRET-donor and AlexaFluor594 as a FRET-acceptor and monitored while diffusing freely through the confocal spot of our microscope37. The low protein concentrations (20 pM) in our experiments effectively suppress the formation of Max homodimers17, 38-39, which makes the disordered state of the proteins directly accessible. Both proteins exhibit high transfer efficiencies that indicate rather compact disordered conformational ensembles, in good agreement with recent NMR-results on the Max protein40 (Fig. 2A,B). The similarity of the transfer efficiencies of both sequences is likely a result of their high sequence homology (61%) that results in similar interaction energies between the amino acid residues in the disordered chains. To quantify the average donor-acceptor distance (RDA) of the disordered proteins, we used a self-avoiding polymer chain model30 that has recently been shown to be in good accord with experimental results from smallangle x-ray scattering and molecular simulations29, 32. Using eq. 1-2, we obtain RDA = 5.3 nm and RDA = 4.9 nm for Myc and Max, respectively. However, the use of a polymer model already assumes that both proteins are extensively intrinsically disordered. We therefore confirmed the disordered nature of the proteins by monitoring the donor-acceptor (DA) distance fluctuations down to sub-microsecond time-resolution using nsFCS33-36, 41. In contrast to folded proteins, disordered proteins exhibit pronounced fluctuations of their donor-acceptor distance33 that cause distinct and anti-correlated fluctuations in the photon rate of donor and acceptor. Contrary to standard nsFCS-experiments that are typically performed at nanomolar concentrations34, we performed these experiments at low picomolar concentrations to exclude molecules with inactive acceptor dye in the analysis33, thus allowing a better comparison of the correlation amplitudes between different experiments. The correlation functions exhibit a pronounced decay for both proteins (Fig. 2C,D) and a positive amplitude in the autocorrelations of donor (gDD) and acceptor (gAA) together with a negative amplitude in the donor-acceptor cross-correlation functions (gAD/DA) unambiguously assigns this component to the changes in the distance between donor


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and acceptor33-36, 42. As expected for IDPs33-36, the donor-acceptor distances of Myc and Max fluctuate on nanometer length-scales. A global fit of the three correlation functions for each protein (eq. 3) results in correlation times of τ c = 88 ns for Max and τ c = 110 ns for Myc. To allow a quantitative comparison of these timescales with previous results on other IDPs and unfolded proteins33-36, 43-44, we modeled these dynamics as a diffusive process in the potential of mean force given by the selfavoiding chain model. In this picture, the measured correlation time τ c obeys a direct relationship to the intra-chain diffusion coefficient D given by42

r



0 δn (r) = n (r) − n .



L

τ c = D−1 ∫ P ( r )  ∫ δ n ( ρ ) P ( ρ ) d ρ  0

−1

r

∫ δ n ( r) P ( r) dr 2

with

0

(6)

where P ( r ) is the donor-acceptor distance distribution (eq. 2) determined from the mean transfer efficiency (Fig. 2A) and n ( r ) is the photon count rate of the donor dye42. As a result, we obtain intra-chain diffusion coefficients of 0.035 nm2/ns and 0.04 nm2/ns for Myc and Max, respectively. Both values are well within the regime of previous results on unfolded and intrinsically disordered proteins34-36, thus corroborating the flexible nature of the disordered monomers of Myc and Max. Monitoring intermediates along two parallel pathways To estimate the relative free energies of intermediates along the two DNA-binding pathways, we start with the dimer pathway. Here, the Myc-Max dimer is the intermediate. By adding unlabeled Myc to labeled Max in the absence of DNA, we trigger the formation of Myc-Max complexes. Unlike Max, Myc has a low selfaffinity and does not form homodimers such that the binding experiments directly report on the Myc-Max affinity. The heterodimers are visible as a population with low transfer efficiency and its relative abundance increases monotonously with increasing concentration of unlabeled Myc (Fig. 3A). The transfer efficiency of this population (E = 0.28) corresponds to a donor-acceptor distance of 6.3 nm, which is in good accord with the extended helical NMR-structure found for the Max homodimer in the absence of DNA45. By increasing the concentration of unlabeled Myc, we completely shift the occupancies from disordered Max to folded Myc-Max. The relative areas of the FRET-peaks directly provide the fraction of dimer and a fit with a simple binding isotherm results in a dissociation constant of K12 = 83 ± 11 nM (Fig. 3B). Hence, in the absence of E-box DNA, the intermediate along the dimer pathway forms with high affinity and the Myc-Max dimer is by ∆G12 = 16 kBT more stable than the dissociated monomeric states ( ∆G12 = − ln K12 ).



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Along the alternative monomer-pathway (Fig. 1), the intermediate corresponds to disordered Max or Myc in complex with the E-box promoter DNA. This complex has so far only implicitly been inferred for Max17, 19, and it is unclear whether the monomers exhibit secondary or even tertiary structure in complex with DNA. To study the interaction of monomers with DNA, we use a 26 bp double-stranded DNA hairpin containing the E-box motif CACGTG in the center of the helix24 (Table). However, the addition of 1 µM E-box to picomolar concentrations of doubly labeled Max and Myc did not cause a significant change in the FRET-histogram of the proteins (Fig. 4A). This result indicates that the DNA-complexes of the disordered proteins are either insufficiently populated to be detected in our experiment or, the DNA-bound proteins exhibit a FRET-efficiency similar to that of the unbound proteins. To distinguish between both alternatives, we used subpopulation-specific nsFCS to monitor the chain dynamics in the presence of E-box DNA. Even if the mean transfer efficiency remains unaltered by DNA-binding, it is unlikely that the dynamics of the DNA-bound monomers are unaffected by the interactions with DNA. However, a comparison shows that the correlation functions for Myc and Max are indeed unaltered by presence of E-box DNA (1 µM) (Fig. 4B and 2B). Within the error of our analysis, the correlation times and the amplitudes of the correlation functions are unchanged by the presence of E-box DNA with diffusion coefficients 0.034 nm2/ns and 0.044 nm2/ns for Myc and Max, respectively. The similarity of the amplitudes is particularly important since the amplitudes of the correlation functions are substantially influenced by the position and width of the distance distribution. We can therefore conclude that the distance distribution and therefore also the conformational ensemble of Myc and Max remain unaffected by the presence of DNA. Thus, if Max and Myc bind DNA in their monomer forms, their dissociation constant must be significantly larger than 1 µM. In fact, we can provide a more precise limit for the dissociation constant of this interaction. The sensitivity in our experiment allows us to identify populations with an occupancy greater than 3%46. In general, with a detection limit p, the lower limit of the dissociation constant is given by

K13 >

1− p d0 − (1− p) x0 . p

(7)

Here, d0 and x0 are the concentrations of DNA and labeled protein, respectively. Since the picomolar concentration of labeled protein is negligible ( x0 = 20-50 pM) compared to that of the E-box DNA ( d0 = 1 µM), the second term in eq. 7 has only a minor impact. With p = 0.03 we therefore find K13 ≥ 30 µM as a lower limit for the dissociation constant, which is thirtyfold higher than previous estimates17 and indicates that monomer-DNA complexes are rather unstable intermediates. In


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consequence, the second step in the monomer pathway (Fig. 1A), e.g., the binding of Max to a Myc-DNA complex, has to have a high affinity to provide a sufficient stability of Max-Myc-DNA complexes. To determine this affinity, we performed binding experiments in presence of all three components Myc, Max, and E-box DNA. We used labeled Max at low picomolar concentrations (50 pM) in the presence of 225 nM unlabeled Myc. Under these conditions, more than 70% of doubly labeled Max is bound to Myc in the absence of E-box DNA (Fig. 5A). When adding E-box DNA, the populations of Max and Myc-Max dimer decrease monotonously and a third peak emerges with a FRET-value that is even lower than that of the Max-Myc dimer (Fig. 5A). This is the behavior expected for the formation of a ternary MaxMyc-DNA complex. While the N-terminal DNA-binding region remains disordered in the folded dimer45, x-ray structures show that this region has helical structure in complex with cognate DNA47. Since our FRET-dyes are positioned N- and Cterminally of the bHLH-LZ region, the formation of this helix increases the donoracceptor distance, thus causing a transfer efficiency that is even lower than that of the Myc-Max dimer in the absence of DNA. Our experiments therefore clearly resolve monomers, heterodimers, and ternary DNA complexes whereas monomer-DNA complexes are too high in free energy to be detected. Given the thermodynamic cycle for the two parallel DNA-binding pathways (Fig. 1A), we are now in the position to determine the affinities of the second steps along each pathway. For the dimer pathway, K12 and K 24 are the affinities for forming a dimer and a ternary dimer-DNA complex, respectively. Along the monomer pathway, K13 and K 34 are the affinities of forming the monomer-DNA complex and the dimer-DNA complex, respectively. Since the thermodynamic cycle constrains one of the three equilibrium constants via K12 K 24 = K13K34 , our estimate of monomer-DNA interactions ( K13 > 30 µM) together with that of the Myc-Max affinity in the absence of DNA ( K12 = 83 ± 11 nM), suffices to determine the missing affinities K 24 and K 34 . A global fit of the relative populations in the DNA-binding experiment results in K 24 = 4.2 nM and K 34 < 12 pM (Fig. 5B). As expected, binding of a second monomer to monomer-DNA complexes ( K 34 ) requires a very high affinity. The distribution of free energies along the two parallel pathways is therefore highly asymmetric. While the intermediate along the dimer pathway is stable and well populated ( ∆G12 = -16 kBT), the monomer-DNA complex is by 6 kBT less stable ( ∆G13 = -10 kBT). The reason for this low DNAaffinity of the disordered monomers likely results from avidity48. The x-ray structure of Myc-Max-DNA complexes shows that DNA interactions of the Myc-Max dimer are mainly formed via two N-terminal basic regions47. According to our results, this interaction lowers the free energy of the dimer-DNA by 19 kBT (K24 = 4.2 nM) relative to that of the free dimer. Assuming that the N-terminal basic tails of Myc and Max contribute equally to this interaction, the removal of one tail would lower the free energy gain by a factor of 2. This substantial drop would result in an expected



DNA-affinity of K13 = 63 µM for a monomer, which indeed is consistent with the limit K13 > 30 µM based on our detection sensitivity. Of course this naïve estimate neglects the multitude of interactions between the disordered chain and DNA that are not present in the dimer-DNA complex. Nevertheless, the order of magnitude is in good accord with our results and the avidity of the basic tails seems to key for the high dimer-DNA affinity. We would like to note that these results are not in conflict with an earlier 17 study that demonstrated a faster association of Max via the monomer pathway compared to the dimer pathway. Our experiments were performed under equilibrium conditions and therefore only probe the relative stabilities and abundances of the formed complexes. Hence, the monomer pathway may represent a faster route towards ternary bHLH-LZ/DNA complexes despite the fact that the intermediate along this pathway is only marginally populated.

Estimating the relevance of the monomer pathway at cellular conditions The described asymmetry between the two alternative pathways does not necessarily mean that monomer-DNA complexes are irrelevant under cellular conditions since the equilibrium concentrations of complexes depends on the concentrations of monomers and DNA in the cell. The intracellular abundance of Myc or Max is likely to be much higher than the picomolar concentrations used in our experiments. In fact, the copy number of Myc in cancer cell lines is estimated49 to be in the order of 105. Unfortunately, absolute concentrations for Max are not available. However, Max is known not to be a particularly abundant protein50 and we arbitrarily assume that its concentration is tenfold smaller than that of Myc. Using the average volume of a cell nucleus (~200 fl)51-52, we obtain a Myc-concentration of ~800 nM if we assume that all Myc proteins reside in the cell nucleus. An upper estimate of Myc-controlled loci in the genome is ~429653, which gives an estimate of ~35 nM for the concentration of DNA-binding sites in the nuclear volume. With these numbers and our affinities for the monomer pathway, we find that the percentage of DNA-sites with a monomer bound is ~ 0.2% (9 sites) whereas ~ 91% (3909 sites) of the sites would be decorated with Myc-Max dimers. Since this estimate neglects that DNA binding-sites may already be covered by other regulatory proteins, the actual number of monomer-DNA complexes may even be lower. Unless other factors such as post-translational modifications increase the monomer-DNA affinity, it therefore seems unlikely that monomer-DNA complexes are regulatory targets for Myc-related transcription processes. Conclusion


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Determining the free energies of intermediates along parallel pathways is inherently challenging due to the need of distinguishing between different molecular species. Here, we used single-molecule fluorescence spectroscopy to distinguish the individual populations of the two intrinsically disordered bHLH-LZ domains Myc and Max in the presence and absence of promoter DNA. The capability of our experiments to distinguish between disordered monomers, folded dimers, and ternary protein-DNA complexes allows us to estimate all equilibrium constants of the thermodynamic cycle without further assumptions. While the Myc-Max dimer, an intermediate towards Myc-Max-DNA complexes along the dimer pathway, forms with high affinity, the intermediate along the alternative monomer pathway, a monomer bound to DNA, is high in free energy. Thus, despite the fact that the monomer pathway is kinetically preferred, the intermediate along this pathway is only marginally populated and therefore unlikely to be of relevance in transcriptional regulation. In addition, protein synthesis preferably occurs in the cytosol such that dimers between Myc and Max and other bHLH-LZ or bHLH proteins can already pre-form in the cytosol. We therefore conclude that monomers, dimers, and dimer-DNA complexes are the biologically relevant species. Acknowledgement This research was supported by the Israel Science Foundation (ISF) grant no. 1549/15, the Benoziyo Fund for the Advancement of Science, the Carolito Foundation, The Gurwin Family Fund for Scientific Research, and The Leir Charitable Foundation.



Table. Amino acid sequences of Myc and Max, and sequence of the DNA hairpin. Labeling positions are underlined. The DNA E-box is underlined, the TTTT-loop in the hairpin is in italic.

Protein

Sequence

MYC

GPGCSGNVKRRTHNVLERQRRNELKRSFFALRDQIPELENNEKAPKVVILKKATAYILSVQAEEQKLISEEDLLRKRREQLKHKLEQLGSC

MAX

GPGCSGADKRAHHNALERKRRDHIKDSFHSLRDSVPSLQGEKASRAQILDKATEYIQYMRRKNHTHQQDIDDLKRQNALLEQQVRALGSC

DNA

5’-TGAAGCAGACCACGTGGTCGTCTTCATTTTTGAAGACGACCACGTGGTCTGCTTCA-3’

Figures Figure 1. Scheme of the thermodynamic cycle of the monomer and dimer pathway for Myc, Max, and DNA. Along the dimer pathway (red), Max and Myc first form a heterodimer (K12) that subsequently binds to the E-box element on DNA (K24). The alternative pathway is the monomer pathway (blue). Here, one of the two monomers (Myc or Max) first bind to DNA (K13), presumably in a disordered conformation, and the binding of the second monomer then results in the formation of the ternary Myc-Max-DNA complex (K34). Figure 2. The properties of disordered Max and Myc. (A) FRET histograms of Max (top) and Myc (bottom). Black lines are fits with a Gaussian function. Colored bins contain molecules with active acceptor dye. (B) Sub-population nsFCS correlation functions of Max (top) and Myc (bottom). The donor (green) and acceptor (red) autocorrelation functions and the donoracceptor (blue) crosscorrelation functions have been fit globally using eq. 3. For a better comparison, the functions are corrected for the triplet-decay and number of molecules in the confocal spot. Figure 3. The interaction between Max and Myc. (A) FRET histograms of labeled Max at increasing concentrations of unlabeled Myc (concentrations indicated). The red and blue shaded peaks are the disordered Max monomer and the folded Myc-Max dimer. The proteins fold in a synergistic folding-coupled binding reaction (scheme right) (B) Fractions of folded Myc-Max dimer as a function of the Myc-concentration. The black line is a fit with a binding isotherm. The blue shaded area indicates the 90% confidence band of the fit. Figure 4. The properties of disordered Max and Myc in the presence of 1 µM E-box DNA. (A) FRET histograms of Max (top) and Myc (bottom). Black lines are fits with a Gaussian function. Colored bins contain molecules with active acceptor dye. (B) Sub-population nsFCS correlation functions of Max (top) and Myc (bottom). The donor (green) and acceptor (red) autocorrelation functions and the donor-acceptor (blue) crosscorrelation functions have been fit globally using eq. 3. For a better comparison, the functions are corrected for the tripletdecay and number of molecules in the confocal spot.


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Figure 5. The interaction between Max, Myc, and DNA. (A) FRET histograms of labeled Max in the presence of 225 nM unlabeled Myc at increasing concentrations of DNA (concentrations indicated). The red, blue, and green shaded peaks are the disordered Max monomer and the folded Myc-Max dimer, and the ternary Myc-Max-DNA complex. (B) Fractions of the three states shown in A as a function of the DNA concentration. The black lines are global fits with the thermodynamic cycle (Fig. 1) with only one free parameter (K24).



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Myc

1

Max

K12

Myc

DNA

Max

2

DNA Dimer

Pathway

K13

Monomer

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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K24

Pathway Myc

3

Max

K34

DNA

Myc

4

DNA ACS Paragon Plus Environment

Max

A

B

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Max

Max

300

1.5

200

1.0

Correlation amplitude gij(t)

Number of molecules

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


100 Myc 200 100 0.0

0.2 0.4 0.6 0.8 Transfer efficiency (E)

1.0

0.5 Myc 1.5 1.0 0.5 -400


-200

0 200 Lag time t (ns)

400


A

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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labeled Max

0 nM

K12

Number of molecules

20 nM unlabeled Myc

50 nM

B Fraction complex

125 nM

250 nM

500 nM 0.0

0.2 0.4 0.6 0.8 Transfer efficiency

1.0

Myc-Max

1.0 0.8 0.6 0.4 0.2 0.0 0.1


1 10 100 1000 Myc concentration (nM)

4 10

A

B

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Max

Max 1.5

200 Correlation amplitude g (t)

Number of molecules

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


100

Myc 200 100 0.0

0.2 0.4 0.6 0.8 Transfer efficiency (E)

1.0

1.0 0.5 Myc 1.5 1.0 0.5 -400


-200

0 200 Lag time t (ns)

400

The Journal of Physical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


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Occupancies in the DNA-Binding Pathways of Intrinsically Disordered

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