MR1 dependent MAIT cell activation is regulated by autophagy associated proteins

  1. Prabhjeet Phalora
  2. James Ussher
  3. Svenja Hester
  4. Emanuele Marchi
  5. Jeffrey Y. W. Mak
  6. David P. Fairlie
  7. Paul Klenerman

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Abstract

The antigen presenting molecule, MR1, presents microbial metabolites to MAIT cells, a population of innate-like, anti-microbial T cells. It also presents an unidentified ligand to MR-1 restricted T cells in the setting of cancer. The cellular co-factors that mediate MR1 antigen presentation have yet to be fully defined. We performed a mass spectrometry-based proteomics screen to identify MR1 interacting proteins and identified the selective autophagy receptor SQSTM1/p62. CRISPR-Cas9-mediated knock out of SQSTM1/p62 increased MAIT cell activation in the presence of E.coli but not the synthetic ligand 5-OP-RU whereas depletion of Atg5 and Atg7, key autophagy proteins, increased MAIT activation irrespective of the ligand used. This regulation appears to occur at an early step in the trafficking pathway. This data implicates distinct roles for autophagy associated proteins in the regulation of MR1 activity and highlights the autophagy pathway as a key regulator of cellular antigen presentation.

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    __Reviewer #1 (Evidence, reproducibility and clarity (Required)):____

    Summary In this study, Phalora et al identified the selective autophagy receptor SQSTM1/p62 as a MR1 interacting protein by proteomics approach using a cell line overexpressing MR1. While SQSTM1/p62 is implicated in autophagy regulation and autophagosome formation, genetic ablation of SQSTM1/p62 resulted in enhanced MAIT cell activation upon challenge with E. coli, but not with a synthetic agonist 5-OP-RU. In contrast, knockout of Atg5 and Atg7, both of which are involved in phagophore expansion engendered increased activation of MAIT cells upon both stimuli. From these data, the authors concluded that some factors in autophagy controlled the MR1 activity, thus the autophagy is a pivotal regulator of cellular antigen presentation.

    Major comments:

    1. The notion that "This regulation appears to occur at an early step in the trafficking pathway." in the summary appears not to be compatible with the present data. What the authors have shown in the study is possible implication of autophagy components such as SQSTM1/p62, Atg5, and Atg7 that are implicated in autophagosome and phagophore formation. Should the authors highlight an "early step of trafficking", Atg14L, Atg13, and/or Atg101 must be analyzed by genetic knockout in addition to PI3 kinase inhibitors that are supposed to affect an early step in autophagy. Such an approach could confirm whether the regulation of MR1 occurs at an early step of trafficking, or at least, at an early step of autophagy.__

    The reviewer may have misinterpreted our conclusion. When we state ‘an early step in the trafficking pathway’ we are referring to MR1 trafficking (from the ER to the PM) and not to early steps in the autophagy pathway. We have modified the text to make this clearer.

    __ In Figure 2, while the degree of β2M depletion from B1 appears to be superior to that in B6 (Figure 2A), why the former was more potent in producing IFN-γ relative to the latter upon E. coli and 5-OP-RU (Figure 2D)?__

    We cannot conclusively say why MAIT cell activation is reduced to a greater extent in clone B6 compared to clone B1, whereas the protein depletion is not as pronounced. Most likely as these are clonal cells there may be genetic/phenotypic differences apart from depletion of B2M that may impact upon antigen presentation. Importantly both B1 and B6 are significantly decreased in terms of MR1 surface expression and MAIT cell activation compared to the control as would be expected.

    __ In Figure 3B, right column, what is Ac-6-FP? The left histograms show MR1 expression level upon DMSO, E. coli, and 5-OP-RU challenge. There is no explanation.__

    We thank the reviewer for pointing this out. The bar chart was mislabelled and should read 5-OP-RU (as in the histogram). This has now been corrected in the figure.

    __ Also in the same figure, was MR1 geomeans in Control, 5-1, 5-2, 5-3, 7-1, 7-2, and 7-3 upon Ac-6-FP superior to DMSO? If so or not, please explain the rational.__

    The difference in MR1 geomeans between DMSO and 5-OP-RU treated cells was significantly different. However as stated in the text the difference between control and Atg depleted cells for each condition was not statistically significant although there is a trend for increasing MR1 expression in KD cells.

    __ Figure 3C is highly intentional. If the authors put two left panels together (Control, 5-1, 5-2, and 5-3), is there still statistical difference among them?__

    The data for Atg5.3 was displayed separately as the experiments for this cell line were performed at a later timepoint using different donor cells. Therefore, it would be inappropriate to combine and/or compare them with the data for Atg 5.1 and 5.2. For clarity the figure has now been modified and this explanation added to the figure legend.

    __ There was no explanation for Figure 4B why the authors used Hela-MR1-HA. Other cell lines were used in the rest of the experiments. It is highly desirable to perform the experiment with THP1-MR1-HA in terms of logical development.__

    As the reviewer correctly states, it would be ideal to use Thp.MR1.HA cells for these microscopy experiments as they have been used throughout the rest of the paper. However, Thp1 cells can be difficult to image and HeLa cells which are more amenable to this technique are commonly used instead, generally and for MR1 studies. We have validated the HeLa.MR1.HA cell lines and can show that they upregulate MR1 at the cell surface in response to antigen and can activate MAIT cells. This data is now included as a supplementary figure (Supplementary Figure 11) and the rationale for the use of these cells explained in the main text.

    __ In addition, Figure 4B represent only the non-activated status. Given that association of SQSTM1/p62 with MR1 is dependent on E.coli and/or 5-OP-RU (Figure 1A), the same immuno-fluorescent imaging in the presence of the inhibitors upon stimulation with these reagents would also be desirable. It will uncover whether MR1 and SQSTM1/p62 colocalize upon stimulation, and such colocalization is perturbed in the presence of the inhibitors.__

    The aim of this microscopy experiment was to demonstrate that perturbations to the autophagy pathway induced by different drug treatments also affected MR1 localisation and/or expression to complement the other experiments in that figure (Figure 4A and 4C). SQSTM1 expression was included as a control as it is known to be regulated by autophagy. Although assessing the interaction between MR1 and SQSTM1 under different autophagy conditions may be of interest we did not find it to be particularly relevant in this case as our focus shifted to the autophagy pathway in general rather than the specific interaction between MR1 and SQSTM1.

    __ Whereas the authors addressed the question as to at which stage MR1 is regulated in trafficking in Figure 5, there was no experiments with 5-OP-RU (an agonist for MAIT cells). This casts the doubt whether observed phenotype really represented the true MR1 trafficking, because there is no guarantee that the trafficking pathway for antagonist (Ac-6-FP) is same as that for agonist.__

    5-OP-RU and Ac-6-FP are small chemically synthesised molecules and an agonist and antagonist of MR1 antigen presentation respectively There is no evidence to suggest that apart from activation of MAIT cells (5-OP-RU is stimulatory, Ac-6-FP is not) that they would behave any differently in terms of trafficking and interaction with MR1. Indeed, both are used interchangeably in the MR1 field.

    __ Given the importance of MR1 overexpression in showing the association between MR1 and SQSTM1/p62, it is worthwhile to consider performing the knockout experiments with Thp1-MR1-HA rather than Thp1. It will further clarify the role(s) of SQSTM1/p62, Atg5, and Atg7 in MR1 trafficking and resultant MAIT cell activation.__

    The interaction studies had to be performed with overexpressed MR1 as the endogenous protein is very difficult to detect for these types of experiments. The majority of the functional studies were performed with the endogenous protein which avoids any issues concerned with the use of overexpressed and tagged proteins and addresses concerns that interactions observed with the overexpressed protein are simply artifactual. As the functional assays validate the interaction data, we believe it is not necessary to repeat the depletion experiments in the MR1 overexpressed cell lines.

    __ Minor comments: 1.Please explain why the authors failed to detect IL23A in the coimmunoprecipitation. Should MR1-IL23A interaction be specific, what is a biological significance?__

    This point is addressed in the discussion. It is sometimes the case that interactions identified by mass spec cannot be recapitulated by co-immunoprecipitation and alternative methods may need to be employed to verify the interaction. Since this work concentrates on the autophagy pathway further experiments involving IL23A were deemed beyond the scope of this manuscript. Of note, IL23A will be strongly induced over very low background levels by E coli, which would amplify the impact of any weak interactions.

    __ When Hela-MR1-HA was used, did the authors obtain the same results as Thp1-MR1-HA as shown in Figure 1C-D? This is relevant to the specificity in the interaction between MR1 and SQSTM1/p62 as shown in Figure 4B.__

    The interaction between MR1 and SQSTM1 in the presence of E.coli was not confirmed in the HeLa.MR1.HA cells. SQSTM1 is included as a positive control as it is known to be regulated by autophagy. As these experiments were performed in the absence of any antigen, we would not expect to observe an interaction in this instance.

    __ While S1, S2, S3, and S4 showed a similar degree of SQSTM1 depletion in Figure 2A, there was difference in the potential of IFN-γ production from MAIT cells among the clones. Only S4 showed decreased potential for IFN-γ upon 5-OP-RU, though E. coli failed to so. Contrary to 5-OP-RU, S1-S3 showed an enhanced potential while S4 failed to do so. Why is that so?__

    As the SQSTM1 knockout cells are clonal cells there may be other genetic/phenotypic differences, besides depletion of SQSTM1, that can account for the observed differences in MAIT cell activation. To mitigate for these differences, we tested 4 different clonal cell lines, with 3 out of 4 clones displaying the same phenotype with respect to activation of MAIT cells.

    __ Given that there was little correlation between MR1 expression level and the potential of S1-S4 to promote or inhibit the ligand-dependent production of IFN-γ (Figure 2C right panel and Figure 2D), it is difficult to conclude that the factors implicated in autophagy play a pivotal role in MR1-dependent MAIT cell activation.__

    Surface MR1 levels on the whole are difficult to detect even in the presence of antigen as MR1 surface expression appears to be very tightly controlled. Although MR1 surface expression levels between the different SQSTM1 clones appeared to be somewhat variable, in the Atg depleted cells they showed a more consistent upregulation compared to the control (although these differences were not statistically significant). In both cases, stimulation with E.coli resulted in increased MAIT activation demonstrating that these autophagy proteins did affect MR1 presentation and that small (perhaps undetectable in some cases) changes in surface expression did impact MR1 function. Therefore, we have concluded that autophagy factors are able to regulate MR1 antigen presentation but to what extent and how remains unclear. We have removed the word ‘pivotal’ from the abstract as we agree with the reviewer that the impact of these interactions has not been conclusively established.

    __ There was no consistency in the experimental design for Figure 5. Please explain the rational why the authors have used 7.1 in A and C, but not in B, D and E?__

    For some of the experiments it was not possible to display and thus quantify all the cell lines in one figure eg the western blot data for the EndoH experiments (Figure 5D). Therefore, one representative cell line from Atg5 and Atg7 depleted cells was chosen, as on the whole all the cell lines behaved similarly. This rationale is now included in the main text.

    __ The control appeared to behave as 7.1 did. Was there statistical difference between 7.1 and 7.2 in Figure 5C? If so, what is the interpretation.__

    As the reviewer correctly notes, in Figure 5C the Atg7.1 cell line had similar kinetics to the control cell line in terms of MR1 surface expression. In other experiments Atg7.1 shows increased MR1 surface expression compared to the control (Figure 3B, although not statistically significant). One major difference between these experiments is the timing, Figure 3B is measured after an overnight incubation while Figure 5C is measured over 6 hours. It may be the case that in this cell line MR1 takes slightly longer to accumulate at the cell surface compared to Atg7.2. As these are heterogenous cell populations, there may be other factors that account for these differences apart from depletion of Atg7. Statistical analysis has now also been included for this data.

    __ Time course over 6 h will be required to assess the MR1 expression in Figure 5C.__

    It has been demonstrated by others that MR1 is able to reach the cell surface within 4 hours of antigen exposure (McWilliams et al, 2016), therefore a time course over 6 hours to measure MR1 surface expression was deemed sufficient.__

    Reviewer #1 (Significance (Required)):

    The present study uncovered the possible implication of autophagy factors in MR1 trafficking, in other words, MAIT cell activation. Although the previous study has demonstrated the importance of the protein loading factors (McWilliam et al., PNAS,117 24974-24985 2020), this study adds another pathway for MAIT cell activation. However, the conceptual significance is limited in that depletion of the factors pertinent to autophagy such as Atg5 and Atg7 in Thp1 resulted in rather weak interference in terms of MR1 trafficking and MAIT cell activation. Thus, this study will interest those who work in basic immunology, in particular, in regulation of antigen-presentation molecules and T cells as well as those who are in the field of MAIT cell biology. Although the field of this reviewer covers biochemistry, molecular biology, developmental biology, immunology and regenerative medicine, proteomics approach (in detailed technique) as seen here to identify the associated molecules is somewhat beyond the reviewer's expert.

    Reviewer #2 (Evidence, reproducibility and clarity (Required)):

    Summary

    The authors used a mass spectrometry proteomics approach to screen for proteins which interact with the MHC-I-related molecule MR1. In addition to expected interacting partners, they identified SQSTM1/p62, a selective autophagy mediator, and demonstrated that MAIT cell responses to fixed E. coli were increased with knockout of SQSTM1. The authors further investigated the role of autophagy in regulating MR1 ligand presentation through knockout of two key autophagy proteins, Atg5 and Atg7, or treatment with various autophagy inhibitors. MR1 surface expression and MAIT cell activation were variably increased following interruption of autophagy in the context of fixed E. coli or synthetic ligand treatment of human monocytes and B cell lines. The authors concluded that preformed pools of MR1 are regulated by autophagy.

    Major comments

    Overall, this is an interesting study that is the first to identify autophagy as a potential regulatory mechanism for MR1. There are a number of conceptual questions relevant to the model system. The main concerns regard a number of the conclusions made, given the analysis of the data as presented. These concerns are described in more detail below.

    Conceptual concerns:

    1. The investigators rightly note the challenge in studying MR1 protein due to low endogenous expression. However, the use of over-expressed MR1 protein begs some questions with regard to the identification of ER degradation and autophagy proteins (which as they note are also involved in the degradation of damaged and defective cellular components). Although they have previously shown that MR1-HA tagged protein goes to the cell surface and presents antigen, it is impossible to know what proportion of the over-expressed molecules are functional, and it is plausible that a proportion of these molecules that end up in ER degradation or autophagy pathways identified, but would still IP with the HA tag. In the data shown, it is not entirely clear that the impacts of the molecules are actually impacting MR1 protein absent overexpression. Example: In Figure 2, there is very little impact of the complete KO of SQSTM1 on MR1 protein expression in WT THP1 cells, despite this protein only interacting with MR1 in E.coli infected cells. In contrast, in the 5-OP-RU incubated cells, there is a difference in MR1 expression in the SQSTM1 mutant clones, but no impact to MAIT cell activation. The authors note these issues and discuss the possibility that the other functions of SQSTM1 are coming in to play and further look at Atg5 and Atg7, however the absence of these proteins also have no significant impact on the expression of MR1 protein. Can the authors comment on this? The authors state that the increase in MAIT cell responses to fixed E. coli-treated polyclonal populations of SQSTM1 KO cells (same cells as SF2D) was blocked by the use of an anti-MR1 antibody, but do not show this data. Why not done with clonal populations? It is unclear why this data was not shown as it would help to support that the impact of inhibited autophagy is really on the functional MR1 protein pool, rather than a pool of non-functional but still HA tagged MR1 that has been shunted to degradation or autophagy pathways.__

    The reviewer rightly acknowledges the challenges associated with detecting endogenous MR1 protein levels which can be difficult to measure even after antigen exposure. For this reason, many researchers use a tagged protein in overexpressing cell lines to study MR1 as we (and others) have done for the proteomics analysis and validation studies. The use of tagged overexpressed proteins can be problematic because they may not recapitulate endogenous protein structure, localisation and/or function. Although we have previously demonstrated that HA tagged MR1 behaves similarly to its endogenous counterpart in terms of trafficking to the cell surface and presentation to MAIT cells (Ussher et al, 2016), there is still a possibility that there is a population of non-functional protein that is targeted for degradation. As we understand, it is the reviewer’s concern that it is this protein pool that is immunoprecipitating with autophagy components.

    Firstly, although the interaction studies were necessarily performed using tagged overexpressed protein, the majority of the functional studies (ie measuring surface MR1 levels and MAIT cell activation in SQSTM1 and Atg depleted cells, Figures 2 and 3) were performed in wildtype Thp1 cells, expressing endogenous levels of MR1. As explained in response to reviewer 1, MR1 surface levels as displayed in Figures 2C and 3B, are very tightly controlled and can be difficult to detect even after antigen exposure as demonstrated in the accompanying histograms. Therefore, subtle differences in MR1 surface levels are to be expected especially when measuring an increase rather than a decrease in expression. Although for SQSTM1 depletion there was some variability in MR1 surface levels, for Atg depletion there was a clear trend towards increased expression, although these differences were not statistically significant. In both cases (depletion of SQSTM1 and Atg) there was a definite effect on MR1 presentation as MAIT cell activation was increased in nearly all cases. It is well established in the literature that MAIT activation, in the 5 hour timecourse of our experiments, is wholly MR1 dependent. Therefore, these subtle, and perhaps sometimes undetectable, differences on endogenous MR1 surface expression do have an effect on MR1 function and we believe this validates the data from the interaction studies using overexpressed protein.

    In addition, experiments performed with the MR1 blocking antibody would not necessarily address the reviewers concerns as again these were done on Thp1 cells expressing endogenous levels of MR1 and not the overexpressing cell lines. However, for completeness this data has now been included as a supplementary figure.

    Secondly one of the top hits from the proteomics analysis was B2M, a protein known to associate with MR1 and to be functionally important. Other proteins identified by our screen include components of the peptide loading complex which have also been reported to be important for MR1 trafficking and antigen presentation. It should also be noted that SQSTM1 was identified in a similar proteomics screen performed by a different lab (McWilliams et al, 2020). Therefore, we believe that these findings also validate use of the HA tagged MR1 construct to generate true protein interactions.

    __ The conclusion that "regulation of MR1 by autophagy is not dependent on new protein synthesis and is most likely occurring on pre-existing pools of MR1" is not strongly supported by the data. If MR1 is processed normally through the golgi in Atg5 and 7 deficient cells (Figure 5D), how can the conclusion be made that the pre-existing pools of MR1 are in the ER? There is a non-significant decrease in MR1 surface expression from CHX treatment in the context of Ac-6-FP stimulation in Atg KO cells. This data is not clear enough to support a firm conclusion in either direction. Have the authors performed this experiment using 5-OP-RU or fixed E. coli as ligand sources? Is there a similar trend seen using the Atg KO C1R cells? Further supporting experiments may be necessary to conclude whether or not this trend is biologically relevant.__

    We thank the reviewer for their comment. The statement that pre-existing pools of MR1 are in the ER is based on reports from the literature where it has been shown that unbound ligand receptive MR1 remains in the ER until it comes into contact with antigen. Since we were able to show that MR1 trafficked normally through the Golgi in Atg depleted cells, the effects of autophagy on MR1 expression and function must occur prior to Golgi processing. This would indicate the ER population of MR1 as the likely targets of regulation by autophagy especially considering the function of SQSTM1 which binds to proteins in the ER.

    The experiments with CHX treatment were used to establish whether it was new or pre existing protein that was targeted by autophagy. Since CHX had no effect on MR1 surface expression this would indicate that new protein synthesis is not required for MR1 trafficking in Atg depleted cells.

    __

    Analysis of Western Blot data:

    1. There are many places throughout the manuscript where statements are made with regard to increases and decreases in the protein expression level with treatment, or comparisons between control and knockout samples. Although the legends generally indicate these experiments were based on at least 3 replicates (except some cases, where noted), there is no quantification of any western blotting data. There is no information in the legends or methods as to how much sample was loaded. Specific examples:

    a. Figure 1/Supp Figure 1: Figure 1C and 1D: There are several differences in the inputs between the 2 blots, including differences in the no antigen samples (which should be the same) or presence of multiple bands in one blot for a given marker but not the other. Fig 1C: the band for Calreticulin in the immunoprecipitated E. coli-treated Thp1.MR1.HA samples (right lane) is very weak. Fig. 1D: the bands are weak and there is no clear difference for Calnexin in the immunoprecipitated 5-OP-RU treated Thp1.MR1.HA samples (right lane) compared to no ligand despite the conclusion that Calnexin weakly associates with MR1 in the context of 5-OP-RU ligand. Are some of these weak associations visible due to different inputs? Why are the input blots for anti-HA so different between the no antigen controls in the E coli vs 5-OP-RU blots? Supp Figure 1B: the +5-OP-RU pulldown of MR1.HA appears as to be more (like with E.coli), but no quantification. Why does so little B2M IP with 5-OP-RU MR1? Supp Figure 1D (and others): statements are made about increases and decreases without quantification. All: Presumably HSP90 is used as a loading control for the input, but this is not discussed nor is there quantification.__

    We thank the reviewer for this comment. As western blotting is a multi-step process often over more than one day, there are numerous points at which variation can occur between blots no matter how carefully the conditions are controlled to minimise this. It is for this reason that it is generally not good practice to compare samples that have been run on different gels. Therefore, we do not believe that comparisons between blots in Figures 1C and 1D, relating to differences in input proteins for example, are appropriate nor informative. If we take the top anti-HA blot for Figure 1C there is a big increase in protein expression in the Ip of E.coli treated cells (final lane) which is not as pronounced with 5-OP-RU treatment (Figure 1D, top blot, final lane). This sample will dictate the exposure time of the blot (so as to prevent saturation of this sample) which then affects detectable expression of less well expressing samples on the same blot (such as the input samples in Figure 1C). Therefore there may appear to be less input protein in Figure 1C than Figure 1D but there is also more protein in the E.coli treated pull down than in the 5-OP-RU treated one, which also needs to be taken into account. This is one example of why it is difficult to compare samples across blots. To accurately and correctly compare these input samples they would need to be run on the same gel.

    The only useful comparison that can be drawn is between samples from the same blot, so comparing input protein in the presence and absence of E.coli for instance. To take the reviewer’s example, for the anti-calreticulin blot in Figure 1C, there is a weak interaction of calreticulin with MR1 in the presence of E.coli. If we compare the input lanes on this blot (effectively the loading control), there actually appears to be slightly more protein in the E.coli negative sample that the positive one. This would argue against the reviewers claim that this weak interaction is actually due to differences in the input and it is instead more likely to simply be a weak interaction. It is important to point out that this interaction, and others involving components of the peptide loading complex, have also been validated by other groups.

    With regards to Calnexin association with MR1 in the presence of 5-OP-RU, we did not mean to imply that this association was only in the presence of 5-OP-RU as it is evident from the data that Calnexin weakly associates even in the absence of antigen. The text has now been changed to make this clearer.

    The anti-HSP90 blot has been included to show that a random protein, not identified by our proteomics screen, does not spuriously associate with MR1, and not as a loading control for the input samples per se. This explanation has now been included in the text.

    Finally with regard to quantification of the co-immunoprecipitation blots, while quantification of western blots in some cases can be informative (eg relative expression of a protein compared to a control), it is at best only a semi-quantitative technique and not generally applied to co-immunoprecipitation data. As we are looking for a binary result (presence/absence of a particular protein) rather than a relative value, we do not see how quantification of this data will make it any more informative. We have included more detail of the sample loading in the methods section as requested by the reviewer and have added quantification of other blots where appropriate. __

    b. Supp Figure 5: The authors conclude there are no difference in protein interactions with MR1 in Atg5 or 7 deficient cells. By eye, there appear to in fact be differences, but there is no quantification to support the conclusions either iway. These data are subsequently used to make interpretive statements about the data in Figure 5. There is no indication of the number of times this experiment was performed.__

    In supplementary figure 5, we aimed to determine whether depletion of Atg 5 or 7 negatively affected the MR1 proteome ie whether interactions that were previously observed were disrupted and whether this contributed to the effects on MR1 antigen presentation observed in these cell lines. The interactions between MR1 and the tested proteins remained intact in Atg depleted cells. However, as Atg depletion increased MR1 protein expression some of these interactions are more pronounced in the depleted cell lines compared to the control cell line. Thus, the reviewer is correct in stating that there are differences in the protein interactions between the cell lines but in all cases the protein interactions remain intact which was the focus of our analysis. We have modified the text to make this clearer. The figure legend now also includes the number of replicates for this experiment.

    __ Figure 4A: No quantification to support conclusions. Unclear why both blocking and inducing autophagy would both increase the amount of MR1 in cells.__

    Quantification of this western blot data has now been included in the figure. Blocking autophagy (3MA and Wort) has a much greater effect on total MR1 protein levels, while inducing autophagy (EBSS) has minimal effects compared to the control. As autophagy is a highly dynamic process with western blotting providing just a snapshot of this process, inhibiting and inducing autophagy can both lead to the same observed phenotype of increased autophagosomes, due to blocking fusion with lysosomes and increased autophagosome formation respectively.

    __

    Analysis of Fluorescence microscopy data (Figure 4B):

    1. There are several concerns with the conclusions drawn from the fluorescence microscopy images (Figure 4B). How many images/fields were taken and cells analyzed per condition? How were individual fields chosen for imaging to be unbiased? Overall, the conclusions are observational and require quantification. For example, the authors indicate "an increase in MR1 cytoplasmic signal intensity following treatment...", but there is not data analysis to support this statement. This could be quantified by analyzing average MR1-HA fluorescence intensity across the cell volume compared to the bright fluorescence intensity of the non-cytoplasmic MR1-HA regions. Similarly, the number and intensity of the SQSTM1 foci should be quantified. Quantification is required to make the stated conclusions.__

    We thank the reviewer for their helpful suggestions regarding the microscopy experiments. Quantification of the data has now been added, including MR1 fluorescent intensity and the number of SQSTM1 foci, which supports the data from Figure 4A. The methods and figure legend have been updated to include more details of the analysis pipeline.

    __ Other statistical concerns:

    1. Some of the figure legends do not clearly state the number of independent experiments performed (2D, 3C-D, 5A, SF2, SF3, SF5). If these experiments were only performed once, additional repeats and appropriate statistical analysis are necessary to validate any conclusions drawn from these results.__

    The number of replicates for each experiment are now included in the figure legends. __

    1. Was statistical analysis performed on the MR1 mRNA expression in Figure 5A, and how many independent experiments are shown? There appears to be a decrease in MR1 expression in the Stg7.1 KO cells, which might impact the overall MR1 expression. Also, statistical analysis seems to be missing from 5B and 5C.__

    This figure has now been altered to reflect the number of replicates (2 biological replicates each consisting of 3 technical replicates) and statistical analysis has also been included. Statistical analysis for Figures 5B and 5C has also now been included. __

    1. In figure 5E, were there statistical comparisons between the Atg KO and control cells in the Ac-6-FP-treated non-CHX condition? It is unclear whether the statement "As previously observed, there was an increase in surface MR1 levels in Atg-depleted cells compared to the control in the presence of Ac-6-FP" is referring to the non-significant results in 3B or to this data presented in 5E. This statement should be revised to reflect the statistical significance of these data.__

    We thank the reviewer for this point. This figure has been amended to include a timecourse of CHX treatment in control and Atg depleted cell lines and statistical analysis has also been included. The statement has been clarified to highlight the point that CHX treatment does not affect the level of MR1 upregulation in control and knockdown cell lines.

    __

    Throughout the figures, several bar plots are missing the individual data points of experimental or technical replicates.__

    All bar plots display either the individual data points where donor cells were used or the average of 3 or more independent experiments with error bars denoting the standard deviation for experiments using cell lines.__

    1. The data in Figures 3C-D could be presented and analyzed as paired data (comparing the response from MAIT cells of each PBMC donor to the Ctrl cells vs the Atg KO clones) to better represent the impact of the KO.__

    We thank the reviewer for this suggestion. We believe that analysis via ANOVA is more appropriate in this instance due to the number of comparisons made with the control cells.__

    Other minor concerns:

    1. The conclusion "Overall, in the absence of SQSTM1, cellular changes induced by E. coli result in increased antigen presentation, which is not replicated with 5-OP-RU where MAIT activation may be adversely affected, implying that regulation of MR1 function by SQSTM1 may be dependent on the nature of the antigen" (page 6) is confusing and may need re-wording.__

    We are sorry for the confusion and have reworded this sentence to make it clearer. __

    1. The x-axis in the bar plots of Fig 3B labels the right group as "Ac-6-FP" in contrast to the histogram label and figure legend, which indicate the cells were treated with 5-OP-RU.__

    We thank the reviewer for pointing this out, the bar plot was indeed mislabelled and has now been corrected. __

    1. The presentation of data in Figure 5B is confusing. Perhaps the DMSO and Ac-6-FP conditions are mis-labeled? For the DMSO-treated samples, it appears that the data presented are percent surface MR1 GeoMean compared to the 0hr timepoint per cell lines. However, treating cells with Ac-6-FP should result in an increased surface MR1 expression (as seen in the non-CHX samples of Fig 5E, for example). If the data presented are percent of the 0hr DMSO control, wouldn't the % MR1 expression be higher for the Ac-6-FP samples than the DMSO samples? Alternately, it might be clearer to separate these two conditions onto separate plots, with % MR1 calculated relative to the 0 hr control of DMSO or Ac-6-FP treatment, respectively.__

    We thank the reviewer for pointing this out, the graph was indeed mislabelled and has now been corrected. The DMSO and Ac-6-FP treated samples are normalised to their own 0-hour timepoint (set at 100%) in order to directly compare the rate of decline of MR1 surface expression between the two conditions. This is now more clearly explained in the figure legend.

    __ Unclear in Figures 3 and 5 (and supplements) why all or only some of the Atg5 and 7 clones are used from experiment to experiment.__

    Please see our response to reviewer 1 on this point.__

    1. The discussion mentions "we found no evidence of an interaction between MR1 and AAKI" on page 9. What data supports this statement?__

    We found no evidence of an interaction between MR1 and AAK1 from our proteomics screen, this is now explained in the text.

    __ The discussion indicates that "This increase in SQSTM1 protein levels still resulted in increased MR1 surface levels and activation of MAIT cells, the same phenotype observed in SQSTM1-depleted cells" as it relates to the presence of E.coli. This statement is not fully supported by the data as SQSTM1 depletion did not lead to an increase in surface MR1 in E.coli treated cells.__

    We thank the reviewer for pointing this out, this sentence has now been corrected. __

    1. In the Proteomics/Mass Spec methods section on page 13, the citations to MaxQuant and Andromeda may need to be fixed.__

    We thank the reviewer for pointing this out, this has now been corrected. __

    1. There is no materials/methods section in the supplement. While most of this is covered by the main manuscript M/M section, there is no information on the IL12 and IL18 cytokine treatment, or treating with il12/il18 or isotype blocking antibody in SF1.__

    A methods section for the supplementary data has now been included. __

    1. Throughout the manuscript, several full stops are missing following in-text citations (ex: page 1, line 6 "...and Granzyme B 2-4 The microbial...").__

    We thank the reviewer for pointing this out, this has now been corrected.__

    1. The figure 1 legend should read "LC-MS/MS" rather than "LC-LC/MS"__

    We thank the reviewer for pointing this out, this has now been corrected.__

    1. Several of the citations need updating. They are listed as "Preprint available at ..." but for several of these references, the DOI links to the fully peer-reviewed publications, not a preprint.__

    We thank the reviewer for pointing this out, this has now been corrected.

    __

    Reviewer #2 (Significance (Required)):

    Significance

    Overall, this work expands the field knowledge of MR1 regulation and antigen presentation. The authors are the first to describe the putative role of key autophagy mediators like SQSTM1 and Atg5/7 in regulating MR1/MAIT cell activation. This report builds upon previous works exploring MR1 trafficking (Huang et al. JEM 2008, McWilliam et al. Nat Imm 2016, Harriff et al. PLoS Path 2016, Karamooz et al. Sci Rep 2019, McWilliam PNAS 2020, Huber et al. Sci Rep 2020) and MR1 protein stability (Abós et al. Biochem Biophys Res Commun 2011, Ussher et al. Eur J Immunol 2016, McWilliam et al. PNAS 2020, Kulicke et al. JBC 2022).

    This report would be of interest to researchers in the field of MR1 trafficking and antigen presentation, particularly in the context of increasing interest in targeting MR1 therapeutically (e.g. in cancer immunobiology or autoimmunity). From these results, future work could include characterization of the specific autophagy mechanisms which target MR1 for degradation, the role of SQSTM1 in modulating MR1 function via direct binding through autophagy or additional mechanisms, the variable mechanisms of MR1 trafficking and antigen presentation in the context of internal vs external ligand sources, and exploring if bacterial modulation of autophagy might impact MR1 antigen presentation.

    Expertise: MR1 trafficking and antigen presentation, MAIT cell activation, cell and molecular techiques, statistical analyses. Difficult to assess: the relevance of these marker in the autophagy field and evaluating the technical methods for LC-MS/MS.

    Reviewer #3 (Evidence, reproducibility and clarity (Required)):

    In the current report, Phalora et al., have identified a number of proteins that bind to human MR1. Some of them, including those associated with the peptide-loading complex, such as tapasin, have been identified by others as well. However, these authors found that molecules associated with autophagy-specifically, SQST1/p62-were negative regulators of MR1 surface expression. In other words, knocking out the gene encoding this protein enhanced MR1 expression in THP-1 cells pulsed with E. coli and consequent MAIT cell activation. Moreover, CRISPR/Cas9-mediated deletion of the autophagy proteins, Atg5 and Atg7, resulted in an even greater enhancement of MR1 surface expression. Chemicals that block autophagy had similar effects in both THP-1 and primary PBMC monocytes. Thus, for the first time, it has been demonstrated that, like in classical HLA class I molecules, autophagy plays a role in the surface expression of the MR1 antigen presenting molecule. Overall, the study is very interesting and technically well-done. I do have a few questions, concerns and criticisms that are indicated in the sections below.

    Major Comments:

    1. It was stated in the text that they used an anti-MR1 mAb to demonstrate the effects on MAIT cell activation were indeed MR1-dependent, yet these data were not shown. Those experiments should be included in the supplemental data section.__

    We thank the reviewer for this suggestion, this data has now been included as a supplementary figure.

    __ The Discussion lacks a "big picture" assessment/speculation about how these observations fit within a particular disease or set of diseases__

    The discussion has now been revised to include assessment of how these findings fit into the wider scope of MR1 restricted T cells in health and disease.

    __ THP-1 and C1R are essentially cancer cells and it has been shown that MR1T cells likely recognize a tumor antigen presented by MR1. Rather than using purified MAIT cells for this study, the authors used purified CD8+ T cells. MAIT cells represent a portion of them. How many of the non-MAIT cells were activated by THP-1 and/or C1R cells? One could compare MAIT vs. MR1T cell activation depending on the APC type.__

    We thank the reviewer for this suggestion. We re-analysed some of the data to focus on the non-MAIT population but we were unable to identify a population of non-MAIT cells stimulated by co-incubation with Thp1 or CR1 cells. In general, MR1T cells are quite rare and difficult to isolate solely from the non-MAIT cell population.

    __ As autophagy proteins have been shown to be important for MHC class I and, thanks to this work, MR1, it would have been helpful to discuss other antigen presenting molecules (e.g., CD1d) and what this could mean in immune responses overall. How does this help the host?__

    We have now included a section in the discussion to address the wider significance of these findings for immune responses via antigen presentation and the implications for other antigen presenting molecules.

    __ Minor Comment:

    1. Some parts of some figures (e.g., Fig. 1B) have text so small that it is extremely difficult to read. This would be problematic in a journal article.__

    We thank the reviewer for pointing this out, the text in the figure has now been adjusted to make it easier to read.

    __

    Reviewer #3 (Significance (Required)):

    This study shows, for the first time, that autophagy processes impact cell surface expression of MR1 and this depends upon the antigen. Because this phenomenon has been demonstrated previously for classical MHC class I molecules (ref. 28) and the lipid-presenting antigen presenting molecule CD1d (Autophagy 13:1025-1036, 2017), the novelty of their findings is somewhat diminished.

    An audience who would be interested in this work would include investigators who study antigen presentation to both classical and innate T cells.

    Keywords: antigen presentation; MAIT cells; MR1; autophagy; innate immunity__

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    Referee #3

    Evidence, reproducibility and clarity

    In the current report, Phalora et al., have identified a number of proteins that bind to human MR1. Some of them, including those associated with the peptide-loading complex, such as tapasin, have been identified by others as well. However, these authors found that molecules associated with autophagy-specifically, SQST1/p62-were negative regulators of MR1 surface expression. In other words, knocking out the gene encoding this protein enhanced MR1 expression in THP-1 cells pulsed with E. coli and consequent MAIT cell activation. Moreover, CRISPR/Cas9-mediated deletion of the autophagy proteins, Atg5 and Atg7, resulted in an even greater enhancement of MR1 surface expression. Chemicals that block autophagy had similar effects in both THP-1 and primary PBMC monocytes. Thus, for the first time, it has been demonstrated that, like in classical HLA class I molecules, autophagy plays a role in the surface expression of the MR1 antigen presenting molecule. Overall, the study is very interesting and technically well-done. I do have a few questions, concerns and criticisms that are indicated in the sections below.

    Major Comments:

    1. It was stated in the text that they used an anti-MR1 mAb to demonstrate the effects on MAIT cell activation were indeed MR1-dependent, yet these data were not shown. Those experiments should be included in the supplemental data section.
    2. The Discussion lacks a "big picture" assessment/speculation about how these observations fit within a particular disease or set of diseases
    3. THP-1 and C1R are essentially cancer cells and it has been shown that MR1T cells likely recognize a tumor antigen presented by MR1. Rather than using purified MAIT cells for this study, the authors used purified CD8+ T cells. MAIT cells represent a portion of them. How many of the non-MAIT cells were activated by THP-1 and/or C1R cells? One could compare MAIT vs. MR1T cell activation depending on the APC type.
    4. As autophagy proteins have been shown to be important for MHC class I and, thanks to this work, MR1, it would have been helpful to discuss other antigen presenting molecules (e.g., CD1d) and what this could mean in immune responses overall. How does this help the host?

    Minor Comment:

    1. Some parts of some figures (e.g., Fig. 1B) have text so small that it is extremely difficult to read. This would be problematic in a journal article.

    Significance

    This study shows, for the first time, that autophagy processes impact cell surface expression of MR1 and this depends upon the antigen. Because this phenomenon has been demonstrated previously for classical MHC class I molecules (ref. 28) and the lipid-presenting antigen presenting molecule CD1d (Autophagy 13:1025-1036, 2017), the novelty of their findings is somewhat diminished.

    An audience who would be interested in this work would include investigators who study antigen presentation to both classical and innate T cells.

    Keywords: antigen presentation; MAIT cells; MR1; autophagy; innate immunity

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    Referee #2

    Evidence, reproducibility and clarity

    Summary

    The authors used a mass spectrometry proteomics approach to screen for proteins which interact with the MHC-I-related molecule MR1. In addition to expected interacting partners, they identified SQSTM1/p62, a selective autophagy mediator, and demonstrated that MAIT cell responses to fixed E. coli were increased with knockout of SQSTM1. The authors further investigated the role of autophagy in regulating MR1 ligand presentation through knockout of two key autophagy proteins, Atg5 and Atg7, or treatment with various autophagy inhibitors. MR1 surface expression and MAIT cell activation were variably increased following interruption of autophagy in the context of fixed E. coli or synthetic ligand treatment of human monocytes and B cell lines. The authors concluded that preformed pools of MR1 are regulated by autophagy.

    Major comments

    Overall, this is an interesting study that is the first to identify autophagy as a potential regulatory mechanism for MR1. There are a number of conceptual questions relevant to the model system. The main concerns regard a number of the conclusions made, given the analysis of the data as presented. These concerns are described in more detail below.

    Conceptual concerns:

    1. The investigators rightly note the challenge in studying MR1 protein due to low endogenous expression. However, the use of over-expressed MR1 protein begs some questions with regard to the identification of ER degradation and autophagy proteins (which as they note are also involved in the degradation of damaged and defective cellular components). Although they have previously shown that MR1-HA tagged protein goes to the cell surface and presents antigen, it is impossible to know what proportion of the over-expressed molecules are functional, and it is plausible that a proportion of these molecules that end up in ER degradation or autophagy pathways identified, but would still IP with the HA tag. In the data shown, it is not entirely clear that the impacts of the molecules are actually impacting MR1 protein absent overexpression. Example: In Figure 2, there is very little impact of the complete KO of SQSTM1 on MR1 protein expression in WT THP1 cells, despite this protein only interacting with MR1 in E.coli infected cells. In contrast, in the 5-OP-RU incubated cells, there is a difference in MR1 expression in the SQSTM1 mutant clones, but no impact to MAIT cell activation. The authors note these issues and discuss the possibility that the other functions of SQSTM1 are coming in to play and further look at Atg5 and Atg7, however the absence of these proteins also have no significant impact on the expression of MR1 protein. Can the authors comment on this? The authors state that the increase in MAIT cell responses to fixed E. coli-treated polyclonal populations of SQSTM1 KO cells (same cells as SF2D) was blocked by the use of an anti-MR1 antibody, but do not show this data. Why not done with clonal populations? It is unclear why this data was not shown as it would help to support that the impact of inhibited autophagy is really on the functional MR1 protein pool, rather than a pool of non-functional but still HA tagged MR1 that has been shunted to degradation or autophagy pathways.
    2. The conclusion that "regulation of MR1 by autophagy is not dependent on new protein synthesis and is most likely occurring on pre-existing pools of MR1" is not strongly supported by the data. If MR1 is processed normally through the golgi in Atg5 and 7 deficient cells (Figure 5D), how can the conclusion be made that the pre-existing pools of MR1 are in the ER? There is a non-significant decrease in MR1 surface expression from CHX treatment in the context of Ac-6-FP stimulation in Atg KO cells. This data is not clear enough to support a firm conclusion in either direction. Have the authors performed this experiment using 5-OP-RU or fixed E. coli as ligand sources? Is there a similar trend seen using the Atg KO C1R cells? Further supporting experiments may be necessary to conclude whether or not this trend is biologically relevant.

    Analysis of Western Blot data:

    1. There are many places throughout the manuscript where statements are made with regard to increases and decreases in the protein expression level with treatment, or comparisons between control and knockout samples. Although the legends generally indicate these experiments were based on at least 3 replicates (except some cases, where noted), there is no quantification of any western blotting data. There is no information in the legends or methods as to how much sample was loaded. Specific examples:
      • a. Figure 1/Supp Figure 1: Figure 1C and 1D: There are several differences in the inputs between the 2 blots, including differences in the no antigen samples (which should be the same) or presence of multiple bands in one blot for a given marker but not the other. Fig 1C: the band for Calreticulin in the immunoprecipitated E. coli-treated Thp1.MR1.HA samples (right lane) is very weak. Fig. 1D: the bands are weak and there is no clear difference for Calnexin in the immunoprecipitated 5-OP-RU treated Thp1.MR1.HA samples (right lane) compared to no ligand despite the conclusion that Calnexin weakly associates with MR1 in the context of 5-OP-RU ligand. Are some of these weak associations visible due to different inputs? Why are the input blots for anti-HA so different between the no antigen controls in the E coli vs 5-OP-RU blots? Supp Figure 1B: the +5-OP-RU pulldown of MR1.HA appears as to be more (like with E.coli), but no quantification. Why does so little B2M IP with 5-OP-RU MR1? Supp Figure 1D (and others): statements are made about increases and decreases without quantification. All: Presumably HSP90 is used as a loading control for the input, but this is not discussed nor is there quantification.
      • b. Supp Figure 5: The authors conclude there are no difference in protein interactions with MR1 in Atg5 or 7 deficient cells. By eye, there appear to in fact be differences, but there is no quantification to support the conclusions either iway. These data are subsequently used to make interpretive statements about the data in Figure 5. There is no indication of the number of times this experiment was performed.
      • c. Figure 4A: No quantification to support conclusions. Unclear why both blocking and inducing autophagy would both increase the amount of MR1 in cells.

    Analysis of Fluorescence microscopy data (Figure 4B):

    1. There are several concerns with the conclusions drawn from the fluorescence microscopy images (Figure 4B). How many images/fields were taken and cells analyzed per condition? How were individual fields chosen for imaging to be unbiased? Overall, the conclusions are observational and require quantification. For example, the authors indicate "an increase in MR1 cytoplasmic signal intensity following treatment...", but there is not data analysis to support this statement. This could be quantified by analyzing average MR1-HA fluorescence intensity across the cell volume compared to the bright fluorescence intensity of the non-cytoplasmic MR1-HA regions. Similarly, the number and intensity of the SQSTM1 foci should be quantified. Quantification is required to make the stated conclusions.

    Other statistical concerns:

    1. Some of the figure legends do not clearly state the number of independent experiments performed (2D, 3C-D, 5A, SF2, SF3, SF5). If these experiments were only performed once, additional repeats and appropriate statistical analysis are necessary to validate any conclusions drawn from these results.
    2. Was statistical analysis performed on the MR1 mRNA expression in Figure 5A, and how many independent experiments are shown? There appears to be a decrease in MR1 expression in the Stg7.1 KO cells, which might impact the overall MR1 expression. Also, statistical analysis seems to be missing from 5B and 5C.
    3. In figure 5E, were there statistical comparisons between the Atg KO and control cells in the Ac-6-FP-treated non-CHX condition? It is unclear whether the statement "As previously observed, there was an increase in surface MR1 levels in Atg-depleted cells compared to the control in the presence of Ac-6-FP" is referring to the non-significant results in 3B or to this data presented in 5E. This statement should be revised to reflect the statistical significance of these data.
    4. Throughout the figures, several bar plots are missing the individual data points of experimental or technical replicates.
    5. The data in Figures 3C-D could be presented and analyzed as paired data (comparing the response from MAIT cells of each PBMC donor to the Ctrl cells vs the Atg KO clones) to better represent the impact of the KO.

    Other minor concerns:

    1. The conclusion "Overall, in the absence of SQSTM1, cellular changes induced by E. coli result in increased antigen presentation, which is not replicated with 5-OP-RU where MAIT activation may be adversely affected, implying that regulation of MR1 function by SQSTM1 may be dependent on the nature of the antigen" (page 6) is confusing and may need re-wording.
    2. The x-axis in the bar plots of Fig 3B labels the right group as "Ac-6-FP" in contrast to the histogram label and figure legend, which indicate the cells were treated with 5-OP-RU.
    3. The presentation of data in Figure 5B is confusing. Perhaps the DMSO and Ac-6-FP conditions are mis-labeled? For the DMSO-treated samples, it appears that the data presented are percent surface MR1 GeoMean compared to the 0hr timepoint per cell lines. However, treating cells with Ac-6-FP should result in an increased surface MR1 expression (as seen in the non-CHX samples of Fig 5E, for example). If the data presented are percent of the 0hr DMSO control, wouldn't the % MR1 expression be higher for the Ac-6-FP samples than the DMSO samples? Alternately, it might be clearer to separate these two conditions onto separate plots, with % MR1 calculated relative to the 0 hr control of DMSO or Ac-6-FP treatment, respectively.
    4. Unclear in Figures 3 and 5 (and supplements) why all or only some of the Atg5 and 7 clones are used from experiment to experiment.
    5. The discussion mentions "we found no evidence of an interaction between MR1 and AAKI" on page 9. What data supports this statement?
    6. The discussion indicates that "This increase in SQSTM1 protein levels still resulted in increased MR1 surface levels and activation of MAIT cells, the same phenotype observed in SQSTM1-depleted cells" as it relates to the presence of E.coli. This statement is not fully supported by the data as SQSTM1 depletion did not lead to an increase in surface MR1 in E.coli treated cells.
    7. In the Proteomics/Mass Spec methods section on page 13, the citations to MaxQuant and Andromeda may need to be fixed.
    8. There is no materials/methods section in the supplement. While most of this is covered by the main manuscript M/M section, there is no information on the IL12 and IL18 cytokine treatment, or treating with il12/il18 or isotype blocking antibody in SF1.
    9. Throughout the manuscript, several full stops are missing following in-text citations (ex: page 1, line 6 "...and Granzyme B 2-4 The microbial...").
    10. The figure 1 legend should read "LC-MS/MS" rather than "LC-LC/MS"
    11. Several of the citations need updating. They are listed as "Preprint available at ..." but for several of these references, the DOI links to the fully peer-reviewed publications, not a preprint.

    Significance

    Overall, this work expands the field knowledge of MR1 regulation and antigen presentation. The authors are the first to describe the putative role of key autophagy mediators like SQSTM1 and Atg5/7 in regulating MR1/MAIT cell activation. This report builds upon previous works exploring MR1 trafficking (Huang et al. JEM 2008, McWilliam et al. Nat Imm 2016, Harriff et al. PLoS Path 2016, Karamooz et al. Sci Rep 2019, McWilliam PNAS 2020, Huber et al. Sci Rep 2020) and MR1 protein stability (Abós et al. Biochem Biophys Res Commun 2011, Ussher et al. Eur J Immunol 2016, McWilliam et al. PNAS 2020, Kulicke et al. JBC 2022).

    This report would be of interest to researchers in the field of MR1 trafficking and antigen presentation, particularly in the context of increasing interest in targeting MR1 therapeutically (e.g. in cancer immunobiology or autoimmunity). From these results, future work could include characterization of the specific autophagy mechanisms which target MR1 for degradation, the role of SQSTM1 in modulating MR1 function via direct binding through autophagy or additional mechanisms, the variable mechanisms of MR1 trafficking and antigen presentation in the context of internal vs external ligand sources, and exploring if bacterial modulation of autophagy might impact MR1 antigen presentation.

    Expertise: MR1 trafficking and antigen presentation, MAIT cell activation, cell and molecular techiques, statistical analyses. Difficult to assess: the relevance of these marker in the autophagy field and evaluating the technical methods for LC-MS/MS.

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    Referee #1

    Evidence, reproducibility and clarity

    Summary

    In this study, Phalora et al identified the selective autophagy receptor SQSTM1/p62 as a MR1 interacting protein by proteomics approach using a cell line overexpressing MR1. While SQSTM1/p62 is implicated in autophagy regulation and autophagosome formation, genetic ablation of SQSTM1/p62 resulted in enhanced MAIT cell activation upon challenge with E. coli, but not with a synthetic agonist 5-OP-RU. In contrast, knockout of Atg5 and Atg7, both of which are involved in phagophore expansion engendered increased activation of MAIT cells upon both stimuli. From these data, the authors concluded that some factors in autophagy controlled the MR1 activity, thus the autophagy is a pivotal regulator of cellular antigen presentation.

    Major comments:

    1. The notion that "This regulation appears to occur at an early step in the trafficking pathway." in the summary appears not to be compatible with the present data. What the authors have shown in the study is possible implication of autophagy components such as SQSTM1/p62, Atg5, and Atg7 that are implicated in autophagosome and phagophore formation. Should the authors highlight an "early step of trafficking", Atg14L, Atg13, and/or Atg101 must be analyzed by genetic knockout in addition to PI3 kinase inhibitors that are supposed to affect an early step in autophagy. Such an approach could confirm whether the regulation of MR1 occurs at an early step of trafficking, or at least, at an early step of autophagy.
    2. In Figure 2, while the degree of β2M depletion from B1 appears to be superior to that in B6 (Figure 2A), why the former was more potent in producing IFN-γ relative to the latter upon E. coli and 5-OP-RU (Figure 2D)?
    3. In Figure 3B, right column, what is Ac-6-FP? The left histograms show MR1 expression level upon DMSO, E. coli, and 5-OP-RU challenge. There is no explanation.
    4. Also in the same figure, was MR1 geomeans in Control, 5-1, 5-2, 5-3, 7-1, 7-2, and 7-3 upon Ac-6-FP superior to DMSO? If so or not, please explain the rational.
    5. Figure 3C is highly intentional. If the authors put two left panels together (Control, 5-1, 5-2, and 5-3), is there still statistical difference among them?
    6. There was no explanation for Figure 4B why the authors used Hela-MR1-HA. Other cell lines were used in the rest of the experiments. It is highly desirable to perform the experiment with THP1-MR1-HA in terms of logical development.
    7. In addition, Figure 4B represent only the non-activated status. Given that association of SQSTM1/p62 with MR1 is dependent on E.coli and/or 5-OP-RU (Figure 1A), the same immuno-fluorescent imaging in the presence of the inhibitors upon stimulation with these reagents would also be desirable. It will uncover whether MR1 and SQSTM1/p62 colocalize upon stimulation, and such colocalization is perturbed in the presence of the inhibitors.
    8. Whereas the authors addressed the question as to at which stage MR1 is regulated in trafficking in Figure 5, there was no experiments with 5-OP-RU (an agonist for MAIT cells). This casts the doubt whether observed phenotype really represented the true MR1 trafficking, because there is no guarantee that the trafficking pathway for antagonist (Ac-6-FP) is same as that for agonist.
    9. Given the importance of MR1 overexpression in showing the association between MR1 and SQSTM1/p62, it is worthwhile to consider performing the knockout experiments with Thp1-MR1-HA rather than Thp1. It will further clarify the role(s) of SQSTM1/p62, Atg5, and Atg7 in MR1 trafficking and resultant MAIT cell activation.

    Minor comments:

    1.Please explain why the authors failed to detect IL23A in the coimmunoprecipitation. Should MR1-IL23A interaction be specific, what is a biological significance?

    1. When Hela-MR1-HA was used, did the authors obtain the same results as Thp1-MR1-HA as shown in Figure 1C-D? This is relevant to the specificity in the interaction between MR1 and SQSTM1/p62 as shown in Figure 4B.
    2. While S1, S2, S3, and S4 showed a similar degree of SQSTM1 depletion in Figure 2A, there was difference in the potential of IFN-γ production from MAIT cells among the clones. Only S4 showed decreased potential for IFN-γ upon 5-OP-RU, though E. coli failed to so. Contrary to 5-OP-RU, S1-S3 showed an enhanced potential while S4 failed to do so. Why is that so?
    3. Given that there was little correlation between MR1 expression level and the potential of S1-S4 to promote or inhibit the ligand-dependent production of IFN-γ (Figure 2C right panel and Figure 2D), it is difficult to conclude that the factors implicated in autophagy play a pivotal role in MR1-dependent MAIT cell activation.
    4. There was no consistency in the experimental design for Figure 5. Please explain the rational why the authors have used 7.1 in A and C, but not in B, D and E?
    5. The control appeared to behave as 7.1 did. Was there statistical difference between 7.1 and 7.2 in Figure 5C? If so, what is the interpretation.
    6. Time course over 6 h will be required to assess the MR1 expression in Figure 5C.

    Significance

    The present study uncovered the possible implication of autophagy factors in MR1 trafficking, in other words, MAIT cell activation. Although the previous study has demonstrated the importance of the protein loading factors (McWilliam et al., PNAS,117 24974-24985 2020), this study adds another pathway for MAIT cell activation. However, the conceptual significance is limited in that depletion of the factors pertinent to autophagy such as Atg5 and Atg7 in Thp1 resulted in rather weak interference in terms of MR1 trafficking and MAIT cell activation. Thus, this study will interest those who work in basic immunology, in particular, in regulation of antigen-presentation molecules and T cells as well as those who are in the field of MAIT cell biology.

    Although the field of this reviewer covers biochemistry, molecular biology, developmental biology, immunology and regenerative medicine, proteomics approach (in detailed technique) as seen here to identify the associated molecules is somewhat beyond the reviewer's expert.

  5. Version published to 10.1101/2022.09.20.508788 on bioRxiv