The prolactin receptor scaffolds Janus kinase 2 via co-structure formation with phosphoinositide-4,5-bisphosphate
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eLife assessment
This important interdisciplinary study substantially advances our understanding of the prolactin receptor interactions with the membrane lipids and the effect of these interactions on cell signaling. The authors use a combination of state-of-the-art NMR structural analysis, simulations, and cellular assays to provide compelling experimental evidence for protein complexes being regulated by IDR-membrane interactions. The work will be of broad interest to structural biologists and biochemists, and the results presented herein are likely relevant for other non-tyrosine kinase receptors.
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Abstract
Class 1 cytokine receptors transmit signals through the membrane by a single transmembrane helix to an intrinsically disordered cytoplasmic domain that lacks kinase activity. While specific binding to phosphoinositides has been reported for the prolactin receptor (PRLR), the role of lipids in PRLR signaling is unclear. Using an integrative approach combining nuclear magnetic resonance spectroscopy, cellular signaling experiments, computational modeling, and simulation, we demonstrate co-structure formation of the disordered intracellular domain of the human PRLR, the membrane constituent phosphoinositide-4,5-bisphosphate (PI(4,5)P 2 ) and the FERM-SH2 domain of the Janus kinase 2 (JAK2). We find that the complex leads to accumulation of PI(4,5)P 2 at the transmembrane helix interface and that the mutation of residues identified to interact specifically with PI(4,5)P 2 negatively affects PRLR-mediated activation of signal transducer and activator of transcription 5 (STAT5). Facilitated by co-structure formation, the membrane-proximal disordered region arranges into an extended structure. We suggest that the co-structure formed between PRLR, JAK2, and PI(4,5)P 2 locks the juxtamembrane disordered domain of the PRLR in an extended structure, enabling signal relay from the extracellular to the intracellular domain upon ligand binding. We find that the co-structure exists in different states which we speculate could be relevant for turning signaling on and off. Similar co-structures may be relevant for other non-receptor tyrosine kinases and their receptors.
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Author Response
Reviewer #1 (Public Review):
For PRLR, the question being asked is whether and how the intracellular domain (ICD) interacts with the cellular membrane or how the disordered ICD can relay and transmit information. The authors show that PI(4,5)P2 in the membrane localizes around the transmembrane domain (TMD) due to charge interactions and facilitates binding of the ICD to the membrane, even in the absence of the TMD. Furthermore, the ICD and PI(4,5)P2 form a co-structure with JAK2 which locks a disordered part of the ICD into an extended conformation, allowing for signal relay and, through multiple complex conformations, may enable switching signalling on and off.
Strengths:
- NMR paired with MD is a powerful way to probe an interaction especially when peaks disappear and become difficult to probe by NMR.
- Using NMR …
Author Response
Reviewer #1 (Public Review):
For PRLR, the question being asked is whether and how the intracellular domain (ICD) interacts with the cellular membrane or how the disordered ICD can relay and transmit information. The authors show that PI(4,5)P2 in the membrane localizes around the transmembrane domain (TMD) due to charge interactions and facilitates binding of the ICD to the membrane, even in the absence of the TMD. Furthermore, the ICD and PI(4,5)P2 form a co-structure with JAK2 which locks a disordered part of the ICD into an extended conformation, allowing for signal relay and, through multiple complex conformations, may enable switching signalling on and off.
Strengths:
- NMR paired with MD is a powerful way to probe an interaction especially when peaks disappear and become difficult to probe by NMR.
- Using NMR and MD to formulate hypotheses which are then tested by cell studies is quite informative. The combination of MD, NMR, and cell biology is a strength.
- The authors are diligent in testing MD simulations on systems with and without PIP2.
- The use of Pep1 and Pep2 to differentiate the KxK region that interacts with PIP2 is helpful.
- The four utilized mutants help illustrate the co-dependence of the respective regions in the formation of the co-structure.
Weaknesses:
- In Figure 2G, there is a big change in CSP between 280 and 290, which the authors do not comment about.
The region referred to contributes to binding but is on the edge of the main binding site and where the local affinities are weaker. Therefore, the exchange rate is high and allows for following the chemical shift changes. In support of this, we see an almost inverse correlation between the CSPs and the changes in intensities. For the main binding site, the exchange rate between bound and free states is slower because the affinity is stronger. Therefore, we cannot follow the chemical shifts to extract the CSPs to the bound state, as the peaks disappear. We have commented on this in the main text (p.8) as follows:
“In the region from D285-E292 we observed an almost inverse correlation between the CSPs and the intensities. This suggests that in contrast to the preceding region, a faster local exchange rate allows us to follow the resonances from the bound state in this region, giving rise to the large CSPs.”
- The data in Figure 2 are summarized as indicating the formation of extended structure in the ICD upon binding. It is not clear to me what data show an extended structure.
The information on the extended structure comes from the analyses of the peptide Pep1 titrated with C8-PI(4,5)P2. The CD signature that develops in the bound state has a minimum ellipticity at 218 nm, which is a strong indicator of extended structure. We find this information adequately described in the main text (p.8), but have emphasized this further as follows:
“In contrast, for Pep1, large spectral changes were seen, which were unrelated to helix formation. Subtracting the spectra in the presence and absence of C8-PI(4,5)P2, revealed a negative ellipticity minimum at 218 nm, a strong indication of B-strands, showing that when bound to C8-PI(4,5)P2, a distinct extended (strand-like structure) signature was seen (Figure 2G).”
- No modelling or experiments were done with PIP3 despite conclusions and models which rely on the phosphorylation of PIP2 to PIP3. At the very least, these would be useful as negative controls.
We have in a previous work addressed the affinity for phosphoinositides using lipid dot blots where we observed a preference for certain species, including PI(4,5)P2 (Haxholm et al., BJ, 2015). In this study, we also observed that there was no affinity for PI(3,4,5)P3, but may not have highlight this sufficiently in the introduction. This can have caused some confusion in understanding our choices. We have now more explicitly described these data, both in the introduction (p.4), in the result section (p. 8) and later in the discussion (p. 21). We thank the reviewer for bringing this up.
- Only R2 experiments were done when the authors mention investigating dynamics. R1 and -HetNOE dynamics would be useful for creating a complete picture.
Our aim with recording the R2 values was not to map the detailed dynamics of the disordered regions, but to explain the changes in the peak intensities we see for the variants when adding C8PI(4,5)P2. In this case, the R2 values supported our suggestion of internal contacts and, although we agree with the reviewer that R1s and HetNOEs would be important and relevant for a more in-depth and complete analyses of the dynamics, we find that in this case, the R2 values suffice.
- Some of the exciting results are under-emphasized including Fig 3H and 3I.
A new version of Figure 3 has been generated to consider the reviewers’ comments and suggestions. This figure has been restructured to further emphasize some of the major conclusions obtained from the simulations. We have moved the former Figure 3 A, B, C and D to the supplemental information to increase this focus.
Reviewer #2 (Public Review):
The authors combine NMR experiments, cell experiments, and molecular simulations to address the question of how lipid interactions of the prolactin receptor contribute to signalling. They assess the interactions of the disordered cytoplasmic tail of the receptor with phosphoinositides among others by chemical shift perturbations from NMR for different PIP2-containing membranes, by coarse-grained simulations, as well as site-directed mutagenesis and subsequent cell signalling experiments to monitor the activation of the mutants. A major result is that PIP2 interactions are functionally important, which so far has not been known for this receptor. Their results are likely relevant for other non-receptor tyrosine kinases.
The hypothesis that the protein complex is regulated by IDR-membrane interactions is very novel. A major strength is the close connection of and feedback between state-of-the-art experiments and simulations.
We thank the reviewer for the positive comments on our work and on the novelty and importance of the work
This is where I see weaknesses:
- The motivation of focusing on LID1 is limited.
We have now provided our rationale for selectively focusing on the LID1 in the PRLR. The selection was done to address the conundrum on how structural disorder in the juxtamembrane regions would be able to transmit the knowledge of extracellular hormone binding to the bound JAK2. This constitute the first step of signaling on the intracellular side and given the distance to the other two LIDs (LID2 and LID3) and their disconnect to the TMD by long disordered regions, they were disregarded, focusing on LID1 in this work. We have emphasized this choice in the introduction and in more detail in the result section (p. 5-6).
- The data and analysis for the JAK2-PRLR complex appear somewhat superficial, and a connection between conformational states to their functional relevance is lacking. In fact, the majority of the simulation part of the paper is about suggesting different states of the PRLR-JAK2 complex but the states and their hypothesized functional relevance are not further taken up, e.g. by experiments, and yet presented as major results, e.g. in the abstract.
In the original manuscript we already provided a detailed analysis of the different states, highlighting accessible residues and lipid interacting residues and compare these across the states. From our experiment, including those performed in cellular assay, we cannot with certainty link the two major state to active and/or inactive states. We have therefore no intention or support from the data to claim this. However, what we do put forward as a major result, in the presence of more than one major state as also stated in the abstract and in the conclusion of the result section as follows:
“Another key observation is the existence of different states in which different regions of both JAK2 FERM-SH2 domain and LID1 of PRLR are exposed to the solvent or hidden below the bilayer.”
In the discussion we do speculate as to which state may be the active and/or inactive dimer/monomer but make no firm claims. We have now made the major find of more states clearer in the text, and further compare the two major states, the Y and the Flat state, to the resent cryo-EM structures of JAK1 bound to IFNAR1, which lend some support to our speculations. The abstract now reads:
“We find that the co-structure exists in different states which we speculate could be relevant for turning signalling on and off.”
To discern the functional relevance of these state, if possible, will require experiments also in cells that by themselves would be a new study. We have to the best of our ability clarified that the functional relevance of the states has not been elucidated by the current work.
- The connection between simulations and mutational study is not very direct. An open question is if the mutants can distinguish between the effects of PRLR-PIP2 interaction or PRLR-JAK2 interaction, even though this conclusion is still drawn from the data.
We have now explained in much more detail by which arguments the different mutations were selected (see also answer above), which property of the co-structure they are most likely to engage in and affect, and we have emphasized that the separation of function by mutation may be complicated by the intimate structure formation among the three components of the co-structure. The conclusion has therefore also been softened.
- The conclusions drawn from the mutagenesis study (lines 547-555) are not directly supported by data. Only a partial correlation between PRLR membrane localisation and STAT5 activation is no reason to attribute the unexplained part of the STAT5 activation to PRLR-JAK2 interactions without further studies.
We have now explained in much more detail by which arguments the different mutations were selected (see also answer above), which property of the co-structure they are most likely to affect and emphasized that the separation of function by mutation may be complicated by the intimate structure formation among the three components of the co-structure. The conclusion has therefore also been softened.
- PIP2 is identified as an important regulator, with very solid support from the presented data. PIP3 is part of the model but not discussed before or as part of the results. The analysis could be similarly applied or the data directly relevant to the understanding of PIP3 plays a similar role, as interactions are likely primarily electrostatically driven.
We have in a previous work addressed the affinity for phosphoinositides using lipid dot blots where we observed a preference for certain species, including PI(4,5)P2 (Haxholm et al., BJ, 2015). In this study, we also observed that there was no affinity for PI(3,4,5)P3, but we agree that we did not highlight this sufficiently in the introduction. This have caused some confusion in understanding our choices. We have not more explicitly described these data, both in the introduction (p.4), in the result section (p. 8) and later in the discussion (p. 21). We thank the reviewer for bringing this up.
Reviewer #3 (Public Review):
Araya-Secchi and coauthors present a very interesting study on the role of PIP2 lipids in the potential modulation of prolactin receptor signaling. The study is well-conducted and employs an integrated approach that combines NMR spectroscopy, modeling (primarily coarse-grain MD simulations), and cell biology. This combination of methods is crucial for gaining a deeper understanding of cell receptors, from their biophysical properties to their cellular functions.
The modelling work is mainly based on both coarse grain forcefield versions Martini2.2 and Martini3. These two versions of the forcefield may produce different results. Therefore, depending on the system being modeled, the results presented here should be considered in light of the limitations inherent to each version of the forcefield.
We thank the reviewer for the positive appraisal of our work and the approach we employed. It is true that one must be aware of the limitations of the tools and models employed in this type of work. We agree that perhaps we were not too explicit about limitations of our methods in the presentation of the results. However, we have addressed and discussed such limitations in the revised version of the manuscript.
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eLife assessment
This important interdisciplinary study substantially advances our understanding of the prolactin receptor interactions with the membrane lipids and the effect of these interactions on cell signaling. The authors use a combination of state-of-the-art NMR structural analysis, simulations, and cellular assays to provide compelling experimental evidence for protein complexes being regulated by IDR-membrane interactions. The work will be of broad interest to structural biologists and biochemists, and the results presented herein are likely relevant for other non-tyrosine kinase receptors.
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Reviewer #1 (Public Review):
For PRLR, the question being asked is whether and how the intracellular domain (ICD) interacts with the cellular membrane or how the disordered ICD can relay and transmit information. The authors show that PI(4,5)P2 in the membrane localizes around the transmembrane domain (TMD) due to charge interactions and facilitates binding of the ICD to the membrane, even in the absence of the TMD. Furthermore, the ICD and PI(4,5)P2 form a co-structure with JAK2 which locks a disordered part of the ICD into an extended conformation, allowing for signal relay and, through multiple complex conformations, may enable switching signalling on and off.
Strengths:
- NMR paired with MD is a powerful way to probe an interaction especially when peaks disappear and become difficult to probe by NMR.
- Using NMR and MD to formulate …Reviewer #1 (Public Review):
For PRLR, the question being asked is whether and how the intracellular domain (ICD) interacts with the cellular membrane or how the disordered ICD can relay and transmit information. The authors show that PI(4,5)P2 in the membrane localizes around the transmembrane domain (TMD) due to charge interactions and facilitates binding of the ICD to the membrane, even in the absence of the TMD. Furthermore, the ICD and PI(4,5)P2 form a co-structure with JAK2 which locks a disordered part of the ICD into an extended conformation, allowing for signal relay and, through multiple complex conformations, may enable switching signalling on and off.
Strengths:
- NMR paired with MD is a powerful way to probe an interaction especially when peaks disappear and become difficult to probe by NMR.
- Using NMR and MD to formulate hypotheses which are then tested by cell studies is quite informative. The combination of MD, NMR, and cell biology is a strength.
- The authors are diligent in testing MD simulations on systems with and without PIP2.
- The use of Pep1 and Pep2 to differentiate the KxK region that interacts with PIP2 is helpful.
- The four utilized mutants help illustrate the co-dependence of the respective regions in the formation of the co-structure.Weaknesses:
- In Figure 2G, there is a big change in CSP between 280 and 290, which the authors do not comment about.
- The data in Figure 2 are summarized as indicating the formation of extended structure in the ICD upon binding. It is not clear to me what data show an extended structure.
- No modelling or experiments were done with PIP3 despite conclusions and models which rely on the phosphorylation of PIP2 to PIP3. At the very least, these would be useful as negative controls.
- Only R2 experiments were done when the authors mention investigating dynamics. R1 and -HetNOE dynamics would be useful for creating a complete picture.
- Some of the exciting results are under-emphasized including Fig 3H and 3I. -
Reviewer #2 (Public Review):
The authors combine NMR experiments, cell experiments, and molecular simulations to address the question of how lipid interactions of the prolactin receptor contribute to signalling. They assess the interactions of the disordered cytoplasmic tail of the receptor with phosphoinositides among others by chemical shift perturbations from NMR for different PIP2-containing membranes, by coarse-grained simulations, as well as site-directed mutagenesis and subsequent cell signalling experiments to monitor the activation of the mutants. A major result is that PIP2 interactions are functionally important, which so far has not been known for this receptor. Their results are likely relevant for other non-receptor tyrosine kinases.
The hypothesis that the protein complex is regulated by IDR-membrane interactions is very …
Reviewer #2 (Public Review):
The authors combine NMR experiments, cell experiments, and molecular simulations to address the question of how lipid interactions of the prolactin receptor contribute to signalling. They assess the interactions of the disordered cytoplasmic tail of the receptor with phosphoinositides among others by chemical shift perturbations from NMR for different PIP2-containing membranes, by coarse-grained simulations, as well as site-directed mutagenesis and subsequent cell signalling experiments to monitor the activation of the mutants. A major result is that PIP2 interactions are functionally important, which so far has not been known for this receptor. Their results are likely relevant for other non-receptor tyrosine kinases.
The hypothesis that the protein complex is regulated by IDR-membrane interactions is very novel. A major strength is the close connection of and feedback between state-of-the-art experiments and simulations.
This is where I see weaknesses:
1. The motivation of focusing on LID1 is limited.
2. The data and analysis for the JAK2-PRLR complex appear somewhat superficial, and a connection between conformational states to their functional relevance is lacking. In fact, the majority of the simulation part of the paper is about suggesting different states of the PRLR-JAK2 complex but the states and their hypothesized functional relevance are not further taken up, e.g. by experiments, and yet presented as major results, e.g. in the abstract.
3. The connection between simulations and mutational study is not very direct.
An open question is if the mutants can distinguish between the effects of PRLR-PIP2 interaction or PRLR-JAK2 interaction, even though this conclusion is still drawn from the data.
4. The conclusions drawn from the mutagenesis study (lines 547-555) are not directly supported by data. Only a partial correlation between PRLR membrane localisation and STAT5 activation is no reason to attribute the unexplained part of the STAT5 activation to PRLR-JAK2 interactions without further studies.
5. PIP2 is identified as an important regulator, with very solid support from the presented data. PIP3 is part of the model but not discussed before or as part of the results. The analysis could be similarly applied or the data directly relevant to the understanding of PIP3 plays a similar role, as interactions are likely primarily electrostatically driven. -
Reviewer #3 (Public Review):
Araya-Secchi and coauthors present a very interesting study on the role of PIP2 lipids in the potential modulation of prolactin receptor signaling. The study is well-conducted and employs an integrated approach that combines NMR spectroscopy, modeling (primarily coarse-grain MD simulations), and cell biology. This combination of methods is crucial for gaining a deeper understanding of cell receptors, from their biophysical properties to their cellular functions.
The modelling work is mainly based on both coarse grain forcefield versions Martini2.2 and Martini3. These two versions of the forcefield may produce different results. Therefore, depending on the system being modeled, the results presented here should be considered in light of the limitations inherent to each version of the forcefield.
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