Legionella ‐ and host‐driven lipid flux at LCV‐ER membrane contact sites promotes vacuole remodeling

  1. Simone Vormittag
  2. Dario Hüsler
  3. Ina Haneburger
  4. Tobias Kroniger
  5. Aby Anand
  6. Manuel Prantl
  7. Caroline Barisch
  8. Sandra Maaß
  9. Dörte Becher
  10. François Letourneur
  11. Hubert Hilbi

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Abstract

Legionella pneumophila replicates in macrophages and amoeba within a unique compartment, the Legionella ‐containing vacuole (LCV). Hallmarks of LCV formation are the phosphoinositide lipid conversion from PtdIns(3) P to PtdIns(4) P , fusion with ER‐derived vesicles and a tight association with the ER. Proteomics of purified LCVs indicate the presence of membrane contact sites (MCS) proteins possibly implicated in lipid exchange. Using dually fluorescence‐labeled Dictyostelium discoideum amoeba, we reveal that VAMP‐associated protein (Vap) and the PtdIns(4) P 4‐phosphatase Sac1 localize to the ER, and Vap also localizes to the LCV membrane. Furthermore, Vap as well as Sac1 promote intracellular replication of L. pneumophila and LCV remodeling. Oxysterol binding proteins (OSBPs) preferentially localize to the ER (OSBP8) or the LCV membrane (OSBP11), respectively, and restrict (OSBP8) or promote (OSBP11) bacterial replication and LCV expansion. The sterol probes GFP‐D4H* and filipin indicate that sterols are rapidly depleted from LCVs, while PtdIns(4) P accumulates. In addition to Sac1, the PtdIns(4) P ‐subverting L. pneumophila effector proteins LepB and SidC also support LCV remodeling. Taken together, the Legionella ‐ and host cell‐driven PtdIns(4) P gradient at LCV‐ER MCSs promotes Vap‐, OSBP‐ and Sac1‐dependent pathogen vacuole maturation.

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  1. Version published to 10.15252/embr.202256007
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    Reply to the reviewers

    Manuscript number: RC-2022-01541

    Corresponding author(s): Hubert Hilbi

    1. General Statements

    Upon infection of eukaryotic host cells, Legionella pneumophila forms a unique compartment, the Legionella-containing vacuole (LCV). While the role of vesicle trafficking pathways for LCV formation has been quite extensively studied, the role of putative membrane contact sites (MCS) between the LCV and the ER has been barely addressed. In our study, we provide a comprehensive analysis of the localization and function of protein and lipid components of LCV-ER MCS in the genetically tractable amoeba Dictyostelium discoideum.

    We would like to thank the 3 reviewers for their thorough and constructive reviews. Overall, the reviewers state that the study is of interest to researchers in the field of Legionella and other intracellular pathogens (Reviewer 2), as well as to cell biologists (Reviewer 3). Reviewer 1 does not ask for additional experiments but is critical about the overall structure of the manuscript and the proteomics approach. As requested by the reviewer, we have substantially restructured the revised manuscript, now clearly outline the hypotheses put forward in the study and streamlined the proteomics data. Reviewer 2 asks for additional experiments to support our model of LCV-ER MCS. In the revised manuscript, we have included additional experiments addressing lipid exchange at the MCS, and we plan to perform further co-localization experiments. Reviewer 3 appreciates the comprehensive LCV proteomics and asks for only minor revisions, which we have incorporated in the revised version of the manuscript. We include below a point-by-point response to all the comments made by the reviewers.

    2. Description of the planned revisions

    Reviewer #2

    Major comment

    1. MCS contain protein complexes or a group of proteins, but the proteins here are studied in isolation and do not support the model shown in Figure 7. Co-localization studies of the putative LCV-ER MCS proteins are critical, especially given that the authors hypothesize the proteins are working together to modulate PI(4)P levels.

    Response: As suggested by the reviewer, we will perform additional co-localization experiments with MCS components. To this end, we will construct mCherry-Vap, and we will co-transfect the parental *D. discoideum *strain Ax3 with plasmids producing mCherry-Vap and OSBP8-GFP or GFP-OSBP11. Using these dually fluorescence labelled D. discoideum strains, the co-localization of Vap with the OSBPs will be assessed at 1, 2, and 8 h post infection. The data will be presented as fluorescence micrographs, and co-localization of Vap with the OSBPs will be quantified using Pearson’s correlation coefficient and fluorescence intensity profiles. The data will be outlined in the text (l. 258 ff.) and shown in the new Fig. 2 and__ Fig. S4__.

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

    Reviewer #1 (Evidence, reproducibility and clarity):

    In the manuscript by Vormittag, et al., the authors perform proteomics identification of proteins associated with the Legionella-containing vacuole (LCV) in the model amoeba Dictyostelium discoideum comparing WT to atlastin knockout mutants. The authors find approximately half the D. discoideum proteome associated with the LCV, but there was enrichment of some proteins on the WT relative to the mutant. They focus on proteins involved in forming membrane contact sites (MCS) that previously were shown to be important for expansion of the Chlamydia-containing vacuole. Most significant are the oxysterol binding proteins (OSBP) and VapA (similar to that seen in Chlamydia). The authors show differential association of these proteins with either the LCV or presumably the ER associated with the LCV. Using a linear scale over 8 days, they show that mutations in some of the MCS reduce yields in two of the OSPB knockout mutants and the growth rate of the vap mutant is slowed but ultimate yield is increased. Using some nice microscopy techniques, they measure LCV size, and the osbK mutant appears particular small relative to other strains, whereas the osbH mutant generates large vacuoles. This doesn't necessarily correlate with the PI4P quantities on the vacuoles (which is higher in all of them), but I am not totally sure how this is measured, and whether is it PI4P/pixel or PI4P/LCV. In all cases, this was reduced by Sac1 mutation. Surprisingly, even though there was uniform increase in PI4P in each of the mutants, loss of PI4P only affects localization of some of the proteins. Finally, in what seems to be a peripherally related experiment, the authors show that a pair of Legionella translocated effectors are required to maintain PI4P levels, although it is not clear how this is related to the other data in the manuscript.

    It is not clear from the manuscript if the authors are just cataloging things or trying to test a hypothesis. This is an extremely difficult manuscript to read and reconstruct what the authors showed. I really think that the only people who will understand what is written are people who are familiar with the work in Chlamydia starting in 2011 in Engel's and Derre's laboratories, which clearly showed that MCS and most specifically Vap/OSBPs are involved in vacuole expansion. If the authors could rewrite the manuscript along these lines, perhaps comparing their data to the Chlamydia data it would help a lot. Otherwise, I don't think anyone else will understand why they are focusing on these things. I don't recommend new experiments (although re-analyzing data is necessary), but the manuscript has to be taken apart and claims removed, and data be interpreted properly. Otherwise, the manuscript seems like just a clearing house for data.

    Response: Thank you for the concise summary of our data and pointing out the need to restructure the manuscript and to clearly outline the hypotheses underlying the study. According to the reviewer’s suggestions, we have now re-structured the manuscript. In the revised manuscript the story unfolds from the observation that the ER tightly associates with (isolated) LCVs, and the proteomics approach is used as a validation of the presence of MCS proteins at the LCV-ER MCS.

    As suggested by the reviewer, we now highlight the seminal work on Chlamydia by the Engel and Derré laboratories not in the Discussion section (as in the original version of the manuscript) but already in the Introduction section (l. 142-148). We believe that it makes a stronger case to start out an analysis of LCV-ER MCS with a Legionella-specific cell biological finding (LCV-ER association) and an unbiased proteomics approach, as compared to a more derivative and defensive approach starting out with what is known about Chlamydia.

    The reviewer’s comment “This is an extremely difficult manuscript to read” appears overly harsh and conflicts with the positive evaluation of Reviewer #2 and Reviewer #3. Finally, we respectfully disagree with the reviewer’s statement that experiments characterizing L. pneumophila effectors implicated in the formation and function of LCV-ER MCS are peripheral. These experiments significantly contribute to a mechanistic understanding of how L. pneumophila forms and exploits LCV-ER MCS, and they are central for studies on pathogen-host interactions. The studies are analogous to the work on Chlamydia effectors by the Engel and Derré laboratories, but the mode of action of Legionella and Chlamydia effectors is obviously different. Another important distinction of our work to the studies on Chlamydia is the use of the genetically tractable amoeba, D. discoideum, which allows an analysis of LCV-ER MCS by fluorescence microscopy at high spatial resolution.

    Specific comments

    The problems start with the first figure, in which the authors state that almost half the *D. discoideum *proteome is LCV-associated. I doubt that this is correct, and they should base this on some selective criterion. Furthermore in Fig. 1A, they show Venn diagrams for how they whittled this down, but the Supplemental Dataset gives us no clue on how this was done. I can only sit down myself with the dataset and try to figure that out, but that is an unreasonable expectation for the reader. The dataset provided should have a series of sheets, describing how the large protein set was whittled down and how they were sorted, so the reader can evaluate how robust the final results were. To me (at least), if they said: "look we got this surprising result that suggests MCS are involved in promoting LCV formation, and although this is well recognized in Chlamydia but poorly recognized in Legionella", that would be satisfactory to me.

    Response: According to the reviewer’s suggestions, we have now thoroughly re-structured the manuscript. In the revised manuscript the story unfolds from the observation that the ER tightly associates with LCVs in infected cells and with isolated LCVs. The proteomics approach is now used as a validation of the presence of MCS proteins at the LCV-ER MCS and relegated to the Supplementary Information section (former Fig. 1, now Fig. S3).

    For the proteomics analysis, all protein identifications have been filtered for robustness applying a constant FDR (false discovery rates) of protein and PSM (peptide spectrum match) of 0.01, which is a commonly accepted threshold in the field. Moreover, two identified unique peptides were required for protein identification. The parallel application of both filter criteria results in very robust and reliable data sets. This is outlined in the Material and Methods section (l. 683-693).

    In the data set of LCV-associated proteins, 2,434 D. discoideum proteins have been identified (Table S1). This is 18.5% of the total of 13,126 predicted D. discoideum proteins (UniprotKB) and considerably less than “almost half the *D. discoideum *proteome”, as stated by the reviewer. Moreover, 1,224 L. pneumophila proteins have been identified (among 3,024 predicted L. pneumophila proteins in the database). This is a reasonable number of proteins identified from an intracellular vacuolar pathogen, given the LCV isolation and proteomics methods applied. We now outline these findings more extensively in the Results section (l. 207-213). Moreover, to render Table S1 more reader-friendly, we added to the datasheet “All data” the datasheets “Dictyostelium”, “Legionella” and “Info”.

    The Venn diagram in __Fig. S3A __(previously Fig. 1A) does not show a subset of proteins “whittled down” from the entire proteomes, but simply summarizes LCV-associated proteins, which were either identified exclusively in the parental strain Ax3 but not in the Δsey1 mutant strain, or only in Δsey1 but not in Ax3, thus identifying possible candidates relevant for the LCV-ER MCS. This information is now outlined more clearly in the text (l. 238-241). Moreover, we now explicitly define in the Material and Methods section (l. 697-704) the “on” and “off” proteins shown in Fig. S3A.

    The overall rational for the comparative proteomics approach was our previous finding that compared to the D. discoideum parental strain Ax3, the Δsey1 mutant strain accumulates less ER around LCVs (PMID: 28835546, 33583106). This finding suggests that formation of the LCV-ER MCS might be compromised in the Δsey1 mutant strain. This hypothesis is now outlined at the beginning of the Results paragraph (l. 204-207).

    I am clueless regarding how Fig. 6 fits with the rest of the manuscript. If this is about MCS, there is no demonstration these effectors are directly involved in MCS other than the somewhat diffuse argument that there is some correlative connection to PI4P levels, that I am not particularly convinced by.

    Response: The PtdIns(4)P gradient between two different cellular membranes is an intrinsic feature of MCS. To date, a quantification of PtdIns(4)P levels on LCVs in response to the presence or absence of specific L. pneumophila effectors is lacking. Accordingly, we opted for quantifying the PtdIns(4)P levels on LCVs in presence and absence of an L. pneumophila effector putatively generating PtdIns(4)P on LCVs, the phosphoinositide 4-kinase LepB, or titrating PtdIns(4)P on LCVs, the PtdIns(4)P-binding ubiquitin ligase SidC. To address the concerns of Reviewer 1 and Reviewer 3 (see below), we now outline in detail the rational to assess the role of LepB and SidC for MCS function (l. 385-387). Importantly, we now also provide data that at LCV-ER MCS PtdIns(4)P/cholesterol lipid exchange is functionally important (new Fig. 6 and Fig. S10). In the revised version of the manuscript, this new data is preceding the experiments with the L. pneumophila effectors, which should render our choice of effectors more comprehensible to the reader and increase the flow of the manuscript.

    Line 146 and associated paragraph. We don't need a catalog of proteins in narrative. There is more detail in the narrative than there is in the tables and figures, which would be a more appropriate way to present the data.

    Response: As suggested by the reviewer, we summarized the LCV-associated D. discoideum proteins and considerably reduced the list in the text (l. 214-230).

    Line 186. There is nothing wrong with pursuing MCS based on the idea that this was seen before with Chlamydia and you wanted to test if this was a previously unappreciated aspect of Legionella biology. I don't see the rationale based on the proteomics, partly because I don't understand how the proteomics dataset was parsed.

    Response: As suggested by the reviewer, we thoroughly re-structured the manuscript and now highlight the seminal work on Chlamydia by the Engel and Derré laboratories already in the Introduction section (not in the Discussion section as in the original version of the manuscript). We believe that it makes a stronger case to start out an analysis of LCV-ER MCS with a Legionella-specific cell biological finding (LCV-ER association) and an unbiased proteomics approach, as compared to a more derivative and defensive approach starting out with what is known about Chlamydia.

    Figure 3: These growth curves are super-weird. I am not used to looking at 8 days of logarithmic growth in a linear scale and seeing no (apparent) growth for 4 days. Considering all the microscopy data are performed in the first 18 hrs of infection, it’s hard to see how this is related to data at 8 days post infection. If this were plotted in logarithmic scale, as microbiologists are used to doing, then perhaps we could see a connection. Also, in some cases, it might be helpful to calculate a growth rate, because it’s possible the author may now see some effects by comparing logarithmic growth rates.

    Response: We have been characterizing growth of L. pneumophila in D. discoideum in several studies using growth curves with RFU vs. time plotted in linear scale (e.g., Finsel et al., 2013, Cell Host Microbe 14:38; Rothmeier et al., 2013, PloS Pathog 9: e1003598; Swart et al., 2020, mBio 11: e00405-20). The D. discoideum-L. pneumophila infection model is peculiar, since the amoebae do not survive temperatures beyond 26 degC. This is substantially below the optimal growth temperature of L. pneumophila (35-40 degC). This means that - due to the many genetic tools available - D. discoideum is an excellent model to investigate cell biological aspects of the infection at early time points (ca. 1-18 h p.i.), but the amoebae are not an optimal system to quantify (several rounds) of intracellular growth.

    Figure 2: The images don't necessarily show what the bar graphs show. In particular, look at Osp8. That image doesn't make sense to me.

    Response: The individual channels of the merged images in Fig. 1 (formerly Fig. 2) are shown in Fig. S2. By looking at the individual channels, it becomes clear that OSBP8-GFP co-localizes with calnexin-mCherry (overlapping signals), but not with P4C-mCherry or AmtA-mCherry (adjacent signals). Co-localization was quantified in a non-biased manner by Pearson’s correlation coefficient. To further visualize co-localization, we now also provide fluorescence intensity profiles for all confocal micrographs (amended Fig. 1).

    In summary, I think the authors hit on something that is probably important for Legionella biology, but it’s not clear what they want to show. They are very invested in connecting everything to PI4P levels, which may or may not be correct, but it seems to me that perhaps taking more care in showing the importance of the Vap/OSPB nexus in supporting Legionella growth should be the first priority.

    Response: Given the importance of the PtdIns(4)P gradient for lipid exchange at MCS, we believe it is justified to put considerable emphasis on this lipid. To further substantiate a functional role of PtdIns(4)P at LCV-ER MCS, we now also show that an increase in PtdIns(4)P at the LCV correlates with a decrease of cholesterol (new Fig. 6 and Fig. S10). The inverse correlation of these two lipids is in agreement with the notion that cholesterol is a counter lipid of PtdIns(4)P at LCV-ER MCS.

    It is not clear from the manuscript if the authors are just cataloging things or trying to test a hypothesis.

    Response: In the revised version of the manuscript, we put forward several specific hypotheses, which we then tested in our study (l. 152-155).

    If I understand Fig. 1, only one of the candidates (VapA) was verified as being more enriched in WT relative to atlastin mutants. This argues even more strongly that the authors have to describe their criteria for choosing these candidates.

    Response: As outlined above (specific point 1), we have now re-structured the manuscript according to the reviewer’s suggestions. In the revised manuscript the story unfolds from the observation that the ER tightly associates with LCVs in infected cells and with isolated LCVs. The proteomics approach is now used as a validation of the presence of MCS proteins at the LCV-ER MCS and relegated to the Supplementary Information section (formerly Fig. 1, now Fig. S3). We consider the proteomics approach a powerful hypothesis generator, and the experimental identification of several MCS proteins by proteomics validated the cell biological and bioinformatics insights.

    Reviewer #1 (Significance (Required)):

    As stated above, the manuscript can't decide if it’s about MCS or PI4P, and I would argue strongly that the emphasis on PI4P detracts from the manuscript, as well as its inability to draw connection to previous work that is likely to be important.

    Response: We respectfully disagree with the reviewer on this important point and hold that proteins as well as lipids are crucial functional determinants of MCS. The PtdIns(4)P gradient is a pivotal process for lipid exchange at MCS. Therefore, we believe it is justified to put considerable emphasis on this lipid. In the Introduction section, we now specify several hypotheses on the localization and function of lipids and proteins at LCV-ER MCS (l. 152-155). Moreover, we now also refer to the previous work on Chlamydia MCS in the Introduction section (l. 142-148).

    Reviewer #2 (Evidence, reproducibility and clarity):

    Summary of paper and major findings

    Membrane contact sites (MCS) are locations where two membranes are in close proximity (10-80nm). MCS have a defined protein composition which tether the membranes together and function in small molecule and lipid exchange. Typically, MCS proteins contain structural (e.g., tethers) and functional (e.g., exchange lipids) proteins, in addition to proteins which regulate the structure and function of the MCS. In this manuscript, Vormittag et al describe protein components of MCS between the Legionella-containing vacuole (LCV) and the host endoplasmic reticulum (ER) in the amoeba Dictyostelium. Proteomics of isolated LCVs followed by microscopy analysis identified several proteins which localize to either the LCV-associated ER (OSBP8), the LCV (OSBP11), or both (VAP and Sac1). The mammalian homologs of these proteins have been shown to play important roles in ER MCS, with VAP serving a structural role, Sac1 a PI(4P) phosphatase regulating PI(4)P levels, and OSBP8 and OSBP11 lipid transferring proteins. Given the importance of PI(4)P in formation and maintenance of the Legionella-containing vacuole, the authors used dicty mutants to determine the importance of these proteins in bacterial growth, LCV size, and PI(4)P levels on the LCV. While VAP and OSBP11 appear to promote Legionella infection, OSBP8 appears to restriction infection, although all identified MCS components appear to play a role in decreasing PI(4P) shortly after infection. Finally, VAP and OSBP8 localization to the LCV is PI(4)P-dependent. Overall, the authors conclude that these MCS components play a role in modulating PI(4)P levels on the LCV.

    Overall, this is an interesting study further exploring the role of PI(4)P in LCV-ER interactions, and how PI(4)P levels are regulated. The figures are clearly presented, there is an impressive amount of data, and rigor appears to be strong with appropriate replicates and statistical analysis. The phenotypes are often mild, but the authors are careful to not overinterpret the data. While this is an interesting study, additional experiments are necessary to support the overall model and the text needs to put the findings into the larger context.

    Response: We would like to thank the reviewer for this positive and constructive assessment. We performed and planned additional experiments to further strengthen the study and support our model.

    Major comments

    1. MCS contain protein complexes or a group of proteins, but the proteins here are studied in isolation and do not support the model shown in Figure 7. Co-localization studies of the putative LCV-ER MCS proteins are critical, especially given that the authors hypothesize the proteins are working together to modulate PI(4)P levels.

    Response: To further explore the possible interactions between Vap and OSBP proteins, we plan co-localization experiments using *D. discoideum *strains producing mCherry-Vap and either OSBP8-GFP or GFP-OSBP11, as outlined above (Section 2, new__ Fig. 2__ and Fig. S4).

    Moreover, we included additional data on PtdIns(4)P/cholesterol lipid exchange (Fig. 6 and Fig. S10), which have been incorporated into the model (amended Fig. 8). Based on the available data, we do not postulate direct interactions between Vap and OSBP proteins. The previous model, which now has been amended, might have been misleading in that respect.

    1. The phenotypes are relatively mild, suggesting functional redundancy. Double knockouts, particularly in VAP and OSBP11, may generate a stronger phenotype that better supports the hypothesis and demonstrate the importance during infection.

    Response: Thank you for this interesting suggestion. Please see Section 4 below for our arguments, why we believe that this intriguing approach is beyond the scope of the current study.

    1. The timing of PI(4)P and MCS protein localization during infection is critical to understanding how MCS might be functioning. Based on Figure 6C, PI(4)P levels decrease on the LCV during infection, but this is not fully explained in the context of what's known in the literature and what is observed the previous figures. How does localization of different MCS components change during infection, and does this correlate with the changes in growth or LCV size? A better description in the Introduction on LCV-associated PI(4)P levels would be beneficial in orienting the reader to why PI(4)P levels are modulated.

    Response: As suggested by the reviewer, we added to the Introduction section more detail about the kinetics of PtdIns(4)P accumulation on LCVs (l. 65-71), and we discuss the limited spatial resolution of the IFC approach (formerly Fig. 6C, now Fig. 7C; l. 407-408). Importantly, we also provide new data showing that within 2 h p.i. an increase in PtdIns(4)P at the LCV coincides with a decrease of cholesterol (new Fig. 6 and Fig. S10). The new data is put into this context in the Discussion section (l. 449-454).

    1. OSW-1 has other targets besides OSBPs, and depleting Sac1 and Arf1 in A549 cells is not specifically targeting the MCS, as these proteins have other functions. The data in mammalian cells is not convincing and should be removed.

    Response: As suggested by the reviewer, we removed the data on depleting Sac1 in A549 cells (Fig. 3D, and Fig. S6BC). We propose to leave the pharmacological data on inhibition of L. pneumophila replication by OSW-1 in the manuscript, but to clearly point out that OSW-1 has other targets besides OSBPs (l. 297-299).

    Minor comments

    1. Figure 2 is missing details on number of experiments/replicates and statistical analysis.

    Response: Thank you for having noted this oversight. The number of independent experiments and statistical analysis have now been added to Fig. 1 (formerly Fig. 2) (l. 1009-1010).

    1. Can the authors hypothesize why VAP promotes growth early during infection, but appears to restrict growth at later timepoints (Figure 3A)?

    Response: Thank you for raising this intriguing point. The opposite effects on growth of Vap at early and later timepoints during infection might be explained by interactions with antagonistic OSBPs. Vap likely co-localizes with OSBP8 as well as with OSBP11 on the limiting LCV membrane or the ER, respectively (experiment to be performed; Fig. 2 and__ Fig. S4__). The absence of OSBP8 (ΔosbH) or OSBP11 (ΔosbK) causes larger or smaller LCVs, and increased or reduced intracellular replication of L. pneumophila, respectively. Thus, OSBP8 seems to restrict and OSBP 11 seems to promote intracellular replication. Accordingly, if Vap affects or interacts with OSBP11 early and with OSBP8 later during infection, opposite effects on growth of Vap might be explained. These reflections are now outlined in the Discussion section (l. 431-441).

    1. There is a large amount of data, which makes it difficult at times to follow. I suggest adding additional information to table 1, including LCV size and whether or not the protein's localization is PI(4)P-dependent.

    Response: Thank you for this suggestion. As proposed by the reviewer, we added the additional information to Table 1 (PtdIns(4)P-dependency of protein localization, LCV size).

    Reviewer #2 (Significance (Required)):

    Membrane contact sites during bacterial infection are a growing area of research. In Legionella, several papers point to the presence of MCS. Further, PI(4)P is known to be an important component on the LCV. This paper shows that MCS protein members are important in modulating LCV PI(4)P levels. The model as presented is not completely supported by the data as co-localization experiments are needed, along with more detailed analysis of how PI(4)P levels change over infection and the role of these MCS proteins in that process. This study will be of interest to those studying Legionella and other vacuolar pathogens. Area of expertise is on membrane contact sites and lipid biology.

    Response: Thank you very much for the overall positive and constructive evaluation.

    Reviewer #3 (Evidence, reproducibility and clarity):

    The authors perform proteomic analysis of Legionella-containing vacuoles. The observe association of membrane contact site (MCS) proteins including VAP, OSBPs, and Sac1. Functional data indicates that these proteins contribute to PI4P levels on LCVs and their ability to acquire lipid from the ER to enable LCV expansion/stability. Overall, the paper is an important contribution to the field and builds upon a growing appreciation for MCS in establishment of intracellular niches by microbial pathogens. I have only minor comments for the authors consideration.

    Response: We would like to thank the reviewer for this enthusiastic assessment.

    Minor comments:

    -line 145, "This approach revealed 3658 host or bacterial proteins identified on LCVs...". This number seems high... how does it compare to prior proteomic studies of pathogen-containing vacuoles?

    Response: As outlined above (reviewer 1, point 1), we have now changed the text (l. 207-213): “This approach revealed 2,434 LCV-associated D. discoideum proteins (Table S1), of a total of 13,126 predicted D. discoideum proteins (UniprotKB). Moreover, 1,224 L. pneumophila proteins were identified (among 3,024 predicted L. pneumophila proteins), which is a reasonable number of proteins identified from an intracellular bacterial pathogen within its vacuole with the proteomics methods applied (Herweg* et al, 2015; Schmölders et al.*, 2017).”

    • line 160. Can the authors comment on why mitochondrial proteins are observed in their proteomic analysis? Are these non-specific background signals or reflecting relevant organelle contact?

    Response: The dynamics of mitochondrial interactions with LCVs and the effects of L. pneumophila infection on mitochondrial functions have been thoroughly analyzed (PMID: 28867389). This seminal work is now cited in the text (l. 227-230).

    • line 268. It is reported that LCVs are smaller with MCS disruption at 2 and 8 h p,i.. Does this also lead to instability or rupture of LCVs? And related to this why would LCVs be bigger at 16h with MCS disruption?

    Response: MCS components affect LCV size positively or negatively. E.g., the absence of OSBP8 (ΔosbH) or OSBP11 (ΔosbK) causes larger or smaller LCVs, and increased or reduced intracellular replication of L. pneumophila, respectively. However, as outlined in the Discussion section (l. 442-454), we believe that the relatively small size likely reflects a structural remodeling of the pathogen vacuole rather than a substantial LCV expansion. LCV rupture takes place only very late in the infection cycle (beyond 48 h) and is followed by lysis of the host amoeba (PMID: 34314090).

    • lines 288 and 299 "data not shown" this data should be included in a supplemental figure.

    Response: The data on the localization of GFP-Sac1 and GFP-Sac1_ΔTMD are included in the Figs. 1A,__ 4A__,__ 5AD__,__ S2A__,__ S7A__, and__ S9__ (l. 328, l. 339).

    • line 327. The authors choose to focus on the role of LepB and SidC in MCS modulation. The rationale for choosing these two amongst the ca 330 effectors was not given. Were other effectors also examined?

    Response: LepB and SidC were chosen due to their activities producing or titrating PtdIns(4)P, respectively, and their LCV localization. This rational is now given in the text (l. 385-387). No other effectors were examined up to this point.

    Reviewer #3 (Significance (Required)):

    Comprehensive LCV proteomics of interest to field of cellular microbiology. Studies of MCS broadly relevant to cell biologists.

    Response: Thank you very much for the overall very positive evaluation.

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

    Reviewer #2

    Major comment

    1. The phenotypes are relatively mild, suggesting functional redundancy. Double knockouts, particularly in VAP and OSBP11, may generate a stronger phenotype that better supports the hypothesis and demonstrate the importance during infection.

    Response: Thank you for raising the important question of functional redundancy. We now outline this concept in the Discussion section (l. 427-429). A further analysis of the genetic and biochemical relationship between Vap and OSBP11 or OSBP8 are without doubt some of the most interesting aspects of further studies on the topic of LCV-ER MCS.

    The construction of a D. discoideum double mutant strain is time consuming and usually takes 1-2 months. Provided that a Vap/OSBP11 double deletion mutant strain is viable and can be generated, it takes another 1-2 months to thoroughly characterize the strain regarding intracellular replication of L. pneumophila (Fig. 3), LCV size (Fig. 4), and PtdIns(4)P score (Fig. 5). Moreover, there is already a large amount of data in the paper (to quote Reviewer #2), and therefore, adding new data might makes it even harder to follow the story and focus on the key points. Finally, we believe that the planned colocalization experiments (Reviewer #2, point 1) and the new data on lipid exchange kinetics (new Fig. 6 and Fig. S10) fit the current story more coherently, and thus, are more straightforward and informative than the generation and characterization of double mutant strains. For these reasons, we believe that the generation and characterization of D. discoideum double mutant strains is beyond the scope of the current study.

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    Referee #3

    Evidence, reproducibility and clarity

    The authors perform proteomic analysis of Legionella containing vacuoles. The observe association of membrane contact site (MCS) proteins including VAP, OSBPs, and Sac1. Functional data indicates that these proteins contribute to PI4P levels on LCVs and their ability to acquire lipid from the ER to enable LCV expansion/stability. Overall the paper is an important contribution to the field and builds upon a growing appreciation for MCS in establishment of intracellular niches by microbial pathogens. I have only minor comments for the authors consideration.

    Minor comments:

    • line 145, "This approach revealed 3658 host or bacterial proteins identified on LCVs...". This number seems high... how does it compare to prior proteomic studies of pathogen-containing vacuoles?
    • line 160. Can the authors comment on why mitochondrial proteins are observed in their proteomic analysis? Are these non-specific background signals or reflecting relevant organelle contact?
    • line 268. It is reported that LCVs are smaller with MCS disruption at 2 and 8 h p,i.. Does this also lead to instability or rupture of LCVs? And related to this why would LCVs be bigger at 16h with MCS disruption?
    • lines 288 and 299 "data not shown" this data should be included in a supplemental figure
    • line 327. The authors choose to focus on the role of LepB and SidC in MCS modulation. The rationale for choosing these two amongst the ca 330 effectors was not given. Were other effectors also examined?

    Significance

    Comprehensive LCV proteomics of interest to field of cellular microbiology. Studies of MCS broadly relevant to cell biologists.

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    Referee #2

    Evidence, reproducibility and clarity

    Summary of paper and major findings

    Membrane contact sites (MCS) are locations where two membranes are in close proximity (10-80nm). MCS have a defined protein composition which tether the membranes together and function in small molecule and lipid exchange. Typically, MCS proteins contain structural (e.g., tethers) and functional (e.g., exchange lipids) proteins, in addition to proteins which regulate the structure and function of the MCS. In this manuscript, Vormittag et al describe protein components of MCS between the Legionella containing vacuole (LCV) and the host endoplasmic reticulum (ER) in the amoeba Dictyostelium. Proteomics of isolated LCVs followed by microscopy analysis identified several proteins which localize to either the LCV-associated ER (OSBP8), the LCV (OSBP11), or both (VAP and Sac1). The mammalian homologs of these proteins have been shown to play important roles in ER MCS, with VAP serving a structural role, Sac1 a PI(4P) phosphatase regulating PI(4)P levels, and OSBP8 and OSBP11 lipid transferring proteins. Given the importance of PI(4)P in formation and maintenance of the Legionella Containing Vacuole, the authors used dicty mutants to determine the importance of these proteins in bacterial growth, LCV size, and PI(4)P levels on the LCV. While VAP and OSBP11 appear to promote Legionella infection, OSBP8 appears to restriction infection, although all identified MCS components appear to play a role in decreasing PI(4P) shortly after infection. Finally, VAP and OSBP8 localization to the LCV is PI(4)P-dependent. Overall, the authors conclude that these MCS components play a role in modulating PI(4)P levels on the LCV.

    Overall, this is an interesting study further exploring the role of PI(4)P in LCV-ER interactions, and how PI(4)P levels are regulated. The figures are clearly presented, there is an impressive amount of data, and rigor appears to be strong with appropriate replicates and statistical analysis. The phenotypes are often mild, but the authors are careful to not overinterpret the data. While this is an interesting study, additional experiments are necessary to support the overall model and the text needs to put the findings into the larger context.

    Major comments

    1. MCS contain protein complexes or a group of proteins, but the proteins here are studied in isolation and do not support the model shown in Figure 7. Co-localization studies of the putative LCV-ER MCS proteins are critical, especially given that the authors hypothesize the proteins are working together to modulate PI(4)P levels.
    2. The phenotypes are relatively mild, suggesting functional redundancy. Double knockouts, particularly in VAP and OSBP11, may generate a stronger phenotype that better supports the hypothesis and demonstrate the importance during infection.
    3. The timing of PI(4)P and MCS protein localization during infection is critical to understanding how MCS might be functioning. Based on Figure 6C, PI(4)P levels decrease on the LCV during infection, but this is not fully explained in the context of what's known in the literature and what is observed the previous figures. How does localization of different MCS components change during infection, and does this correlate with the changes in growth or LCV size? A better description in the Introduction on LCV-associated PI(4)P levels would be beneficial in orienting the reader to why PI(4)P levels are modulated.
    4. OSW-7 has other targets besides OSBPs, and depleting Sac1 and Arf1 in A549 cells is not specifically targeting the MCS, as these proteins have other functions. The data in mammalian cells is not convincing and should be removed.

    Minor comments

    1. Figure 2 is missing details on number of experiments/replicates and statistical analysis.
    2. Can the authors hypothesize why VAP promotes growth early during infection, but appears to restrict growth at later timepoints (Figure 3A)?
    3. There is a large amount of data, which makes it difficult at times to follow. I suggest adding additional information to table 1, including LCV size and whether or not the protein's localization is PI(4)P-dependent.

    Significance

    Membrane contact sites during bacterial infection are a growing area of research. In Legionella, several papers point to the presence of MCS. Further, PI(4)P is known to be an important component on the LCV. This paper shows that MCS protein members are important in modulating LCV PI(4)P levels. The model as presented is not completely supported by the data as co-localization experiments are needed, along with more detailed analysis of how PI(4)P levels change over infection and the role of these MCS proteins in that process. This study will be of interest to those studying Legionella and other vacuolar pathogens.

    Area of expertise is on membrane contact sites and lipid biology.

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    Referee #1

    Evidence, reproducibility and clarity

    In the manuscript by Vormittag, et al., the authors perform proteomics identification of proteins associated with the Legionella-containing vacuole (LCV) in the model amoeba Dictyostelium discoideum comparing WT to atlastin knockout mutants. The authors find approximately half the D. discoideum proteome associated with the LCV, but there was enrichment of some proteins on the WT relative to the mutant. They focus on proteins involved in forming membrane contact sites (MCS) that previously were shown to be important for expansion of the Chlamydia-containing vacuole. Most significant are the oxysterol binding proteins (OSBP) and VapA (similar to that seen in Chlamydia). The authors show differential association of these proteins with either the LCV or presumably the ER associated with the LCV. Using a linear scale over 8days, they show that mutations in some of the MCS reduce yields in two of the OSPB knockout mutants and the growth rate of the vap mutant is slowed but ultimate yield is increased. Using some nice microscopy techniques, they measure LCV size, and the osbK mutant appears particular small relative to other strains, whereas the osbH mutant generates large vacuoles. This doesn't necessarily correlate with the PI4P quantities on the vacuoles (which is higher in all of them), but I am not totally sure how this is measured, and whether is it PI4P/pixel or PI4P/LCV. In all cases, this was reduces by Sac1 mutation. Surprisingly, even though there was uniform increase in PI4P in each of the mutants, loss of PI4P only affects localization of some of the proteins. Finally, in what seems to be a peripherally related experiment, the authors show that a pair of Legionella translocated effectors are required to maintain PIF4P levels, although it is not clear how this is related to the other data in the manuscript.

    It is not clear from the manuscript if the authors are just cataloging things or trying to test a hypothesis. This is an extremely difficult manuscript to read and reconstruct what the authors showed. I really think that the only people who will understand what is written are people who are familiar with the work in Chlamydia starting in 2011 in Engel's and Derre's laboratories, which clearly showed that MCS and most specifically Vap/OSBPs are involved in vacuole expansion. If the authors could rewrite the manuscript along these lines, perhaps comparing their data to the Chlamydia data it would help a log. Otherwise, I don't think anyone else will understand why they are focusing on these things. I don't recommend new experiments (although re-analyzing data is necessary), but the manuscript has to be taken apart and claims removed, and data be interpreted properly. Otherwise, the manuscript seems like just a clearing house for data.

    1. The problems start with the first figure, in which the authors state that almost half the D. discoideum proteome is LCV-associated. I doubt that this is correct, and they should base this on some selective criterion. Furthermore in Fig. 1A, they show Venn diagrams for how they whittled this down, but the Supplemental Dataset gives us no clue on how this was done. I can only sit down myself with the dataset and try to figure that out, but that is an unreasonable expectation for the reader. The dataset provided should have a series of sheets, describing how the large protein set was whittled down and how they were sorted, so the reader can evaluate how robust the final results were. To me (at least), if they said: "look we got this surprising result that suggests MCS are involved in promoting LCV formation, and although this is well recognized in Chlamydia but poorly recognized in Legionella", that would be satisfactory to me.
    2. I am clueless regarding how Fig. 6 fits with the rest of the manuscript. If this is about MCS, there is no demonstration these effectors are directly involved in MCS other than the somewhat diffuse argument that there is some correlative connection to PI4P levels, that I am not particularly convinced by.
    3. Lin 146 and associated paragraph. We don't need a catalog of proteins in narrative. There is more detail in the narrative than there is in the tables and figures, which would be a more appropriate way to present the data.
    4. Line 186. There is nothing wrong with pursuing MCS based on the idea that this was seen before with Chlamydia and you wanted to test if this was a previously unappreciated aspect of Legionella biology. I don't see the rationale based on the proteomics, partly because I don't understand how the proteomics dataset was parsed.
    5. Figure 3: These growth curves are super-weird. I am not used to looking at 8 days of logarithmic growth in a linear scale, and seeing no (apparent) growth for 4 days. Considering all the microscopy data are performed in the first 18 hrs of infection, its hard to see how this is related to data at 8 days post infection. If this were plotted in logarithmic scale, as microbiologists are used to doing, then perhaps we could see a connection. Also, in some cases, it might be helpful to calculate a growth rate, because its possible the author may now see some effects by comparing logarithmic growth rates.
    6. Figure 2: The images don't necessarily show what the bar graphs show. In particular, look at Osp8. That image doesn't make sense to me.

    In summary, I think the authors hit on something that is probably important for Legionella biology, but its not clear what they want to show. They are very invested in connecting everything to PI4P levels, which may or may not be correct, but it seems to me that perhaps taking more care in showing the importance of the Vap/OSPB nexus in supporting Legionella growth should be the first priority.

    It is not clear from the manuscript if the authors are just cataloging things or trying to test a hypothesis.

    If I understand Fig. 1, only one of the candidates (VapA) was verified as being more enriched in WT relative to atlastin mutants. This argues even more strongly that the authors have to describe their criteria for choosing these candidates

    Significance

    As stated above, the mansucript can't decide if its about MCS or PI4P, and I would argue strongly that the emphasis on PI4P detracts from the manuscript, as well as its inability to draw connection to previous work that is likely to be important.

  6. Version published to 10.1101/2022.06.17.496549v2 on bioRxiv
  7. Version published to 10.1101/2022.06.17.496549v1 on bioRxiv