TCR-pMHC complex formation triggers CD3 dynamics

Reviewer #1 (Public Review):

The manuscript entitled: "TCR-pMHC complex formation triggers CD3 dynamics" by Van Eerden et al. mainly uses coarse-grained molecular dynamics to probe the dynamic changes, in terms of CDε spatial arrangements around 226 TCRs, before and after the engagements of MCC/I-Ek. The broader distributions of CDε iso-occupancies after pMHC binding correlate with the decreases of TCR-CD3 contacts and extensions of TCR conformations. Given the observed release of motion restrictions upon antigen recognition, the authors proposed a "drawbridge" model to describe the initial triggering processes from pMHC association to TCR straightening, FG-loop getaway, and CD3 enhanced mobility. In addition, the authors briefly investigated the functional effects of the rigidified connecting peptide (CP) in T-cell activation using in silico and in vitro mutagenesis. The manuscript raises an important and exciting hypothesis about the allostery of TCR-CD3 during TCR triggering; however, due to current not-yet-convincing evidence, both computationally and experimentally, in supporting their conclusions.

1. As mentioned by the authors, the TCR triggering and T cell activation have been illustrated by a number of models, such as mechanosensing and kinetic proofreading, "in which TCRs discriminate agonistic from antagonistic pMHCs." However, the critical feature of antigen discrimination is lacking in the drawbridge model. So far, the CDε movements qualitatively distinguish on and off states. The simulation of the antagonist or weaker binder would strengthen the manuscript by demonstrating the relevance of CDε mobility in the triggering mechanism. 226 TCR associated with K99E/I-Ek has been resolved in Ref (DOI: 10.4049/jimmunol.1100197), which can potentially serve as the "intermediate" system to formulate the gradual increase of CDε dynamics.

2. The linkage between conserved motifs in CP and CDε mobility is less apparent to this reviewer. The notion of the rigidified hinge (PP) requires further clarification. Computationally, the details of fine-grained simulations are required to justify the origin of the apparent mobility increase in PP. The direct comparison between Fig. 2 and Fig. 7 can help assess the relevance of CP through the alignment by FG-loop at a fixed direction in polar coordinates. Experimentally, anti-CD3 positive experiments and, ideally, another antagonist on 3A9 TCRs can strengthen the current functional assay. The baseline level of TCR expression (after positive selection) and 0h activation (Fig. S8) is missing.

3. Regarding the section "The TCRβ FG loop acts as a gatekeeper," besides contact analysis, additional motion analysis, such as RMSF or PCA, can further establish the importance of FG loops.

4. The discussion on anti-CD3 antibody effects and their potential contribution to CD3 mobility is highly recommended.

Reviewer #2 (Public Review):

In this research article a new allosteric mechanism for T cell receptor (TCR) triggering upon peptide-MHC complex binding is presented in which conformational change in the TCR facilitates activation by controlling CD3 dynamics around the TCR. The authors find that the Cb FG loop acts as a gatekeeper and Cb connecting peptide acts as a hinge to control TCR flexibility.

As an initial result, the authors set up two sets of simulations - TCR-CD3 and pMHC-TCR-CD3 in POPC bilayers and identified that the CD3e chains exhibit a wider range of mobility in the pMHC-TCR-CD3 system as compared to the TCR-CD3 system. Next, they examined the contacts between all subunits during the course of both simulations and established that CD3g and CD3eg made far fewer contacts with TCRb in the pMHC-TCR-CD3 simulations. Next, they identified that the TCR is extended in the pMHC-TCR-CD3 simulations with larger tilt angle of 150º and FG loop acts as gatekeeper that allows CD3 movements upon pMHC binding. Finally, Mutations in Cb connecting peptide regions indicated rigidified TCR leading to hypersensitive TCR, proved both by simulations and in vitro experiments.

The following major concerns must be addressed.

Major concerns:

1. The simulations were performed with intracellular regions unfolded and free from the membrane. A more complete system should have the intracellular regions embedded in the membrane. An NMR structure of CD3e is available (Xu et al., Cell, 2008) and could have been modeled into the TCR-CD3 system before the simulation. Prakaash et al., (PLoS, Comput Biol, 2021) studied cytoplasmic domain motions during in their simulation experiments.

2. Comparing Fig. 2C and Fig.7C, the movement of CD3eg is more restricted in Fig.7C. Is this because the simulation time is lower in the mutation experiments?

3. Only TCR-CD3 simulation were performed for PP and AA mutants. A simulation with pMHC (pMHC-TCRmutants-CD3) should be performed to show increased CD3 mobility.

4. Using CD3e antibody, OKT3, for activation instead of pMHC as a separate experiment would add more value to this study. They can look at CD3 mobility and TCR elongation in the system with OKT3 antibody and compare it to the CD3 mobility and TCR elongation with the pMHC system. They can also use OKT3 with AA and PP mutants and perform both simulation and in vitro activation experiments.

5. The activation experimental data is rather underwhelming. The difference between WT and PP in 2hr experiment at 0.016 ug/mL looks exceedingly low. A stronger TCR-pMHC system should be considered for the in vitro activation experiments.

6. There is some concern that the scientific work lacks solid experimental functional data and lack of novelty due to earlier TCR-CD3 simulation studies (Pandey et al., 2021, eLife) that already reported flexibility and elongation of the complex.

Reviewer #3 (Public Review):

The authors first explore structural differences of unbound TCR-CD3 complexes and pMHC-bound TCR-CD3 complexes with coarse-grained simulations. In the simulations with pMHC-bound complexes, the transmembrane (TM) domains of the TCR-CD3 complex and of pMHC are embedded in two opposing membrane patches. In the pMHC membrane patch, a pore is created and stabilised in the simulation setup with the aim to allow water transport in and out of the compartment between the membranes. The authors report a more upright conformation of the TCR extracellular (EC) domain in the simulations in which this EC domain is bound to pMHC, compared to simulations with unbound TCR, and postulate an allosteric signalling model based on these apparent conformational changes and associated changes in TCR-CD3 quaternary arrangements. Subsequently, the authors identify a GxxG motif in the TCRbeta connecting peptide between EC domain and TM domain as putative hinge in allosteric signalling, and explore the effect of double proline and double alanine substitutions in atomistic simulations and experiments.

While these simulation and experimental setups and the addressed questions are of interest in the field, the following weaknesses prevail in my overall assessment of the work:

(1) I am not convinced that the reported coarse-grained simulation results are sound or allow to draw the conclusions stated in the work. In the simulations with a pMHC-bound TCR-CD3 complex, the intermembrane distance in the setup shown in Figure S1 appears excessively large and likely leads to a rather strong force in the membrane-vertical direction and to the reported upright conformation of the TCR EC domain. This upright confirmation thus appears to be a consequence of force from the simulation setup, rather than a consequence of pMHC binding alone as suggested by the authors. While the membrane pore in principle allows water exchange, the relaxation of the intermembrane distance resulting from this water exchange in the 10 microsecond long simulation trajectories is not (but needs to be) addressed. This relaxation eventually would lead to an equilibrated membrane separation, in which essentially no force is exerted on the TCR-pMHC EC complex. However, I suspect that this computationally demanding equilibration is not achieved in the simulations, with the consequence that forces on the TCR-pMHC EC complex in the membrane-vertical direction remain.

In addition, I am not convinced that the Martini force field of the coarse-grained simulations allows a reliable assessment of the quaternary interactions between the TCR and CD3 EC domains. Getting protein structures and interactions right in coarse-grained simulations is notoriously difficult. In simulations with the coarse-grained Martini force field, secondary protein structures are constrained as a standard procedure, and the authors also use a recommended Go-potential procedure, likely to stabilise tertiary protein structures. The quaternary interactions between the TCR EC domain and the pMHC EC domain are modelled by rather strong harmonic constraints to prevent dissociation. While the treatment of the quaternary interactions between the TCR EC domain and the CD3 EC domains in the simulations is not (but needs to be) addressed in detail, I suspect that there are no additional, or only weak constraints to stabilise these interactions. In any case, I think that a faithful representation of these quaternary interactions is beyond the reach of the Martini force field, as is the reported diffusion of the CD3 EC domains around the TCR EC domain, which plays a central role in the allosteric mechanism proposed by the authors (see Fig 2 and 5).

(2) The allosteric model suggested by the authors is motivated in an introduction that appears to omit central controversial aspects in the field, as well as experimental evidence that is not compatible with allosteric conformational changes in the TCR. These aspects are:

- The mechanosensor model is controversial. In original versions of this model, a transversal force has been postulated to be required for T cell activation. However, more recent single-molecule force-sensor experiments reported in J Goehring et al., Nat Commun 12, 1 (2021) provide no evidence for a scenario in which transversal forces beyond 2 pN are associated with T cell activation.

- The role of catch bonds is controversial. Evidence for TCR catch bonds has been mainly obtained in experimental setups using the biomembrane force probe, in which force is applied to TCRs on the surface of T cells, but is not reproduced in experimental setups using isolated TCRs, see e.g. L Limozin et al., PNAS 116, 16943 (2019)

- Ref. 1 of the manuscript prominently discusses the kinetic segregation model of T cell activation, which is not (but needs to be) addressed in the introduction. In this model, exclusion of CD45 from close-contact zones around pMHC-bound TCRs triggers T cell activation. The model is supported by evidence from diverse experiments, see for example M Aramesh et al., PNAS 118, e2107535118 (2021) and Ref. 1. At least part of this evidence is not compatible with mechanosensing or allosteric models of T cell activation.

Author Response

We sincerely appreciate the reviewers for investing their valuable time in assessing our manuscript. We understand the considerable effort involved in the review process, and we will make use of these suggestions in order to make the revised manuscript more complete in terms of explanation, discussion, additional simulations, experiments and analyses.

-Specifically, we will experimentally and computationally investigate how activation via anti-CD3 antibodies relates to our mechanism.

-We will also utilize a weaker pMHC binder in the pMHC-mediated T cell activation experiments.

-We will improve the description of the function of the FG loop and the role of the connecting peptide (CP).

-Furthermore, we will improve our description of and justification for the simulation methodology. We want to emphasize that all potentials have been described, and we will draw attention to these methodological descriptions where needed.

The reviewers also suggested a number of additional simulations that are probably beyond our current capability. These include:

-simulations of TCR in complex with a weaker agonist -simulations of the proline and alanine TCR mutants in complex with a pMHC.

While we agree that such simulations would provide new insights into the mechanism of TCR triggering, they simply are not feasible at this time. We will give a more detailed explanation for these arguments in the revised manuscript.

Below, please find our point-by-point planned action items:

Reviewer #1 (Public Review):

The manuscript entitled: "TCR-pMHC complex formation triggers CD3 dynamics" by Van Eerden et al. mainly uses coarse-grained molecular dynamics to probe the dynamic changes, in terms of CDε spatial arrangements around 226 TCRs, before and after the engagements of MCC/I-Ek. The broader distributions of CDε iso-occupancies after pMHC binding correlate with the decreases of TCR-CD3 contacts and extensions of TCR conformations. Given the observed release of motion restrictions upon antigen recognition, the authors proposed a "drawbridge" model to describe the initial triggering processes from pMHC association to TCR straightening, FG-loop getaway, and CD3 enhanced mobility. In addition, the authors briefly investigated the functional effects of the rigidified connecting peptide (CP) in T-cell activation using in silico and in vitro mutagenesis. The manuscript raises an important and exciting hypothesis about the allostery of TCR-CD3 during TCR triggering; however, due to current not-yet-convincing evidence, both computationally and experimentally, in supporting their conclusions.

I would like to see additional work before supporting the publication of this manuscript in Life. See details below:

1. As mentioned by the authors, the TCR triggering and T cell activation have been illustrated by a number of models, such as mechanosensing and kinetic proofreading, "in which TCRs discriminate agonistic from antagonistic pMHCs." However, the critical feature of antigen discrimination is lacking in the drawbridge model. So far, the CDε movements qualitatively distinguish on and off states. The simulation of the antagonist or weaker binder would strengthen the manuscript by demonstrating the relevance of CDε mobility in the triggering mechanism. 226 TCR associated with K99E/I-Ek has been resolved in Ref (DOI: 10.4049/jimmunol.1100197), which can potentially serve as the "intermediate" system to formulate the gradual increase of CDε dynamics.

Planned actions:

-Explain why the current study can not easily address pMHC discrimination

-Explain why simulation of antagonist or weaker binding pMHC is technically difficult

1. The linkage between conserved motifs in CP and CDε mobility is less apparent to this reviewer. The notion of the rigidified hinge (PP) requires further clarification. Computationally, the details of fine-grained simulations are required to justify the origin of the apparent mobility increase in PP. The direct comparison between Fig. 2 and Fig. 7 can help assess the relevance of CP through the alignment by FG-loop at a fixed direction in polar coordinates. Experimentally, anti-CD3 positive experiments and, ideally, another antagonist on 3A9 TCRs can strengthen the current functional assay. The baseline level of TCR expression (after positive selection) and 0h activation (Fig. S8) is missing.

Planned actions:

-Provide additional analysis of the role of CP as a hinge

-Better clarify the FG simulation methodology

-Align the CG and the FG polar plots

-Perform experiments with anti-CD3 antibody 2C11

-Perform additional experiment using weaker agonist (HEL peptide mutant)

-Measure baseline-level TCR expression

-Perform T cell activation experiments at t=0 h

1. Regarding the section "The TCRβ FG loop acts as a gatekeeper," besides contact analysis, additional motion analysis, such as RMSF or PCA, can further establish the importance of FG loops.

Planned actions:

-Perform additional analyses of FG loop dynamics

1. The discussion on anti-CD3 antibody effects and their potential contribution to CD3 mobility is highly recommended.

Planned actions:

-We will add the discussion of anti-CD3 antibody effects

Reviewer #2 (Public Review):

In this research article a new allosteric mechanism for T cell receptor (TCR) triggering upon peptide-MHC complex binding is presented in which conformational change in the TCR facilitates activation by controlling CD3 dynamics around the TCR. The authors find that the Cb FG loop acts as a gatekeeper and Cb connecting peptide acts as a hinge to control TCR flexibility.

As an initial result, the authors set up two sets of simulations - TCR-CD3 and pMHC-TCR-CD3 in POPC bilayers and identified that the CD3e chains exhibit a wider range of mobility in the pMHC-TCR-CD3 system as compared to the TCR-CD3 system. Next, they examined the contacts between all subunits during the course of both simulations and established that CD3g and CD3eg made far fewer contacts with TCRb in the pMHC-TCR-CD3 simulations. Next, they identified that the TCR is extended in the pMHC-TCR-CD3 simulations with larger tilt angle of 150º and FG loop acts as gatekeeper that allows CD3 movements upon pMHC binding. Finally, Mutations in Cb connecting peptide regions indicated rigidified TCR leading to hypersensitive TCR, proved both by simulations and in vitro experiments.

The following major concerns must be addressed.

Major concerns:

1. The simulations were performed with intracellular regions unfolded and free from the membrane. A more complete system should have the intracellular regions embedded in the membrane. An NMR structure of CD3e is available (Xu et al., Cell, 2008) and could have been modeled into the TCR-CD3 system before the simulation. Prakaash et al., (PLoS, Comput Biol, 2021) studied cytoplasmic domain motions during in their simulation experiments.

Planned actions:

-Explain why we can not perform adequate additional simulations of ITAMs

1. Comparing Fig. 2C and Fig.7C, the movement of CD3eg is more restricted in Fig.7C. Is this because the simulation time is lower in the mutation experiments?

Planned actions:

-Explain the differences between the CG and FG polar plots

1. Only TCR-CD3 simulation were performed for PP and AA mutants. A simulation with pMHC (pMHC-TCRmutants-CD3) should be performed to show increased CD3 mobility.

Planned actions:

-Explain why TCR-CD3-pMHC simulations of the mutants are not feasible at this time

1. Using CD3e antibody, OKT3, for activation instead of pMHC as a separate experiment would add more value to this study. They can look at CD3 mobility and TCR elongation in the system with OKT3 antibody and compare it to the CD3 mobility and TCR elongation with the pMHC system. They can also use OKT3 with AA and PP mutants and perform both simulation and in vitro activation experiments.

Planned actions:

-Perform anti-CD3 (2C11) experiments

-Perform CG simulation of TCR with CD3 Fab fragment

-Explain why we cannot perform FG simulations of TCR mutants with CD3

1. The activation experimental data is rather underwhelming. The difference between WT and PP in 2hr experiment at 0.016 ug/mL looks exceedingly low. A stronger TCR-pMHC system should be considered for the in vitro activation experiments.

Planned actions:

-Explain that this is a dilution curve, which is why at lower concentrations the effect is smaller, but at higher concentrations the effect is clear

1. There is some concern that the scientific work lacks solid experimental functional data and lack of novelty due to earlier TCR-CD3 simulation studies (Pandey et al., 2021, eLife) that already reported flexibility and elongation of the complex.

Planned actions:

-Explain the similarities and difference between this and Pandey’s work; clarify how our study contributes novel findings

Reviewer #3 (Public Review):

The authors first explore structural differences of unbound TCR-CD3 complexes and pMHC-bound TCR-CD3 complexes with coarse-grained simulations. In the simulations with pMHC-bound complexes, the transmembrane (TM) domains of the TCR-CD3 complex and of pMHC are embedded in two opposing membrane patches. In the pMHC membrane patch, a pore is created and stabilised in the simulation setup with the aim to allow water transport in and out of the compartment between the membranes. The authors report a more upright conformation of the TCR extracellular (EC) domain in the simulations in which this EC domain is bound to pMHC, compared to simulations with unbound TCR, and postulate an allosteric signalling model based on these apparent conformational changes and associated changes in TCR-CD3 quaternary arrangements. Subsequently, the authors identify a GxxG motif in the TCRbeta connecting peptide between EC domain and TM domain as putative hinge in allosteric signalling, and explore the effect of double proline and double alanine substitutions in atomistic simulations and experiments.

While these simulation and experimental setups and the addressed questions are of interest in the field, the following weaknesses prevail in my overall assessment of the work:

(1) I am not convinced that the reported coarse-grained simulation results are sound or allow to draw the conclusions stated in the work. In the simulations with a pMHC-bound TCR-CD3 complex, the intermembrane distance in the setup shown in Figure S1 appears excessively large and likely leads to a rather strong force in the membrane-vertical direction and to the reported upright conformation of the TCR EC domain. This upright confirmation thus appears to be a consequence of force from the simulation setup, rather than a consequence of pMHC binding alone as suggested by the authors. While the membrane pore in principle allows water exchange, the relaxation of the intermembrane distance resulting from this water exchange in the 10 microsecond long simulation trajectories is not (but needs to be) addressed. This relaxation eventually would lead to an equilibrated membrane separation, in which essentially no force is exerted on the TCR-pMHC EC complex. However, I suspect that this computationally demanding equilibration is not achieved in the simulations, with the consequence that forces on the TCR-pMHC EC complex in the membrane-vertical direction remain.

In addition, I am not convinced that the Martini force field of the coarse-grained simulations allows a reliable assessment of the quaternary interactions between the TCR and CD3 EC domains. Getting protein structures and interactions right in coarse-grained simulations is notoriously difficult. In simulations with the coarse-grained Martini force field, secondary protein structures are constrained as a standard procedure, and the authors also use a recommended Go-potential procedure, likely to stabilise tertiary protein structures. The quaternary interactions between the TCR EC domain and the pMHC EC domain are modelled by rather strong harmonic constraints to prevent dissociation. While the treatment of the quaternary interactions between the TCR EC domain and the CD3 EC domains in the simulations is not (but needs to be) addressed in detail, I suspect that there are no additional, or only weak constraints to stabilise these interactions. In any case, I think that a faithful representation of these quaternary interactions is beyond the reach of the Martini force field, as is the reported diffusion of the CD3 EC domains around the TCR EC domain, which plays a central role in the allosteric mechanism proposed by the authors (see Fig 2 and 5).

Planned actions:

-We will provide further description and justification for the CG simulations

(2) The allosteric model suggested by the authors is motivated in an introduction that appears to omit central controversial aspects in the field, as well as experimental evidence that is not compatible with allosteric conformational changes in the TCR. These aspects are:

• The mechanosensor model is controversial. In original versions of this model, a transversal force has been postulated to be required for T cell activation. However, more recent single-molecule force-sensor experiments reported in J Goehring et al., Nat Commun 12, 1 (2021) provide no evidence for a scenario in which transversal forces beyond 2 pN are associated with T cell activation.

• The role of catch bonds is controversial. Evidence for TCR catch bonds has been mainly obtained in experimental setups using the biomembrane force probe, in which force is applied to TCRs on the surface of T cells, but is not reproduced in experimental setups using isolated TCRs, see e.g. L Limozin et al., PNAS 116, 16943 (2019)

• Ref. 1 of the manuscript prominently discusses the kinetic segregation model of T cell activation, which is not (but needs to be) addressed in the introduction. In this model, exclusion of CD45 from close-contact zones around pMHC-bound TCRs triggers T cell activation. The model is supported by evidence from diverse experiments, see for example M Aramesh et al., PNAS 118, e2107535118 (2021) and Ref. 1. At least part of this evidence is not compatible with mechanosensing or allosteric models of T cell activation.

Planned actions:

-We will add the requested literature references and include a better description of the kinetic segregation model