Proximity Interactome analyses unveil novel regulators of IRE1α canonical signaling

  1. Simon Le Goupil
  2. Céline Philippe
  3. Hadrien Laprade
  4. Mathéo Lode
  5. Rachel Boniface
  6. Diana Pelizzari-Raymundo
  7. Kurt Dejgaard
  8. Gregor Jansen
  9. Celia Limia
  10. Claudio Hetz
  11. S. Jalil Mahdizadeh
  12. Luc Negroni
  13. Marc Aubry
  14. Jean-Ehrland Ricci
  15. Leif A. Eriksson
  16. Eric Chevet

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Abstract

The unfolded protein response (UPR) is a key adaptive pathway that controls endoplasmic reticulum (ER) homeostasis. The UPR is transduced by three ER-resident sensors of ER homeostasis disruption in the lumen of this compartment. They trigger select downstream signaling pathways in the cytosol and nucleus. Among them, IRE1α (referred to as IRE1 hereafter), a type I transmembrane protein, senses accumulation of improperly folded proteins in the ER lumen and transduces signals through both kinase and endoribonuclease (RNase) activities in the cytosol. IRE1 catalyzes XBP1 mRNA unconventional splicing and RNA degradation (Regulated IRE1 Dependent Decay, termed RIDD). Recent studies have reported that IRE1-dependent protein-protein interactions (PPi) drive additional non-canonical IRE1 functions. Herein, we define the IRE1 signalosome as a list of IRE1 binding partners (direct or not) which alter IRE1 signaling towards XBP1 mRNA splicing and RIDD. Here we determined the IRE1 in situ interactome using BioID, putatively connecting IRE1 to previously unrecognized cellular functions. In addition, we link the binding of several IRE1 partners to the regulation of its RNase. Furthermore, we identify HNRNPL as an IRE1-interacting partner, previously unrecognized, which stabilizes IRE1 under basal conditions by counteracting ERAD-mediated degradation. Overall, the characterization of the IRE1 signalosome not only reveals the multi-faceted control of IRE1 RNase activity and stability by its interacting partners and allow us to discuss putative additional IRE1 regulators and cellular functions based on the nature of its interactome and its localization.

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    Reply to the reviewers

    Manuscript number: RC-2024-02810

    Corresponding author(s): Eric CHEVET

    1. General Statements [optional]

    This section is optional. Insert here any general statements you wish to make about the goal of the study or about the reviews.

    We would like to thank the reviewers who pointed towards specific points in our manuscript which once addressed will make the work stronger.

    2. Description of the planned revisions

    Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

    • Reviewer 1 (General comments) raised the possibility that some interactions are post-lysis artifacts as ER lumen proteins are biotinylated. This is indeed true and this was our first reaction when analyzing the data. We and others previously demonstrated that a subset of ER luminal proteins can reflux (PMID: 38865586) out of the ER to the cytosol in both mammalian cells (PMID: 33710763, PMID: 37925033) and yeast (PMID: 32246734, PMID: 31101715) upon ER stress notably in mammalian cells some PDIs (PMID: 33710763) or some chaperones such as BiP (PMID: 37487081). To address whether PDIA4 could possibly be biotinylated by BirA*, we tested if PDIA4 could be found in the cytosolic fraction (using methodologies previously reported) (Fig. 1) (see also section 3).

    These experiments show that PDIA4 can be found in the cytosol under ER stress conditions and thereby become a substrate for our fusion IRE1-BirA* protein. Moreover, our interactome study we found other ER-resident proteins, actually also found in other IRE1 proximitome approaches using TurboID (PMID: 38727283) such as HSP90AB1. This information will be added in the revised manuscript as well. To further address this reviewer’s comment, we propose, using the subcellular-fractionation protocol previously used, to assess the presence of other ER luminal protein from our BioID experiment (such as HSP90AB1 or GRP78/BiP) in the cytosol upon basal and ER stress conditions and test the interaction IRE1/PDIA4 using in situ cross-linking followed by a co-immunoprecipitation approach with or without ER stress.

    • Reviewer 1 & 2 (Specific points):
    • Figure2D: Reviewer 1 cannot appreciate the ER stress-induced expression of XBP1s.
    • Reviewer 2 questions the uses of different stressors along the paper.

    We agree that these points could be significantly improved. We will address these specific points by transfecting HEK293T cells with BirA* alone or IRE1-BirA and stressing the cells with 3 different ER stressors used in this study (DTT, Tg, Tm) and then evaluate XBP1 mRNA splicing using RT-qPCR and XBP1s expression using Western blotting. IRE1-BirA overexpression will be quantified compared to endogenous IRE1. Regarding Fig 2D the WB in MA2-KO cells with increasing amount of transfected IRE1-BirA will be repeated to show a better image of the XBP1s blot.

    • Reviewer 1 (Specific point) suggests that BirA might not be expressed since the protein is not visible on the western blot Fig2E. The cytosolic BirA* (cBirA*) has been expressed and was detected by mass spectrometry. All the mass spectrometry data presented in the manuscript corresponded to those found using IRE1-BirA* of which those found with cBirA* alone were removed. This information was indeed missing and will be added in the revised version as well as the datasets corresponding to cBirA* alone. In addition, we will show the western blot on cBirA transfected cells.
    • Reviewer 1 & 3 (Specific points):
    • Figure7: Reviewer 1 asks for a IRE1/hnRNPL co-immunoprecipitation.
    • Figure7: Reviewer 3 asks to develop the results obtained on hnRNPL. Does the depletion of HNRNPL influence the expression of SEL1L? Does it influence some other aspect of IRE1 stability maybe through a protein-protein interactions?

    We will perform IRE1 immunoprecipitation by transfecting HEK293T cells with IRE1-flag and then blot hnRNRPL, SEL1L and SYNV1. We will also test the expression of SEL1L upon hnRNRPL knockdown and test other ERAD proteins clients by western blotting to address whether our result is specific to IRE1. Moreover, to further document the role of hnRNRPL on the biology of IRE1 we will evaluate how the absence of hnRNPL impacts on IRE1 signaling through comparison of RNAseq data from IRE1 deficient cells (or IRE1 RNase inhibitor treated cells) with those obtained from hnRNPL silenced cells. This should allow us to identify gene networks specific of IRE1 (or IRE1 RNase) and common to those impacted by hnRNPL silencing. At last, we will evaluate how the relationship hnRNPL/IRE1 impacts on cells’ ability to cope with chemically induced ER stress. To do so we first propose to compare ER stress-induced cell death in cells invalidated for IRE1 (genetically or pharmacologically) and others silenced for hnRNPL. These results will be confronted to those obtained in vivo in the fly (collaboration Pedro Domingos ongoing).

    • Reviewer 2 & 3 (Specific points):
    • Reviewer 2 raised the possibility that the large basal interactor might be due to the very long time periods in the BioID process. The reviewer asks if we did perform a time course of biotin treatment.
    • Reviewer 3 asks for a timecourse of ER stress (with treatment shorter than 16h) to better catch the dynamic nature of IRE1 PPIs that regulate IRE1 activity.

    We agree with these comments. We used a BirA* enzyme to characterize the IRE1 interactome, this enzyme (BirA*) which requires at least 16h to label efficiently proteins at proximity with biotin. To validate (or not) our interactome data, we propose to perform experiments with shorter labelling time, and use an IRE1-TurboID and perform different time course (ranging from 30min to 8h) with or without stress in the presence of biotin. Biotinylated proteins will be purified and we will test the presence of different proteins that have been captured in our first IRE1-BioID analysis using Western blotting with specific antibodies.

    • Reviewer 3 (Specific points):
    • Reviewer 3 says that other RIDD targets should be tested, notably BLOS1 (Fig5D). Moreover, the reviewer suggests to include a condition with a RNAse inhibitor as positive control.

    We will perform transfection in HEK293T cells with the different siRNA candidates as we did in Fig5D. Then we will assess the effect of the different knockdown on RIDD targets by testing BLOS1 and DGAT2, two robust RIDD targets, by RT-qPCR. This experiment will be performed with or without stress, in the presence or not of MKC8866 and in the presence of Actinomycin D in order to block transcription which could lead to confounding effects in terms of gene expression.

    • Reviewer 3 (Specific points):
    • Reviewer 3 asks to validate the direct interaction between PTPN1 and IRE1 and to further developed the role of IRE1/PTPN1 interaction in the splicing activity of IRE1.

    To test the direct interaction between IRE1 and PTPN1, we are planning to use GST-PTPN1 (commercially available) and HIS-IRE1 recombinant proteins produced in the laboratory (either WT or N638D) as previously reported by us (PMID: 20237204). We will then perform successive GST-pulldown in presence of GST-PTPN1 and HIS-IRE1. In addition, we are also planning to measure XBP1 mRNA splicing by RT-qPCR upon PTPN1 knockdown in HEK293Tcells expressing IRE1 WT or IRE1 N638D mutant and treated, or not, with ER stress inducers. In these conditions, the activity of IRE1 and its mutant in terms of RNase activity (XBP1 mRNA splicing and RIDD) will be evaluated.

    • The reviewers asked for some precisions that could be answered directly in the manuscript. Here are the modifications of the text.
    • Reviewer 1 (specific point) found that Figure 1 is misleading.

    The meta-analysis depicted in Figure 1 of the manuscript includes data from many studies aiming at identifying IRE1 interactors using high-throughput methods. However, one must consider that those interactors were studied in different backgrounds: different cell types, technics and treatments. In addition, considering the low abundance of IRE1 and the high number of interactors shown in Figure 1, it should be highly improbable that all those IRE1 interactions occur at the same time. The comment of Figure 1 will be modified to better appreciate the way this network was built alongside its associated bias. We agree that we could use this figure in supplemental material to justify our strategy for in situ proximity labelling.

    • Reviewer 1 (specific point) asks how the MS analysis was carried out to avoid false positive. Mass spectrometry data were indeed analyzed by subtracting the hits found in control conditions (cBirA*) from the hits detected with IRE1-BirA*, as hypothesized by the reviewer. The manuscript text will be modified accordingly to better appreciate the curation that was performed and the cBirA* dataset added on the ProteomeXchange database.
    • Reviewer 1 (minor points) argues that apoptosis is not a major cluster from the stressed interactome. Here, we highlight that the term “Regulation of apoptotic process” is exclusively enriched in the stressed interactome, therefore referring to terminal UPR that occurs during prolonged stress. Also, this term includes 16 IRE1 interactors (which corresponds to 30% of the stressed interactome and 7% of the global interactome). Altogether, this explains why we considered this term to comment to comment the Gene Ontology. The manuscript will be modified to better illustrate the choice of this term.
    • Reviewer 1 (minor points) asks to discuss the possibility of interactions due to IRE1 overexpression and the bias associated with the technic (plus how authors fixed these issues). Bias due to IRE1 overexpression are discussed in the Section “Approach limitations” as follows: “Since we used transient overexpression of IRE1 for our BioID study, there might be an increased basal level of ER stress compared to stable transfection, modifying the basal UPR signaling properties.” This will be modified to discuss a potential increase in the number of IRE1 interactors due to IRE1 overexpression. Regarding the technical approach, our BioID approach does not allow to detect transient interactions, a limitation that will be commented to this section.
    • Reviewer 2 (specific points) argues that addition of the bars from Figure S2C should reach 100%. The analysis carried out for Fig S2C uses the COMPARTMENTS plugin on Cytoscape (Binder et al. 2014) and does not aim to add up the percentage to 100%. In detail, this plugin individually calculates a score (from 0 to 5) for a protein in each subcellular compartments listed in the panel, based on manually curated literature, high-throughput screens, automatic text mining, and sequence-based prediction methods. Then for each compartment, we counted the number of proteins with a score higher than 4,75 (= 95% of 5) and calculated the abundance percentage relatively to the total number of proteins of the datasets (for BioID or Ref independently), providing the values displayed in the panel S2C. The fact that each analysis is independent from one another and that one protein may be counted in several compartments makes the addition to 100% irrelevant.
    • Reviewer 2 (minor points) specifies that the Adamson dataset used in our analysis is a Perturb-Seq. We thank the reviewer for noticing this imprecision. The manuscript will be revised to be more specific about the nature of the Adamson dataset (e.g. replacing CRISPR screen by CRISPRi screen coupled with Perturb-Seq).
    • Reviewer 2 (minor points) asks to rework some figures to enlarge the size of the font and to better separate the panels of some figures. Additionally, he suggests that the manuscript could benefit of a careful English editing. We thank the reviewer for this comment. Figures will be reworked for improved readability (e.g. font size and panel boundaries). Regarding the manuscript, it will be reworked to improve the writing quality and correct the mistakes.
    • Reviewer 2 (minor points) pointed on page 10 the sentence “Thus, IRE1 BioID identified new IRE1 interactors and revealed that IRE1 interactions are responsive to stress” while the majority of the interactions occur in basal. We thank the reviewer for this comment and agree that the sentence could be clarified. The fact that 25% of the interactions appear specifically during ER stress treatment despite the stress already induced by IRE1 overexpression suggests that the exogenous stress is still able to modify IRE1 interactions. It therefore indicates that overexpressed IRE1 interacts with a different landscape of proteins upon induced ER stress.
    • Reviewer 3 (specific points) asks for some precision about the duration of the stress treatments used for the BioID. We thank the reviewer for noticing some of these inconsistencies in the manuscript. To be precise, the stress treatment (Tg or TM) of the BioID carried out for mass spectrometry is concomitant to the addition of exogenous biotin, which is indeed 16h treatment. While we agree such stress treatment is longer than usual, we highlight that both biotin and ER stress treatment had to be added for the same duration, to allow the detection of ER stress interactors during the slow kinetic of BirA* dependent biotinylation. The results section, figure legends and Materials and Methods will be edited to harmonize the concomitant ER stress/biotin treatment for BioID coupled with mass spectrometry.

    3. Description of the revisions that have already been incorporated in the transferred manuscript

    Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

    • Reviewer 1 (General comments) raised the possibility that some interactions are post-lysis artifacts as ER lumen proteins are biotinylated. PDIA4 is an ER luminal protein identified by our cytosolic BioID. To test whether this protein could be found in the cytosol, we performed subcellular fractionation and were able to observe PDIA4 in the cytosolic fraction (Fig 1 Revision). This was confirmed by quantifying the relative signal between PDIA4 and Calnexin used as the ER marker. The experiment will be expanded to other ER luminal proteins found in our interactome.
    • Reviewer 1 (Specific point) suggests that BirA might not be expressed since the protein is not visible on the western blot Fig2. In addition, Reviewer 1 asks how the MS analysis was carried out to avoid false positive. As mentioned above, BirA has not been detected by western blot so far. However, it was by mass spectrometry, as shown by the table displaying BirA Signal Intensity (Fig 2 Revision). BirA is less expressed in control condition than fused with IRE1, which may explain a low signal exerted by the streptavidin-HRP blot.
    • Reviewer 1 (Specific point) asks for an improved visualization of panel 5A, showing a NATIVE-PAGE with higher exposure associated quantification of %oligomerization. Also, reviewer 1 suggests adding a corresponding SDS-PAGE for IRE1. Regarding IRE1 oligomerization, Panel 5A has been reworked according to the reviewer’s comment (Fig 3 Revision). A higher exposed picture of the NATIVE-PAGE is provided and SDS-PAGE in the same conditions is shown. Quantification of % IRE1 oligomerization is also provided to better appreciate this result. Figure 5 of the manuscript will be reworked to implement such modifications.

    Figure ____3____ Revision: Rework of panel 5A with IRE1 SDS-PAGE and quantification of IRE1 oligomerization.

    • Reviewer 3 (specific point) asks for a quantification of IRE1-BirA overexpression compared to WT. To address this reviewer’s comment, a preliminary result has been obtained using Western blot, regarding the comparison of the expression between overexpressed IRE1-BirA* and WT IRE1. This shows that IRE1-BirA* is expressed between 5 to 8 times more than WT, independently of ER stress induction by DTT (Fig 4 Revision). This will be repeated at least twice independently to consolidate the data.
    • Reviewer 3 (Specific point) asks for a comparison of the IRE1 BioID with the Turbo-ID recently published by Ahmed et al. Ahmed et al identified 155 interactors for IRE1α and 137 for IRE1β in the HMC1.2 leukemia cell line. Yet, the entire list of these interactors is neither available in the manuscript nor on the ProteomeXchange database. When comparing our interactors with the hits released in their work (Ahmed et al. 2024), we find 20 (including IRE1) that are shared with our dataset (__Fig 5 Revision, __IRE1 is not indicated on the Venn diagram).

    Figure ____5____ Revision: Venn diagram of IRE1 shared interactors between Le Goupil et al BioID and the available data in Ahmed et al TurboID 2024 (data on ProteomeXchange PXD047343 not yet available).

    Considering that the approach Ahmed et al. used relies on another proximity labeling method, that the experiment was carried out in another cell line and that the total number of hits is of the same order of magnitude as that obtained in our analysis, one can be relatively confident about our results. We agree that a full comparison will be more informative (we will provide a full comparison in the revised version by using the proteomeXchange dataset if available, if not, we will contact them directly).

    • Reviewer 3 (Specific point) asks whether the IRE1 N683D mutant could exert a different basal activity than the WT IRE1. The IRE1α mutant N683D has been controlled upon reception. Preliminary results measuring the splicing of XBP1 by RT-qPCR in basal conditions showed that the mutant’s basal activity is at a steady-state level through time, comparable to the WT (Fig 6 Revision). Provided that this mutant is expressed at a lower level than IRE1 WT, one might consider that the ability of N683D to exert a higher XBP1 mRNA splicing activity on its own than the WT is neglectable.

    4. Description of analyses that authors prefer not to carry out

    Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.

    • Reviewer 2 (Specific point) suggests to develop the results regarding the comparison between IRE1α, IRE1β and PERK interactors. Regarding the IRE1α/PERK comparison, both interactome was performed in HEK293T cells using the BirA* system (PMID: 37366380), minoring the issues regarding methodological bias. Functionally, both sensors aim to alleviate ER stress, and one might hypothesize that these interactors commonly regulate IRE1 and PERK pathways, either to promote or limit the ER stress response. In accordance the GO further suggests that these interactors are closely associated with ER stress regulation. When focusing on structural aspects, IRE1 and PERK both display a kinase domain. Alignment of the sequence of IRE1α and PERK kinase domain only shows a limited conservation (24% identity calculated with Clustal Omega), however, when looking at 3D structures of the respective kinase domain (PDB: 4G31 for PERK and PDB: 4YZ9 for IRE1), we observe common features (e.g. N-lobe, 7 α-helixes in the C-lobe), which might underline similar ways of interactor-dependent regulation.

    We agree with this reviewer that the comparison of the different interactomes is of great interest and that this will be part of our investigations in the future. At present time, we provide

    below a Venn diagram that integrates data from different datasets (our data on IRE1α and b bioID interactomes in HEK293T cells (https://doi.org/10.1101/2024.10.27.620453), the PERK bioID interactome in HEK293T cells (PMID: 37366380), the IRE1α turboID interactome in HMC1.2 cells (PMID: 38727283) and the IRE1b IP/MS interactome in goblet cell lines (PMID: 38177501)).

    Figure 6: Venn diagram of the shared interactors between IRE1a, IRE1b, and PERK from several studies.

    This shows that the IRE1α and PERK interactomes, generated using BirA* fusions in HEK293T cells share 43 proteins which may be of course highly interesting to evaluate whether these interactions could occur through IRE1α and/or PERK kinase domains (e.g., PERK and IRE1α interaction with PTPN1). Regarding the IRE1α/IRE1β comparison, the IRE1β interactome was evaluated either using bioID (our data) or using IP-MS in LS174T goblet-like cells (PMID: 38177501) - provided that data from Ahmed et al. not available yet. Hence, we agree here that these differences impose biases that are not optimal to compare the interactomes (for instance AGR2 is not endogenously expressed in HEK293T cells). Overall, we do not plan to extend the experiments on these topics, as this is not directly aligned with the main scope of our study, but are definitely interested in pursuing the relevance of the shared interactomes in future studies. As the manuscript does not provide much explanation of these panels in the results section, we are considering either improving the discussion of existing panels, or deleting them from the manuscript.

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    Referee #3

    Evidence, reproducibility and clarity

    In this manuscript, the authors utilize a proximity ligation approach to probe protein-protein interactions involved in regulating the activity and stability of the ER stress sensing protein IRE1. Specifically, they express an IRE1-BirA fusion protein that they use to identify specific protein-protein interactions that influence the relative IRE1 RNAse activities of XBP1 splicing and RIDD. They go on to focus on two hits, PTPN1 and HNRPL, showing that these proteins influence IRE1 RNAse activity and stability, respectively.

    Overall, the primary value of this manuscript is the list of potential interactors that is generated through this approach. Limitations are largely discussed in the manuscript. These include the fact that only interactors in the cytosol are accurately profiled owing the construct design and the potential for overexpression artifacts. Apart from those, there are some other issues with the manuscript that should be addressed, which are highlighted in more detail below. Ultimately, this manuscript doesn't provide a lot to move the field forward apart from providing another list of potential IRE1 interactors. The two 'hits' pursued are not sufficiently developed to reveal new insights into IRE1 regulation, as the mechanisms are not well developed and it isn't clear something 'new' has been discovered that directly relates to IRE1. I strongly recommend that the authors advance on of these hits to more deeply understand the mechanistic insights related to their (potential) involvement of IRE1 regulation.

    Specific Comments.

    1. The authors bring up the potential for overexpression artifacts, but they should define how much overexpression is observed by comparing the relative expression of overexpressed protein to endogenous IRE1 by western blotting.
    2. There is some confusion regarding the timing of the BioID experiments, especially as it relates to the addition of ER stress. In the text, it seems that the authors treat with ER stress for 16 h, while the legend suggests 6 h treatments. A 16 h treatment is far too long to interpret potential regulators of IRE1 activity, so this is an important point. Related, the authors should do a timecourse of ER stress to better catch the dynamic nature of IRE1 PPIs that regulate IRE1 activity (but this should be a short timecourse).
    3. Along the same lines as above, Ahmed et al recently published another proximity ligase profile for IRE1, as highlighted by the authors. Yet, the authors do not show any comparisons between their list and the list generated by Ahmed et al. This is critical, as it could help generate a more reliable list of IRE1 interactors identified by this approach. In many ways, as alluded to by the authors, the more rapid labeling afforded by TurboID used by Ahmed et al would show a better snapshot of IRE1 interactors, limiting the potential impact of this study, so it is essential to benchmark their approach to the previous manuscript.
    4. The authors use CD59 as a putative RIDD target for the studies described in Fig. 5D. Other targets should also be used to convince that these effects can be attributed to RIDD. Notably, the canonical RIDD target BLOS1 should be used. Further, the authors should show that the Tg-dependent reduction in CD59 is sensitive to co-treatment with IRE1 RNAse inhibitors. Without further experiments on this point, these experiments are difficult to interpret as RIDD targets (apart from BLOS1) are well established to not be canonical across cell types.
    5. The authors have previously demonstrated that PTPN1 is involved in regulating XBP1 splicing, although the work presented here is suggested to reveal a new importance for direct interactions with IRE1. However, this needs to be further developed. The authors use a bioinformatic approach termed iPIN to suggest interactions, although this appears to be a proprietary software that has not been published. The identify a potential interface for this interaction and then show that some mutations near this potential site of interaction seem to reduce IRE1 stability, while increasing interactions with PTPN1 (overexpressed) and XBP1 splicing. However, there are a number of concerns here. Does the mutation, N638D basally increase the specific activity of splicing, which can be measured using recombinant proteins. Further, the co-IPs are not well controlled, as there is no evidence that PTPN1-mCherry doesn't come down with beads or any other protein. In other words, the potential role for PTPN1 in regulating XBP1 splicing needs to be better developed to convince that this represents an important activity mediated through direct IRE1 interactions.
    6. Similarly, the results with HNRNPL need to be further developed. It is well established that IRE1 ERAD is regulated by the activity of SYNV1 (HRD1) and SEL1L. So does genetic depletion of HNRPNL influence expression of these factors (HRD1 is shown but not SEL1L). Does it affect their interaction? Or does it influence some other aspect of IRE1 stability maybe through a protein-protein interactions? Again, more information is needed to determine the potential importance of HNRNPL in IRE1 stabilization.

    Significance

    Overall, the primary value of this manuscript is the list of potential interactors that is generated through this approach. Limitations are largely discussed in the manuscript. These include the fact that only interactors in the cytosol are accurately profiled owing the construct design and the potential for overexpression artifacts.

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    Referee #2

    Evidence, reproducibility and clarity

    The manuscript by Le Goupil et al. presents the results of a protein proximity screen for the UPR sensor IRE1 using the method BioID. The data include a list of interactors, their comparison with computational analysis of curated databases as well as previously published experimental data such as genome wide siRNA or CRISPRi screens and focused Perturb-Seq data. By focusing on the intersection of these data sets, the authors putatively connect IRE1 to previously unknown cellular activities. The authors also make an effort to validate these data by couple of examples where they identify HNRNPL as an interacting partner and stabilizer of IRE1. Overall, this manuscript makes important contributions towards establishing a framework to understand IRE1 biology more fully; however, significant validation and functional characterization would be required to fully evaluate the robustness/utility of the IRE1 interactome that is presented.

    Specific points:

    1. What is the reason to use different ER stressors in different experiments, i.e. DTT, TG, or TM?
    2. Figure S2C: percentages should add up to 100% for enabling meaningful comparison of the two.
    3. Are the number of common interactors between IRE1 and PERK too high for structurally different proteins? Is it because they are embedded in the same membrane and thus there may be some ´non-specific´ interactors? It may also be due to long incubation periods (see below). For proper examination of this, of course, requires BioID experiment in the same cell type under the same conditions. This should be underlined in the text. The same goes for the comparison of IRE1 and IRE1
    4. It may be surprising that the great majority of the interactors are at the basal level, without stress. Since IRE1 activity is stress-induced, how are these basal interactors change IRE1 activity upon stress? Could this large basal interactor set be due to the very long time periods in the BioID process (18-24 h)? Or are the majority of the interactors mediating non-canonical IRE1 functions, as suggested in the literature (even some of these are stress activated)? Regarding this, did the authors do a time course to identify the optimal time of biotin treatment, the time point at which a plateau is reached in terms of approximate number of proteins associated?

    Minor points:

    1. The manuscript will significantly benefit from careful English language editing. There are spelling errors, omission of punctuations, half sentences, and repetitive language.
    2. The data from Adamson et al. paper referenced on page 6 is a CRISPRi screen coupled to Perturb-Seq, not a simple CRISPR screen.
    3. 50 nM Thapsigargin is referred to as a mild stressor, but it is actually a strong stressor that can even kill some cell types.
    4. Figure texts are often too small and hard to follow, e.g. in the Venn-diagrams.
    5. Boundries of Figures S2D-E-F are too difficult to discern.
    6. Statement on top of page 10: ¨Thus, IRE1 BioID identified new IRE1 interactors and revealed that IRE1 interactions are responsive to stress¨. However, the majority of the interactors ara basal, not responsive to stress.

    Significance

    Strengths:

    Robust experimental approach with a well-established technique that provides in situ interactome data for a central protein in proteostasis.

    Weakness:

    Lack of further experimental validation of the data. This is, however, a big task, and will take significant additional effort and time.

    Advance:

    The study makes conceptual and incremental increase in defining the IRE1 interactome and opens the way for further studies.

    Audience:

    The findings of this study is of interest to basic molecular and cell biologists with an interest in intracellular signaling, as well as those that may be interested in UPR-disease connection, e.g. cancer and neurodegenerative disease.

    Reviewer Expertise:

    UPR biology in normal and pathological conditions.

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    Referee #1

    Evidence, reproducibility and clarity

    Goupil et al. developed a proximity labeling approach using BioID and identified many interacting proteins for the conserved ER stress sensor. The authors validated their results by comparing previously known IRE1a interacting proteins with their list. Indeed, many interacting proteins are in their list, including HSPA5, HSP90B1, PTPN1, and UPF1. Surprisingly, some of these proteins are localized in the ER lumen, which should not be biotinylated by BirA*, thus raising the possibility that some interactions are post-lysis artifacts. The authors also identify HNRNPL as a novel interacting protein of IRE1a. They further demonstrate that the depletion of HNRNPL leads to faster degradation under basal conditions but not during ER stress. Overall, the authors have employed the BioID approach to map the interactome of IRE1. However, the authors should be cautioned to give the impression to readers that all these interactions are true, and many of them could be false positives due to overexpression of IRE1a and highly sensitive mass spectrometry.

    Major Comments:

    The logic of analyzing existing data in Figure 1 is unclear to me. As I mentioned in my summary, it misleads the readers that all these components of biological pathways directly interact with IRE1. Biochemical and functional studies have never been done to support many high-throughput interaction studies. Also, IRE1 is an extremely low abundant protein (~416 molecules/HeLa cell) (PMID: 24487582). How do such low-interacting proteins interact with hundreds of proteins unless using an overexpression system? While Figure 2C shows a nice ER stress-dependent induction of XBP1s, it is not easy to appreciate the ER stress-induced expression of XBP1s in Figure 2D. The authors need to show better XBP1s blot. Surprisingly, biotinylated proteins were not detected when cytosolic BirA* was expressed, suggesting that the construct was not expressed, missing a crucial control. Figure 3: Simply enriching biotinylated proteins from IRE1a-BirA* expressing cells could yield false positives. This is because of the half-life of the biotin adenylate ester on the minute scale. The best way to avoid false positives is to subtract the signal from hits obtained from the cytosolic BirA* cells. It is unclear whether the authors used such an approach to prevent false positives. Figure 5A: IRE1a oligomerization on Native PAGE immunoblotting cannot be readily appreciated. They should show a longer exposure and quantify the % of oligomers relative to the total signal. They should also include IRE1a and Tubulin immunoblots performed using a standard SDS PAGE. The role of HNRNPL in protecting IRE1 from degradation is convincing in Figure 7. The data could be further supported by showing the interaction between IRE1a and HNRNPL by co-immunoprecipitation.

    Minor Comments:

    On page 6, the author mentions "protein processing in the ER and apoptosis as major clusters." While protein processing is a major cluster, apoptosis is not compared to other pathways. Authors often mention direct interactions between IRE1a and other proteins. I would be cautious in saying this unless these interactions were truly demonstrated using purified IRE1 and the partner protein. Otherwise, the interaction could be mediated by other factors in cells. The authors need to discuss the possibility of non-specific interactions due to IRE1a overexpression and intrinsic flaws of BioID and what steps the authors took to mitigate these effects.

    Significance

    The study is significant as it identifies new interacting proteins for IRE1a, a conserved ER stress sensor protein.

  5. Version published to 10.1101/2024.10.27.620453v1 on bioRxiv