The LC3-interacting region of NBR1 is a protein interaction hub enabling optimal flux

  1. Brian J North
  2. Amelia E Ohnstad
  3. Michael J Ragusa
  4. Christopher J Shoemaker

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Abstract

During autophagy, potentially toxic cargo is enveloped by a newly formed autophagosome and trafficked to the lysosome for degradation. Ubiquitinated protein aggregates, a key target for autophagy, are identified by multiple autophagy receptors. NBR1 is an archetypal autophagy receptor and an excellent model for deciphering the role of the multivalent, heterotypic interactions made by cargo-bound receptors. Using NBR1 as a model, we find that three critical binding partners – ATG8-family proteins, FIP200, and TAX1BP1 – each bind to a short linear interaction motif (SLiM) within NBR1. Mutational peptide arrays indicate that these binding events are mediated by distinct overlapping determinants, rather than a single, convergent, SLiM. AlphaFold modeling underlines the need for conformational flexibility within the NBR1 SLiM, as distinct conformations mediate each binding event. To test the extent to which overlapping SLiMs exist beyond NBR1, we performed peptide binding arrays on >100 established LC3-interacting regions (LIRs), revealing that FIP200 and/or TAX1BP1 binding to LIRs is a common phenomenon and suggesting LIRs as protein interaction hotspots. Comparative analysis of phosphomimetic peptides highlights that while FIP200 and Atg8-family binding are generally augmented by phosphorylation, TAX1BP1 binding is nonresponsive, suggesting differential regulation of these binding events. In vivo studies confirm that LIR-mediated interactions with TAX1BP1 enhance NBR1 activity, increasing autophagosomal delivery by leveraging an additional LIR from TAX1BP1. In sum, these results reveal a one-to-many binding modality in NBR1, providing key insights into the cooperative mechanisms among autophagy receptors. Furthermore, these findings underscore the pervasive role of multifunctional SLiMs in autophagy, offering substantial avenues for further exploration into their regulatory functions.

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    Reply to the reviewers

    Manuscript number: RC-2024-02516

    Corresponding author(s): Christopher Shoemaker

    __1. __General Statements [optional]

    Thank you to all the reviewers for their helpful efforts on behalf of our manuscript. We appreciate the time and effort they have invested in providing valuable feedback.

    Overall, the positive reception from our reviewers highlighted their appreciation for our approach and findings. Moreover, their comments underscored the relevance and potential impact of our findings, particularly within the fields of autophagy and protein interaction networks. Their detailed and constructive critiques will also help refine both the content and presentation of our work.

    In response to the reviews, we have proposed targeted revisions to the manuscript, all of which are well within our lab's capabilities and can be executed efficiently. We have detailed our responses to each specific point raised by the reviewers below. * *

    __2. __Description of the planned revisions

    Reviewer #1

    Evidence, reproducibility and clarity

    1. EVIDENCE, REPRODUCIBILITY AND CLARITY Summary:

    Selective autophagy receptors (SARs) of the Sequestosome-1 like receptor group (SLRs) including SQSTM1(Sequestosome-1)/p62, NBR1, TAX1BP1, NDP52, CALCOCO1 and Optineurin are soluble SARs that engage cargo and ATG8 family proteins as well as components of the core autophagy machinery like FIP200/RBCC1 to bring about the autophagic degradation of the cargo and themselves. In the autophagic degradation of protein aggregates (aggrephagy) the most studied SAR p62 collaborates with the archetypal autophagy receptor NBR1 and also TAX1BP1 to bring about effective turnover of ubiquitinated cargos sequestered into p62 bodies or droplets by liquid-liquid phase separation. How this intricate co-operation of these SARs is orchestrated is incompletely understood. In the paper by North et al entitled "The LC3-interacting region of NBR1 is a protein interaction hub enabling optimal flux" the authors use peptide arrays to map the binding sites for ATG8-family proteins LC3A and GABARAPL1, FIP200 and TAX1BP1 to the autophagy receptor NBR1. The authors find that three short linear interaction motifs (SLiMs), the LIR, FIR and TIR interacting with ATG8 family proteins, FIP200 and TAX1BP1, respectively, partly overlap in a short region of NBR1 that can adopt different conformations to accommodate the different binding partners. In short, the different interactions are mediated by distinct overlapping determinants, rather than a single, convergent, SLiM. While the important binding determinants for ATG8 proteins and FIP200 show more overlap and it was not possible here to find mutations that distinguish LIR and FIR binding, TAX1BP1 bound more to a region downstream of the LIR and a specific mutation in NBR1 and in TAX1BP1 could abolish binding. Checking the role of phosphorylations in augmenting binding using phosphomimetic mutations it was seen that while FIP200 and Atg8-family binding were generally augmented by phosphorylation, TAX1BP1 binding did not respond to these mutations. Very interestingly, the authors found that co-expression of TAX1BP1 with tandem-tagged NBR1 in pentaKO cells (not expressing the SLRs p62, NBR1, NDP52, TAX1BP1 and OPTN) increased significantly the autophagic turnover of NBR1. None of the other SLRs could do this. Instead, this over-expression assay revealed a competition.

    Major points:

    1. In Fig 4 the peptide array binding assay is not sufficient as it is only semiquantitative. The data shown should be accompanied by a more direct binding assay allowing the determination of kDs for the binding where the WT peptides are directly compared to the phosphor mimicking mutant peptides. Here the fluorescence anisotropy assay the authors use in Suppl Fig. 1E or ITC, OctetRed96 or another assay suitable for kD determinations should be used.

    Response: Thank you for the constructive comments regarding our peptide array binding assay. We agree that the semi-quantitative nature of this method limits its ability to provide detailed binding affinity measurements. To address this, we will purify multiple peptides and assess the binding affinities between phosphomimetic+/- LIR peptides and Atg8s, FIP200, and TAX1BP1. While testing all peptides may be cost and time prohibitive, we will prioritize a representative range for this validation effort.

    1. As this paper is already dominated by the use of peptides it would significantly enhance the quality of the data if the authors had included studied with peptides phosphorylated at the specific positions to allow comparison with the phosphomimetic substitutions to aspartate.

    Response: Thank you for your insightful comment. We agree that incorporating studies with peptides phosphorylated at specific positions could provide a more nuanced comparison with the phosphomimetic substitutions to aspartate. Previous studies, including Popelka and Klionsky (2022) and Kliche et al. (2022), have indeed suggested that phosphomimetic substitutions do not perfectly replicate phosphorylation events.

    In response, we plan to order a peptide array containing phosphorylated peptides, not merely phosphomimetics, and will conduct additional experiments with TAX1BP1, FIP200, and LC3A. This approach will allow us to directly assess the effects of actual phosphorylation compared to phosphomimetic substitutions.

    While we acknowledge the possibility of subtle differences in binding affinity or regulatory interactions, we anticipate that the primary conclusions of our study—namely, that TAX1BP1 is largely insensitive to phosphorylation, whereas FIP200 and LC3A binding activities are affected—will remain unchanged. These experiments will provide valuable data to confirm the robustness of our conclusions under the conditions of true phosphorylation.

    1. The quality of the 2D peptide array probing of GST-LC3A binding in Fig 3A is poor. Is this a stripped and re-probed membrane? I do not think these data are publication quality and the experiment should be redone unless the authors have very good arguments against my suggestion. It would also be nice to see a 2D peptide array of GABARAPL1 binding too to make the comparative study complete.

    Response: Thank you for your constructive feedback regarding the quality of the 2D peptide array probing of GST-LC3A in Figure 3A. As you rightly pointed out, the membrane was indeed stripped and reprobed, with LC3A being the final probe. This method sometimes introduces artifacts, such as the 'ring' effect observed, which are common with this technique. However, the results consistently aligned with established consensus sequences for LC3, reinforcing the reliability of our findings despite the suboptimal image quality.

    Recognizing the concerns about the quality of the blot, we are prepared to repeat this experiment using a new commercial vendor, as our previous collaborator is no longer available. We anticipate some differences in the appearance of the blots due to changes in dot size and spacing from the new supplier. Given these variations, we propose adding the revised blot to the supplementary materials rather than the main figures to avoid disrupting the visual continuity of the data presentation.

    Additionally, in response to the reviewer’s suggestion, we will include a 2D peptide array probing for GABARAPL1. This will enhance the comparative analysis within our study.

    One alternative (related to Reviewer 3, comment 3) that we can deliver is using our LIR arrays to derive consensus sequences for LC3 binders and GABARAPL1 binders. In doing this, we find the same differences in LC3 and GABARAP binding preferences that were reported previously in Rogov et al 2017. Recovering these known, and somewhat subtle, differences in binding preference further bolster the validity of our approach.

    1. For the data shown in Fig 6 it should be noted that although these are very interesting results a clear limitation of the study is that the results on the autophagic turnover is based on overexpressing the SLRs in the pentaKO cells. In a physiological setting with all relevant actors in place and with a different stoichiometry the effects could likely be different.

    Response: We appreciate the observation regarding the limitations of our study due to the use of overexpressed SLRs in pentaKO cells. As the reviewer rightly points out, the stoichiometry and interaction dynamics in a physiological setting might differ significantly. Critically, after submission of this manuscript, a recent preprint by Sascha Martens’ group (Bauer et al. BioRxiv) has shown similar results using endogenously tagged p62, TAX1BP1, and NBR1. This study corroborates our results, suggesting that the interactions we observed are not merely artifacts of overexpression but reflect genuine biological phenomena. We will incorporate a detailed discussion of this study in the Discussion section of our manuscript to contextualize our findings within a more physiologically relevant framework.

    Therefore, we believe that our reductionist approach, while not fully reflective of physiological conditions, offers valuable and generalizable insights into the intricate cooperation of SARs in autophagy.

    Minor points:

    1. It would be beneficial for the reader to show a cartoon of the domain organization of both TAX1BP1 and NBR1 in Figure 1. NBR1 is shown in supplemental figure 1, but there is no depiction of the domain organization of TAX1BP1.

    Response: As suggested, a domain schematic for NBR1 and TAX1BP1 will be included.

    1. The authors say at the bottom of page 4 "Complementary in vivo studies reveal that while SLRs typically compete". But do they actually typically compete? Is this not a result of the experimental strategies employed? There is more a shortage of SLRs based on cargo competition as shown recently by Peter Kim's group that excessive pexophagy may reduce mitophagy etc. (Germain et al. 2023).

    Response: Thank you for pointing out this overstatement. We will soften this statement.

    1. In Fig. 3D it should be shown that D, E, A and V are preferred residues at position +1 for LC3A binding.

    Response: As suggested, we will amend the figure to include these residues at the +1 position.

    1. In such a 2D mutational analysis it is often just as important to determine which residues are not allowed for binding. It would therefore be nice if the authors could summarize/visualize their results in a better way in Fig 3D to also show the residues that lead to loss of binding. These could be shown below the sequence and the use of color to distinguish basic, acidic, hydrophobic and aromatic residues could be attempted.

    Response: As suggested, we will add to this figure to make it more comprehensive by including residues that are both preferred and lead to loss of binding. Furthermore, we have incorporated the use of color to distinguish the traits of different residues (basic, acidic, hydrophobic and aromatic) that are dis(favored) at each position.

    1. Line 327: To be clear about the fact that this is an overexpression assay "simultaneous expression" should be corrected to simultaneous overexpression".

    Response: We will make the suggested change.

    1. There are LIRs and FIRs that overlap and those that do not. To check the degree of overlaps that may occur among known LIRs the authors made a peptide array with 100 established LIR sequences taken from the LIR-Central database (Chatzichristofi et al., 2023). The peptide array was probed with LC3A (29 bound), GABARAPL1 (49 bound), the FIP200 Claw domain (57 bound) and the TAX1BP1 CC2 domain (49 bound). As much as one third (32) of the LIR peptides were not bound by any of the four probes. Do the authors have a good explanation for the fact that so many peptides did not bind?

    Response: Thank you for highlighting the significant number of LIR peptides that did not bind to any of the probes in our study. At first, we were similarly surprised by this. In our manuscript, we will expand on several factors that might explain this observation:

    • Specificity of Atg8 Family Proteins: The LIR-Central database indicates that these sequences bind at least one Atg8-family protein, but not necessarily all. Our assay might not have included the specific Atg8 proteins that some LIRs preferentially bind.
    • Peptide Solubility and Conformation: The solubility and conformational stability of peptides printed on an array can vary, affecting binding efficiency. Certain sequences may not adopt the optimal conformation for binding under these assay conditions.
    • Sequence Context and Accessibility: The native context in which the LIR motif is contained, including neighboring amino acids, can influence binding. Peptide arrays strip these peptides of their physiological context. As short linear interaction motifs, the assumption is that context will not strongly affect binding, but it’s known that many LIRs adopt partially structured motifs that influence binding (e.g. a C-terminal helix). Our peptide array approach is likely to impede such secondary structures from forming and may limit binding.
    • Misannotated sequences. The LIRs included from the database have varying levels of validation. Some sequences might be misannotated and, therefore, do not bind any of the probes. These discussion points will be included in the manuscript to provide a comprehensive explanation for the observed data.
    1. Strangely enough, the NBR1 peptide used in Figure 2A did not bind any of the probes while the NBR1 peptides used in Fig. 1C bound very well. Do the authors have any explanation for this?

    Response: Thank you for noting the discrepancy in NBR1 peptide binding observed in Figure 2A compared to Figure 1C. This observation was noted by all reviewers. The difference likely arises from the solubility issues associated with the NBR1 peptide in the format used for Figure 2A, where the peptide sequence included the LIR motif plus 10 amino acids on each side. The core LIR sequence of NBR1 (YIII) is highly hydrophobic, which can affect its solubility and, consequently, its observed binding in our peptide array.

    To overcome this, we optimized the LIR sequence of NBR1 for peptide arrays (amino acids 725-749), which includes seven residues before the LIR and 14 residues after. This shift enhanced solubility and facilitated more reliable probing in our experiments (notably Fig 3). In Fig2A and other assays, both the standard and the optimized formats of the NBR1 LIR were included: the standard format to maintain consistency with other LIRs extracted from the LIR-Central database and the optimized version as a control to validate our results.

    We will detail this explanation in the manuscript, clarifying the rationale behind the observed binding differences.

    Significance

    SIGNIFICANCE

    I found this paper very interesting to read with a lot of interesting new detailed and useful information on binding specificity for the proteins and motifs involved. It is a generally well performed study with interesting results. I also very much enjoyed the Discussion section which opens up for several interesting possible scenarios. The study also produced important point mutants that can be used in future studies to selectively abolish TAX1BP1 binding to NBR1. I think this is a "must read" paper for researchers interested in selective autophagy and co-operation between SARs, and more generally for getting some insight into how SLiMs may work. As such, this paper will be of interest for all interested in autophagy research and for a wider audience too as it is in essence about how overlapping SLiMs may be employed to orchestrate multiple protein-protein interactions using distinct overlapping determinants, rather than a single, convergent, SLiM. It is also one of the very few papers I have come across exploiting the power of the peptide array method so extensively with success for mapping protein binding sites.

    It could perhaps be interesting if the authors discussed their results in relation to another study from the group of Sascha Martens on the role of TAX1BP1 in p62 bodies or condensates (doi: https://doi.org/10.1101/2024.05.17.594671). These two papers should be read together as they are both very interesting and important contributions.

    Response: Thank you for pointing out this important reference that was posted shortly after our manuscript was submitted. As mentioned above, we will include an expanded discussion section to discuss these corroborating findings. We will also include a citation to Ferrari et al (PMID: ) on Tau evasion of autophagy through exclusion of TAX1BP1.

    Reviewer #2

    Evidence, reproducibility and clarity

    Summary In this manuscript, North et al. examined how short linear interaction motifs (SLiMs) help to orchester selective autophagy receptors (SARs) function during cargo engulfment in autophagosomes. In particular, the authors focused on NBR1 as a model SAR to address the role of its role in the clearance of protein aggregates (aggrephagy). Using binding assays, the authors showed that a SLiM harboring NBR1's LIR motif also mediates binding to FIP200 and TAX1BP1. Intrigued by these overlapping binding sites, the authors probed 100 LIRs for their binding to TAX1BP1's coiled-coil 2 region (CC2), FIP200's claw domain and two different ATG8 family members and found heterogenous binding pattern and distinct correlation between these four binding partners. Using mutational peptide arrays of NBR1's SLiM, the authors revealed unique binding determinants of these NBR1 partners and their potential differential regulation by phosphorylation. Taking advantage of their new NBR1 binding insights, the authors structurally modeled the binding of TAX1BP1's CC2 to NBR1's SLiM and identified crucial residues in both proteins for this interaction. Lastly, the authors turned to autophagy flux assays in cells and showed that TAX1BP1 acts synergistically with NBR1 to increase its lysosomal delivery. Overall, the claims and the conclusions are largely supported by the data. However, a few critical issues should be addressed.

    Are the data and the methods presented in such a way that they can be reproduced?

    Are the experiments adequately replicated and statistical analysis adequate?

    Major comments

    1. What are the expression levels of the different tf-SAR fusions compared to the endogenous levels of the respective SAR? And are tf-NBR1 protein levels changed upon co-expression of the other SARs?

    __Response: __We appreciate the questions concerning the expression levels of tf-SAR fusions relative to the endogenous levels of the respective SARs, similar to inquiries from Reviewer 1 (major comment 4). In our study, the levels of tf-NBR1 are notably higher than the endogenous levels. Interestingly, we observed that the co-expression of autophagy-competent NBR1 and TAX1BP1 generally leads to a decrease in the levels of both proteins, likely due to enhanced autophagic turnover. This pattern is not seen with autophagy-deficient mutants, suggesting a functional interaction affecting protein stability.

    Furthermore, a recent preprint by Sascha Martens’ group (Bauer et al., BioRxiv) has presented findings that echo our results using endogenously tagged versions of p62, TAX1BP1, and NBR1. This study supports our observations, indicating that the interactions and effects we report are not artifacts of overexpression but are reflective of genuine biological processes. These findings will be thoroughly discussed in the Discussion section of our manuscript to provide context for our results within a physiologically relevant framework.

    Therefore, we believe that our reductionist approach, while not fully reflective of physiological conditions, offers valuable and generalizable insights into the intricate cooperation of SARs in autophagy.

    1. Which of the 100 LIRs have been shown to specifically bind LC3A or GABARAPL1? The authors should include this information from the literature in Figure 2 (e.g., highlighted by color or else).

    __Response: __Thank you for your suggestion to detail the specific interactions between the 100 LIRs and Atg8 homologs like LC3A and GABARAPL1 in Figure 2. While each LIR in the LIR-Central database has been validated, detailed information on which LIRs bind specific Atg8 homologs—and with what relative affinity—is often lacking in the literature. This gap makes it challenging to present comprehensive binding preferences in a visually coherent way within Figure 2.

    Nevertheless, we recognize the value of such information. We plan to conduct a thorough literature review on all 100 LIRs included in our study. Should we find sufficient and reliable data regarding binding specificities, we will incorporate this into Figure 2, potentially using color coding or another method to highlight these relationships clearly.

    We can also perform the reciprocal experiment by using our LIR arrays to derive consensus sequences for LC3 binders and GABARAPL1 binders. In doing this, we find the same differences in LC3 and GABARAP preferences that were reported previously in Rogov et al 2017. Recovering these known, and somewhat subtle, differences in binding preference further bolster the validity of our approach. These new data will be added to the manuscript.

    1. How effective is the stripping of the peptide array? The authors should provide evidence that there is no carry over binding from sequential probing the array. As a control, the authors should at least repeat probing for the last binder in their sequential binding assay with a new peptide array that has not yet been incubated with a different binder and then stripped.

    __Response: __This is an important question, related to Reviewer 1 (comment 3), as the stripping of the peptide array can be variably affective. Prior to performing any of the arrays included in this manuscript, we did several validation arrays to identify the proper ordering of probes (e.g. what proteins can be stripped, which cannot). FIP200 and TAX1BP1 probing was performed on fresh or successfully stripped blots. LC3A probing was done last, as there is substantial previous literature defining the LC3 motif. However, the results of the LC3A binding consistently aligned with established consensus sequences for LC3, reinforcing the reliability of our findings despite the stripping process. Therefore, while stripping sometimes introduces artifacts, such as the 'ring effect’ observed in Figure 3A, the results did not appear to be influenced by prior probes.

    As suggested, we are prepared to repeat the LC3A probing on a new array to fully cement this interpretation. We note, however, that this will be done using a new commercial vendor, as our previous collaborator is no longer available (The original blots were ordered over 3 years ago). We anticipate some differences in the appearance of the blots due to changes in dot size and spacing from the new supplier. Given these variations, we propose adding the revised blot to the supplementary materials rather than the main figures to avoid disrupting the visual continuity of the data presentation.

    1. What is the number of replicates for the peptide array assays?

    __Response: __Due to cost considerations, peptide array assays in our study were conducted as one or two replicates. We understand the limitations this presents in terms of statistical robustness and variability assessment. However, where possible, we supplemented these assays with additional validation experiments and controls to ensure reliability of our findings. For critical experiments, including key interaction validations, we used independent biochemical assays to confirm the results obtained from the peptide arrays.

    1. The authors should test whether the enhancement of NBR1 flux by TAX1BP1 is only due to the contribution of an additional LIR or potential other functions of TAX1BP1 (e.g. ubiquitin binding or FIP200 binding). The authors should expand the panel shown in Figure 6E with TAX1BP1 mutant which are deficient in ubiquitin or FIP200 binding.

    __Response: __We thank the reviewer for their suggestion. We will include data with TAX1BP1 mutants that are deficient in ubiquitin or FIP200 binding

    Minor comments

    1. Molecular weight markers are missing on immunoblots.

    __Response: __We apologize for this oversight. We will amend figure to include molecular weight markers.

    1. It would be more informative (since some proteins have more than one LIR) if the actual LIR motif would be displayed next to the peptide array (as e.g. done for NBR1) and not only in the supplements.

    __Response: __We appreciate this thoughtful input and will consider its implementation carefully. We will explore the feasibility of integrating this detail in a manner that maintains figure clarity.

    1. Along this line in Figure 2A, NBR1's LIR (marked with a red star) is among the LIRs for which no binding was observed. The authors should explain this.

    Response: Thank you for noting the discrepancy in NBR1 peptide binding observed in Figure 2A compared to Figure 1C. This observation was noted by all reviewers. The difference likely arises from the solubility issues associated with the NBR1 peptide in the format used for Figure 2A, where the peptide sequence included the LIR motif plus 10 amino acids on each side. The core LIR sequence of NBR1 (YIII) is highly hydrophobic, which can affect its solubility and, consequently, its observed binding in our peptide array.

    To overcome this, we optimized the LIR sequence of NBR1 for peptide arrays (amino acids 725-749), which includes seven residues before the LIR and 14 residues after. This shift enhanced solubility and facilitated more reliable probing in our experiments (notably Fig 3). In Fig2A and other assays, both the standard and the optimized formats of the NBR1 LIR were included: the standard format to maintain consistency with other LIRs extracted from the LIR-Central database and the optimized version as a control to validate our results.

    We will detail this explanation in the manuscript, clarifying the rationale behind the observed binding differences.

    Significance

    Collectively, the work of North and colleagues provide valuable new mechanistic insights into the network of interaction that governs the function of SARs. Importantly, this works extends the knowledge in the field that SARs are acting in an orchestrated manner which reinforces their delivery to lysosomes. However, given the involvement of several SARs in the same process, it is crucial to dissect the binding modalities among these factors. In this regard, the current study on fine mapping binding sites provides an important contribution. In particular, in probing the in vitro findings in reconstituted KO cells. This part is really strong. In addition, the identification of critical residues for these bindings events represents important tools for the autophagy community which will be among the basic research audience most interested in this technical study.

    __ __

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    Referee #3

    Evidence, reproducibility and clarity

    North et al., using NBR1 as a model, found that three ATG8-family proteins, FIP200, and TAX1BP1 - each bind to a short linear interaction motif (SLiM) within NBR1. Mutational peptide arrays showed that these binding events are mediated by distinct overlapping determinants, rather than a single, convergent, SLiM. They performed peptide binding arrays on >100 established LC3-interacting regions (LIRs), and showed that that FIP200 and/or TAX1BP1 binding to LIRs is a common phenomenon and suggesting LIRs as protein interaction hotspots. Comparative analysis of phosphomimetic peptides showed that while FIP200 and Atg8-family binding are generally augmented by phosphorylation, TAX1BP1 binding is nonresponsive. In vivo studies confirmed that LIR-mediated interactions with TAX1BP1 enhance NBR1 activity, increasing autophagosomal delivery by leveraging an additional LIR from TAX1BP1.

    Suggestions for further improvement of the paper:

    1. Figure 1: Data in figure 1 would be strengthened with cellular localization studies of the various constructs. What is the localization pattern of TIR mutants?
    2. Figure 2: Some more elaborate analysis and discussion is needed to explain the reason of 'never-binders'
    3. GIM (GABARAP interaction motifs) have been previously identified (Rogov et al., 2017). Can the authors extend/comment/discuss their findings in the context of GIMs?
    4. Figure 3: Data in figure 3 would be strengthened with cellular localization studies of the various constructs.
    5. The statement : 'LIR motif of NBR1 is a protein interaction hub enabling optimal flux' is not well discussed in the discussion and does not come through very clearly throughout the paper.

    Significance

    This is a very interesting and well structured study with clear and convincing data.

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    Referee #2

    Evidence, reproducibility and clarity

    Summary

    In this manuscript, North et al. examined how short linear interaction motifs (SLiMs) help to orchester selective autophagy receptors (SARs) function during cargo engulfment in autophagosomes. In particular, the authors focused on NBR1 as a model SAR to address the role of its role in the clearance of protein aggregates (aggrephagy). Using binding assays, the authors showed that a SLiM harboring NBR1's LIR motif also mediates binding to FIP200 and TAX1BP1. Intrigued by these overlapping binding sites, the authors probed 100 LIRs for their binding to TAX1BP1's coiled-coil 2 region (CC2), FIP200's claw domain and two different ATG8 family members and found heterogenous binding pattern and distinct correlation between these four binding partners. Using mutational peptide arrays of NBR1's SLiM, the authors revealed unique binding determinants of these NBR1 partners and their potential differential regulation by phosphorylation. Taking advantage of their new NBR1 binding insights, the authors structurally modeled the binding of TAX1BP1's CC2 to NBR1's SLiM and identified crucial residues in both proteins for this interaction. Lastly, the authors turned to autophagy flux assays in cells and showed that TAX1BP1 acts synergistically with NBR1 to increase its lysosomal delivery. Overall, the claims and the conclusions are largely supported by the data. However, a few critical issues should be addressed.

    Are the data and the methods presented in such a way that they can be reproduced? Are the experiments adequately replicated and statistical analysis adequate?

    Major comments

    1. What are the expression levels of the different tf-SAR fusions compared to the endogenous levels of the respective SAR? And are tf-NBR1 protein levels changed upon co-expression of the other SARs?
    2. Which of the 100 LIRs have been shown to specifically bind LC3A or GABARAPL1? The authors should include this information form the literature in Figure 2 (e.g., highlighted by color or else).
    3. How effective is the stripping of the peptide array? The authors should provide evidence that there is no carry over binding from sequential probing the array. As a control, the authors should at least repeat probing for the last binder in their sequential binding assay with a new peptide array that has not yet been incubated with a different binder and then stripped.
    4. What is the number of replicates for the peptide array assays?
    5. The authors should test whether the enhancement of NBR1 flux by TAX1BP1 is only due to the contribution of an additional LIR or potential other functions of TAX1BP1 (e.g. ubiquitin binding or FIP200 binding). The authors should expand the panel shown in Figure 6E with TAX1BP1 mutant which are deficient in ubiquitin or FIP200 binding.

    Minor comments

    1. Molecular weight markers are missing on immunoblots.
    2. It would be more informative (since some proteins have more than one LIR) if the actual LIR motif would be displayed next to the peptide array (as e.g. done for NBR1) and not only in the supplements.
    3. Along this line in Figure 2A, NBR1's LIR (marked with a red star) is among the LIRs for which no binding was observed. The authors should explain this.

    Referee Cross-Commenting

    I find that all reviewers raised valid and important points that the authors should address to increase the quality and impact of their manuscript.

    Significance

    Collectively, the work of North and colleagues provide valuable new mechanistic insights into the network of interaction that governs the function of SARs. Importantly, this works extends the knowledge in the field that SARs are acting in an orchestered manner which reinforces their delivery to lysosomes. However, given the involvement of several SARs in the same process, it is crucial to dissect the binding modalities among these factors. In this regard, the current study on fine mapping binding sites provides an important contribution. In particular, in probing the in vitro findings in reconstituted KO cells. This part is really strong. In addition, the identification of critical residues for these bindings events represents important tools for the autophagy community which will be among the basic research audience most interested in this technical study.

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    Referee #1

    Evidence, reproducibility and clarity

    Summary:

    Selective autophagy receptors (SARs) of the Sequestosome-1 like receptor group (SLRs) including SQSTM1(Sequestosome-1)/p62, NBR1, TAX1BP1, NDP52, CALCOCO1 and Optineurin are soluble SARs that engage cargo and ATG8 family proteins as well as components of the core autophagy machinery like FIP200/RBCC1 to bring about the autophagic degradation of the cargo and themselves. In the autophagic degradation of protein aggregates (aggrephagy) the most studied SAR p62 collaborates with the archetypal autophagy receptor NBR1 and also TAX1BP1 to bring about effective turnover of ubiquitinated cargos sequestered into p62 bodies or droplets by liquid-liquid phase separation. How this intricate co-operation of these SARs is orchestrated is incompletely understood. In the paper by North et al entitled "The LC3-interacting region of NBR1 is a protein interaction hub enabling optimal flux" the authors use peptide arrays to map the binding sites for ATG8-family proteins LC3A and GABARAPL1, FIP200 and TAX1BP1 to the autophagy receptor NBR1. The authors find that three short linear interaction motifs (SLiMs), the LIR, FIR and TIR interacting with ATG8 family proteins, FIP200 and TAX1BP1, respectively, partly overlap in a short region of NBR1 that can adopt different conformations to accommodate the different binding partners. In short, the different interactions are mediated by distinct overlapping determinants, rather than a single, convergent, SLiM. While the important binding determinants for ATG8 proteins and FIP200 show more overlap and it was not possible here to find mutations that distinguish LIR and FIR binding, TAX1BP1 bound more to a region downstream of the LIR and a specific mutation in NBR1 and in TAX1BP1 could abolish binding. Checking the role of phosphorylations in augmenting binding using phosphomimetic mutations it was seen that while FIP200 and Atg8-family binding were generally augmented by phosphorylation, TAX1BP1 binding did not respond to these mutations. Very interestingly, the authors found that co-expression of TAX1BP1 with tandem-tagged NBR1 in pentaKO cells (not expressing the SLRs p62, NBR1, NDP52, TAX1BP1 and OPTN) increased significantly the autophagic turnover of NBR1. None of the other SLRs could do this. Instead, this over-expression assay revealed a competition.

    Major points:

    In Fig 4 the peptide array binding assay is not sufficient as it is only semiquantitative. The data shown should be accompanied by a more direct binding assay allowing the determination of kDs for the binding where the WT peptides are directly compared to the phosphor mimicking mutant peptides. Here the fluorescence anisotropy assay the authors use in Suppl Fig. 1E or ITC, OctetRed96 or another assay suitable for kD determinations should be used.

    As this paper is already dominated by the use of peptides it would significantly enhance the quality of the data if the authors had included studied with peptides phosphorylated at the specific positions to allow comparison with the phosphomimetic substitutions to aspartate.

    The quality of the 2D peptide array probing of GST-LC3A binding in Fig 3A is poor. Is this a stripped and re-probed membrane? I do not think these data are publication quality and the experiment should be redone unless the authors have very good arguments against my suggestion. It would also be nice to see a 2D peptide array of GABARAPL1 binding too to make the comparative study complete.

    For the data shown in Fig 6 it should be noted that although these are very interesting results a clear limitation of the study is that the results on the autophagic turnover is based on overexpressing the SLRs in the pentaKO cells. In a physiological setting with all relevant actors in place and with a different stoichiometry the effects could likely be different.

    Minor points:

    It would be beneficial for the reader to show a cartoon of the domain organization of both TAX1BP1 and NBR1 in Figure 1. NBR1 is shown in supplemental figure 1, but there is no depiction of the domain organization of TAX1BP1.

    The authors say at the bottom of page 4 "Complementary in vivo studies reveal that while SLRs typically compete". But do they actually typically compete? Is this not a result of the experimental strategies employed? There is more a shortage of SLRs based on cargo competition as shown recently by Peter Kim's group that excessive pexophagy may reduce mitophagy etc. (Germain et al. 2023).

    In Fig. 3D it should be shown that D, E, A and V are preferred residues at position +1 for LC3A binding.

    In such a 2D mutational analysis it is often just as important to determine which residues are not allowed for binding. It would therefore be nice if the authors could summarize/visualize their results in a better way in Fig 3D to also show the residues that lead to loss of binding. These could be shown below the sequence and the use of color to distinguish basic, acidic, hydrophobic and aromatic residues could be attempted.

    Line 327: To be clear about the fact that this is an overexpression assay "simultaneous expression" should be corrected to simultaneous overexpression".

    There are LIRs and FIRs that overlap and those that do not. To check the degree of overlaps that may occur among known LIRs the authors made a peptide array with 100 established LIR sequences taken from the LIR-Central database (Chatzichristofi et al., 2023). The peptide array was probed with LC3A (29 bound), GABARAPL1 (49 bound), the FIP200 Claw domain (57 bound) and the TAX1BP1 CC2 domain (49 bound). As much as one third (32) of the LIR peptides were not bound by any of the four probes. Do the authors have a good explanation for the fact that so many peptides did not bind? Strangely enough, the NBR1 peptide used in Figure 2A did not bind any of the probes while the NBR1 peptides used in Fig. 1C bound very well. Do the authors have any explanation for this?

    Significance

    I found this paper very interesting to read with a lot of interesting new detailed and useful information on binding specificity for the proteins and motifs involved. It is a generally well performed study with interesting results. I also very much enjoyed the Discussion section which opens up for several interesting possible scenarios. The study also produced important point mutants that can be used in future studies to selectively abolish TAX1BP1 binding to NBR1. I think this is a "must read" paper for researchers interested in selective autophagy and co-operation between SARs, and more generally for getting some insight into how SLiMs may work. As such, this paper will be of interest for all interested in autophagy research and for a wider audience too as it is in essence about how overlapping SLiMs may be employed to orchestrate multiple protein-protein interactions using distinct overlapping determinants, rather than a single, convergent, SLiM. It is also one of the very few papers I have come across exploiting the power of the peptide array method so extensively with success for mapping protein binding sites. It could perhaps be interesting if the authors discussed their results in relation to another study from the group of Sascha Martens on the role of TAX1BP1 in p62 bodies or condensates (doi: https://doi.org/10.1101/2024.05.17.594671). These two papers should be read together as they are both very interesting and important contributions.

  5. Version published to 10.1101/2024.05.09.593318v1 on bioRxiv