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Introduction

Weber et al., 2025 present “Arabidopsis HYPERSENSITIVE INDUCED REACTION 2 affects plasma membrane receptor pathways and organization”, in which they describe a role of Hypersensitive Induced Reaction 2 (HIR2) in organising large structures in the cell membrane. They draw upon several interaction experiments, mutant studies, transcriptomics, and single-particle tracking photoactivated localisation microscopy (sptPALM) to demonstrate HIR2 interacting with key cell membrane proteins and highlight its role in normal plant development and cell membrane organisation.

Through sptPALM they investigate the mobility of HIR2 and potential interactors, involved in plant immunity or development, such as receptor kinase BAK1, and conduct amino acid substitutions to explore the cell membrane localisation of HIR2. Finally, they provide a structural model of HIR2 organisation in the cell membrane using AlphaFold.

Taken altogether, these experiments create a convincing narrative of the role of HIR2 in plant health and development. This research represents a valuable contribution towards understanding organisation of cell membrane proteins, and their role in biotic stress response. We commend the authors for the wide range of experimental methods they drew upon in their analysis.

In this PREreview, we make a small number of suggestions to help improve the clarity of the published work, and strengthen the results presented. We hope the authors find these constructive.

Major issues

Throughout this paper, we have concerns about the negative controls used in biochemical assays and protein localisation experiments.

In several co-immunoprecipitation experiments (co-IPs), a blank lane (infiltration of p19 alone) is used as a negative control, which serves as a useful technical control against sample cross-contamination but does not offer much in terms of data interpretation (Examples: Fig. 1A, 1C, 1E). Further, we’re unconvinced of the suitability of p19 as a negative control. It’s not described throughout the paper why it is appropriate as a negative control - indeed, it is only mentioned once throughout the entire manuscript. Was it used elsewhere? A more valuable negative control would be to test interaction between HIR2 and a protein not expected to interact with it. The same goes for confocal microscopy experiments and BN-PAGES throughout the manuscript that often lacked controls altogether.

On this note, where the Introduction states “[HIR2] can interact with all tested membrane proteins” (Line 68 -70), we believe more precise phrasing (i.e. specifying the exact proteins you are referring to in parentheses) would be more appropriate. Moreover, the above statement is even more reason to include a powerful negative control for protein interaction experiments, otherwise the reader might assume that HIR2 is a sticky protein that appears to bind anything that is screened against it, rather than binding to the candidates tested, due to its function in immunity/development/membrane organisation. You might want to consider a protein that is not membrane-associated as a negative control.  

Previous research has linked HIR2, and several other proteins studied in this project, with plant immunity and cell death. However, the role of immunity in the membrane organisation is only briefly explored in this paper, as ROS assays and largely non-significant colony counts. Why only hir2-2 had increased colony counts is unclear. Therefore, we question the suitability of the emphasis on HIR2’s role in plant immunity in the abstract.

Minor issues

• Occasionally, in-line figure references don’t refer to the correct figure.

• CSA1 is mentioned in the last line of the Introduction, but not mentioned again.

• Where multiple comparisons are performed against the same control, an appropriate multiple comparison’s statistical test should have been used rather than a t-test (e.g. Fig2, Fig3). It would be nice to also justify the use of non-parametric tests (e.g. Fig 4).

Main Figures

Figure 1

We appreciate the use of multiple methods to demonstrate interactions between HIR2 and other plasma membrane proteins. However, we had some issues with the use of negative controls (see major comments feedback). Moreover, it is unclear why only BIR3 is shown in Figure 1, and BIR2 only shown in the supplementary data, especially as BIR2 is mentioned in the abstract. In a similar vein, why are confocal images of BAK1 only shown in the supplementary figures?

In b), d) and f), HIR2-GFP, BIR3-RFP, BRI1-RFP and CERK1-mCherry are overexpressed across the cell membrane; it’s possible the interaction between these proteins is a result of their abundance, rather than a real interaction. We would recommend optimising protein expression (OD₆₀₀); then achieving precise overlap of HIR2 and interacting proteins on the plasmodesmata would provide convincing evidence of interaction.

Furthermore, why is CERK1 tagged with mCherry, whereas the other acceptors are tagged with RFP?

Figure 2

We are curious about the extreme growth defect observed in hir2-5. It doesn’t seem to conform with the data represented in the box plots. Additionally, we would like to see a boxplot for root length.

Figure 3

With regards to the transcriptomics analysis, in Line 400, it is described that “bioinformatic analysis was performed”. We believe a far more in-depth description is required.

This figure would have been easier to understand had all the plots been labelled with a heading – this is particularly true of g), h), and i).

Ultimately, we do not believe this figure is a compelling addition to the narrative of the paper – particularly f-i). We would have preferred more standard representation of DEGs – such as volcano plots, indicating statistical significance. Transcripts quantified for each mutant and overlapping between mutants can simply be referred to in the text. 

Regarding g), h) and i), it is worth clarifying that this analysis is (presumably) GO Term overrepresentation analysis. As a transcriptome analysis tool, GO Term overrepresentation analysis is widely used, however does not represent transcript abundance, and can be biased depending on the background enrichment analysis was performed against, or the functions looked for. It would be worthwhile addressing these limitations in-text or performing further functional analysis on the transcriptome.

Figure 4

We are unsure why ROP6 is an appropriate control in a) and would appreciate its discussion in-text. It is possible b) is appropriate within the field of plasma membrane receptors, however as readers outside the field, we would have appreciated a more in-depth reference to this figure in the text.

Figure 5

In text, this figure is introduced with the context, “We found a myristoylation site at glycine 2 and predicted palmitoylation sites at cysteine 6 and cysteine 7, which may account for this localization” (Lines 180 – 182). How did you identify/predict these sites? This should be described in text. It is also not described in text, and we were not sure, why mannitol treatment was used.

The Z-stacks presented to accompany a) and d) are confusing. Do they represent the mannitol or mock treatments? What is their purpose in the figure? It is unclear what they represent as they do not always correspond to the leaf tissues shown to the left, for either mock or mannitol treatments.

In c), it’s not clear what the blue/white colour code refers to, which are the hydrophobic and which are the hydrophilic sites? What about the numbers? They are not mentioned in the figure legend. Please include a key. It might also be worthwhile highlighting the myristoylation and palmitoylation sites on this structural model.

Figure 6

This figure should include a Predicted Aligned Error (PAE) confidence plot for the structure otherwise the structural model presented here is unsupported.

It is also unclear why you chose to model HIR2 as a 17-mer, other than it being the greatest oligomerisation number possible. A more informative figure could include plotting PAE scores against number of oligomerising HIR2 particles.  

We are confused by the mixed use of Alphafold2 and Alphafold3 and recommend that structures predicted using AF2 are updated (Fig.5).

Regarding e), BN-PAGE controls are absent instead reps of the same treatments are shown. In accompanying SDS-PAGEs, protein samples should be broken down into primary structures (monomers) from DTT and heat applied, why is this not the case here? 

In f), we would advise against cropping the gels into separate boxes, especially if the same ladder is used as it appears to be the case here, as it suggests the data shown are from separate gels and cannot be compared side-by-side, using the same ladder. In general, it is always preferrable to show the gels uncropped.

As this paper demonstrates HIR2 closely interacting with several membrane proteins, we question whether the BN-PAGE data can be used to prove it has a large molecular weight, or whether indeed you are pulling down HIR2 together with some of its interactors, causing a high molecular weight streak appear on the gel. On this note, it would be nice to test whether non-oligomerising mutants fail to IP together with previously established interactors of HIR2.

Supplementary Figures

Supp. Figure 1

In e), it’s not clear what NubWT and NubA are.

In f), what are the negative controls? Neither the “donor only” nor the “free RFP” are suitable – we would like to see an acceptor not expected to interact with HIR2 as a control.

Supp. Figure 2

Free GFP on a separate gel, with a separate ladder is not an appropriate control.

Supp. Figure 3

We would have liked to see the HIR2oe plant in the main text/figure, phenotyped as thoroughly (older plants, and root length, and a boxplot summarising the replicates).

Supp. Figure 8

In b) and d), we wonder why there are so many empty lanes?

We hope these suggestions will help improve the clarity and impact of this valuable manuscript.

Competing interests

The authors declare that they have no competing interests.