Conformation-gated binding drives negative cooperativity in ATP:cob(I)alamin Adenosyltransferase for optimized cobalamin handling

Conformation-gated binding drives negative cooperativity in ATP:cob(I)alamin Adenosyltransferase for optimized cobalamin handling | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Conformation-gated binding drives negative cooperativity in ATP:cob(I)alamin Adenosyltransferase for optimized cobalamin handling Guangjie Yan , Manhua Pan , Aaron M. Keller , Ace George Santiago , Michael Lofgren , Ruma Banerjee , Peng Chen , Tai-Yen Chen doi: https://doi.org/10.1101/2025.01.07.631765 Guangjie Yan a Department of Chemistry, University of Houston , Houston, TX 77204 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Manhua Pan a Department of Chemistry, University of Houston , Houston, TX 77204 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Aaron M. Keller b Department of Chemistry and Chemical Biology, Cornell University , Ithaca, NY 14853 c Department of Chemistry, William Jewell College , Liberty, MO 64068 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ace George Santiago b Department of Chemistry and Chemical Biology, Cornell University , Ithaca, NY 14853 d 10x Genomics , Pleasanton, CA 94588 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michael Lofgren e Department of Biological Chemistry, University of Michigan , Ann Arbor, MI 48109 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ruma Banerjee e Department of Biological Chemistry, University of Michigan , Ann Arbor, MI 48109 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Peng Chen b Department of Chemistry and Chemical Biology, Cornell University , Ithaca, NY 14853 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tai-Yen Chen a Department of Chemistry, University of Houston , Houston, TX 77204 Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: tchen37{at}central.uh.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Vitamin B 12 (cobalamin) is a high-value yet scarce cofactor required for various metabolic processes, making its efficient handling important for maintaining metabolic homeostasis. While the involvement of ATP:cob(I)alamin adenosyltransferases (MMAB) in the synthesis, delivery, and repair of 5’-deoxyadenosylcobalamin (AdoCbl) is well established, the kinetic mechanisms that regulate this process, particularly its negative cooperativity, remain poorly understood. Understanding these mechanisms is key to clarifying how MMAB efficiently uses AdoCbl, prevents resource wastage, and supports bacterial survival in nutrient-limited environments. Using single-molecule relative fluorescence (SRF) spectroscopy, we found that conformation-gated binding is the driving force behind MMAB’s preference for AdoCbl over hydroxocobalamin and is the underlying mechanism for negative cooperativity. This mechanism significantly slows down the binding of the second equivalent of AdoCbl, favoring the singly bound state. Our findings indicate that MMAB predominantly binds a single AdoCbl, optimizing the AdoCbl loading to methylmalonyl-CoA mutase. Additionally, our SRF approach also serves as a tool to explore other cofactor interactions, such as those between riboswitches and cobalamin derivatives, to provide insights into regulatory mechanisms of cobalamin sensing and gene regulation, which are crucial for bacterial adaptation to changing nutrient conditions. Significance Statement MMAB is important for B 12 -dependent propionate metabolism in bacteria. Our findings reveal that conformation-driven binding mechanism underlines the negative cooperativity of MMAB, as it favors the binding of the first AdoCbl while limiting further binding. The larger k on for the first site, combined with similar unbinding rates for both sites, could provide a solution for optimizing cobalamin handling and minimize unnecessary waste. Our single-molecule fluorescence approach offers a powerful tool for investigating other dynamic cofactor interactions, providing new insights into regulatory mechanisms in bacterial metabolism. Introduction Vitamin B 12 , or cobalamin, is a high-value cofactor for bacterial and mammalian physiology, and is trafficked by a network of chaperones that ensure its proper intracellular handling and targeting ( 1 – 4 ). Within this network, ATP:cob(I)alamin adenosyltransferase (MMAB or ATR) synthesizes 5’-deoxyadenosylcobalamin (AdoCbl) in situ ( Fig. 1 , step 1). In the absence of apo-methylmalonyl-CoA mutase (MMUT or MCM, step 2), AdoCbl and triphosphate (PPPi) can dissociate directly from MMAB, leading to potential wastage of a valuable cofactor. To minimize AdoCbl dissociation, MMAB initiates a homolytic reaction, forming cob(II)alamin that has a higher affinity for MMAB, and leading to cofactor sequestration instead. However, air oxidation of cob(II)alamin produces hydroxocobalamin (OHCbl), which then dissociates from MMAB ( 5 – 7 ). MMAB loads AdoCbl directly onto apo-MMUT to generate holo-MMUT ( step 3), which catalyzes the conversion of methylmalonyl-CoA to succinyl-CoA ( step 4), replenishing the TCA cycle and supporting energy metabolism ( 2 , 3 , 5 , 6 , 8 – 10 ). Download figure Open in new tab Figure 1. MMAB-catalyzed AdoCbl synthesis and transfer to MMUT. MMAB catalyzes AdoCbl synthesis from cob(II)alamin using ATP (step 1). Without apo-MMUT, AdoCbl undergoes homolysis and oxidation being converted to OHCbl, which dissociates from MMAB (step 2). Alternatively, MMAB transfers AdoCbl to apo-MMUT, forming holo-MMUT (step 3), which catalyzes the conversion of methylmalonyl-CoA to succinyl-CoA, replenishing the TCA cycle (step 4). MMAB can bind a maximum of two cob(II)alamin molecules. Consecutive binding and catalytic steps are omitted for clarity. This process is part of a larger protein network that optimizes B 12 synthesis, trafficking, and utilization. MMAB is a homotrimer and exhibits negative cooperativity, wherein binding of the first AdoCbl molecule decreases affinity for the second. The D180X truncation, corresponding to a clinical variant of human MMAB leads to loss of negative cooperativity and to inefficient cofactor transfer ( 11 – 14 ). Recent crystallographic studies have highlighted the importance of protein dynamics, particularly the role of mobile loops in in MMAB for mediating conformational changes during cobalamin binding and transfer ( 7 ). These findings suggest a potential link between structural flexibility and negative cooperativity, motivating elucidation of the kinetic basis of this regulatory mechanism. The detailed binding and unbinding rates that might explain how MMAB handles AdoCbl have not been described. Investigating the interaction kinetics between MMAB and B 12 derivatives at the ensemble level poses several challenges. The dynamic nature of these interactions can obscure transient states or rare conformations essential for enzyme function ( 15 – 17 ). Additionally, the homotrimeric architecture of MMAB complicates the measurement of cofactor stoichiometry. Traditional ensemble techniques like isothermal titration calorimetry, while informative, do not capture the full scope of these rapid and cooperative interactions ( 18 , 19 ). To obtain a clearer, high-resolution view of kinetic behavior, more advanced methods such as single-molecule techniques ( 20 – 23 ) and/or advanced computational simulations ( 24 – 26 ) are required. In this study, we have investigated the interaction kinetics of MMAB with B 12 derivatives using a single-molecule relative fluorescence (SRF) approach. The instability of the native substrate, cob(II)alamin, which is highly prone to air oxidation ( 27 , 28 ), complicates kinetic analysis and makes it difficult to directly study the substrate in its native form. To address this, we used a stable derivative of cobalamin, i.e., OHCbl, as a surrogate of the cob(II)alamin substrate, and the product, AdoCbl, to probe MMAB cofactor interactions. The SRF intensities enabled us to distinguish between MMAB states with 0-2 bound B 12 equivalents, and to determine the transition times between these states. We find that a two-step kinetic model, derived from dwell-time distributions, effectively describes the interaction of MMAB with AdoCbl and OHCbl. Our kinetic model indicates that MMAB undergoes a conformational change before binding AdoCbl or OHCbl. The data reveals that the faster binding of the first B 12 moiety, rather than faster unbinding of the second B 12 moiety, is responsible for the observed negative cooperativity. The model further suggests that loss of negative cooperativity and impaired cofactor handling of the D180X MMAB variant could be due to a disruption of this binding mechanism. These findings offer a clearer understanding of the kinetic mechanisms governing AdoCbl binding to and release from MMAB. Results SRF trajectories visualize MMAB-AdoCbl interactions The UV-visible absorption of AdoCbl makes it a strong fluorescence quencher ( Fig. 2 A ), enabling the investigation of MMAB-AdoCbl interactions using fluorescence microscopy. To streamline the dye-labeling procedure and avoid complications, the cysteines in MMAB, which are not conserved, were converted to serine, yielding a Cys-less variant. In this background, Ser-99 and Ser-169 were subsequently mutated to cysteine for labeling ( SI Appendix , section 1). We selected trimeric MMAB with a single equivalent of Alexa555 dye at Cys-99 to test the AdoCbl concentration-dependent fluorescence at the ensemble level ( SI Appendix , section 2). The fluorescence intensity decreased with increasing AdoCbl concentration ( Fig. 2 B ), indicating that AdoCbl binding could be probed by fluorescence quenching. To directly visualize MMAB-AdoCbl interaction events in real-time, we conducted Förster resonance energy transfer (FRET)-based SRF imaging ( SI Appendix , section 3). We immobilized the Alex555-labeled MMAB on a glass slide, flowed AdoCbl solutions into the imaging chamber, and detected single-molecule fluorescence. The dwell times of the intensity fluctuations report on the MMAB-AdoCbl interaction kinetics. Download figure Open in new tab Figure 2. The generation of single-molecule relative fluorescence (SRF) trajectory. ( A ) Cobalamin absorption spectra overlayed with the Alexa555 emission spectrum. ( B ) Normalized fluorescence spectra of labeled MMAB in the solution with AdoCbl varying from 0 to 60 µM. ( C ) Fluorescence micrograph of Alexa555 labeled MMAB. The red, blue, and green curves mark the boundaries of the central, middle, and peripheral parts of the laser beam profile. ( D ) Intensity trajectories of red, blue, and green boxes in C . ( E ) Normalizing D by the average intensity of each trajectory gives the corresponding SRF trajectories. ( F ) Intensity trajectories of the red box in C at [AdoCbl] = 0 μM (red line) and 20 μM (blue line). ( G ) The normalized SRF trajectories of F . To differentiate unbound ( MMAB U ), singly bound ( MMAB S ), and doubly bound ( MMAB D ) MMAB, we carefully removed the complications of inhomogeneous laser excitation and generated SRF trajectories ( SI Appendix , section 4). Fig. 2 C shows the single-molecule fluorescence image without AdoCbl. Each bright spot represents a single MMAB U and maintains a relatively stable intensity over time ( Fig. 2 D ). However, inhomogeneous laser excitation results in fluorescence signals with various intensities, even though all MMAB exist in an unbound state. To address this complication, we normalized each fluorescence signal of MMAB U by its own average intensity to generate the SRF dataset ( Fig. 2 E - G ). The SRF approach allows a direct combination and comparison of all fluorescence trajectories from different protein molecules. Since the quenching efficiency is directly related to the number of AdoCbl bound to MMAB, the SRF approach allows the differentiation of MMAB U , MMAB S , and MMAB D . SRF states reveal various MMAB-AdoCbl binding configurations Fig. 3 A shows SRF trajectories reporting interactions between MMAB and AdoCbl with different AdoCbl concentrations. The normalized SRF histograms (overall area equal to 1), generated from >200 SRF trajectories at each concentration, can be described by a combination of high ( F H ≈ 1.0), middle ( F M ≈ 0.77), and low ( F L ≈ 0.1) fluorescence states ( Fig. 3 B ). We globally fit the histograms using a three-state Gaussian model. The center position and width of each Gaussian distribution were shared across all concentrations while allowing the relative populations of the three states to float. As AdoCbl increases from 0 to 20 µM, the F H population decreased and shifted toward F M while the F L population grew continuously. A clear F M peak appeared when AdoCbl was >40 µM, and the F L peak gradually saturated. Thus, while F H decreases, F M and F L increased and approached saturating populations ( SI Appendix section 5 , Fig. S4 C ). Download figure Open in new tab Figure 3. SRF states reveal various AdoCbl binding stoichiometries. ( A ) SRF trajectories at different AdoCbl concentrations. The solid lines are the corresponding transition trajectory generated from ebFRET. ( B ) SRF intensity histogram generated from A (blue solid circle) and the global fitting results (black line). The relative populations of F H , F M , and F L are highlighted with blue, green, and red shades, respectively. ( C ) Assignment of various AdoCbl binding geometries of MMAB to the three SRF states. MMAB U , MMAB S , and MMAB D represent MMAB under unbound, singly bound, and doubly bound state, respectively. Using AdoCbl-dependent populations, we assigned SRF states to MMAB binding stoichiometries. Labeling MMAB with a single Alexa555 broke its trilateral symmetry and resulted in different binding configurations. Fig. 3 C summarizes all possible MMAB binding configurations. In the absence of AdoCbl, the histogram shows a single state with F H ≈ 1.0 ( Fig. 3 B , top), indicating that only MMAB U contributed to the F H state ( Fig. 3 C , top left). At AdoCbl = 60 µM, a saturating concentration, MMAB exists predominantly in the doubly bound form, MMAB D , giving three binding configurations. The ratio of F M to F L was ∼2:1 ( Fig. 3 B ), indicating that two and one MMAB D contributed to F M and F L states, respectively. Since the SRF intensity is dependent on the distance between the label and bound AdoCbl, we assigned the MMAB D with two AdoCbl bound in the closest positions to the F L state and the other two to the F M state ( Fig. 3 C , Box 1). This assignment also indicates that the quenching efficiency of AdoCbl bound to the farthest site is insignificant. Application of this concept to the singly bound case led to the assignment of the MMAB S species in the F H and F M states in a 1:2 ratio ( Fig. 3 C , Box 2). These assignments were also supported by another MMAB construct labeled at Cys-169 ( SI Appendix section 5). From the above analysis, we associated F H with MMAB U + 1/3 MMAB S , F M with 2/3 MMAB s + 2/3 MMAB D , and F L state with 1/3 MMAB D . Dwell-time analysis reveals an intermediate species and a kinetic model for MMAB-AdoCbl interactions Most AdoCbl-induced transitions occur between F H and F M or F M and F L, while direct transitions between F H and F L states are occasionally observed (∼5%). This observation indicates that MMAB D forms primarily through two sequential AdoCbl bindings and that simultaneous binding and unbinding of two AdoCbl is rare and thus not considered further. To quantify interaction kinetics, SRF trajectories were first analyzed using the empirical Bayes hidden Markov model analysis software, ebFRET, to generate transition trajectories (solid lines in Fig. 3 A, SI Appendix , section 6) ( 29 – 31 ). We extracted transition dwell times from trajectories and generated the probability density functions ( PDF ) of dwell times ( SI Appendix , section 7). Τ HM is the microscopic dwell time in F H before transitioning to the F M state. The overall average transition rate, ⟨Τ HM ⟩ -1 , increased with increasing AdoCbl concentrations ( Fig. 4 A ). However, the faster rate constant (i.e., steeper slope) in the low AdoCbl concentration region indicates a faster MMAB U to MMAB S than MMAB S to MMAB D transition. Interestingly, the distribution of Τ HM , instead of being a simple single-exponential decay, shows an exponential rise and decay, suggesting a kinetic intermediate in the F H state ( 32 , 33 ). This rise-and-decay feature is most visible at low (<10 μM) but vanishes at high AdoCbl concentrations (40 μM, Fig. 4 B ), suggesting that this intermediate is primarily associated with the MMAB U to MMAB S transitions. We posit this intermediate as a conformational change in MMAB U instead of MMAB S in the F H state. Using a single-molecule interaction simulation (SMIS, SI Appendix , section 8) ( 24 ), we confirmed that MMAB undergoes a conformational change (i.e., the transition from MMAB U1 to MMAB U2 ) before the first AdoCbl binds. Download figure Open in new tab Figure 4. Microscopic dwell times inform a minimal kinetic model for MMAB-AdoCbl interactions. ( A ) AdoCbl dependent -1 shows the averaged binding rate increases with AdoCbl concentrations. ( B ) PDF HM under low and high AdoCbl concentrations. ( C ) AdoCbl-dependent -1 shows that the unbinding rate from MMAB D is AdoCbl independent. ( D ) Same as B but for PDF LM . ( E ) AdoCbl-dependent -1 and -1 show a similar dose dependence. ( F ) The ratio of transition events between Τ ML and Τ MH processes increases linearly with AdoCbl. ( G ) Proposed kinetic model describing MMAB-AdoCbl interactions. MMAB U1 needs to undergo a conformational change (i.e., transition to MMAB U2 ) before the first AdoCbl binding. On the other hand, Τ LM captures the transitions from the F L to the F M state and describes AdoCbl unbinding from the MMAB D . The ⟨Τ LM ⟩ -1 and PDF LM remain the same across all AdoCbl concentrations ( Fig. 4 C and D ). The dose-independent rates indicate that AdoCbl unbinds from MMAB D via a typical unimolecular mechanism. Τ ML and Τ MH , the microscopic dwell times of the F M state before respectively transitioning to the F L and F H states, contain mixed AdoCbl binding and unbinding information for MMAB S and MMAB D . Both ⟨Τ ML ⟩ -1 and ⟨Τ MH ⟩ -1 reveal the overall rates of all kinetic processes that start from the F M state, which is supported by the fact that both ⟨Τ ML ⟩ -1 and ⟨Τ MH ⟩ -1 show identical AdoCbl dependence ( Fig. 4 E ). The ratio of the number of transition events for Τ ML and Τ MH process (i.e., # ML / # MH ) increases linearly with AdoCbl ( Fig. 4 F ). Since the binding rate of AdoCbl to MMAB is expected to be scaled linearly with AdoCbl, the # ML / # MH data indicate that AdoCbl unbinding from MMAB S also occurs through a unimolecular mechanism. The above kinetic analysis revealed that: (i) AdoCbl binds to MMAB mainly through a two-step binding model (reflected by rare direct transitions between F H and F L ); (ii) Binding kinetics of AdoCbl to MMAB show a clear AdoCbl dose dependence. The binding of the first AdoCbl equivalent requires the formation of a different conformational intermediate (reflected by the rise- and-decay feature of Τ HM distribution), indicating that unbound MMAB equilibrates between at least two different conformations. This observation is also supported by the recent crystal structure showing that MMAB undergoes conformational changes upon binding AdoCbl or ATP ( 7 ). (iii) AdoCbl unbinding from both sites of MMAB follows an unimolecular mechanism (reflected by dose-independent ⟨Τ LM ⟩ -1 and dose-dependent # ML / # MH ). Although it is clear that AdoCbl unbinding from MMAB D leads to MMAB S , unbinding from MMAB S can lead to either MMAB U1 or MMAB U2 . We thus examined both kinetic models using SMIS and found that only the model in which AdoCbl unbinding leads to MMAB U1 describes all dwell time distributions ( SI Appendix , section 9). Combining this information, we formulated a minimal kinetic model to describe the interactions between MMAB and AdoCbl ( Fig. 4 G ). The kinetic model describes the complex kinetics of MMAB-AdoCbl interactions Applying the MMAB-AdoCbl binding configurations ( Fig. 3 C ) to a minimal kinetic model ( Fig. 4 G ) resulted in a fairly complex system ( Fig. 5 A ), precluding the feasibility of deriving an analytical solution for most dwell-time PDF s (i.e., f HM (Τ), f ML (Τ), and f MH (Τ)). f LM (Τ) is the only exception, because it only describes the unbinding step for MMAB D . Fitting the distributions of Τ LM with f LM (Τ) crossing all AdoCbl concentrations revealed the unbinding rate constants k r2 ( Fig. 5 B ). The derivation of either f HM (Τ), f MH (Τ), or f ML (Τ) was too complicated due to the ill-defined ratio of the initial species (i.e., F H and F M states). To circumvent this challenge, we defined and extracted two additional dwell times, Τ LMH and Τ LML . Τ LMH and Τ LML represent the subsets of Τ MH and Τ ML , respectively, which include only the dwell time starting from the F L state. This selection results in Τ LMH and Τ LML having a well-defined initial state (i.e., MMAB S in the F M state, Fig. 5 A ) and enables derivations of f LML (Τ) and f LMH (Τ) ( SI Appendix , section 10). The global fitting of PDF LML and PDF LMH with f LML (Τ) and f LMH (Τ) (Fig.5 C ) yielded k 2 and k r1 . To quantify and k 1 , we used SMIS to test a large range of and k 1 and obtained a solution set that satisfactorily described our data ( Fig. 5 D ) ( 24 ). Based on the kinetic model, we derived the unbinding equilibrium constants K D1 and K D2 ( SI Appendix , section 11). Download figure Open in new tab Figure 5. Kinetic parameters for MMAB-AdoCbl interactions. ( A ) The minimal kinetic model associates different MMAB species to SRF states. ( B ) Fitting the PDF LM (blue bar) by a single-exponential function (red curve) reports k r2 . The AdoCbl independent fitted k r2 suggests AdoCbl unbinds from MMAB D through single-step dissociation ( C ) The global fitting of PDF LML and PDF LMH with f LML (Τ) and f LMH (Τ) reports k 2 and k r1 . ( D ) The extraction of, - , and k 1 was achieved using SMIS. The simulated Τ HM distributions (bottom) satisfactorily describes the experimental data (top). k f1 and k r1 represent the forward binding and reverse unbinding rate constants for transitions between MMAB U and MMAB S, while k f2 and k r2 for transitions between MMAB S and MMAB D . Table 1 summarizes the extracted rate constants and reports values for K D1 = 5.6 ± 2.9 μM and K D2 = 41.7 ± 13.9 μM. K D2 is 7-fold larger than K D1 , which is significantly larger than the 3.3-fold difference predicted for a system exhibiting no cooperativity ( SI Appendix , section 12), indicating the negative cooperativity. View this table: View inline View popup Download powerpoint Table 1. Kinetic parameters for MMAB-B 12 interactions. HOCbl interacts with MMAB using a kinetic model similar to AdoCbl HOCbl binding to MMAB showed a stronger quenching than AdoCbl because of its larger FRET spectral overlap with the Alexa dye ( Fig. 2 A ). SRF intensity histograms identified three fluorescence states ( Fig. 6 A ), which were used to determine the HOCbl-dependent populations ( Fig. 6 B ) and assign possible binding configurations ( Fig. 6 C and SI Appendix , section 13). By carefully analyzing the dwell time distributions ( Fig. 6 D ), we proposed a similar minimal kinetic model to describe the MMAB-HOCbl interactions ( Fig. 6 E and SI Appendix , section 14). MMAB also required a conformational change ( MMAB U1 to MMAB U3 ) to bind the first equivalent of HOCbl ( Fig. 6 E ). We derived analytical equations for all dwell times (i.e., Τ HM , Τ MH , Τ ML, and Τ LM , SI Appendix , section 15), applied equations to fit the dwell-time distributions, and summarized the rate constants in Table 1 . Notably, the conformational change rate constants of MMAB U1 for HOCbl are very different from those of AdoCbl. These differences suggest that MMAB U1 adopts a different conformation, which was designated MMAB U3 . The binding affinity of MMAB to HOCbl is much weaker than that to AdoCbl ( K D1 = 15.2 ± 5.0 μM and K D2 = 189 ± 110 μM), but they still show a negative cooperativity originated from the slower second binding. Download figure Open in new tab Figure 6. Kinetic analysis of MMAB-OHCbl interactions. ( A ) OHCbl-dependent SRF intensity histogram. ( B ) OHCbl-dependent populations of F H , F M , and F L states. ( C ) Assignment of all possible OHCbl binding configurations of MMAB ( MMAB U , MMAB S , and MMAB D ) to the three SRF states. ( D ) Experimental dwell time distributions of Τ HM , Τ LM , and Τ ML . ( E ) Proposed kinetic model describing MMAB-OHCbl interactions. MMAB U1 , MMAB S , and MMAB D represent MMAB in the unbound, singly and doubly bound states, respectively. MMAB U1 needs to undergo a conformational transition to MMAB U3 before binding the first equivalent of OHCbl. Discussion Kinetic model describes ensemble results Using the SRF assay, we described a two-step kinetic model and quantified the kinetic and thermodynamic constants for interactions between MMAB and cobalamin. Before MMAB binds the first equivalent of cobalamin, it must adopt a specific conformation ( MMAB U2 and MMAB U3 ). Binding of the first cobalamin moiety slows down binding of the second, leading to negative cooperativity. Unbinding of cobalamin from MMAB follows a unimolecular pathway and is independent of cobalamin concentration. Using the extracted rate constants ( Table 1 ) and kinetic model ( Fig. 4 G and Fig. 6 E ), we simulated the stopped-flow differential absorption traces for AdoCbl binding to apo-MMAB ( SI Appendix , section 15), which captured the AdoCbl dependence of differential ensemble absorption spectra reported previously,( 6 ) thus validating our model. D180X loses negative cooperativity due to reduced k on for the first substrate In wild-type MMAB, negative cooperativity could stem from either a larger k on for the first substrate relative to the second, or a larger k off for the second substrate. Our kinetic data ruled out the second possibility, as the unbinding rates were similar across the binding sites. Therefore, the D180X mutation likely disrupted the first substrate binding event by reducing k on . This slower initial substrate capture is reflected in a 2-fold higher K M , as the enzyme now requires more substrate to reach half-maximal activity. The threefold lower k cat is a direct consequence of inefficient turnover, due to inefficient binding of the first substrate equivalent, which slows down the overall catalytic cycle. The decrease in k on corresponded to an increase in K d , explaining the observed 400-fold reduction in AdoCbl affinity. Biological implications of the kinetic model Since the intracellular concentration of B 12 derivatives is relatively low (nM to low µM), efficient substrate capture is important for the catalytic efficiency of ATR. A larger k on for binding at the first site allows ATR to rapidly bind cob(II)alamin and convert it to AdoCbl, facilitating cofactor synthesis under substrate-limited conditions. Previous studies have shown that when MMAB is doubly loaded, ATP selectively ejects AdoCbl from the weaker-binding second site while retaining the tightly bound AdoCbl at the first site ( 34 ). This selective ejection minimizes premature cofactor loss into solution and results in MMAB retaining one AdoCbl equivalent, potentially serving as a functional reserve. Negative cooperativity slows down the binding of a second equivalent of AdoCbl, which contributes to disfavoring back transfer of the cofactor from MMUT to MMAB. If both sites were to bind cob(II)alamin and convert it to AdoCbl at similar rates, the balance between cofactor synthesis and transfer could be disrupted, increasing the likelihood of premature AdoCbl release into solution. Thus, the combination of negative cooperativity and ATP-driven AdoCbl transfer appears to represent a solution for balancing cob(II)alamin availability with the AdoCbl demand. Broader applicability of SRF Our SRF approach revealed the dynamic interactions and binding kinetics of MMAB with B 12 derivatives and provided insights into the basic mechanism of cofactor handling by MMAB. The SRF approach holds the potential for broader applications, for example, to study the interaction between riboswitches and cobalamin derivatives ( 35 – 37 ), offering a powerful tool for probing the regulatory mechanisms governing cobalamin sensing and gene regulation in bacterial systems. Materials and Methods Materials and methods are described in SI Appendix , section 1 to section 16. These include Alexa-labeled MMAB and functional validation, experimental setups for single-molecule and ensemble fluorescence imaging, procedures for image and data analyses, experimental dwell-time distribution generation, dwell-time analytical solution derivation based on kinetic models, and stopped-flow differential absorption simulations. Acknowledgments The authors thank the Biotechnology Resource Center for protein mass spectrometry analysis. 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