Elevator mechanism dynamics in a sodium-coupled dicarboxylate transporter

Kinz-Thompson, Colin D.; Redondo, M. Lopez; Mulligan, Christopher; Sauer, David; Marden, Jennifer J.; Song, Jinmei; Tajkhorshid, Emad; Hunt, John F.; Stokes, David L.; Mindell, Joseph A.; Wang, Da-Neng; Gonzalez, Ruben L

doi:10.1101/2022.05.01.490196

Cited by 6 publications

(6 citation statements)

References 47 publications

(119 reference statements)

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“…While the structures of the unliganded protein and the protein bound to Neu5Ac are in the inward-open conformation, the density of the binding site of Neu5Ac is unambiguous ( Figure 5A ). The architecture of the Neu5Ac binding site is similar to that of citrate/malate/fumarate in the di/tricarboxylate transporter of V. cholerae ( Vc INDY) (Kinz-Thompson et al, 2022). Neu5Ac binds to the transport domain and there are no direct interactions with the residues in the scaffold domain.…”

Section: Resultsmentioning

confidence: 99%

“…The polar groups bind to both the C1-caboxylate side of the molecule and the C8-C9 carbonyls, suggesting that SSS transporters have probably evolved to transport nine-carbon sugars such as Neu5Ac (Wahlgren et al, 2018). Interestingly, even the dicarboxylate transporter from V. cholerae ( Vc INDY) binds to its ligand via electrostatic interactions with both carboxylate groups ( Figure 6C ) (Kinz-Thompson et al, 2022). The high affinity of the substrate-binding component ( Fn SiaP) to Neu5Ac is physiologically relevant because it sequesters Neu5Ac in a volume where the concentration of Neu5Ac is very low.…”

Section: Resultsmentioning

confidence: 99%

“…Both Hi SiaQM and Pp SiaQM lack information on the Neu5Ac binding site, which was identified based on modeling studies that relied on the ligand-bound structure of Vc INDY (Kinz-Thompson et al, 2022). Moreover, only the structures of SiaQM in the elevator-down conformation (inward-facing) have been reported, and further conformations along the transport cycle must be elucidated.…”

Section: Introductionmentioning

confidence: 99%

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Molecular determinants of Neu5Ac binding to a tripartite ATP independent periplasmic (TRAP) transporter

Goyal,

Dhanabalan,

Scalise

et al. 2024

Preprint

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N-Acetylneuraminic acid (Neu5Ac) is a negatively charged nine-carbon sugar that is often the peripheral sugar in human cell-surface glycoconjugates. Some bacteria scavenge, import, and metabolize Neu5Ac or redeploy it on their cell surfaces for immune evasion. The import of Neu5Ac by many bacteria is mediated by tripartite ATP-independent periplasmic (TRAP) transporters. Previously, we reported the structures of SiaQM, a membrane-embedded component of theHaemophilus influenzaeTRAP transport system (HiSiaPQM) (Currie, M J, et. al 2024). The published structures do not contain Neu5Ac bound to SiaQM. This information is critical for inferring the mechanism of transport and for further structure-activity relationship studies. Here, we report the structure ofFusobacterium nucleatumSiaQM (FnSiaQM) with and without Neu5Ac binding. The structures were in an inward (cytoplasmic side) facing conformation. The structure revealed the interactions of Neu5Ac with the transporter and its relationship with the Na+binding sites. Two of the Na+-binding sites are similar to those described previously. We show the presence of a third metal-binding site that is further away and buried in the elevator domain. Ser300 and Ser345 interact with the C1-carboxylate group of Neu5Ac. Proteoliposome-based transport assays showed that Ser300-Neu5Ac interaction is critical for transport, whereas Ser345 is dispensable. Neu5Ac primarily interacts with residues in the elevator domain of the protein, thereby supporting the elevator with an operator mechanism. The residues interacting with Neu5Ac are conserved, providing fundamental information required to design inhibitors against this class of proteins.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Molecular determinants of Neu5Ac binding to a tripartite ATP independent periplasmic (TRAP) transporter

Goyal,

Dhanabalan,

Scalise

et al. 2024

Preprint

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“…To demonstrate the use of KDA we are fo- cusing on the biophysics of secondary active transporters, [27][28][29] an area covered originally in Hill's work 11,12 with many recent applications of kinetic models. [1][2][3][4][5][6][30][31][32][33] These membrane proteins use the free energy stored in a transmembrane ionic gradient to drive energetically uphill transport of a substrate (another ion or small molecule) by alternating between multiple protein conformations in a manner that is coupled to ion and substrate binding. Secondary active transporters are prime examples of free energy transduction in biology 12 and serve as systems to study non-equilibrium behavior at the molecular scale.…”

Section: Introductionmentioning

confidence: 99%

Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Biochemical Systems Analytically

Awtrey,

Beckstein

2024

Preprint

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Kinetic diagrams are commonly used to represent biochemical systems in order to study phenomena such as free energy transduction and ion selectivity. While numerical methods are commonly used to analyze such kinetic networks, the diagram method by King, Altman and Hill makes it possible to construct exact algebraic expressions for steady-state observables in terms of the rate constants of the kinetic diagram. However, manually obtaining these expressions becomes infeasible for models of even modest complexity as the number of the required intermediate diagrams grows with the factorial of the number of states in the diagram. We developedKinetic Diagram Analysis(KDA), a Python library that programmatically generates the relevant diagrams and expressions from a user-defined kinetic diagram.KDAoutputs symbolic expressions for state probabilities and cycle fluxes at steady-state that can be symbolically manipulated and evaluated to quantify macroscopic system observables. We demonstrate theKDAapproach for examples drawn from the biophysics of active secondary transmembrane transporters. For a generic 6-state antiporter model, we show how the introduction of a single leakage transition reduces transport efficiency by quantifying substrate turnover. We applyKDAto a real-world example, the 8-state free exchange model of the small multidrug resistance transporter EmrE of Hussey et al (J General Physiology152(2020), e201912437), where a change in transporter phenotype is achieved by biasing two different subsets of kinetic rates: alternating access and substrate unbinding rates.KDAis made available as open source software under the GNU General Public License version 3.

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“…The level of defocusing mentioned in (iii) for each trajectory was quantified by the level of maximum intensity. Trajectories with maximum normalized intensities that were greater than 1.1 and lasted for more than one continuous frame were not included.The normalized, AF546 fluorescence intensity vs. time trajectories from each movie were analyzed together using a variational Bayesian Hidden Markov Model (HMM) to yield a global model of the single-molecule observations and dynamics present in each replicate movie of each experiment58,59 . Two-state HMMs were used to analyze the B12 binding data in Fig.S5aand the resulting transition matrices were used estimate the values of kbinding and krelease .…”

mentioning

confidence: 99%

Realtime observation of ATP-driven single B12 molecule translocation through BtuCD-F

Hunt

Kim

et al. 2022

Preprint

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ATP-Binding Cassette (ABC) Transporters use ATP binding and hydrolysis to power transmembrane transport of chemically diverse substrates. Current knowledge of their mechanism comes primarily from static structures of stable intermediates along the transport cycle. Recently, single-molecule fluorescence resonance energy transfer (smFRET) measurements have generated insight into the functional dynamics of transmembrane transporters, but studies to date lack direct information on the physical movement of the transport substrate. Here, we report development of an smFRET system that exploits fluorescence quenching by vitamin B12 to track its location in real time during ATP-driven transport by nanodisc-reconstituted E. coli BtuCD-F, an extensively studied type II ABC importer. Our data demonstrate that transmembrane translocation of B12 is driven by two sequential high-energy conformational changes that are inaccessible to standard structural methods because they are inherently transient. The first moves B12 from the periplasm into the transmembrane domain of the transporter; notably, this reaction is driven by hydrolysis of a single ATP molecule, in contrast to the mechanism established for several other ABC Transporter families in which ATP-binding drives the mechanochemical power-stroke prior to hydrolysis. The second mediates B12 release on the opposite side of the transporter, and it is driven by formation of a hyper-stable complex between BtuCD and BtuF. Hydrolysis of a second single ATP molecule is then required to dissociate BtuCD from the BtuF substrate-binding protein to enable it to bind B12 and initiate another round of transport. Our experiments have visualized substrate translocation in real-time at a single-molecule level and provided unprecedented information on the mechanism and dynamics of a paradigmatic transmembrane transport process.

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Elevator mechanism dynamics in a sodium-coupled dicarboxylate transporter

Cited by 6 publications

References 47 publications

Molecular determinants of Neu5Ac binding to a tripartite ATP independent periplasmic (TRAP) transporter

Molecular determinants of Neu5Ac binding to a tripartite ATP independent periplasmic (TRAP) transporter

Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Biochemical Systems Analytically

Realtime observation of ATP-driven single B12 molecule translocation through BtuCD-F

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