Convergent Evolution of Effector Protease Recognition by Arabidopsis and Barley

  1. Morgan E. Carter
  2. Matthew Helm
  3. Antony V. E. Chapman
  4. Emily Wan
  5. Ana Maria Restrepo Sierra
  6. Roger W. Innes
  7. Adam J. Bogdanove
  8. Roger P. Wise

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Abstract

The Pseudomonas syringae cysteine protease AvrPphB activates the Arabidopsis resistance protein RPS5 by cleaving a second host protein, PBS1. AvrPphB induces defense responses in other plant species, but the genes and mechanisms mediating AvrPphB recognition in those species have not been defined. Here, we show that AvrPphB induces defense responses in diverse barley cultivars. We also show that barley contains two PBS1 orthologs, that their products are cleaved by AvrPphB, and that the barley AvrPphB response maps to a single locus containing a nucleotide-binding leucine-rich repeat (NLR) gene, which we termed AvrPphB Response 1 (Pbr1). Transient coexpression of PBR1 with wild-type AvrPphB but not with a protease inactive mutant triggered defense responses, indicating that PBR1 detects AvrPphB protease activity. Additionally, PBR1 coimmunoprecipitated with barley and Nicotiana benthamiana PBS1 proteins, suggesting mechanistic similarity to detection by RPS5. Lastly, we determined that wheat cultivars also recognize AvrPphB protease activity and contain two putative Pbr1 orthologs. Phylogenetic analyses showed, however, that Pbr1 is not orthologous to RPS5. Our results indicate that the ability to recognize AvrPphB evolved convergently and imply that selection to guard PBS1-like proteins occurs across species. Also, these results suggest that PBS1-based decoys may be used to engineer protease effector recognition–based resistance in barley and wheat.

Article activity feed

  1. Version published to 10.1094/mpmi-07-18-0202-fi
  2. Version published to 10.1101/374264v2 on bioRxiv
  3. PREreview

    This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/7624537.

    UIUC Plant Physiology Journal Club: 2018-08-13   

    Steven Burgess (0000-0003-2353-7794), Samuel Fernandes, Antony Digrado, Charles Pignon, Elsa de Becker, Naomi Housego Day, Lusya Manukyan, Stephanie Cullum, Isla Causon, Iulia Floristeanu, Young Cho, Freya Way, Judy Savitskya, Robert Collison, Aoife Sweeney, Pietro Hughes, Cindy Chan

    Abstract

    The paper "Arabidopsis species employ distinct strategies to cope with drought stress" by Bouzid et al. (https://doi.org/10.1101/341859) investigates whether responses to water limitation vary between closely related species by assessing the growth and survival of A. thaliana, A. lyrata and A. halleri accessions in a dry down experiment. By including multiple accessions of each species the authors were able to analyse variation in response to drought stress within and between species based on eight phenotypic parameters. The authors went on to perform comparative transcriptomic analysis between A. lyrata and A. halleri over a time course of drought treatment and identified differentially expressed genes. GO ontology analysis suggest the species analysed adopt different strategies to cope with drought stress, with A. lyrata employing avoidance and tolerance mechanisms, whereas A. thaliana showed strong avoidance but no tolerance. We were impressed with the amount of work performed and thought the  study aims to address an interesting question. During the hour long journal club participants were asked to focus on three aspects of the paper as part of a training exercise, including novelty, interest, soundness as well as writing and presentation.

    Review

    There are several published papers looking at the effect of drought stress in Arabidopsis species including A. lyrata (Sletvold and Agren 2011; Paccard et al. 2014) and A. thaliana (Ferguson et al. 2018; Kalladan et al. 2017). We suggest toning down the assertion on Line 28 that little is known about the physiological response to drought in closely related species. Although not in a single paper, this issue has been addressed within a species by Sletvold and Agren (2012) and Davila Olivas et al. (2017) and there is a fairly large collection of papers looking at this within a species. To our knowledge, the novelty of this work lies in analysis of drought responses within and between several species of Arabidopsis in one article. We thought this was an interesting approach and that the authors can make more of this point, highlighting the new information that it yields.

    The article is well written in clear sentences and it was easy to read. We felt the authors had collected a lot of data and believe this could be explored further in the discussion, particularly the differential expression data. There is a lot of microarray and transcriptomic data available for the response of A. thaliana to drought conditions and would like to have seen some form of comparison between these data and that collected for A. lyrata and A. halleri.

    In addition, it would help to provide more information about why analysis of Arabidopsis accessions was limited to late flowering varieties. Does excluding accessions which can terminate life cycle early bias the experiment? Termination is a major strategy for survival and may impacts upon the conclusion that "response to depletion in SWC did not reveal significant differences between accessions (line 591)." Further discussion of this conclusion in the context of previous studies would be illuminating as it appears to contrast with some findings, for example Bouchabke et al. (2008) which suggested there are differences in response to depletion of SWC between A. thaliana accessions. Readers would also benefit from discussion about how the results from the phenotypic analysis relates to other studies which have implicated trichome production, rosette leaf size and flowering time as drivers for drought tolerance.

    We commend the fact the methods are detailed which should aid anyone wanting to replicate the study. Several aspects were highlighted as excellent practices, in particular: the fact that all program versions are provided, software parameters are included and accessions and materials are well catalogued. To build on this we recommend depositing the data (particularly transcriptomic analysis) in a public repository such as GEO, SRA or Zendo as required by some journals. This means data can be built upon in future studies and could increase the likelihood of the paper being cited. Inclusion of extended methods in an accompanying Bioprotocol paper or on sites such as Protocols.io and sharing custom scripts in a github repository (or on Zendo) would make the reporting of methods outstanding. 

    Minor comments

    The paper may benefit from clarify a number of questions raised by participants:   

    • How was soil mixture chosen?
    • Line 192 under what conditions were the plants grown in the greenhouse?
    • Line 206: How were the first signs of wilting defined? It might be worth mentioning this earlier in the manuscript (line 206)
    • Line 232 - How was loss of turgidity measured?
    • The colors used in the figures will create difficulty for those individuals with color blindness, using color oracle (https://colororacle.org/) can help address this issue.
    • Figure 2 - no scale bars are included
    • Figure 2 - how many plants per pot were analyzed? This could have impacted on measurements displayed images suggested this was variable.
    • Figure 5 - we thought it was excellent that unit level data is provided, this could be extended to the other figures too.
    • Figure legends could be improved e.g. by changing "halleri" to "A. halleri"*Formating of legend (line 1326 )extra space and period.
    • The article might benefit from consistent formatting/presentation of figures
    • A table might be more appropriate for Figures 7 and 8
    • Inclusion of n= numbers in the figures would help readers assess the data.
    • We were confused about how the experiment was designed, why is data for only on biological replicate displayed in figures 7 and 8.

    References

    Bouchabke et al. 2008 https://doi.org/10.1371/journal.pone.0001705

    Davila Olivas et al. (2017) https://doi.org/10.1111/mec.14100

    Des Marais, et al. (2012) https://doi.org/10.1105/tpc.112.096180

    Huttunen et al. 2010 https://doi.org/10.5735/085.047.0304

    Kalladan et al. (2017) https://doi.org/10.1073/pnas.1705884114

    Paccard et al. (2014) doi: 10.1007/s00442-014-2932-8

    Sletvold and Agren (2011) https://doi.org/10.1007/s10682-011-9502-x

  4. Version published to 10.1101/374264v1 on bioRxiv